[Research on spatially modulated Fourier transform imaging spectrometer data processing method].

PubMed

Huang, Min; Xiangli, Bin; Lü, Qun-Bo; Zhou, Jin-Song; Jing, Juan-Juan; Cui, Yan

2010-03-01

Fourier transform imaging spectrometer is a new technic, and has been developed very rapidly in nearly ten years. The data catched by Fourier transform imaging spectrometer is indirect data, can not be used by user, and need to be processed by various approaches, including data pretreatment, apodization, phase correction, FFT, and spectral radicalization calibration. No paper so far has been found roundly to introduce this method. In the present paper, the author will give an effective method to process the interfering data to spectral data, and with this method we can obtain good result.

Comparison and evaluation on image fusion methods for GaoFen-1 imagery

NASA Astrophysics Data System (ADS)

Zhang, Ningyu; Zhao, Junqing; Zhang, Ling

2016-10-01

Currently, there are many research works focusing on the best fusion method suitable for satellite images of SPOT, QuickBird, Landsat and so on, but only a few of them discuss the application of GaoFen-1 satellite images. This paper proposes a novel idea by using four fusion methods, such as principal component analysis transform, Brovey transform, hue-saturation-value transform, and Gram-Schmidt transform, from the perspective of keeping the original image spectral information. The experimental results showed that the transformed images by the four fusion methods not only retain high spatial resolution on panchromatic band but also have the abundant spectral information. Through comparison and evaluation, the integration of Brovey transform is better, but the color fidelity is not the premium. The brightness and color distortion in hue saturation-value transformed image is the largest. Principal component analysis transform did a good job in color fidelity, but its clarity still need improvement. Gram-Schmidt transform works best in color fidelity, and the edge of the vegetation is the most obvious, the fused image sharpness is higher than that of principal component analysis. Brovey transform, is suitable for distinguishing the Gram-Schmidt transform, and the most appropriate for GaoFen-1 satellite image in vegetation and non-vegetation area. In brief, different fusion methods have different advantages in image quality and class extraction, and should be used according to the actual application information and image fusion algorithm.

Method for determining and displaying the spacial distribution of a spectral pattern of received light

DOEpatents

Bennett, C.L.

1996-07-23

An imaging Fourier transform spectrometer is described having a Fourier transform infrared spectrometer providing a series of images to a focal plane array camera. The focal plane array camera is clocked to a multiple of zero crossing occurrences as caused by a moving mirror of the Fourier transform infrared spectrometer and as detected by a laser detector such that the frame capture rate of the focal plane array camera corresponds to a multiple of the zero crossing rate of the Fourier transform infrared spectrometer. The images are transmitted to a computer for processing such that representations of the images as viewed in the light of an arbitrary spectral ``fingerprint`` pattern can be displayed on a monitor or otherwise stored and manipulated by the computer. 2 figs.

Beam profile for the Herschel-SPIRE Fourier transform spectrometer.

PubMed

Makiwa, Gibion; Naylor, David A; Ferlet, Marc; Salji, Carl; Swinyard, Bruce; Polehampton, Edward; van der Wiel, Matthijs H D

2013-06-01

One of the instruments on board the Herschel Space Observatory is the Spectral and Photometric Imaging Receiver (SPIRE). SPIRE employs a Fourier transform spectrometer with feed-horn-coupled bolometers to provide imaging spectroscopy. To interpret the resultant spectral images requires knowledge of the wavelength-dependent beam, which in the case of SPIRE is complicated by the use of multimoded feed horns. In this paper we describe a series of observations and the analysis conducted to determine the wavelength dependence of the SPIRE spectrometer beam profile.

Wavelet Filter Banks for Super-Resolution SAR Imaging

NASA Technical Reports Server (NTRS)

Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

2011-01-01

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

SAR image change detection using watershed and spectral clustering

NASA Astrophysics Data System (ADS)

Niu, Ruican; Jiao, L. C.; Wang, Guiting; Feng, Jie

2011-12-01

A new method of change detection in SAR images based on spectral clustering is presented in this paper. Spectral clustering is employed to extract change information from a pair images acquired on the same geographical area at different time. Watershed transform is applied to initially segment the big image into non-overlapped local regions, leading to reduce the complexity. Experiments results and system analysis confirm the effectiveness of the proposed algorithm.

Calibrating AIS images using the surface as a reference

NASA Technical Reports Server (NTRS)

Smith, M. O.; Roberts, D. A.; Shipman, H. M.; Adams, J. B.; Willis, S. C.; Gillespie, A. R.

1987-01-01

A method of evaluating the initial assumptions and uncertainties of the physical connection between Airborne Imaging Spectrometer (AIS) image data and laboratory/field spectrometer data was tested. The Tuscon AIS-2 image connects to lab reference spectra by an alignment to the image spectral endmembers through a system gain and offset for each band. Images were calibrated to reflectance so as to transform the image into a measure that is independent of the solar radiant flux. This transformation also makes the image spectra directly comparable to data from lab and field spectrometers. A method was tested for calibrating AIS images using the surface as a reference. The surface heterogeneity is defined by lab/field spectral measurements. It was found that the Tuscon AIS-2 image is consistent with each of the initial hypotheses: (1) that the AIS-2 instrument calibration is nearly linear; (2) the spectral variance is caused by sub-pixel mixtures of spectrally distinct materials and shade, and (3) that sub-pixel mixtures can be treated as linear mixtures of pure endmembers. It was also found that the image can be characterized by relatively few endmembers using the AIS-2 spectra.

Fast data reconstructed method of Fourier transform imaging spectrometer based on multi-core CPU

NASA Astrophysics Data System (ADS)

Yu, Chunchao; Du, Debiao; Xia, Zongze; Song, Li; Zheng, Weijian; Yan, Min; Lei, Zhenggang

2017-10-01

Imaging spectrometer can gain two-dimensional space image and one-dimensional spectrum at the same time, which shows high utility in color and spectral measurements, the true color image synthesis, military reconnaissance and so on. In order to realize the fast reconstructed processing of the Fourier transform imaging spectrometer data, the paper designed the optimization reconstructed algorithm with OpenMP parallel calculating technology, which was further used for the optimization process for the HyperSpectral Imager of `HJ-1' Chinese satellite. The results show that the method based on multi-core parallel computing technology can control the multi-core CPU hardware resources competently and significantly enhance the calculation of the spectrum reconstruction processing efficiency. If the technology is applied to more cores workstation in parallel computing, it will be possible to complete Fourier transform imaging spectrometer real-time data processing with a single computer.

GIFTS SM EDU Radiometric and Spectral Calibrations

NASA Technical Reports Server (NTRS)

Tian, J.; Reisse, R. a.; Johnson, D. G.; Gazarik, J. J.

2007-01-01

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiance using a Fourier transform spectrometer (FTS). The GIFTS instrument gathers measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the processing algorithms involved in the calibration. The calibration procedures can be subdivided into three categories: the pre-calibration stage, the calibration stage, and finally, the post-calibration stage. Detailed derivations for each stage are presented in this paper.

Automated road network extraction from high spatial resolution multi-spectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Qiaoping

For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a road network. The extracted road network is evaluated against a reference dataset using a line segment matching algorithm. The entire process is unsupervised and fully automated. Based on extensive experimentation on a variety of remotely-sensed multi-spectral images, the proposed methodology achieves a moderate success in automating road network extraction from high spatial resolution multi-spectral imagery.

Method for determining and displaying the spacial distribution of a spectral pattern of received light

DOEpatents

Bennett, Charles L.

1996-01-01

An imaging Fourier transform spectrometer (10, 210) having a Fourier transform infrared spectrometer (12) providing a series of images (40) to a focal plane array camera (38). The focal plane array camera (38) is clocked to a multiple of zero crossing occurrences as caused by a moving mirror (18) of the Fourier transform infrared spectrometer (12) and as detected by a laser detector (50) such that the frame capture rate of the focal plane array camera (38) corresponds to a multiple of the zero crossing rate of the Fourier transform infrared spectrometer (12). The images (40) are transmitted to a computer (45) for processing such that representations of the images (40) as viewed in the light of an arbitrary spectral "fingerprint" pattern can be displayed on a monitor (60) or otherwise stored and manipulated by the computer (45).

Pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform

NASA Astrophysics Data System (ADS)

Shi, Cheng; Liu, Fang; Li, Ling-Ling; Hao, Hong-Xia

2014-01-01

The goal of pan-sharpening is to get an image with higher spatial resolution and better spectral information. However, the resolution of the pan-sharpened image is seriously affected by the thin clouds. For a single image, filtering algorithms are widely used to remove clouds. These kinds of methods can remove clouds effectively, but the detail lost in the cloud removal image is also serious. To solve this problem, a pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform (NSST) is proposed. For the low-resolution multispectral (LR MS) and high-resolution panchromatic images with thin clouds, a mask dodging method is used to remove clouds. For the cloud removal LR MS image, an adaptive principal component analysis transform is proposed to balance the spectral information and spatial resolution in the pan-sharpened image. Since the clouds removal process causes the detail loss problem, a weight matrix is designed to enhance the details of the cloud regions in the pan-sharpening process, but noncloud regions remain unchanged. And the details of the image are obtained by NSST. Experimental results over visible and evaluation metrics demonstrate that the proposed method can keep better spectral information and spatial resolution, especially for the images with thin clouds.

Hyperspectral imaging using the single-pixel Fourier transform technique

NASA Astrophysics Data System (ADS)

Jin, Senlin; Hui, Wangwei; Wang, Yunlong; Huang, Kaicheng; Shi, Qiushuai; Ying, Cuifeng; Liu, Dongqi; Ye, Qing; Zhou, Wenyuan; Tian, Jianguo

2017-03-01

Hyperspectral imaging technology is playing an increasingly important role in the fields of food analysis, medicine and biotechnology. To improve the speed of operation and increase the light throughput in a compact equipment structure, a Fourier transform hyperspectral imaging system based on a single-pixel technique is proposed in this study. Compared with current imaging spectrometry approaches, the proposed system has a wider spectral range (400-1100 nm), a better spectral resolution (1 nm) and requires fewer measurement data (a sample rate of 6.25%). The performance of this system was verified by its application to the non-destructive testing of potatoes.

Snapshot Imaging Spectrometry in the Visible and Long Wave Infrared

NASA Astrophysics Data System (ADS)

Maione, Bryan David

Imaging spectrometry is an optical technique in which the spectral content of an object is measured at each location in space. The main advantage of this modality is that it enables characterization beyond what is possible with a conventional camera, since spectral information is generally related to the chemical composition of the object. Due to this, imaging spectrometers are often capable of detecting targets that are either morphologically inconsistent, or even under resolved. A specific class of imaging spectrometer, known as a snapshot system, seeks to measure all spatial and spectral information simultaneously, thereby rectifying artifacts associated with scanning designs, and enabling the measurement of temporally dynamic scenes. Snapshot designs are the focus of this dissertation. Three designs for snapshot imaging spectrometers are developed, each providing novel contributions to the field of imaging spectrometry. In chapter 2, the first spatially heterodyned snapshot imaging spectrometer is modeled and experimentally validated. Spatial heterodyning is a technique commonly implemented in non-imaging Fourier transform spectrometry. For Fourier transform imaging spectrometers, spatial heterodyning improves the spectral resolution trade space. Additionally, in this chapter a unique neural network based spectral calibration is developed and determined to be an improvement beyond Fourier and linear operator based techniques. Leveraging spatial heterodyning as developed in chapter 2, in chapter 3, a high spectral resolution snapshot Fourier transform imaging spectrometer, based on a Savart plate interferometer, is developed and experimentally validated. The sensor presented in this chapter is the highest spectral resolution sensor in its class. High spectral resolution enables the sensor to discriminate narrowly spaced spectral lines. The capabilities of neural networks in imaging spectrometry are further explored in this chapter. Neural networks are used to perform single target detection on raw instrument data, thereby eliminating the need for an explicit spectral calibration step. As an extension of the results in chapter 2, neural networks are once again demonstrated to be an improvement when compared to linear operator based detection. In chapter 4 a non-interferometric design is developed for the long wave infrared (wavelengths spanning 8-12 microns). The imaging spectrometer developed in this chapter is a multi-aperture filtered microbolometer. Since the detector is uncooled, the presented design is ultra-compact and low power. Additionally, cost effective polymer absorption filters are used in lieu of interference filters. Since, each measurement of the system is spectrally multiplexed, an SNR advantage is realized. A theoretical model for the filtered design is developed, and the performance of the sensor for detecting liquid contaminants is investigated. Similar to past chapters, neural networks are used and achieve false detection rates of less than 1%. Lastly, this dissertation is concluded with a discussion on future work and potential impact of these devices.

Multispectral multisensor image fusion using wavelet transforms

USGS Publications Warehouse

Lemeshewsky, George P.

1999-01-01

Fusion techniques can be applied to multispectral and higher spatial resolution panchromatic images to create a composite image that is easier to interpret than the individual images. Wavelet transform-based multisensor, multiresolution fusion (a type of band sharpening) was applied to Landsat thematic mapper (TM) multispectral and coregistered higher resolution SPOT panchromatic images. The objective was to obtain increased spatial resolution, false color composite products to support the interpretation of land cover types wherein the spectral characteristics of the imagery are preserved to provide the spectral clues needed for interpretation. Since the fusion process should not introduce artifacts, a shift invariant implementation of the discrete wavelet transform (SIDWT) was used. These results were compared with those using the shift variant, discrete wavelet transform (DWT). Overall, the process includes a hue, saturation, and value color space transform to minimize color changes, and a reported point-wise maximum selection rule to combine transform coefficients. The performance of fusion based on the SIDWT and DWT was evaluated with a simulated TM 30-m spatial resolution test image and a higher resolution reference. Simulated imagery was made by blurring higher resolution color-infrared photography with the TM sensors' point spread function. The SIDWT based technique produced imagery with fewer artifacts and lower error between fused images and the full resolution reference. Image examples with TM and SPOT 10-m panchromatic illustrate the reduction in artifacts due to the SIDWT based fusion.

EIT Imaging Regularization Based on Spectral Graph Wavelets.

PubMed

Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Vauhkonen, Marko; Wolf, Gerhard; Mueller-Lisse, Ullrich; Moeller, Knut

2017-09-01

The objective of electrical impedance tomographic reconstruction is to identify the distribution of tissue conductivity from electrical boundary conditions. This is an ill-posed inverse problem usually solved under the finite-element method framework. In previous studies, standard sparse regularization was used for difference electrical impedance tomography to achieve a sparse solution. However, regarding elementwise sparsity, standard sparse regularization interferes with the smoothness of conductivity distribution between neighboring elements and is sensitive to noise. As an effect, the reconstructed images are spiky and depict a lack of smoothness. Such unexpected artifacts are not realistic and may lead to misinterpretation in clinical applications. To eliminate such artifacts, we present a novel sparse regularization method that uses spectral graph wavelet transforms. Single-scale or multiscale graph wavelet transforms are employed to introduce local smoothness on different scales into the reconstructed images. The proposed approach relies on viewing finite-element meshes as undirected graphs and applying wavelet transforms derived from spectral graph theory. Reconstruction results from simulations, a phantom experiment, and patient data suggest that our algorithm is more robust to noise and produces more reliable images.

A method based on IHS cylindrical transform model for quality assessment of image fusion

NASA Astrophysics Data System (ADS)

Zhu, Xiaokun; Jia, Yonghong

2005-10-01

Image fusion technique has been widely applied to remote sensing image analysis and processing, and methods for quality assessment of image fusion in remote sensing have also become the research issues at home and abroad. Traditional assessment methods combine calculation of quantitative indexes and visual interpretation to compare fused images quantificationally and qualitatively. However, in the existing assessment methods, there are two defects: on one hand, most imdexes lack the theoretic support to compare different fusion methods. On the hand, there is not a uniform preference for most of the quantitative assessment indexes when they are applied to estimate the fusion effects. That is, the spatial resolution and spectral feature could not be analyzed synchronously by these indexes and there is not a general method to unify the spatial and spectral feature assessment. So in this paper, on the basis of the approximate general model of four traditional fusion methods, including Intensity Hue Saturation(IHS) triangle transform fusion, High Pass Filter(HPF) fusion, Principal Component Analysis(PCA) fusion, Wavelet Transform(WT) fusion, a correlation coefficient assessment method based on IHS cylindrical transform is proposed. By experiments, this method can not only get the evaluation results of spatial and spectral features on the basis of uniform preference, but also can acquire the comparison between fusion image sources and fused images, and acquire differences among fusion methods. Compared with the traditional assessment methods, the new methods is more intuitionistic, and in accord with subjective estimation.

Hypercomplex Fourier transforms of color images.

PubMed

Ell, Todd A; Sangwine, Stephen J

2007-01-01

Fourier transforms are a fundamental tool in signal and image processing, yet, until recently, there was no definition of a Fourier transform applicable to color images in a holistic manner. In this paper, hypercomplex numbers, specifically quaternions, are used to define a Fourier transform applicable to color images. The properties of the transform are developed, and it is shown that the transform may be computed using two standard complex fast Fourier transforms. The resulting spectrum is explained in terms of familiar phase and modulus concepts, and a new concept of hypercomplex axis. A method for visualizing the spectrum using color graphics is also presented. Finally, a convolution operational formula in the spectral domain is discussed.

Preliminary spectral and geologic analysis of Landsat-4 Thematic Mapper data, Wind River Basin area, Wyoming

NASA Technical Reports Server (NTRS)

Conel, J. E.; Lang, H. R.; Paylor, E. D.; Alley, R. E.

1985-01-01

A Landsat-4 Thematic Mapper (TM) image of the Wind River Basin area in Wyoming is currently under analysis for stratigraphic and structural mapping and for assessment of spectral and spatial characteristics using visible, near infrared, and short wavelength infrared bands. To estimate the equivalent Lambertian surface reflectance, TM radiance data were calibrated to remove atmospheric and instrumental effects. Reflectance measurements for homogeneous natural and cultural targets were acquired about one year after data acquisition. Calibration data obtained during the analysis were used to calculate new gains and offsets to improve scanner response for earth science applications. It is shown that the principal component images calculated from the TM data were the result of linear transformations of ground reflectance. In images prepared from this transform, the separation of spectral classes was independent of systematic atmospheric and instrumental factors. Several examples of the processed images are provided.

High-speed spectral domain optical coherence tomography using non-uniform fast Fourier transform

PubMed Central

Chan, Kenny K. H.; Tang, Shuo

2010-01-01

The useful imaging range in spectral domain optical coherence tomography (SD-OCT) is often limited by the depth dependent sensitivity fall-off. Processing SD-OCT data with the non-uniform fast Fourier transform (NFFT) can improve the sensitivity fall-off at maximum depth by greater than 5dB concurrently with a 30 fold decrease in processing time compared to the fast Fourier transform with cubic spline interpolation method. NFFT can also improve local signal to noise ratio (SNR) and reduce image artifacts introduced in post-processing. Combined with parallel processing, NFFT is shown to have the ability to process up to 90k A-lines per second. High-speed SD-OCT imaging is demonstrated at camera-limited 100 frames per second on an ex-vivo squid eye. PMID:21258551

A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation

NASA Astrophysics Data System (ADS)

Zhou, Xiran; Liu, Jun; Liu, Shuguang; Cao, Lei; Zhou, Qiming; Huang, Huawen

2014-02-01

High spatial resolution and spectral fidelity are basic standards for evaluating an image fusion algorithm. Numerous fusion methods for remote sensing images have been developed. Some of these methods are based on the intensity-hue-saturation (IHS) transform and the generalized IHS (GIHS), which may cause serious spectral distortion. Spectral distortion in the GIHS is proven to result from changes in saturation during fusion. Therefore, reducing such changes can achieve high spectral fidelity. A GIHS-based spectral preservation fusion method that can theoretically reduce spectral distortion is proposed in this study. The proposed algorithm consists of two steps. The first step is spectral modulation (SM), which uses the Gaussian function to extract spatial details and conduct SM of multispectral (MS) images. This method yields a desirable visual effect without requiring histogram matching between the panchromatic image and the intensity of the MS image. The second step uses the Gaussian convolution function to restore lost edge details during SM. The proposed method is proven effective and shown to provide better results compared with other GIHS-based methods.

New algorithm for lossless hyper-spectral image compression with mixing transform to eliminate redundancy

NASA Astrophysics Data System (ADS)

Xie, ChengJun; Xu, Lin

2008-03-01

This paper presents a new algorithm based on mixing transform to eliminate redundancy, SHIRCT and subtraction mixing transform is used to eliminate spectral redundancy, 2D-CDF(2,2)DWT to eliminate spatial redundancy, This transform has priority in hardware realization convenience, since it can be fully implemented by add and shift operation. Its redundancy elimination effect is better than (1D+2D)CDF(2,2)DWT. Here improved SPIHT+CABAC mixing compression coding algorithm is used to implement compression coding. The experiment results show that in lossless image compression applications the effect of this method is a little better than the result acquired using (1D+2D)CDF(2,2)DWT+improved SPIHT+CABAC, still it is much better than the results acquired by JPEG-LS, WinZip, ARJ, DPCM, the research achievements of a research team of Chinese Academy of Sciences, NMST and MST. Using hyper-spectral image Canal of American JPL laboratory as the data set for lossless compression test, on the average the compression ratio of this algorithm exceeds the above algorithms by 42%,37%,35%,30%,16%,13%,11% respectively.

Fusion of spectral and panchromatic images using false color mapping and wavelet integrated approach

NASA Astrophysics Data System (ADS)

Zhao, Yongqiang; Pan, Quan; Zhang, Hongcai

2006-01-01

With the development of sensory technology, new image sensors have been introduced that provide a greater range of information to users. But as the power limitation of radiation, there will always be some trade-off between spatial and spectral resolution in the image captured by specific sensors. Images with high spatial resolution can locate objects with high accuracy, whereas images with high spectral resolution can be used to identify the materials. Many applications in remote sensing require fusing low-resolution imaging spectral images with panchromatic images to identify materials at high resolution in clutter. A pixel-based false color mapping and wavelet transform integrated fusion algorithm is presented in this paper, the resulting images have a higher information content than each of the original images and retain sensor-specific image information. The simulation results show that this algorithm can enhance the visibility of certain details and preserve the difference of different materials.

Physically motivated correlation formalism in hyperspectral imaging

NASA Astrophysics Data System (ADS)

Roy, Ankita; Rafert, J. Bruce

2004-05-01

Most remote sensing data-sets contain a limiting number of independent spatial and spectral measurements, beyond which no effective increase in information is achieved. This paper presents a Physically Motivated Correlation Formalism (PMCF) ,which places both Spatial and Spectral data on an equivalent mathematical footing in the context of a specific Kernel, such that, optimal combinations of independent data can be selected from the entire Hypercube via the method of "Correlation Moments". We present an experimental and computational analysis of Hyperspectral data sets using the Michigan Tech VFTHSI [Visible Fourier Transform Hyperspectral Imager] based on a Sagnac Interferometer, adjusted to obtain high SNR levels. The captured Signal Interferograms of different targets - aerial snaps of Houghton and lab-based data (white light , He-Ne laser , discharge tube sources) with the provision of customized scan of targets with the same exposures are processed using inverse imaging transformations and filtering techniques to obtain the Spectral profiles and generate Hypercubes to compute Spectral/Spatial/Cross Moments. PMCF answers the question of how optimally the entire hypercube should be sampled and finds how many spatial-spectral pixels are required for a particular target recognition.

3D spectral imaging with synchrotron Fourier transform infrared spectro-microtomography

Treesearch

Michael C. Martin; Charlotte Dabat-Blondeau; Miriam Unger; Julia Sedlmair; Dilworth Y. Parkinson; Hans A. Bechtel; Barbara Illman; Jonathan M. Castro; Marco Keiluweit; David Buschke; Brenda Ogle; Michael J. Nasse; Carol J. Hirschmugl

2013-01-01

We report Fourier transform infrared spectro-microtomography, a nondestructive three-dimensional imaging approach that reveals the distribution of distinctive chemical compositions throughout an intact biological or materials sample. The method combines mid-infrared absorption contrast with computed tomographic data acquisition and reconstruction to enhance chemical...

Hyperspectral fundus imager

NASA Astrophysics Data System (ADS)

Truitt, Paul W.; Soliz, Peter; Meigs, Andrew D.; Otten, Leonard John, III

2000-11-01

A Fourier Transform hyperspectral imager was integrated onto a standard clinical fundus camera, a Zeiss FF3, for the purposes of spectrally characterizing normal anatomical and pathological features in the human ocular fundus. To develop this instrument an existing FDA approved retinal camera was selected to avoid the difficulties of obtaining new FDA approval. Because of this, several unusual design constraints were imposed on the optical configuration. Techniques to calibrate the sensor and to define where the hyperspectral pushbroom stripe was located on the retina were developed, including the manufacturing of an artificial eye with calibration features suitable for a spectral imager. In this implementation the Fourier transform hyperspectral imager can collect over a hundred 86 cm-1 spectrally resolved bands with 12 micro meter/pixel spatial resolution within the 1050 nm to 450 nm band. This equates to 2 nm to 8 nm spectral resolution depending on the wavelength. For retinal observations the band of interest tends to lie between 475 nm and 790 nm. The instrument has been in use over the last year successfully collecting hyperspectral images of the optic disc, retinal vessels, choroidal vessels, retinal backgrounds, and macula diabetic macular edema, and lesions of age-related macular degeneration.

Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.

Use of the TM tasseled cap transform for interpretation of spectral contrasts in an urban scene

NASA Technical Reports Server (NTRS)

Goward, S. N.; Wharton, S. W.

1984-01-01

Investigations are being conducted with the objective to develop automated numerical image analysis procedures. In this context, an examination is performed of physically-based multispectral data transforms as a means to incorporate a priori knowledge of land radiance properties in the analysis process. A physically-based transform of TM observations was developed. This transform extends the Landsat MSS Tasseled Cap transform reported by Kauth and Thomas (1976) to TM data observations. The present study has the aim to examine the utility of the TM Tasseled Cap transform as applied to TM data from an urban landscape. The analysis conducted is based on 512 x 512 subset of the Washington, DC November 2, 1982 TM scene, centered on Springfield, VA. It appears that the TM tasseled cap transformation provides a good means to explain land physical attributes of the Washington scene. This result provides a suggestion regarding a direction by which a priori knowledge of landscape spectral patterns may be incorporated into numerical image analysis.

Definition of a metrology servo-system for a solar imaging fourier transform spectrometer working in the far UV (IFTSUV)

NASA Astrophysics Data System (ADS)

Ruiz de Galarreta Fanju, C.; Philippon, A.; Bouzit, M.; Appourchaux, T.; Vial, J.-C.; Maillard, J.-P.; Lemaire, P.

2017-11-01

The understanding of the solar outer atmosphere requires a simultaneous combination of imaging and spectral observations concerning the far UV lines that arise from the high chromospheres up to the corona. These observations must be performed with enough spectral, spatial and temporal resolution to reveal the small atmospheric structures and to resolve the solar dynamics. An Imaging Fourier Transform Spectrometer working in the far-UV (IFTSUV, Figure 1) is an attractive instrumental solution to fulfill these requirements. However, due to the short wavelength, to preserve IFTSUV spectral precision and Signal to Noise Ratio (SNR) requires a high optical surface quality and a very accurate (linear and angular) metrology to maintain the optical path difference (OPD) during the entire scanning process by: optical path difference sampling trigger; and dynamic alignment for tip/tilt compensation (Figure 2).

Spectral reconstruction of dental X-ray tubes using laplace inverse transform of the attenuation curve

NASA Astrophysics Data System (ADS)

Malezan, A.; Tomal, A.; Antoniassi, M.; Watanabe, P. C. A.; Albino, L. D.; Poletti, M. E.

2015-11-01

In this work, a spectral reconstruction methodology for diagnostic X-ray, using Laplace inverse transform of the attenuation, was successfully applied to dental X-ray equipments. The attenuation curves of 8 commercially available dental X-ray equipment, from 3 different manufactures (Siemens, Gnatus and Dabi Atlante), were obtained by using an ionization chamber and high purity aluminium filters, while the kVp was obtained with a specific meter. A computational routine was implemented in order to adjust a model function, whose inverse Laplace transform is analytically known, to the attenuation curve. This methodology was validated by comparing the reconstructed and the measured (using semiconductor detector of cadmium telluride) spectra of a given dental X-ray unit. The spectral reconstruction showed the Dabi Atlante equipments generating similar shape spectra. This is a desirable feature from clinic standpoint because it produces similar levels of image quality and dose. We observed that equipments from Siemens and Gnatus generate significantly different spectra, suggesting that, for a given operating protocol, these units will present different levels of image quality and dose. This fact claims for the necessity of individualized operating protocols that maximize image quality and dose. The proposed methodology is suitable to perform a spectral reconstruction of dental X-ray equipments from the simple measurements of attenuation curve and kVp. The simplified experimental apparatus and the low level of technical difficulty make this methodology accessible to a broad range of users. The knowledge of the spectral distribution can help in the development of operating protocols that maximize image quality and dose.

Signal-to-noise analysis of a birefringent spectral zooming imaging spectrometer

NASA Astrophysics Data System (ADS)

Li, Jie; Zhang, Xiaotong; Wu, Haiying; Qi, Chun

2018-05-01

Study of signal-to-noise ratio (SNR) of a novel spectral zooming imaging spectrometer (SZIS) based on two identical Wollaston prisms is conducted. According to the theory of radiometry and Fourier transform spectroscopy, we deduce the theoretical equations of SNR of SZIS in spectral domain with consideration of the incident wavelength and the adjustable spectral resolution. An example calculation of SNR of SZIS is performed over 400-1000 nm. The calculation results indicate that SNR with different spectral resolutions of SZIS can be optionally selected by changing the spacing between the two identical Wollaston prisms. This will provide theoretical basis for the design, development and engineering of the developed imaging spectrometer for broad spectrum and SNR requirements.

Hyper-spectral imaging of aircraft exhaust plumes

NASA Astrophysics Data System (ADS)

Bowen, Spencer; Bradley, Kenneth; Gross, Kevin; Perram, Glen; Marciniak, Michael

2008-10-01

An imaging Fourier-transform spectrometer has been used to determine low spatial resolution temperature and chemical species concentration distributions of aircraft jet engine exhaust plumes. An overview of the imaging Fourier transform spectrometer and the methodology of the project is presented. Results to date are shared and future work is discussed. Exhaust plume data from a Turbine Technologies, LTD, SR-30 turbojet engine at three engine settings was collected using a Telops Field-portable Imaging Radiometric Spectrometer Technology Mid-Wave Extended (FIRST-MWE). Although the plume exhibited high temporal frequency fluctuations, temporal averaging of hyper-spectral data-cubes produced steady-state distributions, which, when co-added and Fourier transformed, produced workable spectra. These spectra were then reduced using a simplified gaseous effluent model to fit forward-modeled spectra obtained from the Line-By-Line Radiative Transfer Model (LBLRTM) and the high-resolution transmission (HITRAN) molecular absorption database to determine approximate temperature and concentration distributions. It is theorized that further development of the physical model will produce better agreement between measured and modeled data.

Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning

NASA Astrophysics Data System (ADS)

Beck, J. M.; Bridges, S.; Collins, C.; Rushing, J.; Graves, S. J.

2017-12-01

Researchers at the Information Technology and Systems Center at the University of Alabama in Huntsville are using Deep Learning with Convolutional Neural Networks (CNNs) to develop a method for enhancing the spatial resolutions of moderate resolution (10-60m) multispectral satellite imagery. This enhancement will effectively match the resolutions of imagery from multiple sensors to provide increased global temporal-spatial coverage for a variety of Earth science products. Our research is centered on using Deep Learning for automatically generating transformations for increasing the spatial resolution of remotely sensed images with different spatial, spectral, and temporal resolutions. One of the most important steps in using images from multiple sensors is to transform the different image layers into the same spatial resolution, preferably the highest spatial resolution, without compromising the spectral information. Recent advances in Deep Learning have shown that CNNs can be used to effectively and efficiently upscale or enhance the spatial resolution of multispectral images with the use of an auxiliary data source such as a high spatial resolution panchromatic image. In contrast, we are using both the spatial and spectral details inherent in low spatial resolution multispectral images for image enhancement without the use of a panchromatic image. This presentation will discuss how this technology will benefit many Earth Science applications that use remotely sensed images with moderate spatial resolutions.

Improving 3D Wavelet-Based Compression of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Klimesh, Matthew; Kiely, Aaron; Xie, Hua; Aranki, Nazeeh

2009-01-01

Two methods of increasing the effectiveness of three-dimensional (3D) wavelet-based compression of hyperspectral images have been developed. (As used here, images signifies both images and digital data representing images.) The methods are oriented toward reducing or eliminating detrimental effects of a phenomenon, referred to as spectral ringing, that is described below. In 3D wavelet-based compression, an image is represented by a multiresolution wavelet decomposition consisting of several subbands obtained by applying wavelet transforms in the two spatial dimensions corresponding to the two spatial coordinate axes of the image plane, and by applying wavelet transforms in the spectral dimension. Spectral ringing is named after the more familiar spatial ringing (spurious spatial oscillations) that can be seen parallel to and near edges in ordinary images reconstructed from compressed data. These ringing phenomena are attributable to effects of quantization. In hyperspectral data, the individual spectral bands play the role of edges, causing spurious oscillations to occur in the spectral dimension. In the absence of such corrective measures as the present two methods, spectral ringing can manifest itself as systematic biases in some reconstructed spectral bands and can reduce the effectiveness of compression of spatially-low-pass subbands. One of the two methods is denoted mean subtraction. The basic idea of this method is to subtract mean values from spatial planes of spatially low-pass subbands prior to encoding, because (a) such spatial planes often have mean values that are far from zero and (b) zero-mean data are better suited for compression by methods that are effective for subbands of two-dimensional (2D) images. In this method, after the 3D wavelet decomposition is performed, mean values are computed for and subtracted from each spatial plane of each spatially-low-pass subband. The resulting data are converted to sign-magnitude form and compressed in a manner similar to that of a baseline hyperspectral- image-compression method. The mean values are encoded in the compressed bit stream and added back to the data at the appropriate decompression step. The overhead incurred by encoding the mean values only a few bits per spectral band is negligible with respect to the huge size of a typical hyperspectral data set. The other method is denoted modified decomposition. This method is so named because it involves a modified version of a commonly used multiresolution wavelet decomposition, known in the art as the 3D Mallat decomposition, in which (a) the first of multiple stages of a 3D wavelet transform is applied to the entire dataset and (b) subsequent stages are applied only to the horizontally-, vertically-, and spectrally-low-pass subband from the preceding stage. In the modified decomposition, in stages after the first, not only is the spatially-low-pass, spectrally-low-pass subband further decomposed, but also spatially-low-pass, spectrally-high-pass subbands are further decomposed spatially. Either method can be used alone to improve the quality of a reconstructed image (see figure). Alternatively, the two methods can be combined by first performing modified decomposition, then subtracting the mean values from spatial planes of spatially-low-pass subbands.

Multiscale image fusion using the undecimated wavelet transform with spectral factorization and nonorthogonal filter banks.

PubMed

Ellmauthaler, Andreas; Pagliari, Carla L; da Silva, Eduardo A B

2013-03-01

Multiscale transforms are among the most popular techniques in the field of pixel-level image fusion. However, the fusion performance of these methods often deteriorates for images derived from different sensor modalities. In this paper, we demonstrate that for such images, results can be improved using a novel undecimated wavelet transform (UWT)-based fusion scheme, which splits the image decomposition process into two successive filtering operations using spectral factorization of the analysis filters. The actual fusion takes place after convolution with the first filter pair. Its significantly smaller support size leads to the minimization of the unwanted spreading of coefficient values around overlapping image singularities. This usually complicates the feature selection process and may lead to the introduction of reconstruction errors in the fused image. Moreover, we will show that the nonsubsampled nature of the UWT allows the design of nonorthogonal filter banks, which are more robust to artifacts introduced during fusion, additionally improving the obtained results. The combination of these techniques leads to a fusion framework, which provides clear advantages over traditional multiscale fusion approaches, independent of the underlying fusion rule, and reduces unwanted side effects such as ringing artifacts in the fused reconstruction.

Ultraspectral imaging for propulsion test monitoring

NASA Astrophysics Data System (ADS)

Otten, Leonard John, III; Jones, Bernard A.; Prinzing, Philip; Swantner, William H.; Rafert, Bruce

2002-02-01

Under a NASA Stennis Space Center (SSC) SBIR, technologies required for an imaging spectral radiometer with wavenumber spectral resolution and milliradian spatial resolution that operates over the 8 micrometers to 12 micrometers (LWIR), and 3 micrometers to 5 micrometers (MWIR) bands, for use in a non-intrusive monitoring static rocket firing application are being investigated. The research is based on a spatially modulated Fourier transform spectral imager to take advantage of the inherent benefits in these devices in the MWIR and LWIR. The research verified optical techniques that could be merged with a Sagnac interferometer to create conceptual designs for an LWIR imaging spectrometer that has a 0.4 cm-1 spectral resolution using an available HgCdTe detector. These same techniques produce an MWIR imaging spectrometer with 1.5 cm-1 spectral resolution based on a commercial InSb array. Initial laboratory measurements indicate that the modeled spectral resolution is being met. Applications to environmental measurement applications under standard temperatures can be undertaken by taking advantage of several unique features of the Sagnac interferometer in being able to decouple the limiting aperature from the spectral resolution.

Feature Transformation Detection Method with Best Spectral Band Selection Process for Hyper-spectral Imaging

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike; Brickhouse, Mark

2015-11-01

We present a newly developed feature transformation (FT) detection method for hyper-spectral imagery (HSI) sensors. In essence, the FT method, by transforming the original features (spectral bands) to a different feature domain, may considerably increase the statistical separation between the target and background probability density functions, and thus may significantly improve the target detection and identification performance, as evidenced by the test results in this paper. We show that by differentiating the original spectral, one can completely separate targets from the background using a single spectral band, leading to perfect detection results. In addition, we have proposed an automated best spectral band selection process with a double-threshold scheme that can rank the available spectral bands from the best to the worst for target detection. Finally, we have also proposed an automated cross-spectrum fusion process to further improve the detection performance in lower spectral range (<1000 nm) by selecting the best spectral band pair with multivariate analysis. Promising detection performance has been achieved using a small background material signature library for concept-proving, and has then been further evaluated and verified using a real background HSI scene collected by a HYDICE sensor.

Fusion and quality analysis for remote sensing images using contourlet transform

NASA Astrophysics Data System (ADS)

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

2013-05-01

Recent developments in remote sensing technologies have provided various images with high spatial and spectral resolutions. However, multispectral images have low spatial resolution and panchromatic images have low spectral resolution. Therefore, image fusion techniques are necessary to improve the spatial resolution of spectral images by injecting spatial details of high-resolution panchromatic images. The objective of image fusion is to provide useful information by improving the spatial resolution and the spectral information of the original images. The fusion results can be utilized in various applications, such as military, medical imaging, and remote sensing. This paper addresses two issues in image fusion: i) image fusion method and ii) quality analysis of fusion results. First, a new contourlet-based image fusion method is presented, which is an improvement over the wavelet-based fusion. This fusion method is then applied to a case study to demonstrate its fusion performance. Fusion framework and scheme used in the study are discussed in detail. Second, quality analysis for the fusion results is discussed. We employed various quality metrics in order to analyze the fusion results both spatially and spectrally. Our results indicate that the proposed contourlet-based fusion method performs better than the conventional wavelet-based fusion methods.

Onboard spectral imager data processor

NASA Astrophysics Data System (ADS)

Otten, Leonard J.; Meigs, Andrew D.; Franklin, Abraham J.; Sears, Robert D.; Robison, Mark W.; Rafert, J. Bruce; Fronterhouse, Donald C.; Grotbeck, Ronald L.

1999-10-01

Previous papers have described the concept behind the MightySat II.1 program, the satellite's Fourier Transform imaging spectrometer's optical design, the design for the spectral imaging payload, and its initial qualification testing. This paper discusses the on board data processing designed to reduce the amount of downloaded data by an order of magnitude and provide a demonstration of a smart spaceborne spectral imaging sensor. Two custom components, a spectral imager interface 6U VME card that moves data at over 30 MByte/sec, and four TI C-40 processors mounted to a second 6U VME and daughter card, are used to adapt the sensor to the spacecraft and provide the necessary high speed processing. A system architecture that offers both on board real time image processing and high-speed post data collection analysis of the spectral data has been developed. In addition to the on board processing of the raw data into a usable spectral data volume, one feature extraction technique has been incorporated. This algorithm operates on the basic interferometric data. The algorithm is integrated within the data compression process to search for uploadable feature descriptions.

Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

NASA Technical Reports Server (NTRS)

Blonksi, Slawomir; Gasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

2001-01-01

Multispectral data requirements for Earth science applications are not always studied rigorously studied before a new remote sensing system is designed. A study of the spatial resolution, spectral bandpasses, and radiometric sensitivity requirements of real-world applications would focus the design onto providing maximum benefits to the end-user community. To support systematic studies of multispectral data requirements, the Applications Research Toolbox (ART) has been developed at NASA's Stennis Space Center. The ART software allows users to create and assess simulated datasets while varying a wide range of system parameters. The simulations are based on data acquired by existing multispectral and hyperspectral instruments. The produced datasets can be further evaluated for specific end-user applications. Spectral synthesis of multispectral images from hyperspectral data is a key part of the ART software. In this process, hyperspectral image cubes are transformed into multispectral imagery without changes in spatial sampling and resolution. The transformation algorithm takes into account spectral responses of both the synthesized, broad, multispectral bands and the utilized, narrow, hyperspectral bands. To validate the spectral synthesis algorithm, simulated multispectral images are compared with images collected near-coincidentally by the Landsat 7 ETM+ and the EO-1 ALI instruments. Hyperspectral images acquired with the airborne AVIRIS instrument and with the Hyperion instrument onboard the EO-1 satellite were used as input data to the presented simulations.

Compression of hyper-spectral images using an accelerated nonnegative tensor decomposition

NASA Astrophysics Data System (ADS)

Li, Jin; Liu, Zilong

2017-12-01

Nonnegative tensor Tucker decomposition (NTD) in a transform domain (e.g., 2D-DWT, etc) has been used in the compression of hyper-spectral images because it can remove redundancies between spectrum bands and also exploit spatial correlations of each band. However, the use of a NTD has a very high computational cost. In this paper, we propose a low complexity NTD-based compression method of hyper-spectral images. This method is based on a pair-wise multilevel grouping approach for the NTD to overcome its high computational cost. The proposed method has a low complexity under a slight decrease of the coding performance compared to conventional NTD. We experimentally confirm this method, which indicates that this method has the less processing time and keeps a better coding performance than the case that the NTD is not used. The proposed approach has a potential application in the loss compression of hyper-spectral or multi-spectral images

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Bryant, W. F.

1976-01-01

A C-130 aircraft was flown over the Sam Houston National Forest on March 21, 1973 at 10,000 feet altitude to collect multispectral scanner (MSS) data. Existing textural and spatial automatic processing techniques were used to classify the MSS imagery into specified timber categories. Several classification experiments were performed on this data using features selected from the spectral bands and a textural transform band. The results indicate that (1) spatial post-processing a classified image can cut the classification error to 1/2 or 1/3 of its initial value, (2) spatial post-processing the classified image using combined spectral and textural features produces a resulting image with less error than post-processing a classified image using only spectral features and (3) classification without spatial post processing using the combined spectral textural features tends to produce about the same error rate as a classification without spatial post processing using only spectral features.

Analysis of the Advantages and Limitations of Stationary Imaging Fourier Transform Spectrometer. Revised

NASA Technical Reports Server (NTRS)

Beecken, Brian P.; Kleinman, Randall R.

2004-01-01

New developments in infrared sensor technology have potentially made possible a new space-based system which can measure far-infrared radiation at lower costs (mass, power and expense). The Stationary Imaging Fourier Transform Spectrometer (SIFTS) proposed by NASA Langley Research Center, makes use of new detector array technology. A mathematical model which simulates resolution and spectral range relationships has been developed for analyzing the utility of such a radically new approach to spectroscopy. Calculations with this forward model emulate the effects of a detector array on the ability to retrieve accurate spectral features. Initial computations indicate significant attenuation at high wavenumbers.

Transforming the Geocomputational Battlespace Framework with HDF5

DTIC Science & Technology

2010-08-01

layout level, dataset arrays can be stored in chunks or tiles , enabling fast subsetting of large datasets, including compressed datasets. HDF software...Image Base (CIB) image of the AOI: an orthophoto made from rectified grayscale aerial images b. An IKONOS satellite image made up of 3 spectral

Diagnosis of skin cancer using image processing

NASA Astrophysics Data System (ADS)

Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué; Coronel-Beltrán, Ángel

2014-10-01

In this papera methodology for classifying skin cancerin images of dermatologie spots based on spectral analysis using the K-law Fourier non-lineartechnique is presented. The image is segmented and binarized to build the function that contains the interest area. The image is divided into their respective RGB channels to obtain the spectral properties of each channel. The green channel contains more information and therefore this channel is always chosen. This information is point to point multiplied by a binary mask and to this result a Fourier transform is applied written in nonlinear form. If the real part of this spectrum is positive, the spectral density takeunit values, otherwise are zero. Finally the ratio of the sum of the unit values of the spectral density with the sum of values of the binary mask are calculated. This ratio is called spectral index. When the value calculated is in the spectral index range three types of cancer can be detected. Values found out of this range are benign injure.

Mapping accuracy via spectrally and structurally based filtering techniques: comparisons through visual observations

NASA Astrophysics Data System (ADS)

Chockalingam, Letchumanan

2005-01-01

The data of Gunung Ledang region of Malaysia acquired through LANDSAT are considered to map certain hydrogeolocial features. To map these significant features, image-processing tools such as contrast enhancement, edge detection techniques are employed. The advantages of these techniques over the other methods are evaluated from the point of their validity in properly isolating features of hydrogeolocial interest are discussed. As these techniques take the advantage of spectral aspects of the images, these techniques have several limitations to meet the objectives. To discuss these limitations, a morphological transformation, which generally considers the structural aspects rather than spectral aspects from the image, are applied to provide comparisons between the results derived from spectral based and the structural based filtering techniques.

Fusion of Modis and Palsar Principal Component Images Through Curvelet Transform for Land Cover Classification

NASA Astrophysics Data System (ADS)

Singh, Dharmendra; Kumar, Harish

Earth observation satellites provide data that covers different portions of the electromagnetic spectrum at different spatial and spectral resolutions. The increasing availability of information products generated from satellite images are extending the ability to understand the patterns and dynamics of the earth resource systems at all scales of inquiry. In which one of the most important application is the generation of land cover classification from satellite images for understanding the actual status of various land cover classes. The prospect for the use of satel-lite images in land cover classification is an extremely promising one. The quality of satellite images available for land-use mapping is improving rapidly by development of advanced sensor technology. Particularly noteworthy in this regard is the improved spatial and spectral reso-lution of the images captured by new satellite sensors like MODIS, ASTER, Landsat 7, and SPOT 5. For the full exploitation of increasingly sophisticated multisource data, fusion tech-niques are being developed. Fused images may enhance the interpretation capabilities. The images used for fusion have different temporal, and spatial resolution. Therefore, the fused image provides a more complete view of the observed objects. It is one of the main aim of image fusion to integrate different data in order to obtain more information that can be de-rived from each of the single sensor data alone. A good example of this is the fusion of images acquired by different sensors having a different spatial resolution and of different spectral res-olution. Researchers are applying the fusion technique since from three decades and propose various useful methods and techniques. The importance of high-quality synthesis of spectral information is well suited and implemented for land cover classification. More recently, an underlying multiresolution analysis employing the discrete wavelet transform has been used in image fusion. It was found that multisensor image fusion is a tradeoff between the spectral information from a low resolution multi-spectral images and the spatial information from a high resolution multi-spectral images. With the wavelet transform based fusion method, it is easy to control this tradeoff. A new transform, the curvelet transform was used in recent years by Starck. A ridgelet transform is applied to square blocks of detail frames of undecimated wavelet decomposition, consequently the curvelet transform is obtained. Since the ridgelet transform possesses basis functions matching directional straight lines therefore, the curvelet transform is capable of representing piecewise linear contours on multiple scales through few significant coefficients. This property leads to a better separation between geometric details and background noise, which may be easily reduced by thresholding curvelet coefficients before they are used for fusion. The Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) instrument provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 m to 14.4 m and also it is freely available. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. In this paper, the band 1 of spatial resolution 250 m and bandwidth 620-670 nm, and band 2, of spatial resolution of 250m and bandwidth 842-876 nm is considered as these bands has special features to identify the agriculture and other land covers. In January 2006, the Advanced Land Observing Satellite (ALOS) was successfully launched by the Japan Aerospace Exploration Agency (JAXA). The Phased Arraytype L-band SAR (PALSAR) sensor onboard the satellite acquires SAR imagery at a wavelength of 23.5 cm (frequency 1.27 GHz) with capabilities of multimode and multipolarization observation. PALSAR can operate in several modes: the fine-beam single (FBS) polarization mode (HH), fine-beam dual (FBD) polariza-tion mode (HH/HV or VV/VH), polarimetric (PLR) mode (HH/HV/VH/VV), and ScanSAR (WB) mode (HH/VV) [15]. These makes PALSAR imagery very attractive for spatially and temporally consistent monitoring system. The Overview of Principal Component Analysis is that the most of the information within all the bands can be compressed into a much smaller number of bands with little loss of information. It allows us to extract the low-dimensional subspaces that capture the main linear correlation among the high-dimensional image data. This facilitates viewing the explained variance or signal in the available imagery, allowing both gross and more subtle features in the imagery to be seen. In this paper we have explored the fusion technique for enhancing the land cover classification of low resolution satellite data espe-cially freely available satellite data. For this purpose, we have considered to fuse the PALSAR principal component data with MODIS principal component data. Initially, the MODIS band 1 and band 2 is considered, its principal component is computed. Similarly the PALSAR HH, HV and VV polarized data are considered, and there principal component is also computed. con-sequently, the PALSAR principal component image is fused with MODIS principal component image. The aim of this paper is to analyze the effect of classification accuracy on major type of land cover types like agriculture, water and urban bodies with fusion of PALSAR data to MODIS data. Curvelet transformation has been applied for fusion of these two satellite images and Minimum Distance classification technique has been applied for the resultant fused image. It is qualitatively and visually observed that the overall classification accuracy of MODIS image after fusion is enhanced. This type of fusion technique may be quite helpful in near future to use freely available satellite data to develop monitoring system for different land cover classes on the earth.

WISPIR: A Wide-Field Imaging SPectrograph for the InfraRed for the SPICA Observatory

NASA Technical Reports Server (NTRS)

Benford, Dominic J.; Mundy, Lee G.

2010-01-01

We have undertaken a study of a far infrared imaging spectrometer based on a Fourier transform spectrometer that uses well-understood, high maturity optics, cryogenics, and detectors to further our knowledge of the chemical and astrophysical evolution of the Universe as it formed planets, stars, and the variety of galaxy morphologies that we observe today. The instrument, Wide-field Imaging Spectrometer for the InfraRed (WISPIR), would operate on the SPICA observatory, and will feature a spectral range from 35 - 210 microns and a spectral resolving power of R=1,000 to 6,000, depending on wavelength. WISPIR provides a choice of full-field spectral imaging over a 2'x2' field or long-slit spectral imaging along a 2' slit for studies of astrophysical structures in the local and high-redshift Universe. WISPIR in long-slit mode will attain a sensitivity two orders of magnitude better than what is currently available.

Approximating tasseled cap values to evaluate brightness, greenness, and wetness for the Advanced Land Imager (ALI)

USGS Publications Warehouse

Yamamoto, Kristina H.; Finn, Michael P.

2012-01-01

The Tasseled Cap transformation is a method of image band conversion to enhance spectral information. It primarily is used to detect vegetation using the derived brightness, greenness, and wetness bands. An approximation of Tasseled Cap values for the Advanced Land Imager was investigated and compared to the Landsat Thematic Mapper Tasseled Cap values. Despite sharing similar spectral, temporal, and spatial resolution, the two systems are not interchangeable with regard to Tasseled Cap matrices.

Electro-Optical Imaging Fourier-Transform Spectrometer

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Zhou, Hanying

2006-01-01

An electro-optical (E-O) imaging Fourier-transform spectrometer (IFTS), now under development, is a prototype of improved imaging spectrometers to be used for hyperspectral imaging, especially in the infrared spectral region. Unlike both imaging and non-imaging traditional Fourier-transform spectrometers, the E-O IFTS does not contain any moving parts. Elimination of the moving parts and the associated actuator mechanisms and supporting structures would increase reliability while enabling reductions in size and mass, relative to traditional Fourier-transform spectrometers that offer equivalent capabilities. Elimination of moving parts would also eliminate the vibrations caused by the motions of those parts. Figure 1 schematically depicts a traditional Fourier-transform spectrometer, wherein a critical time delay is varied by translating one the mirrors of a Michelson interferometer. The time-dependent optical output is a periodic representation of the input spectrum. Data characterizing the input spectrum are generated through fast-Fourier-transform (FFT) post-processing of the output in conjunction with the varying time delay.

Guided filter and principal component analysis hybrid method for hyperspectral pansharpening

NASA Astrophysics Data System (ADS)

Qu, Jiahui; Li, Yunsong; Dong, Wenqian

2018-01-01

Hyperspectral (HS) pansharpening aims to generate a fused HS image with high spectral and spatial resolution through integrating an HS image with a panchromatic (PAN) image. A guided filter (GF) and principal component analysis (PCA) hybrid HS pansharpening method is proposed. First, the HS image is interpolated and the PCA transformation is performed on the interpolated HS image. The first principal component (PC1) channel concentrates on the spatial information of the HS image. Different from the traditional PCA method, the proposed method sharpens the PAN image and utilizes the GF to obtain the spatial information difference between the HS image and the enhanced PAN image. Then, in order to reduce spectral and spatial distortion, an appropriate tradeoff parameter is defined and the spatial information difference is injected into the PC1 channel through multiplying by this tradeoff parameter. Once the new PC1 channel is obtained, the fused image is finally generated by the inverse PCA transformation. Experiments performed on both synthetic and real datasets show that the proposed method outperforms other several state-of-the-art HS pansharpening methods in both subjective and objective evaluations.

Fourier Spectral Filter Array for Optimal Multispectral Imaging.

PubMed

Jia, Jie; Barnard, Kenneth J; Hirakawa, Keigo

2016-04-01

Limitations to existing multispectral imaging modalities include speed, cost, range, spatial resolution, and application-specific system designs that lack versatility of the hyperspectral imaging modalities. In this paper, we propose a novel general-purpose single-shot passive multispectral imaging modality. Central to this design is a new type of spectral filter array (SFA) based not on the notion of spatially multiplexing narrowband filters, but instead aimed at enabling single-shot Fourier transform spectroscopy. We refer to this new SFA pattern as Fourier SFA, and we prove that this design solves the problem of optimally sampling the hyperspectral image data.

Hyper-spectral image compression algorithm based on mixing transform of wave band grouping to eliminate redundancy

NASA Astrophysics Data System (ADS)

Xie, ChengJun; Xu, Lin

2008-03-01

This paper presents an algorithm based on mixing transform of wave band grouping to eliminate spectral redundancy, the algorithm adapts to the relativity difference between different frequency spectrum images, and still it works well when the band number is not the power of 2. Using non-boundary extension CDF(2,2)DWT and subtraction mixing transform to eliminate spectral redundancy, employing CDF(2,2)DWT to eliminate spatial redundancy and SPIHT+CABAC for compression coding, the experiment shows that a satisfied lossless compression result can be achieved. Using hyper-spectral image Canal of American JPL laboratory as the data set for lossless compression test, when the band number is not the power of 2, lossless compression result of this compression algorithm is much better than the results acquired by JPEG-LS, WinZip, ARJ, DPCM, the research achievements of a research team of Chinese Academy of Sciences, Minimum Spanning Tree and Near Minimum Spanning Tree, on the average the compression ratio of this algorithm exceeds the above algorithms by 41%,37%,35%,29%,16%,10%,8% respectively; when the band number is the power of 2, for 128 frames of the image Canal, taking 8, 16 and 32 respectively as the number of one group for groupings based on different numbers, considering factors like compression storage complexity, the type of wave band and the compression effect, we suggest using 8 as the number of bands included in one group to achieve a better compression effect. The algorithm of this paper has priority in operation speed and hardware realization convenience.

An adaptive band selection method for dimension reduction of hyper-spectral remote sensing image

NASA Astrophysics Data System (ADS)

Yu, Zhijie; Yu, Hui; Wang, Chen-sheng

2014-11-01

Hyper-spectral remote sensing data can be acquired by imaging the same area with multiple wavelengths, and it normally consists of hundreds of band-images. Hyper-spectral images can not only provide spatial information but also high resolution spectral information, and it has been widely used in environment monitoring, mineral investigation and military reconnaissance. However, because of the corresponding large data volume, it is very difficult to transmit and store Hyper-spectral images. Hyper-spectral image dimensional reduction technique is desired to resolve this problem. Because of the High relation and high redundancy of the hyper-spectral bands, it is very feasible that applying the dimensional reduction method to compress the data volume. This paper proposed a novel band selection-based dimension reduction method which can adaptively select the bands which contain more information and details. The proposed method is based on the principal component analysis (PCA), and then computes the index corresponding to every band. The indexes obtained are then ranked in order of magnitude from large to small. Based on the threshold, system can adaptively and reasonably select the bands. The proposed method can overcome the shortcomings induced by transform-based dimension reduction method and prevent the original spectral information from being lost. The performance of the proposed method has been validated by implementing several experiments. The experimental results show that the proposed algorithm can reduce the dimensions of hyper-spectral image with little information loss by adaptively selecting the band images.

Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.

PubMed

Zhang, Lefei; Zhang, Qian; Du, Bo; Huang, Xin; Tang, Yuan Yan; Tao, Dacheng

2018-01-01

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier. However, multiple features from various domains definitely have different physical meanings and statistical properties, and thus such concatenation has not efficiently explore the complementary properties among different features, which should benefit for boost the feature discriminability. Furthermore, it is also difficult to interpret the transformed results of the concatenated vector. Consequently, finding a physically meaningful consensus low dimensional feature representation of original multiple features is still a challenging task. In order to address these issues, we propose a novel feature learning framework, i.e., the simultaneous spectral-spatial feature selection and extraction algorithm, for hyperspectral images spectral-spatial feature representation and classification. Specifically, the proposed method learns a latent low dimensional subspace by projecting the spectral-spatial feature into a common feature space, where the complementary information has been effectively exploited, and simultaneously, only the most significant original features have been transformed. Encouraging experimental results on three public available hyperspectral remote sensing datasets confirm that our proposed method is effective and efficient.

Spectrographic imaging system

DOEpatents

Morris, Michael D.; Treado, Patrick J.

1991-01-01

An imaging system for providing spectrographically resolved images. The system incorporates a one-dimensional spatial encoding mask which enables an image to be projected onto a two-dimensional image detector after spectral dispersion of the image. The dimension of the image which is lost due to spectral dispersion on the two-dimensional detector is recovered through employing a reverse transform based on presenting a multiplicity of different spatial encoding patterns to the image. The system is especially adapted for detecting Raman scattering of monochromatic light transmitted through or reflected from physical samples. Preferably, spatial encoding is achieved through the use of Hadamard mask which selectively transmits or blocks portions of the image from the sample being evaluated.

Forest tree species clssification based on airborne hyper-spectral imagery

NASA Astrophysics Data System (ADS)

Dian, Yuanyong; Li, Zengyuan; Pang, Yong

2013-10-01

Forest precision classification products were the basic data for surveying of forest resource, updating forest subplot information, logging and design of forest. However, due to the diversity of stand structure, complexity of the forest growth environment, it's difficult to discriminate forest tree species using multi-spectral image. The airborne hyperspectral images can achieve the high spatial and spectral resolution imagery of forest canopy, so it will good for tree species level classification. The aim of this paper was to test the effective of combining spatial and spectral features in airborne hyper-spectral image classification. The CASI hyper spectral image data were acquired from Liangshui natural reserves area. Firstly, we use the MNF (minimum noise fraction) transform method for to reduce the hyperspectral image dimensionality and highlighting variation. And secondly, we use the grey level co-occurrence matrix (GLCM) to extract the texture features of forest tree canopy from the hyper-spectral image, and thirdly we fused the texture and the spectral features of forest canopy to classify the trees species using support vector machine (SVM) with different kernel functions. The results showed that when using the SVM classifier, MNF and texture-based features combined with linear kernel function can achieve the best overall accuracy which was 85.92%. It was also confirm that combine the spatial and spectral information can improve the accuracy of tree species classification.

Analysis of hyperspectral fluorescence images for poultry skin tumor inspection

NASA Astrophysics Data System (ADS)

Kong, Seong G.; Chen, Yud-Ren; Kim, Intaek; Kim, Moon S.

2004-02-01

We present a hyperspectral fluorescence imaging system with a fuzzy inference scheme for detecting skin tumors on poultry carcasses. Hyperspectral images reveal spatial and spectral information useful for finding pathological lesions or contaminants on agricultural products. Skin tumors are not obvious because the visual signature appears as a shape distortion rather than a discoloration. Fluorescence imaging allows the visualization of poultry skin tumors more easily than reflectance. The hyperspectral image samples obtained for this poultry tumor inspection contain 65 spectral bands of fluorescence in the visible region of the spectrum at wavelengths ranging from 425 to 711 nm. The large amount of hyperspectral image data is compressed by use of a discrete wavelet transform in the spatial domain. Principal-component analysis provides an effective compressed representation of the spectral signal of each pixel in the spectral domain. A small number of significant features are extracted from two major spectral peaks of relative fluorescence intensity that have been identified as meaningful spectral bands for detecting tumors. A fuzzy inference scheme that uses a small number of fuzzy rules and Gaussian membership functions successfully detects skin tumors on poultry carcasses. Spatial-filtering techniques are used to significantly reduce false positives.

Acquisition and visualization techniques for narrow spectral color imaging.

PubMed

Neumann, László; García, Rafael; Basa, János; Hegedüs, Ramón

2013-06-01

This paper introduces a new approach in narrow-band imaging (NBI). Existing NBI techniques generate images by selecting discrete bands over the full visible spectrum or an even wider spectral range. In contrast, here we perform the sampling with filters covering a tight spectral window. This image acquisition method, named narrow spectral imaging, can be particularly useful when optical information is only available within a narrow spectral window, such as in the case of deep-water transmittance, which constitutes the principal motivation of this work. In this study we demonstrate the potential of the proposed photographic technique on nonunderwater scenes recorded under controlled conditions. To this end three multilayer narrow bandpass filters were employed, which transmit at 440, 456, and 470 nm bluish wavelengths, respectively. Since the differences among the images captured in such a narrow spectral window can be extremely small, both image acquisition and visualization require a novel approach. First, high-bit-depth images were acquired with multilayer narrow-band filters either placed in front of the illumination or mounted on the camera lens. Second, a color-mapping method is proposed, using which the input data can be transformed onto the entire display color gamut with a continuous and perceptually nearly uniform mapping, while ensuring optimally high information content for human perception.

Fast Infrared Chemical Imaging with a Quantum Cascade Laser

PubMed Central

2015-01-01

Infrared (IR) spectroscopic imaging systems are a powerful tool for visualizing molecular microstructure of a sample without the need for dyes or stains. Table-top Fourier transform infrared (FT-IR) imaging spectrometers, the current established technology, can record broadband spectral data efficiently but requires scanning the entire spectrum with a low throughput source. The advent of high-intensity, broadly tunable quantum cascade lasers (QCL) has now accelerated IR imaging but results in a fundamentally different type of instrument and approach, namely, discrete frequency IR (DF-IR) spectral imaging. While the higher intensity of the source provides a higher signal per channel, the absence of spectral multiplexing also provides new opportunities and challenges. Here, we couple a rapidly tunable QCL with a high performance microscope equipped with a cooled focal plane array (FPA) detector. Our optical system is conceptualized to provide optimal performance based on recent theory and design rules for high-definition (HD) IR imaging. Multiple QCL units are multiplexed together to provide spectral coverage across the fingerprint region (776.9 to 1904.4 cm–1) in our DF-IR microscope capable of broad spectral coverage, wide-field detection, and diffraction-limited spectral imaging. We demonstrate that the spectral and spatial fidelity of this system is at least as good as the best FT-IR imaging systems. Our configuration provides a speedup for equivalent spectral signal-to-noise ratio (SNR) compared to the best spectral quality from a high-performance linear array system that has 10-fold larger pixels. Compared to the fastest available HD FT-IR imaging system, we demonstrate scanning of large tissue microarrays (TMA) in 3-orders of magnitude smaller time per essential spectral frequency. These advances offer new opportunities for high throughput IR chemical imaging, especially for the measurement of cells and tissues. PMID:25474546

Fast infrared chemical imaging with a quantum cascade laser.

PubMed

Yeh, Kevin; Kenkel, Seth; Liu, Jui-Nung; Bhargava, Rohit

2015-01-06

Infrared (IR) spectroscopic imaging systems are a powerful tool for visualizing molecular microstructure of a sample without the need for dyes or stains. Table-top Fourier transform infrared (FT-IR) imaging spectrometers, the current established technology, can record broadband spectral data efficiently but requires scanning the entire spectrum with a low throughput source. The advent of high-intensity, broadly tunable quantum cascade lasers (QCL) has now accelerated IR imaging but results in a fundamentally different type of instrument and approach, namely, discrete frequency IR (DF-IR) spectral imaging. While the higher intensity of the source provides a higher signal per channel, the absence of spectral multiplexing also provides new opportunities and challenges. Here, we couple a rapidly tunable QCL with a high performance microscope equipped with a cooled focal plane array (FPA) detector. Our optical system is conceptualized to provide optimal performance based on recent theory and design rules for high-definition (HD) IR imaging. Multiple QCL units are multiplexed together to provide spectral coverage across the fingerprint region (776.9 to 1904.4 cm(-1)) in our DF-IR microscope capable of broad spectral coverage, wide-field detection, and diffraction-limited spectral imaging. We demonstrate that the spectral and spatial fidelity of this system is at least as good as the best FT-IR imaging systems. Our configuration provides a speedup for equivalent spectral signal-to-noise ratio (SNR) compared to the best spectral quality from a high-performance linear array system that has 10-fold larger pixels. Compared to the fastest available HD FT-IR imaging system, we demonstrate scanning of large tissue microarrays (TMA) in 3-orders of magnitude smaller time per essential spectral frequency. These advances offer new opportunities for high throughput IR chemical imaging, especially for the measurement of cells and tissues.

Application and evaluation of ISVR method in QuickBird image fusion

NASA Astrophysics Data System (ADS)

Cheng, Bo; Song, Xiaolu

2014-05-01

QuickBird satellite images are widely used in many fields, and applications have put forward high requirements for the integration of the spatial information and spectral information of the imagery. A fusion method for high resolution remote sensing images based on ISVR is identified in this study. The core principle of ISVS is taking the advantage of radicalization targeting to remove the effect of different gain and error of satellites' sensors. Transformed from DN to radiance, the multi-spectral image's energy is used to simulate the panchromatic band. The linear regression analysis is carried through the simulation process to find a new synthetically panchromatic image, which is highly linearly correlated to the original panchromatic image. In order to evaluate, test and compare the algorithm results, this paper used ISVR and other two different fusion methods to give a comparative study of the spatial information and spectral information, taking the average gradient and the correlation coefficient as an indicator. Experiments showed that this method could significantly improve the quality of fused image, especially in preserving spectral information, to maximize the spectral information of original multispectral images, while maintaining abundant spatial information.

PET and MRI image fusion based on combination of 2-D Hilbert transform and IHS method.

PubMed

Haddadpour, Mozhdeh; Daneshvar, Sabalan; Seyedarabi, Hadi

2017-08-01

The process of medical image fusion is combining two or more medical images such as Magnetic Resonance Image (MRI) and Positron Emission Tomography (PET) and mapping them to a single image as fused image. So purpose of our study is assisting physicians to diagnose and treat the diseases in the least of the time. We used Magnetic Resonance Image (MRI) and Positron Emission Tomography (PET) as input images, so fused them based on combination of two dimensional Hilbert transform (2-D HT) and Intensity Hue Saturation (IHS) method. Evaluation metrics that we apply are Discrepancy (D k ) as an assessing spectral features and Average Gradient (AG k ) as an evaluating spatial features and also Overall Performance (O.P) to verify properly of the proposed method. In this paper we used three common evaluation metrics like Average Gradient (AG k ) and the lowest Discrepancy (D k ) and Overall Performance (O.P) to evaluate the performance of our method. Simulated and numerical results represent the desired performance of proposed method. Since that the main purpose of medical image fusion is preserving both spatial and spectral features of input images, so based on numerical results of evaluation metrics such as Average Gradient (AG k ), Discrepancy (D k ) and Overall Performance (O.P) and also desired simulated results, it can be concluded that our proposed method can preserve both spatial and spectral features of input images. Copyright © 2017 Chang Gung University. Published by Elsevier B.V. All rights reserved.

Multispectral image sharpening using wavelet transform techniques and spatial correlation of edges

USGS Publications Warehouse

Lemeshewsky, George P.; Schowengerdt, Robert A.

2000-01-01

Several reported image fusion or sharpening techniques are based on the discrete wavelet transform (DWT). The technique described here uses a pixel-based maximum selection rule to combine respective transform coefficients of lower spatial resolution near-infrared (NIR) and higher spatial resolution panchromatic (pan) imagery to produce a sharpened NIR image. Sharpening assumes a radiometric correlation between the spectral band images. However, there can be poor correlation, including edge contrast reversals (e.g., at soil-vegetation boundaries), between the fused images and, consequently, degraded performance. To improve sharpening, a local area-based correlation technique originally reported for edge comparison with image pyramid fusion is modified for application with the DWT process. Further improvements are obtained by using redundant, shift-invariant implementation of the DWT. Example images demonstrate the improvements in NIR image sharpening with higher resolution pan imagery.

Cinematic camera emulation using two-dimensional color transforms

NASA Astrophysics Data System (ADS)

McElvain, Jon S.; Gish, Walter

2015-02-01

For cinematic and episodic productions, on-set look management is an important component of the creative process, and involves iterative adjustments of the set, actors, lighting and camera configuration. Instead of using the professional motion capture device to establish a particular look, the use of a smaller form factor DSLR is considered for this purpose due to its increased agility. Because the spectral response characteristics will be different between the two camera systems, a camera emulation transform is needed to approximate the behavior of the destination camera. Recently, twodimensional transforms have been shown to provide high-accuracy conversion of raw camera signals to a defined colorimetric state. In this study, the same formalism is used for camera emulation, whereby a Canon 5D Mark III DSLR is used to approximate the behavior a Red Epic cinematic camera. The spectral response characteristics for both cameras were measured and used to build 2D as well as 3x3 matrix emulation transforms. When tested on multispectral image databases, the 2D emulation transforms outperform their matrix counterparts, particularly for images containing highly chromatic content.

Hyperspectral imaging for the detection of retinal disease

NASA Astrophysics Data System (ADS)

Harvey, Andrew R.; Lawlor, Joanne; McNaught, Andrew I.; Williams, John W.; Fletcher-Holmes, David W.

2002-11-01

Hyperspectral imaging (HSI) shows great promise for the detection and classification of several diseases, particularly in the fields of "optical biopsy" as applied to oncology, and functional retinal imaging in ophthalmology. In this paper, we discuss the application of HSI to the detection of retinal diseases and technological solutions that address some of the fundamental difficulties of spectral imaging within the eye. HSI of the retina offers a route to non-invasively deduce biochemical and metabolic processes within the retina. For example it shows promise for the mapping of retinal blood perfusion using spectral signatures of oxygenated and deoxygenated hemoglobin. Compared with other techniques using just a few spectral measurements, it offers improved classification in the presence of spectral cross-contamination by pigments and other components within the retina. There are potential applications for this imaging technique in the investigation and treatment of the eye complications of diabetes, and other diseases involving disturbances to the retinal, or optic-nerve-head circulation. It is well known that high-performance HSI requires high signal-to-noise ratios (SNR) whereas the application of any imaging technique within the eye must cope with the twin limitations of the small numerical aperture provided by the entrance pupil to the eye and the limit on the radiant power at the retina. We advocate the use of spectrally-multiplexed spectral imaging techniques (the traditional filter wheel is a traditional example). These approaches enable a flexible approach to spectral imaging, with wider spectral range, higher SNRs and lower light intensity at the retina than could be achieved using a Fourier-transform (FT) approach. We report the use of spectral imaging to provide calibrated spectral albedo images of healthy and diseased retinas and the use of this data for screening purposes. These images clearly demonstrate the ability to distinguish between oxygenated and deoxygenated hemoglobin using spectral imaging and this shows promise for the early detection of various retinopathies.

Superpixel Based Factor Analysis and Target Transformation Method for Martian Minerals Detection

NASA Astrophysics Data System (ADS)

Wu, X.; Zhang, X.; Lin, H.

2018-04-01

The Factor analysis and target transformation (FATT) is an effective method to test for the presence of particular mineral on Martian surface. It has been used both in thermal infrared (Thermal Emission Spectrometer, TES) and near-infrared (Compact Reconnaissance Imaging Spectrometer for Mars, CRISM) hyperspectral data. FATT derived a set of orthogonal eigenvectors from a mixed system and typically selected first 10 eigenvectors to least square fit the library mineral spectra. However, minerals present only in a limited pixels will be ignored because its weak spectral features compared with full image signatures. Here, we proposed a superpixel based FATT method to detect the mineral distributions on Mars. The simple linear iterative clustering (SLIC) algorithm was used to partition the CRISM image into multiple connected image regions with spectral homogeneous to enhance the weak signatures by increasing their proportion in a mixed system. A least square fitting was used in target transformation and performed to each region iteratively. Finally, the distribution of the specific minerals in image was obtained, where fitting residual less than a threshold represent presence and otherwise absence. We validate our method by identifying carbonates in a well analysed CRISM image in Nili Fossae on Mars. Our experimental results indicate that the proposed method work well both in simulated and real data sets.

Sharpending of the Vnir and SWIR Bands of the Wide Band Spectral Imager Onboard Tiangong-II Imagery Using the Selected Bands

NASA Astrophysics Data System (ADS)

Liu, Q.; Li, X.; Liu, G.; Huang, C.; Li, H.; Guan, X.

2018-04-01

The Tiangong-II space lab was launched at the Jiuquan Satellite Launch Center of China on September 15, 2016. The Wide Band Spectral Imager (WBSI) onboard the Tiangong-II has 14 visible and near-infrared (VNIR) spectral bands covering the range from 403-990 nm and two shortwave infrared (SWIR) bands covering the range from 1230-1250 nm and 1628-1652 nm respectively. In this paper the selected bands are proposed which aims at considering the closest spectral similarities between the VNIR with 100 m spatial resolution and SWIR bands with 200 m spatial resolution. The evaluation of Gram-Schmidt transform (GS) sharpening techniques embedded in ENVI software is presented based on four types of the different low resolution pan band. The experimental results indicated that the VNIR band with higher CC value with the raw SWIR Band was selected, more texture information was injected the corresponding sharpened SWIR band image, and at that time another sharpened SWIR band image preserve the similar spectral and texture characteristics to the raw SWIR band image.

Fourier transform infrared spectroscopy microscopic imaging classification based on spatial-spectral features

NASA Astrophysics Data System (ADS)

Liu, Lian; Yang, Xiukun; Zhong, Mingliang; Liu, Yao; Jing, Xiaojun; Yang, Qin

2018-04-01

The discrete fractional Brownian incremental random (DFBIR) field is used to describe the irregular, random, and highly complex shapes of natural objects such as coastlines and biological tissues, for which traditional Euclidean geometry cannot be used. In this paper, an anisotropic variable window (AVW) directional operator based on the DFBIR field model is proposed for extracting spatial characteristics of Fourier transform infrared spectroscopy (FTIR) microscopic imaging. Probabilistic principal component analysis first extracts spectral features, and then the spatial features of the proposed AVW directional operator are combined with the former to construct a spatial-spectral structure, which increases feature-related information and helps a support vector machine classifier to obtain more efficient distribution-related information. Compared to Haralick’s grey-level co-occurrence matrix, Gabor filters, and local binary patterns (e.g. uniform LBPs, rotation-invariant LBPs, uniform rotation-invariant LBPs), experiments on three FTIR spectroscopy microscopic imaging datasets show that the proposed AVW directional operator is more advantageous in terms of classification accuracy, particularly for low-dimensional spaces of spatial characteristics.

Hyperspectral imaging simulation of object under sea-sky background

NASA Astrophysics Data System (ADS)

Wang, Biao; Lin, Jia-xuan; Gao, Wei; Yue, Hui

2016-10-01

Remote sensing image simulation plays an important role in spaceborne/airborne load demonstration and algorithm development. Hyperspectral imaging is valuable in marine monitoring, search and rescue. On the demand of spectral imaging of objects under the complex sea scene, physics based simulation method of spectral image of object under sea scene is proposed. On the development of an imaging simulation model considering object, background, atmosphere conditions, sensor, it is able to examine the influence of wind speed, atmosphere conditions and other environment factors change on spectral image quality under complex sea scene. Firstly, the sea scattering model is established based on the Philips sea spectral model, the rough surface scattering theory and the water volume scattering characteristics. The measured bi directional reflectance distribution function (BRDF) data of objects is fit to the statistical model. MODTRAN software is used to obtain solar illumination on the sea, sky brightness, the atmosphere transmittance from sea to sensor and atmosphere backscattered radiance, and Monte Carlo ray tracing method is used to calculate the sea surface object composite scattering and spectral image. Finally, the object spectrum is acquired by the space transformation, radiation degradation and adding the noise. The model connects the spectrum image with the environmental parameters, the object parameters, and the sensor parameters, which provide a tool for the load demonstration and algorithm development.

Two Long-Wave Infrared Spectral Polarimeters for Use in Understanding Polarization Phenomenology

DTIC Science & Technology

2002-05-01

3550 Aberdeen SE Kirtland Air Force Base, New Mexico 87117 Abstract. Spectrally varying long-wave infrared ( LWIR ) polarization measurements can be used...to identify materials and to discriminate samples from a cluttered background. Two LWIR instruments have been built and fielded by the Air Force...Research Laboratory: a multispectral LWIR imaging polarimeter (LIP) and a full-Stokes Fourier transform in- frared (FTIR) spectral polarimeter (FSP

A hybrid spatial-spectral denoising method for infrared hyperspectral images using 2DPCA

NASA Astrophysics Data System (ADS)

Huang, Jun; Ma, Yong; Mei, Xiaoguang; Fan, Fan

2016-11-01

The traditional noise reduction methods for 3-D infrared hyperspectral images typically operate independently in either the spatial or spectral domain, and such methods overlook the relationship between the two domains. To address this issue, we propose a hybrid spatial-spectral method in this paper to link both domains. First, principal component analysis and bivariate wavelet shrinkage are performed in the 2-D spatial domain. Second, 2-D principal component analysis transformation is conducted in the 1-D spectral domain to separate the basic components from detail ones. The energy distribution of noise is unaffected by orthogonal transformation; therefore, the signal-to-noise ratio of each component is used as a criterion to determine whether a component should be protected from over-denoising or denoised with certain 1-D denoising methods. This study implements the 1-D wavelet shrinking threshold method based on Stein's unbiased risk estimator, and the quantitative results on publicly available datasets demonstrate that our method can improve denoising performance more effectively than other state-of-the-art methods can.

A new method of Quickbird own image fusion

NASA Astrophysics Data System (ADS)

Han, Ying; Jiang, Hong; Zhang, Xiuying

2009-10-01

With the rapid development of remote sensing technology, the means of accessing to remote sensing data become increasingly abundant, thus the same area can form a large number of multi-temporal, different resolution image sequence. At present, the fusion methods are mainly: HPF, IHS transform method, PCA method, Brovey, Mallat algorithm and wavelet transform and so on. There exists a serious distortion of the spectrums in the IHS transform, Mallat algorithm omits low-frequency information of the high spatial resolution images, the integration results of which has obvious blocking effects. Wavelet multi-scale decomposition for different sizes, the directions, details and the edges can have achieved very good results, but different fusion rules and algorithms can achieve different effects. This article takes the Quickbird own image fusion as an example, basing on wavelet transform and HVS, wavelet transform and IHS integration. The result shows that the former better. This paper introduces the correlation coefficient, the relative average spectral error index and usual index to evaluate the quality of image.

Electro-optic Imaging Fourier Transform Spectrometer

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

2005-01-01

JPL is developing an innovative compact, low mass, Electro-Optic Imaging Fourier Transform Spectrometer (E-O IFTS) for hyperspectral imaging applications. The spectral region of this spectrometer will be 1 - 2.5 micron (1000-4000/cm) to allow high-resolution, high-speed hyperspectral imaging applications. One application will be the remote sensing of the measurement of a large number of different atmospheric gases simultaneously in the same airmass. Due to the use of a combination of birefringent phase retarders and multiple achromatic phase switches to achieve phase delay, this spectrometer is capable of hyperspectral measurements similar to that of the conventional Fourier transform spectrometer but without any moving parts. In this paper, the principle of operations, system architecture and recent experimental progress will be presented.

Electro-optic Imaging Fourier Transform Spectrometer

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

2005-01-01

JPL is developing an innovative compact, low mass, Electro-Optic Imaging Fourier Transform Spectrometer (E-0IFTS) for hyperspectral imaging applications. The spectral region of this spectrometer will be 1 - 2.5 pm (1000 -4000 cm-') to allow high-resolution, high-speed hyperspectral imaging applications [l-51. One application will be theremote sensing of the measurement of a large number of different atmospheric gases simultaneously in the sameairmass. Due to the use of a combination of birefiingent phase retarders and multiple achromatic phase switches toachieve phase delay, this spectrometer is capable of hyperspectral measurements similar to that of the conventionalFourier transform spectrometer but without any moving parts. In this paper, the principle of operations, systemarchitecture and recent experimental progress will be presen.

Comparison of the Spectral Properties of Pansharpened Images Generated from AVNIR-2 and Prism Onboard Alos

NASA Astrophysics Data System (ADS)

Matsuoka, M.

2012-07-01

A considerable number of methods for pansharpening remote-sensing images have been developed to generate higher spatial resolution multispectral images by the fusion of lower resolution multispectral images and higher resolution panchromatic images. Because pansharpening alters the spectral properties of multispectral images, method selection is one of the key factors influencing the accuracy of subsequent analyses such as land-cover classification or change detection. In this study, seven pixel-based pansharpening methods (additive wavelet intensity, additive wavelet principal component, generalized Laplacian pyramid with spectral distortion minimization, generalized intensity-hue-saturation (GIHS) transform, GIHS adaptive, Gram-Schmidt spectral sharpening, and block-based synthetic variable ratio) were compared using AVNIR-2 and PRISM onboard ALOS from the viewpoint of the preservation of spectral properties of AVNIR-2. A visual comparison was made between pansharpened images generated from spatially degraded AVNIR-2 and original images over urban, agricultural, and forest areas. The similarity of the images was evaluated in terms of the image contrast, the color distinction, and the brightness of the ground objects. In the quantitative assessment, three kinds of statistical indices, correlation coefficient, ERGAS, and Q index, were calculated by band and land-cover type. These scores were relatively superior in bands 2 and 3 compared with the other two bands, especially over urban and agricultural areas. Band 4 showed a strong dependency on the land-cover type. This was attributable to the differences in the observing spectral wavelengths of the sensors and local scene variances.

Research on Remote Sensing Image Classification Based on Feature Level Fusion

NASA Astrophysics Data System (ADS)

Yuan, L.; Zhu, G.

2018-04-01

Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

Electro-optic imaging Fourier transform spectrometer

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor); Znod, Hanying (Inventor)

2009-01-01

An Electro-Optic Imaging Fourier Transform Spectrometer (EOIFTS) for Hyperspectral Imaging is described. The EOIFTS includes an input polarizer, an output polarizer, and a plurality of birefringent phase elements. The relative orientations of the polarizers and birefringent phase elements can be changed mechanically or via a controller, using ferroelectric liquid crystals, to substantially measure the spectral Fourier components of light propagating through the EIOFTS. When achromatic switches are used as an integral part of the birefringent phase elements, the EIOFTS becomes suitable for broadband applications, with over 1 micron infrared bandwidth.

Remote Sensing Image Fusion Method Based on Nonsubsampled Shearlet Transform and Sparse Representation

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen; Li, Shutao

2015-12-01

The remote sensing image fusion is an important preprocessing technique in remote sensing image processing. In this paper, a remote sensing image fusion method based on the nonsubsampled shearlet transform (NSST) with sparse representation (SR) is proposed. Firstly, the low resolution multispectral (MS) image is upsampled and color space is transformed from Red-Green-Blue (RGB) to Intensity-Hue-Saturation (IHS). Then, the high resolution panchromatic (PAN) image and intensity component of MS image are decomposed by NSST to high and low frequency coefficients. The low frequency coefficients of PAN and the intensity component are fused by the SR with the learned dictionary. The high frequency coefficients of intensity component and PAN image are fused by local energy based fusion rule. Finally, the fused result is obtained by performing inverse NSST and inverse IHS transform. The experimental results on IKONOS and QuickBird satellites demonstrate that the proposed method provides better spectral quality and superior spatial information in the fused image than other remote sensing image fusion methods both in visual effect and object evaluation.

Computerized simulation of color appearance for anomalous trichromats using the multispectral image.

PubMed

Yaguchi, Hirohisa; Luo, Junyan; Kato, Miharu; Mizokami, Yoko

2018-04-01

Most color simulators for color deficiencies are based on the tristimulus values and are intended to simulate the appearance of an image for dichromats. Statistics show that there are more anomalous trichromats than dichromats. Furthermore, the spectral sensitivities of anomalous cones are different from those of normal cones. Clinically, the types of color defects are characterized through Rayleigh color matching, where the observer matches a spectral yellow to a mixture of spectral red and green. The midpoints of the red/green ratios deviate from a normal trichromat. This means that any simulation based on the tristimulus values defined by a normal trichromat cannot predict the color appearance of anomalous Rayleigh matches. We propose a computerized simulation of the color appearance for anomalous trichromats using multispectral images. First, we assume that anomalous trichromats possess a protanomalous (green shifted) or deuteranomalous (red shifted) pigment instead of a normal (L or M) one. Second, we assume that the luminance will be given by L+M, and red/green and yellow/blue opponent color stimulus values are defined through L-M and (L+M)-S, respectively. Third, equal-energy white will look white for all observers. The spectral sensitivities of the luminance and the two opponent color channels are multiplied by the spectral radiance of each pixel of a multispectral image to give the luminance and opponent color stimulus values of the entire image. In the next stage of color reproduction for normal observers, the luminance and two opponent color channels are transformed into XYZ tristimulus values and then transformed into sRGB to reproduce a final image for anomalous trichromats. The proposed simulation can be used to predict the Rayleigh color matches for anomalous trichromats. We also conducted experiments to evaluate the appearance of simulated images by color deficient observers and verified the reliability of the simulation.

Blind Forensics of Successive Geometric Transformations in Digital Images Using Spectral Method: Theory and Applications.

PubMed

Chen, Chenglong; Ni, Jiangqun; Shen, Zhaoyi; Shi, Yun Qing

2017-06-01

Geometric transformations, such as resizing and rotation, are almost always needed when two or more images are spliced together to create convincing image forgeries. In recent years, researchers have developed many digital forensic techniques to identify these operations. Most previous works in this area focus on the analysis of images that have undergone single geometric transformations, e.g., resizing or rotation. In several recent works, researchers have addressed yet another practical and realistic situation: successive geometric transformations, e.g., repeated resizing, resizing-rotation, rotation-resizing, and repeated rotation. We will also concentrate on this topic in this paper. Specifically, we present an in-depth analysis in the frequency domain of the second-order statistics of the geometrically transformed images. We give an exact formulation of how the parameters of the first and second geometric transformations influence the appearance of periodic artifacts. The expected positions of characteristic resampling peaks are analytically derived. The theory developed here helps to address the gap left by previous works on this topic and is useful for image security and authentication, in particular, the forensics of geometric transformations in digital images. As an application of the developed theory, we present an effective method that allows one to distinguish between the aforementioned four different processing chains. The proposed method can further estimate all the geometric transformation parameters. This may provide useful clues for image forgery detection.

Sculpting narrowband Fano resonances inherent in the large-area mid-infrared photonic crystal microresonators for spectroscopic imaging

PubMed Central

Liu, Jui-Nung; Schulmerich, Matthew V.; Bhargava, Rohit; Cunningham, Brian T.

2014-01-01

Fourier transform infrared (FT-IR) imaging spectrometers are almost universally used to record microspectroscopic imaging data in the mid-infrared (mid-IR) spectral region. While the commercial standard, interferometry necessitates collection of large spectral regions, requires a large data handling overhead for microscopic imaging and is slow. Here we demonstrate an approach for mid-IR spectroscopic imaging at selected discrete wavelengths using narrowband resonant filtering of a broadband thermal source, enabled by high-performance guided-mode Fano resonances in one-layer, large-area mid-IR photonic crystals on a glass substrate. The microresonant devices enable discrete frequency IR (DF-IR), in which a limited number of wavelengths that are of interest are recorded using a mechanically robust instrument. This considerably simplifies instrumentation as well as overhead of data acquisition, storage and analysis for large format imaging with array detectors. To demonstrate the approach, we perform DF-IR spectral imaging of a polymer USAF resolution target and human tissue in the C−H stretching region (2600−3300 cm−1). DF-IR spectroscopy and imaging can be generalized to other IR spectral regions and can serve as an analytical tool for environmental and biomedical applications. PMID:25089433

Calibration of the Geostationary Imaging Fourier Transform Spectrometer (GIFTS)

NASA Technical Reports Server (NTRS)

Best, F. A.; Revercomb, H. E.; Bingham, G. E.; Knuteson, R. O.; Tobin, D. C.; LaPorte, D. D.; Smith, W. L.

2001-01-01

The NASA New Millennium Program's Geostationary Imaging Fourier Transform Spectrometer (GIFTS) requires highly accurate radiometric and spectral calibration in order to carry out its mission to provide water vapor, wind, temperature, and trace gas profiling from geostationary orbit. A calibration concept has been developed for the GIFTS Phase A instrument design. The in-flight calibration is performed using views of two on-board blackbody sources along with cold space. A radiometric calibration uncertainty analysis has been developed and used to show that the expected performance for GIFTS exceeds its top level requirement to measure brightness temperature to better than 1 K. For the Phase A GIFTS design, the spectral calibration is established by the highly stable diode laser used as the reference for interferogram sampling, and verified with comparisons to atmospheric calculations.

Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS): Imaging and Tracking Capability

NASA Technical Reports Server (NTRS)

Zhou, D. K.; Larar, A. M.; Liu, Xu; Reisse, R. A.; Smith, W. L.; Revercomb, H. E.; Bingham, G. E.; Zollinger, L. J.; Tansock, J. J.; Huppi, Ronald J.

2007-01-01

The geosynchronous-imaging Fourier transform spectrometer (GIFTS) engineering demonstration unit (EDU) is an imaging infrared spectrometer designed for atmospheric soundings. It measures the infrared spectrum in two spectral bands (14.6 to 8.8 microns, 6.0 to 4.4 microns) using two 128 128 detector arrays with a spectral resolution of 0.57/cm with a scan duration of approx. 11 seconds. From a geosynchronous orbit, the instrument will have the capability of taking successive measurements of such data to scan desired regions of the globe, from which atmospheric status, cloud parameters, wind field profiles, and other derived products can be retrieved. The GIFTS EDU provides a flexible and accurate testbed for the new challenges of the emerging hyperspectral era. The EDU ground-based measurement experiment, held in Logan, Utah during September 2006, demonstrated its extensive capabilities and potential for geosynchronous and other applications (e.g., Earth observing environmental measurements). This paper addresses the experiment objectives and overall performance of the sensor system with a focus on the GIFTS EDU imaging capability and proof of the GIFTS measurement concept.

Multispectral Wavefronts Retrieval in Digital Holographic Three-Dimensional Imaging Spectrometry

NASA Astrophysics Data System (ADS)

Yoshimori, Kyu

2010-04-01

This paper deals with a recently developed passive interferometric technique for retrieving a set of spectral components of wavefronts that are propagating from a spatially incoherent, polychromatic object. The technique is based on measurement of 5-D spatial coherence function using a suitably designed interferometer. By applying signal processing, including aperture synthesis and spectral decomposition, one may obtains a set of wavefronts of different spectral bands. Since each wavefront is equivalent to the complex Fresnel hologram at a particular spectrum of the polychromatic object, application of the conventional Fresnel transform yields 3-D image of different spectrum. Thus, this technique of multispectral wavefronts retrieval provides a new type of 3-D imaging spectrometry based on a fully passive interferometry. Experimental results are also shown to demonstrate the validity of the method.

Use of feature extraction techniques for the texture and context information in ERTS imagery: Spectral and textural processing of ERTS imagery. [classification of Kansas land use

NASA Technical Reports Server (NTRS)

Haralick, R. H. (Principal Investigator); Bosley, R. J.

1974-01-01

The author has identified the following significant results. A procedure was developed to extract cross-band textural features from ERTS MSS imagery. Evolving from a single image texture extraction procedure which uses spatial dependence matrices to measure relative co-occurrence of nearest neighbor grey tones, the cross-band texture procedure uses the distribution of neighboring grey tone N-tuple differences to measure the spatial interrelationships, or co-occurrences, of the grey tone N-tuples present in a texture pattern. In both procedures, texture is characterized in such a way as to be invariant under linear grey tone transformations. However, the cross-band procedure complements the single image procedure by extracting texture information and spectral information contained in ERTS multi-images. Classification experiments show that when used alone, without spectral processing, the cross-band texture procedure extracts more information than the single image texture analysis. Results show an improvement in average correct classification from 86.2% to 88.8% for ERTS image no. 1021-16333 with the cross-band texture procedure. However, when used together with spectral features, the single image texture plus spectral features perform better than the cross-band texture plus spectral features, with an average correct classification of 93.8% and 91.6%, respectively.

Coregistration refinement of hyperspectral images and DSM: An object-based approach using spectral information

NASA Astrophysics Data System (ADS)

Avbelj, Janja; Iwaszczuk, Dorota; Müller, Rupert; Reinartz, Peter; Stilla, Uwe

2015-02-01

For image fusion in remote sensing applications the georeferencing accuracy using position, attitude, and camera calibration measurements can be insufficient. Thus, image processing techniques should be employed for precise coregistration of images. In this article a method for multimodal object-based image coregistration refinement between hyperspectral images (HSI) and digital surface models (DSM) is presented. The method is divided in three parts: object outline detection in HSI and DSM, matching, and determination of transformation parameters. The novelty of our proposed coregistration refinement method is the use of material properties and height information of urban objects from HSI and DSM, respectively. We refer to urban objects as objects which are typical in urban environments and focus on buildings by describing them with 2D outlines. Furthermore, the geometric accuracy of these detected building outlines is taken into account in the matching step and for the determination of transformation parameters. Hence, a stochastic model is introduced to compute optimal transformation parameters. The feasibility of the method is shown by testing it on two aerial HSI of different spatial and spectral resolution, and two DSM of different spatial resolution. The evaluation is carried out by comparing the accuracies of the transformations parameters to the reference parameters, determined by considering object outlines at much higher resolution, and also by computing the correctness and the quality rate of the extracted outlines before and after coregistration refinement. Results indicate that using outlines of objects instead of only line segments is advantageous for coregistration of HSI and DSM. The extraction of building outlines in comparison to the line cue extraction provides a larger amount of assigned lines between the images and is more robust to outliers, i.e. false matches.

The angular difference function and its application to image registration.

PubMed

Keller, Yosi; Shkolnisky, Yoel; Averbuch, Amir

2005-06-01

The estimation of large motions without prior knowledge is an important problem in image registration. In this paper, we present the angular difference function (ADF) and demonstrate its applicability to rotation estimation. The ADF of two functions is defined as the integral of their spectral difference along the radial direction. It is efficiently computed using the pseudopolar Fourier transform, which computes the discrete Fourier transform of an image on a near spherical grid. Unlike other Fourier-based registration schemes, the suggested approach does not require any interpolation. Thus, it is more accurate and significantly faster.

A compact LWIR imaging spectrometer with a variable gap Fabry-Perot interferometer

NASA Astrophysics Data System (ADS)

Zhang, Fang; Gao, Jiaobo; Wang, Nan; Zhao, Yujie; Zhang, Lei; Gao, Shan

2017-02-01

Fourier transform spectroscopy is a widely employed method for obtaining spectra, with applications ranging from the desktop to remote sensing. The long wave infrared (LWIR) interferometric spectral imaging system is always with huge volume and large weight. In order to miniaturize and light the instrument, a new method of LWIR spectral imaging system based on a variable gap Fabry-Perot (FP) interferometer is researched. With the system working principle analyzed, theoretically, it is researched that how to make certain the primary parameter, such as, the reflectivity of the two interferometric cavity surfaces, field of view (FOV) and f-number of the imaging lens. A prototype is developed and a good experimental result of CO2 laser is obtained. The research shows that besides high throughput and high spectral resolution, the advantage of miniaturization is also simultaneously achieved in this method.

ICER-3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images

NASA Technical Reports Server (NTRS)

Kiely, A.; Klimesh, M.; Xie, H.; Aranki, N.

2005-01-01

ICER-3D is a progressive, wavelet-based compressor for hyperspectral images. ICER-3D is derived from the ICER image compressor. ICER-3D can provide lossless and lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The three-dimensional wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of hyperspectral data sets, while facilitating elimination of spectral ringing artifacts. Correlation is further exploited by a context modeler that effectively exploits spectral dependencies in the wavelet-transformed hyperspectral data. Performance results illustrating the benefits of these features are presented.

Regional regularization method for ECT based on spectral transformation of Laplacian

NASA Astrophysics Data System (ADS)

Guo, Z. H.; Kan, Z.; Lv, D. C.; Shao, F. Q.

2016-10-01

Image reconstruction in electrical capacitance tomography is an ill-posed inverse problem, and regularization techniques are usually used to solve the problem for suppressing noise. An anisotropic regional regularization algorithm for electrical capacitance tomography is constructed using a novel approach called spectral transformation. Its function is derived and applied to the weighted gradient magnitude of the sensitivity of Laplacian as a regularization term. With the optimum regional regularizer, the a priori knowledge on the local nonlinearity degree of the forward map is incorporated into the proposed online reconstruction algorithm. Simulation experimentations were performed to verify the capability of the new regularization algorithm to reconstruct a superior quality image over two conventional Tikhonov regularization approaches. The advantage of the new algorithm for improving performance and reducing shape distortion is demonstrated with the experimental data.

Reversible Data Hiding in FTIR Microspectroscopy Images with Tamper Indication and Payload Error Correction

PubMed Central

Seppänen, Tapio

2017-01-01

Fourier transform infrared (FTIR) microspectroscopy images contain information from the whole infrared spectrum used for microspectroscopic analyses. In combination with the FTIR image, visible light images are used to depict the area from which the FTIR spectral image was sampled. These two images are traditionally acquired as separate files. This paper proposes a histogram shifting-based data hiding technique to embed visible light images in FTIR spectral images producing single entities. The primary objective is to improve data management efficiency. Secondary objectives are confidentiality, availability, and reliability. Since the integrity of biomedical data is vital, the proposed method applies reversible data hiding. After extraction of the embedded data, the FTIR image is reversed to its original state. Furthermore, the proposed method applies authentication tags generated with keyed Hash-Based Message Authentication Codes (HMAC) to detect tampered or corrupted areas of FTIR images. The experimental results show that the FTIR spectral images carrying the payload maintain good perceptual fidelity and the payload can be reliably recovered even after bit flipping or cropping attacks. It has been also shown that extraction successfully removes all modifications caused by the payload. Finally, authentication tags successfully indicated tampered FTIR image areas. PMID:29259987

Ground-Based Measurement Experiment and First Results with Geosynchronous-Imaging Fourier Transform Spectrometer Engineering Demonstration Unit

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Smith, William L.; Bingham, Gail E.; Huppi, Ronald J.; Revercomb, Henry E.; Zollinger, Lori J.; Larar, Allen M.; Liu, Xu; Tansock, Joseph J.; Reisse, Robert A.;

Estimation of spectral distribution of sky radiance using a commercial digital camera.

PubMed

Saito, Masanori; Iwabuchi, Hironobu; Murata, Isao

2016-01-10

Methods for estimating spectral distribution of sky radiance from images captured by a digital camera and for accurately estimating spectral responses of the camera are proposed. Spectral distribution of sky radiance is represented as a polynomial of the wavelength, with coefficients obtained from digital RGB counts by linear transformation. The spectral distribution of radiance as measured is consistent with that obtained by spectrometer and radiative transfer simulation for wavelengths of 430-680 nm, with standard deviation below 1%. Preliminary applications suggest this method is useful for detecting clouds and studying the relation between irradiance at the ground and cloud distribution.

Comparison of hyperspectral transformation accuracies of multispectral Landsat TM, ETM+, OLI and EO-1 ALI images for detecting minerals in a geothermal prospect area

NASA Astrophysics Data System (ADS)

Hoang, Nguyen Tien; Koike, Katsuaki

2018-03-01

Hyperspectral remote sensing generally provides more detailed spectral information and greater accuracy than multispectral remote sensing for identification of surface materials. However, there have been no hyperspectral imagers that cover the entire Earth surface. This lack points to a need for producing pseudo-hyperspectral imagery by hyperspectral transformation from multispectral images. We have recently developed such a method, a Pseudo-Hyperspectral Image Transformation Algorithm (PHITA), which transforms Landsat 7 ETM+ images into pseudo-EO-1 Hyperion images using multiple linear regression models of ETM+ and Hyperion band reflectance data. This study extends the PHITA to transform TM, OLI, and EO-1 ALI sensor images into pseudo-Hyperion images. By choosing a part of the Fish Lake Valley geothermal prospect area in the western United States for study, the pseudo-Hyperion images produced from the TM, ETM+, OLI, and ALI images by PHITA were confirmed to be applicable to mineral mapping. Using a reference map as the truth, three main minerals (muscovite and chlorite mixture, opal, and calcite) were identified with high overall accuracies from the pseudo-images (> 95% and > 42% for excluding and including unclassified pixels, respectively). The highest accuracy was obtained from the ALI image, followed by ETM+, TM, and OLI images in descending order. The TM, OLI, and ALI images can be alternatives to ETM+ imagery for the hyperspectral transformation that aids the production of pseudo-Hyperion images for areas without high-quality ETM+ images because of scan line corrector failure, and for long-term global monitoring of land surfaces.

Alternative techniques for high-resolution spectral estimation of spectrally encoded endoscopy

NASA Astrophysics Data System (ADS)

Mousavi, Mahta; Duan, Lian; Javidi, Tara; Ellerbee, Audrey K.

2015-09-01

Spectrally encoded endoscopy (SEE) is a minimally invasive optical imaging modality capable of fast confocal imaging of internal tissue structures. Modern SEE systems use coherent sources to image deep within the tissue and data are processed similar to optical coherence tomography (OCT); however, standard processing of SEE data via the Fast Fourier Transform (FFT) leads to degradation of the axial resolution as the bandwidth of the source shrinks, resulting in a well-known trade-off between speed and axial resolution. Recognizing the limitation of FFT as a general spectral estimation algorithm to only take into account samples collected by the detector, in this work we investigate alternative high-resolution spectral estimation algorithms that exploit information such as sparsity and the general region position of the bulk sample to improve the axial resolution of processed SEE data. We validate the performance of these algorithms using bothMATLAB simulations and analysis of experimental results generated from a home-built OCT system to simulate an SEE system with variable scan rates. Our results open a new door towards using non-FFT algorithms to generate higher quality (i.e., higher resolution) SEE images at correspondingly fast scan rates, resulting in systems that are more accurate and more comfortable for patients due to the reduced image time.

GPU-accelerated non-uniform fast Fourier transform-based compressive sensing spectral domain optical coherence tomography.

PubMed

Xu, Daguang; Huang, Yong; Kang, Jin U

2014-06-16

We implemented the graphics processing unit (GPU) accelerated compressive sensing (CS) non-uniform in k-space spectral domain optical coherence tomography (SD OCT). Kaiser-Bessel (KB) function and Gaussian function are used independently as the convolution kernel in the gridding-based non-uniform fast Fourier transform (NUFFT) algorithm with different oversampling ratios and kernel widths. Our implementation is compared with the GPU-accelerated modified non-uniform discrete Fourier transform (MNUDFT) matrix-based CS SD OCT and the GPU-accelerated fast Fourier transform (FFT)-based CS SD OCT. It was found that our implementation has comparable performance to the GPU-accelerated MNUDFT-based CS SD OCT in terms of image quality while providing more than 5 times speed enhancement. When compared to the GPU-accelerated FFT based-CS SD OCT, it shows smaller background noise and less side lobes while eliminating the need for the cumbersome k-space grid filling and the k-linear calibration procedure. Finally, we demonstrated that by using a conventional desktop computer architecture having three GPUs, real-time B-mode imaging can be obtained in excess of 30 fps for the GPU-accelerated NUFFT based CS SD OCT with frame size 2048(axial) × 1,000(lateral).

Novel spectral imaging system combining spectroscopy with imaging applications for biology

NASA Astrophysics Data System (ADS)

Malik, Zvi; Cabib, Dario; Buckwald, Robert A.; Garini, Yuval; Soenksen, Dirk G.

1995-02-01

A novel analytical spectral-imaging system and its results in the examination of biological specimens are presented. The SpectraCube 1000 system measures the transmission, absorbance, or fluorescence spectra of images studied by light microscopy. The system is based on an interferometer combined with a CCD camera, enabling measurement of the interferogram for each pixel constructing the image. Fourier transformation of the interferograms derives pixel by pixel spectra for 170 X 170 pixels of the image. A special `similarity mapping' program has been developed, enabling comparisons of spectral algorithms of all the spatial and spectral information measured by the system in the image. By comparing the spectrum of each pixel in the specimen with a selected reference spectrum (similarity mapping), there is a depiction of the spatial distribution of macromolecules possessing the characteristics of the reference spectrum. The system has been applied to analyses of bone marrow blood cells as well as fluorescent specimens, and has revealed information which could not be unveiled by other techniques. Similarity mapping has enabled visualization of fine details of chromatin packing in the nucleus of cells and other cytoplasmic compartments. Fluorescence analysis by the system has enabled the determination of porphyrin concentrations and distribution in cytoplasmic organelles of living cells.

Multi-pass encoding of hyperspectral imagery with spectral quality control

NASA Astrophysics Data System (ADS)

Wasson, Steven; Walker, William

2015-05-01

Multi-pass encoding is a technique employed in the field of video compression that maximizes the quality of an encoded video sequence within the constraints of a specified bit rate. This paper presents research where multi-pass encoding is extended to the field of hyperspectral image compression. Unlike video, which is primarily intended to be viewed by a human observer, hyperspectral imagery is processed by computational algorithms that generally attempt to classify the pixel spectra within the imagery. As such, these algorithms are more sensitive to distortion in the spectral dimension of the image than they are to perceptual distortion in the spatial dimension. The compression algorithm developed for this research, which uses the Karhunen-Loeve transform for spectral decorrelation followed by a modified H.264/Advanced Video Coding (AVC) encoder, maintains a user-specified spectral quality level while maximizing the compression ratio throughout the encoding process. The compression performance may be considered near-lossless in certain scenarios. For qualitative purposes, this paper presents the performance of the compression algorithm for several Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Hyperion datasets using spectral angle as the spectral quality assessment function. Specifically, the compression performance is illustrated in the form of rate-distortion curves that plot spectral angle versus bits per pixel per band (bpppb).

Skin condition measurement by using multispectral imaging system (Conference Presentation)

NASA Astrophysics Data System (ADS)

Jung, Geunho; Kim, Sungchul; Kim, Jae Gwan

2017-02-01

There are a number of commercially available low level light therapy (LLLT) devices in a market, and face whitening or wrinkle reduction is one of targets in LLLT. The facial improvement could be known simply by visual observation of face, but it cannot provide either quantitative data or recognize a subtle change. Clinical diagnostic instruments such as mexameter can provide a quantitative data, but it costs too high for home users. Therefore, we designed a low cost multi-spectral imaging device by adding additional LEDs (470nm, 640nm, white LED, 905nm) to a commercial USB microscope which has two LEDs (395nm, 940nm) as light sources. Among various LLLT skin treatments, we focused on getting melanin and wrinkle information. For melanin index measurements, multi-spectral images of nevus were acquired and melanin index values from color image (conventional method) and from multi-spectral images were compared. The results showed that multi-spectral analysis of melanin index can visualize nevus with a different depth and concentration. A cross section of wrinkle on skin resembles a wedge which can be a source of high frequency components when the skin image is Fourier transformed into a spatial frequency domain map. In that case, the entropy value of the spatial frequency map can represent the frequency distribution which is related with the amount and thickness of wrinkle. Entropy values from multi-spectral images can potentially separate the percentage of thin and shallow wrinkle from thick and deep wrinkle. From the results, we found that this low cost multi-spectral imaging system could be beneficial for home users of LLLT by providing the treatment efficacy in a quantitative way.

Super-resolution algorithm based on sparse representation and wavelet preprocessing for remote sensing imagery

NASA Astrophysics Data System (ADS)

Ren, Ruizhi; Gu, Lingjia; Fu, Haoyang; Sun, Chenglin

2017-04-01

An effective super-resolution (SR) algorithm is proposed for actual spectral remote sensing images based on sparse representation and wavelet preprocessing. The proposed SR algorithm mainly consists of dictionary training and image reconstruction. Wavelet preprocessing is used to establish four subbands, i.e., low frequency, horizontal, vertical, and diagonal high frequency, for an input image. As compared to the traditional approaches involving the direct training of image patches, the proposed approach focuses on the training of features derived from these four subbands. The proposed algorithm is verified using different spectral remote sensing images, e.g., moderate-resolution imaging spectroradiometer (MODIS) images with different bands, and the latest Chinese Jilin-1 satellite images with high spatial resolution. According to the visual experimental results obtained from the MODIS remote sensing data, the SR images using the proposed SR algorithm are superior to those using a conventional bicubic interpolation algorithm or traditional SR algorithms without preprocessing. Fusion algorithms, e.g., standard intensity-hue-saturation, principal component analysis, wavelet transform, and the proposed SR algorithms are utilized to merge the multispectral and panchromatic images acquired by the Jilin-1 satellite. The effectiveness of the proposed SR algorithm is assessed by parameters such as peak signal-to-noise ratio, structural similarity index, correlation coefficient, root-mean-square error, relative dimensionless global error in synthesis, relative average spectral error, spectral angle mapper, and the quality index Q4, and its performance is better than that of the standard image fusion algorithms.

Compression of multispectral Landsat imagery using the Embedded Zerotree Wavelet (EZW) algorithm

NASA Technical Reports Server (NTRS)

Shapiro, Jerome M.; Martucci, Stephen A.; Czigler, Martin

1994-01-01

The Embedded Zerotree Wavelet (EZW) algorithm has proven to be an extremely efficient and flexible compression algorithm for low bit rate image coding. The embedding algorithm attempts to order the bits in the bit stream in numerical importance and thus a given code contains all lower rate encodings of the same algorithm. Therefore, precise bit rate control is achievable and a target rate or distortion metric can be met exactly. Furthermore, the technique is fully image adaptive. An algorithm for multispectral image compression which combines the spectral redundancy removal properties of the image-dependent Karhunen-Loeve Transform (KLT) with the efficiency, controllability, and adaptivity of the embedded zerotree wavelet algorithm is presented. Results are shown which illustrate the advantage of jointly encoding spectral components using the KLT and EZW.

User oriented ERTS-1 images. [vegetation identification in Canada through image enhancement

NASA Technical Reports Server (NTRS)

Shlien, S.; Goodenough, D.

1974-01-01

Photographic reproduction of ERTS-1 images are capable of displaying only a portion of the total information available from the multispectral scanner. Methods are being developed to generate ERTS-1 images oriented towards special users such as agriculturists, foresters, and hydrologists by applying image enhancement techniques and interactive statistical classification schemes. Spatial boundaries and linear features can be emphasized and delineated using simple filters. Linear and nonlinear transformations can be applied to the spectral data to emphasize certain ground information. An automatic classification scheme was developed to identify particular ground cover classes such as fallow, grain, rape seed or various vegetation covers. The scheme applies the maximum likelihood decision rule to the spectral information and classifies the ERTS-1 image on a pixel by pixel basis. Preliminary results indicate that the classifier has limited success in distinguishing crops, but is well adapted for identifying different types of vegetation.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Optical information processing with transformation of the spatial coherence of light

NASA Astrophysics Data System (ADS)

Bykovskii, Yurii A.; Markilov, A. A.; Rodin, V. G.; Starikov, S. N.

1995-10-01

A description is given of systems with spatially incoherent illumination, intended for spectral and correlation analysis, and for the recording of Fourier holograms. These systems make use of transformation of the degree of the spatial coherence of light. The results are given of the processing of images and signals, including those transmitted by a bundle of fibre-optic waveguides both as monochromatic light and as quasimonochromatic radiation from a cathode-ray tube. The feasibility of spatial frequency filtering and of correlation analysis of images with a bipolar impulse response is considered for systems with spatially incoherent illumination where these tasks are performed by double transformation of the spatial coherence of light. A description is given of experimental systems and the results of image processing are reported.

High-speed real-time image compression based on all-optical discrete cosine transformation

NASA Astrophysics Data System (ADS)

Guo, Qiang; Chen, Hongwei; Wang, Yuxi; Chen, Minghua; Yang, Sigang; Xie, Shizhong

2017-02-01

In this paper, we present a high-speed single-pixel imaging (SPI) system based on all-optical discrete cosine transform (DCT) and demonstrate its capability to enable noninvasive imaging of flowing cells in a microfluidic channel. Through spectral shaping based on photonic time stretch (PTS) and wavelength-to-space conversion, structured illumination patterns are generated at a rate (tens of MHz) which is three orders of magnitude higher than the switching rate of a digital micromirror device (DMD) used in a conventional single-pixel camera. Using this pattern projector, high-speed image compression based on DCT can be achieved in the optical domain. In our proposed system, a high compression ratio (approximately 10:1) and a fast image reconstruction procedure are both achieved, which implicates broad applications in industrial quality control and biomedical imaging.

Hyperspectral imager for components identification in the atmosphere

NASA Astrophysics Data System (ADS)

Dewandel, Jean-Luc; Beghuin, Didier; Dubois, Xavier; Antoine, Philippe

2017-11-01

Several applications require the identification of chemical elements during re-entry of material in the atmosphere. The materials can be from human origin or meteorites. The Automated Transfer Vehicle (ATV) re-entry has been filmed with conventional camera from airborne manual operation. In order to permit the identification of the separate elements from their glow, spectral analysis needs to be added to the video data. In a LET-SME contract with ESA, Lambda-X has built a Fourier Transform Imaging Spectrometer to permit, in a future work, to bring the technology to the readiness level required for the application. In this paper, the principles of the Fourier Transform Imaging spectroscopy are recalled, the different interferometers suitable for supporting the technique are reviewed and the selection process is explained. The final selection of the interferometer corresponds to a birefringent prism based common path shear interferometer. The design of the breadboard and its performances are presented in terms of spatial resolution, aperture, and spectral resolution. A discussion is open regarding perspective of the technique for other remote sensing applications compared to more usual push broom configurations.

The role of the continuous wavelet transform in mineral identification using hyperspectral imaging in the long-wave infrared by using SVM classifier

NASA Astrophysics Data System (ADS)

Sojasi, Saeed; Yousefi, Bardia; Liaigre, Kévin; Ibarra-Castanedo, Clemente; Beaudoin, Georges; Maldague, Xavier P. V.; Huot, François; Chamberland, Martin

2017-05-01

Hyperspectral imaging (HSI) in the long-wave infrared spectrum (LWIR) provides spectral and spatial information concerning the emissivity of the surface of materials, which can be used for mineral identification. For this, an endmember, which is the purest form of a mineral, is used as reference. All pure minerals have specific spectral profiles in the electromagnetic wavelength, which can be thought of as the mineral's fingerprint. The main goal of this paper is the identification of minerals by LWIR hyperspectral imaging using a machine learning scheme. The information of hyperspectral imaging has been recorded from the energy emitted from the mineral's surface. Solar energy is the source of energy in remote sensing, while a heating element is the energy source employed in laboratory experiments. Our work contains three main steps where the first step involves obtaining the spectral signatures of pure (single) minerals with a hyperspectral camera, in the long-wave infrared (7.7 to 11.8 μm), which measures the emitted radiance from the minerals' surface. The second step concerns feature extraction by applying the continuous wavelet transform (CWT) and finally we use support vector machine classifier with radial basis functions (SVM-RBF) for classification/identification of minerals. The overall accuracy of classification in our work is 90.23+/- 2.66%. In conclusion, based on CWT's ability to capture the information of signals can be used as a good marker for classification and identification the minerals substance.

GIFTS SM EDU Data Processing and Algorithms

NASA Technical Reports Server (NTRS)

Tian, Jialin; Johnson, David G.; Reisse, Robert A.; Gazarik, Michael J.

2007-01-01

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiances using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three Focal Plane Arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the processing algorithms involved in the calibration stage. The calibration procedures can be subdivided into three stages. In the pre-calibration stage, a phase correction algorithm is applied to the decimated and filtered complex interferogram. The resulting imaginary part of the spectrum contains only the noise component of the uncorrected spectrum. Additional random noise reduction can be accomplished by applying a spectral smoothing routine to the phase-corrected blackbody reference spectra. In the radiometric calibration stage, we first compute the spectral responsivity based on the previous results, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. During the post-processing stage, we estimate the noise equivalent spectral radiance (NESR) from the calibrated ABB and HBB spectra. We then implement a correction scheme that compensates for the effect of fore-optics offsets. Finally, for off-axis pixels, the FPA off-axis effects correction is performed. To estimate the performance of the entire FPA, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is designed based on the pixel performance evaluation.

Airborne measurements in the infrared using FTIR-based imaging hyperspectral sensors

NASA Astrophysics Data System (ADS)

Puckrin, E.; Turcotte, C. S.; Lahaie, P.; Dubé, D.; Lagueux, P.; Farley, V.; Marcotte, F.; Chamberland, M.

2009-09-01

Hyperspectral ground mapping is being used in an ever-increasing extent for numerous applications in the military, geology and environmental fields. The different regions of the electromagnetic spectrum help produce information of differing nature. The visible, near-infrared and short-wave infrared radiation (400 nm to 2.5 μm) has been mostly used to analyze reflected solar light, while the mid-wave (3 to 5 μm) and long-wave (8 to 12 μm or thermal) infrared senses the self-emission of molecules directly, enabling the acquisition of data during night time. Push-broom dispersive sensors have been typically used for airborne hyperspectral mapping. However, extending the spectral range towards the mid-wave and long-wave infrared brings performance limitations due to the self emission of the sensor itself. The Fourier-transform spectrometer technology has been extensively used in the infrared spectral range due to its high transmittance as well as throughput and multiplex advantages, thereby reducing the sensor self-emission problem. Telops has developed the Hyper-Cam, a rugged and compact infrared hyperspectral imager. The Hyper-Cam is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides passive signature measurement capability, with up to 320x256 pixels at spectral resolutions of up to 0.25 cm-1. The Hyper-Cam has been used on the ground in several field campaigns, including the demonstration of standoff chemical agent detection. More recently, the Hyper-Cam has been integrated into an airplane to provide airborne measurement capabilities. A special pointing module was designed to compensate for airplane attitude and forward motion. To our knowledge, the Hyper-Cam is the first commercial airborne hyperspectral imaging sensor based on Fourier-transform infrared technology. The first airborne measurements and some preliminary performance criteria for the Hyper-Cam are presented in this paper.

Airborne measurements in the infrared using FTIR-based imaging hyperspectral sensors

NASA Astrophysics Data System (ADS)

Puckrin, E.; Turcotte, C. S.; Lahaie, P.; Dubé, D.; Farley, V.; Lagueux, P.; Marcotte, F.; Chamberland, M.

2009-05-01

Hyperspectral ground mapping is being used in an ever-increasing extent for numerous applications in the military, geology and environmental fields. The different regions of the electromagnetic spectrum help produce information of differing nature. The visible, near-infrared and short-wave infrared radiation (400 nm to 2.5 μm) has been mostly used to analyze reflected solar light, while the mid-wave (3 to 5 μm) and long-wave (8 to 12 μm or thermal) infrared senses the self-emission of molecules directly, enabling the acquisition of data during night time. Push-broom dispersive sensors have been typically used for airborne hyperspectral mapping. However, extending the spectral range towards the mid-wave and long-wave infrared brings performance limitations due to the self emission of the sensor itself. The Fourier-transform spectrometer technology has been extensively used in the infrared spectral range due to its high transmittance as well as throughput and multiplex advantages, thereby reducing the sensor self-emission problem. Telops has developed the Hyper-Cam, a rugged and compact infrared hyperspectral imager. The Hyper-Cam is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides passive signature measurement capability, with up to 320x256 pixels at spectral resolutions of up to 0.25 cm-1. The Hyper-Cam has been used on the ground in several field campaigns, including the demonstration of standoff chemical agent detection. More recently, the Hyper-Cam has been integrated into an airplane to provide airborne measurement capabilities. A special pointing module was designed to compensate for airplane attitude and forward motion. To our knowledge, the Hyper-Cam is the first commercial airborne hyperspectral imaging sensor based on Fourier-transform infrared technology. The first airborne measurements and some preliminary performance criteria for the Hyper-Cam are presented in this paper.

Neural-net-based image matching

NASA Astrophysics Data System (ADS)

Jerebko, Anna K.; Barabanov, Nikita E.; Luciv, Vadim R.; Allinson, Nigel M.

2000-04-01

The paper describes a neural-based method for matching spatially distorted image sets. The matching of partially overlapping images is important in many applications-- integrating information from images formed from different spectral ranges, detecting changes in a scene and identifying objects of differing orientations and sizes. Our approach consists of extracting contour features from both images, describing the contour curves as sets of line segments, comparing these sets, determining the corresponding curves and their common reference points, calculating the image-to-image co-ordinate transformation parameters on the basis of the most successful variant of the derived curve relationships. The main steps are performed by custom neural networks. The algorithms describe in this paper have been successfully tested on a large set of images of the same terrain taken in different spectral ranges, at different seasons and rotated by various angles. In general, this experimental verification indicates that the proposed method for image fusion allows the robust detection of similar objects in noisy, distorted scenes where traditional approaches often fail.

Evaluation of solar angle variation over digital processing of LANDSAT imagery. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Novo, E. M. L. M.

1984-01-01

The effects of the seasonal variation of illumination over digital processing of LANDSAT images are evaluated. Original images are transformed by means of digital filtering to enhance their spatial features. The resulting images are used to obtain an unsupervised classification of relief units. After defining relief classes, which are supposed to be spectrally different, topographic variables (declivity, altitude, relief range and slope length) are used to identify the true relief units existing on the ground. The samples are also clustered by means of an unsupervised classification option. The results obtained for each LANDSAT overpass are compared. Digital processing is highly affected by illumination geometry. There is no correspondence between relief units as defined by spectral features and those resulting from topographic features.

The application of the piecewise linear approximation to the spectral neighborhood of soil line for the analysis of the quality of normalization of remote sensing materials

NASA Astrophysics Data System (ADS)

Kulyanitsa, A. L.; Rukhovich, A. D.; Rukhovich, D. D.; Koroleva, P. V.; Rukhovich, D. I.; Simakova, M. S.

2017-04-01

The concept of soil line can be to describe the temporal distribution of spectral characteristics of the bare soil surface. In this case, the soil line can be referred to as the multi-temporal soil line, or simply temporal soil line (TSL). In order to create TSL for 8000 regular lattice points for the territory of three regions of Tula oblast, we used 34 Landsat images obtained in the period from 1985 to 2014 after their certain transformation. As Landsat images are the matrices of the values of spectral brightness, this transformation is the normalization of matrices. There are several methods of normalization that move, rotate, and scale the spectral plane. In our study, we applied the method of piecewise linear approximation to the spectral neighborhood of soil line in order to assess the quality of normalization mathematically. This approach allowed us to range normalization methods according to their quality as follows: classic normalization > successive application of the turn and shift > successive application of the atmospheric correction and shift > atmospheric correction > shift > turn > raw data. The normalized data allowed us to create the maps of the distribution of a and b coefficients of the TSL. The map of b coefficient is characterized by the high correlation with the ground-truth data obtained from 1899 soil pits described during the soil surveys performed by the local institute for land management (GIPROZEM).

High throughput operando studies using Fourier transform infrared imaging and Raman spectroscopy.

PubMed

Li, Guosheng; Hu, Dehong; Xia, Guanguang; White, J M; Zhang, Conrad

2008-07-01

A prototype high throughput operando (HTO) reactor designed and built for catalyst screening and characterization combines Fourier transform infrared (FT-IR) imaging and Raman spectroscopy in operando conditions. Using a focal plane array detector (HgCdTe focal plane array, 128x128 pixels, and 1610 Hz frame rate) for the FT-IR imaging system, the catalyst activity and selectivity of all parallel reaction channels can be simultaneously followed. Each image data set possesses 16 384 IR spectra with a spectral range of 800-4000 cm(-1) and with an 8 cm(-1) resolution. Depending on the signal-to-noise ratio, 2-20 s are needed to generate a full image of all reaction channels for a data set. Results on reactant conversion and product selectivity are obtained from FT-IR spectral analysis. Six novel Raman probes, one for each reaction channel, were specially designed and house built at Pacific Northwest National Laboratory, to simultaneously collect Raman spectra of the catalysts and possible reaction intermediates on the catalyst surface under operando conditions. As a model system, methanol partial oxidation reaction on silica-supported molybdenum oxide (MoO3SiO2) catalysts has been studied under different reaction conditions to demonstrate the performance of the HTO reactor.

Demonstration of the Wide-Field Imaging Interferometer Testbed Using a Calibrated Hyperspectral Image Projector

NASA Technical Reports Server (NTRS)

Bolcar, Matthew R.; Leisawitz, David; Maher, Steve; Rinehart, Stephen

2012-01-01

The Wide-field Imaging Interferometer testbed (WIIT) at NASA's Goddard Space Flight Center uses a dual-Michelson interferometric technique. The WIIT combines stellar interferometry with Fourier-transform interferometry to produce high-resolution spatial-spectral data over a large field-of-view. This combined technique could be employed on future NASA missions such as the Space Infrared Interferometric Telescope (SPIRIT) and the Sub-millimeter Probe of the Evolution of Cosmic Structure (SPECS). While both SPIRIT and SPECS would operate at far-infrared wavelengths, the WIIT demonstrates the dual-interferometry technique at visible wavelengths. The WIIT will produce hyperspectral image data, so a true hyperspectral object is necessary. A calibrated hyperspectral image projector (CHIP) has been constructed to provide such an object. The CHIP uses Digital Light Processing (DLP) technology to produce customized, spectrally-diverse scenes. CHIP scenes will have approximately 1.6-micron spatial resolution and the capability of . producing arbitrary spectra in the band between 380 nm and 1.6 microns, with approximately 5-nm spectral resolution. Each pixel in the scene can take on a unique spectrum. Spectral calibration is achieved with an onboard fiber-coupled spectrometer. In this paper we describe the operation of the CHIP. Results from the WIIT observations of CHIP scenes will also be presented.

Apparatus and method using a holographic optical element for converting a spectral distribution to image points

NASA Technical Reports Server (NTRS)

McGill, Matthew J. (Inventor); Scott, Vibart S. (Inventor); Marzouk, Marzouk (Inventor)

2001-01-01

A holographic optical element transforms a spectral distribution of light to image points. The element comprises areas, each of which acts as a separate lens to image the light incident in its area to an image point. Each area contains the recorded hologram of a point source object. The image points can be made to lie in a line in the same focal plane so as to align with a linear array detector. A version of the element has been developed that has concentric equal areas to match the circular fringe pattern of a Fabry-Perot interferometer. The element has high transmission efficiency, and when coupled with high quantum efficiency solid state detectors, provides an efficient photon-collecting detection system. The element may be used as part of the detection system in a direct detection Doppler lidar system or multiple field of view lidar system.

Techniques for identifying dust devils in mars pathfinder images

USGS Publications Warehouse

Metzger, S.M.; Carr, J.R.; Johnson, J. R.; Parker, T.J.; Lemmon, M.T.

2000-01-01

Image processing methods used to identify and enhance dust devil features imaged by IMP (Imager for Mars Pathfinder) are reviewed. Spectral differences, visible red minus visible blue, were used for initial dust devil searches, driven by the observation that Martian dust has high red and low blue reflectance. The Martian sky proved to be more heavily dust-laden than pre-Pathfinder predictions, based on analysis of images from the Hubble Space Telescope. As a result, these initial spectral difference methods failed to contrast dust devils with background dust haze. Imager artifacts (dust motes on the camera lens, flat-field effects caused by imperfections in the CCD, and projection onto a flat sensor plane by a convex lens) further impeded the ability to resolve subtle dust devil features. Consequently, reference images containing sky with a minimal horizon were first subtracted from each spectral filter image to remove camera artifacts and reduce the background dust haze signal. Once the sky-flat preprocessing step was completed, the red-minus-blue spectral difference scheme was attempted again. Dust devils then were successfully identified as bright plumes. False-color ratios using calibrated IMP images were found useful for visualizing dust plumes, verifying initial discoveries as vortex-like features. Enhancement of monochromatic (especially blue filter) images revealed dust devils as silhouettes against brighter background sky. Experiments with principal components transformation identified dust devils in raw, uncalibrated IMP images and further showed relative movement of dust devils across the Martian surface. A variety of methods therefore served qualitative and quantitative goals for dust plume identification and analysis in an environment where such features are obscure.

Toward optimal spatial and spectral quality in widefield infrared spectromicroscopy of IR labelled single cells.

PubMed

Mattson, Eric C; Unger, Miriam; Clède, Sylvain; Lambert, François; Policar, Clotilde; Imtiaz, Asher; D'Souza, Roshan; Hirschmugl, Carol J

2013-10-07

Advancements in widefield infrared spectromicroscopy have recently been demonstrated following the commissioning of IRENI (InfraRed ENvironmental Imaging), a Fourier Transform infrared (FTIR) chemical imaging beamline at the Synchrotron Radiation Center. The present study demonstrates the effects of magnification, spatial oversampling, spectral pre-processing and deconvolution, focusing on the intracellular detection and distribution of an exogenous metal tris-carbonyl derivative 1 in a single MDA-MB-231 breast cancer cell. We demonstrate here that spatial oversampling for synchrotron-based infrared imaging is critical to obtain accurate diffraction-limited images at all wavelengths simultaneously. Resolution criteria and results from raw and deconvoluted images for two Schwarzschild objectives (36×, NA 0.5 and 74×, NA 0.65) are compared to each other and to prior reports for raster-scanned, confocal microscopes. The resolution of the imaging data can be improved by deconvolving the instrumental broadening that is determined with the measured PSFs, which is implemented with GPU programming architecture for fast hyperspectral processing. High definition, rapidly acquired, FTIR chemical images of respective spectral signatures of the cell 1 and shows that 1 is localized next to the phosphate- and Amide-rich regions, in agreement with previous infrared and luminescence studies. The infrared image contrast, localization and definition are improved after applying proven spectral pre-processing (principal component analysis based noise reduction and RMie scattering correction algorithms) to individual pixel spectra in the hyperspectral cube.

Resampling algorithm for the Spatial Infrared Imaging Telescope (SPIRIT III) Fourier transform spectrometer

NASA Astrophysics Data System (ADS)

Sargent, Steven D.; Greenman, Mark E.; Hansen, Scott M.

1998-11-01

The Spatial Infrared Imaging Telescope (SPIRIT III) is the primary sensor aboard the Midcourse Space Experiment (MSX), which was launched 24 April 1996. SPIRIT III included a Fourier transform spectrometer that collected terrestrial and celestial background phenomenology data for the Ballistic Missile Defense Organization (BMDO). This spectrometer used a helium-neon reference laser to measure the optical path difference (OPD) in the spectrometer and to command the analog-to-digital conversion of the infrared detector signals, thereby ensuring the data were sampled at precise increments of OPD. Spectrometer data must be sampled at accurate increments of OPD to optimize the spectral resolution and spectral position of the transformed spectra. Unfortunately, a failure in the power supply preregulator at the MSX spacecraft/SPIRIT III interface early in the mission forced the spectrometer to be operated without the reference laser until a failure investigation was completed. During this time data were collected in a backup mode that used an electronic clock to sample the data. These data were sampled evenly in time, and because the scan velocity varied, at nonuniform increments of OPD. The scan velocity profile depended on scan direction and scan length, and varied over time, greatly degrading the spectral resolution and spectral and radiometric accuracy of the measurements. The Convert software used to process the SPIRIT III data was modified to resample the clock-sampled data at even increments of OPD, using scan velocity profiles determined from ground and on-orbit data, greatly improving the quality of the clock-sampled data. This paper presents the resampling algorithm, the characterization of the scan velocity profiles, and the results of applying the resampling algorithm to on-orbit data.

Spectral Topography Generation for Arbitrary Grids

NASA Astrophysics Data System (ADS)

Oh, T. J.

2015-12-01

A new topography generation tool utilizing spectral transformation technique for both structured and unstructured grids is presented. For the source global digital elevation data, the NASA Shuttle Radar Topography Mission (SRTM) 15 arc-second dataset (gap-filling by Jonathan de Ferranti) is used and for land/water mask source, the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) 30 arc-second land water mask dataset v5 is used. The original source data is coarsened to a intermediate global 2 minute lat-lon mesh. Then, spectral transformation to the wave space and inverse transformation with wavenumber truncation is performed for isotropic topography smoothness control. Target grid topography mapping is done by bivariate cubic spline interpolation from the truncated 2 minute lat-lon topography. Gibbs phenomenon in the water region can be removed by overwriting ocean masked target coordinate grids with interpolated values from the intermediate 2 minute grid. Finally, a weak smoothing operator is applied on the target grid to minimize the land/water surface height discontinuity that might have been introduced by the Gibbs oscillation removal procedure. Overall, the new topography generation approach provides spectrally-derived, smooth topography with isotropic resolution and minimum damping, enabling realistic topography forcing in the numerical model. Topography is generated for the cubed-sphere grid and tested on the KIAPS Integrated Model (KIM).

A new approach for fast indexing of hyperspectral image data for knowledge retrieval and mining

NASA Astrophysics Data System (ADS)

Clowers, Robert; Dua, Sumeet

2005-11-01

Multispectral sensors produce images with a few relatively broad wavelength bands. Hyperspectral remote sensors, on the other hand, collect image data simultaneously in dozens or hundreds of narrow and adjacent spectral bands. These measurements make it possible to derive a continuous spectrum for each image cell, generating an image cube across multiple spectral components. Hyperspectral imaging has sound applications in a variety of areas such as mineral exploration, hazardous waste remediation, mapping habitat, invasive vegetation, eco system monitoring, hazardous gas detection, mineral detection, soil degradation, and climate change. This image has a strong potential for transforming the imaging paradigms associated with several design and manufacturing processes. In this paper, we describe a novel approach for fast indexing of multi-dimensional hyperspectral image data, especially for data mining applications. The index exploits the spectral and spatial relationships embedded in these image sets. The index will be employed for knowledge retrieval applications that require fast information interpretation approaches. The index can also be deployed in real-time mission-critical domains, as it is shown to exhibit speed with high degrees of dimensionality associated with the data. The strength of this index in terms of degree of false dismissals and false alarms will also be demonstrated. The paper will highlight some common applications of this imaging computational paradigm and will conclude with directions for future improvement and investigation.

Scaling dimensions in spectroscopy of soil and vegetation

NASA Astrophysics Data System (ADS)

Malenovský, Zbyněk; Bartholomeus, Harm M.; Acerbi-Junior, Fausto W.; Schopfer, Jürg T.; Painter, Thomas H.; Epema, Gerrit F.; Bregt, Arnold K.

2007-05-01

The paper revises and clarifies definitions of the term scale and scaling conversions for imaging spectroscopy of soil and vegetation. We demonstrate a new four-dimensional scale concept that includes not only spatial but also the spectral, directional and temporal components. Three scaling remote sensing techniques are reviewed: (1) radiative transfer, (2) spectral (un)mixing, and (3) data fusion. Relevant case studies are given in the context of their up- and/or down-scaling abilities over the soil/vegetation surfaces and a multi-source approach is proposed for their integration. Radiative transfer (RT) models are described to show their capacity for spatial, spectral up-scaling, and directional down-scaling within a heterogeneous environment. Spectral information and spectral derivatives, like vegetation indices (e.g. TCARI/OSAVI), can be scaled and even tested by their means. Radiative transfer of an experimental Norway spruce ( Picea abies (L.) Karst.) research plot in the Czech Republic was simulated by the Discrete Anisotropic Radiative Transfer (DART) model to prove relevance of the correct object optical properties scaled up to image data at two different spatial resolutions. Interconnection of the successive modelling levels in vegetation is shown. A future development in measurement and simulation of the leaf directional spectral properties is discussed. We describe linear and/or non-linear spectral mixing techniques and unmixing methods that demonstrate spatial down-scaling. Relevance of proper selection or acquisition of the spectral endmembers using spectral libraries, field measurements, and pure pixels of the hyperspectral image is highlighted. An extensive list of advanced unmixing techniques, a particular example of unmixing a reflective optics system imaging spectrometer (ROSIS) image from Spain, and examples of other mixture applications give insight into the present status of scaling capabilities. Simultaneous spatial and temporal down-scaling by means of a data fusion technique is described. A demonstrative example is given for the moderate resolution imaging spectroradiometer (MODIS) and LANDSAT Thematic Mapper (TM) data from Brazil. Corresponding spectral bands of both sensors were fused via a pyramidal wavelet transform in Fourier space. New spectral and temporal information of the resultant image can be used for thematic classification or qualitative mapping. All three described scaling techniques can be integrated as the relevant methodological steps within a complex multi-source approach. We present this concept of combining numerous optical remote sensing data and methods to generate inputs for ecosystem process models.

High-speed spectral calibration by complex FIR filter in phase-sensitive optical coherence tomography.

PubMed

Kim, Sangmin; Raphael, Patrick D; Oghalai, John S; Applegate, Brian E

2016-04-01

Swept-laser sources offer a number of advantages for Phase-sensitive Optical Coherence Tomography (PhOCT). However, inter- and intra-sweep variability leads to calibration errors that adversely affect phase sensitivity. While there are several approaches to overcoming this problem, our preferred method is to simply calibrate every sweep of the laser. This approach offers high accuracy and phase stability at the expense of a substantial processing burden. In this approach, the Hilbert phase of the interferogram from a reference interferometer provides the instantaneous wavenumber of the laser, but is computationally expensive. Fortunately, the Hilbert transform may be approximated by a Finite Impulse-Response (FIR) filter. Here we explore the use of several FIR filter based Hilbert transforms for calibration, explicitly considering the impact of filter choice on phase sensitivity and OCT image quality. Our results indicate that the complex FIR filter approach is the most robust and accurate among those considered. It provides similar image quality and slightly better phase sensitivity than the traditional FFT-IFFT based Hilbert transform while consuming fewer resources in an FPGA implementation. We also explored utilizing the Hilbert magnitude of the reference interferogram to calculate an ideal window function for spectral amplitude calibration. The ideal window function is designed to carefully control sidelobes on the axial point spread function. We found that after a simple chromatic correction, calculating the window function using the complex FIR filter and the reference interferometer gave similar results to window functions calculated using a mirror sample and the FFT-IFFT Hilbert transform. Hence, the complex FIR filter can enable accurate and high-speed calibration of the magnitude and phase of spectral interferograms.

High-speed spectral calibration by complex FIR filter in phase-sensitive optical coherence tomography

PubMed Central

Kim, Sangmin; Raphael, Patrick D.; Oghalai, John S.; Applegate, Brian E.

2016-01-01

Swept-laser sources offer a number of advantages for Phase-sensitive Optical Coherence Tomography (PhOCT). However, inter- and intra-sweep variability leads to calibration errors that adversely affect phase sensitivity. While there are several approaches to overcoming this problem, our preferred method is to simply calibrate every sweep of the laser. This approach offers high accuracy and phase stability at the expense of a substantial processing burden. In this approach, the Hilbert phase of the interferogram from a reference interferometer provides the instantaneous wavenumber of the laser, but is computationally expensive. Fortunately, the Hilbert transform may be approximated by a Finite Impulse-Response (FIR) filter. Here we explore the use of several FIR filter based Hilbert transforms for calibration, explicitly considering the impact of filter choice on phase sensitivity and OCT image quality. Our results indicate that the complex FIR filter approach is the most robust and accurate among those considered. It provides similar image quality and slightly better phase sensitivity than the traditional FFT-IFFT based Hilbert transform while consuming fewer resources in an FPGA implementation. We also explored utilizing the Hilbert magnitude of the reference interferogram to calculate an ideal window function for spectral amplitude calibration. The ideal window function is designed to carefully control sidelobes on the axial point spread function. We found that after a simple chromatic correction, calculating the window function using the complex FIR filter and the reference interferometer gave similar results to window functions calculated using a mirror sample and the FFT-IFFT Hilbert transform. Hence, the complex FIR filter can enable accurate and high-speed calibration of the magnitude and phase of spectral interferograms. PMID:27446666

Spatial compression algorithm for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R [Albuquerque, NM

2008-07-15

A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

Euclidean commute time distance embedding and its application to spectral anomaly detection

NASA Astrophysics Data System (ADS)

Albano, James A.; Messinger, David W.

2012-06-01

Spectral image analysis problems often begin by performing a preprocessing step composed of applying a transformation that generates an alternative representation of the spectral data. In this paper, a transformation based on a Markov-chain model of a random walk on a graph is introduced. More precisely, we quantify the random walk using a quantity known as the average commute time distance and find a nonlinear transformation that embeds the nodes of a graph in a Euclidean space where the separation between them is equal to the square root of this quantity. This has been referred to as the Commute Time Distance (CTD) transformation and it has the important characteristic of increasing when the number of paths between two nodes decreases and/or the lengths of those paths increase. Remarkably, a closed form solution exists for computing the average commute time distance that avoids running an iterative process and is found by simply performing an eigendecomposition on the graph Laplacian matrix. Contained in this paper is a discussion of the particular graph constructed on the spectral data for which the commute time distance is then calculated from, an introduction of some important properties of the graph Laplacian matrix, and a subspace projection that approximately preserves the maximal variance of the square root commute time distance. Finally, RX anomaly detection and Topological Anomaly Detection (TAD) algorithms will be applied to the CTD subspace followed by a discussion of their results.

Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

PubMed

Liu, Da; Li, Jianxun

2016-12-16

Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

A comparison of spectral decorrelation techniques and performance evaluation metrics for a wavelet-based, multispectral data compression algorithm

NASA Technical Reports Server (NTRS)

Matic, Roy M.; Mosley, Judith I.

1994-01-01

Future space-based, remote sensing systems will have data transmission requirements that exceed available downlinks necessitating the use of lossy compression techniques for multispectral data. In this paper, we describe several algorithms for lossy compression of multispectral data which combine spectral decorrelation techniques with an adaptive, wavelet-based, image compression algorithm to exploit both spectral and spatial correlation. We compare the performance of several different spectral decorrelation techniques including wavelet transformation in the spectral dimension. The performance of each technique is evaluated at compression ratios ranging from 4:1 to 16:1. Performance measures used are visual examination, conventional distortion measures, and multispectral classification results. We also introduce a family of distortion metrics that are designed to quantify and predict the effect of compression artifacts on multi spectral classification of the reconstructed data.

Reference software implementation for GIFTS ground data processing

NASA Astrophysics Data System (ADS)

Garcia, R. K.; Howell, H. B.; Knuteson, R. O.; Martin, G. D.; Olson, E. R.; Smuga-Otto, M. J.

2006-08-01

Future satellite weather instruments such as high spectral resolution imaging interferometers pose a challenge to the atmospheric science and software development communities due to the immense data volumes they will generate. An open-source, scalable reference software implementation demonstrating the calibration of radiance products from an imaging interferometer, the Geosynchronous Imaging Fourier Transform Spectrometer1 (GIFTS), is presented. This paper covers essential design principles laid out in summary system diagrams, lessons learned during implementation and preliminary test results from the GIFTS Information Processing System (GIPS) prototype.

Wide spectral-range imaging spectroscopy of photonic crystal microbeads for multiplex biomolecular assay applications

NASA Astrophysics Data System (ADS)

Li, Jianping

2014-05-01

Suspension assay using optically color-encoded microbeads is a novel way to increase the reaction speed and multiplex of biomolecular detection and analysis. To boost the detection speed, a hyperspectral imaging (HSI) system is of great interest for quickly decoding the color codes of the microcarriers. Imaging Fourier transform spectrometer (IFTS) is a potential candidate for this task due to its advantages in HSI measurement. However, conventional IFTS is only popular in IR spectral bands because it is easier to track its scanning mirror position in longer wavelengths so that the fundamental Nyquist criterion can be satisfied when sampling the interferograms; the sampling mechanism for shorter wavelengths IFTS used to be very sophisticated, high-cost and bulky. In order to overcome this handicap and take better usage of its advantages for HSI applications, a new wide spectral range IFTS platform is proposed based on an optical beam-folding position-tracking technique. This simple technique has successfully extended the spectral range of an IFTS to cover 350-1000nm. Test results prove that the system has achieved good spectral and spatial resolving performances with instrumentation flexibilities. Accurate and fast measurement results on novel colloidal photonic crystal microbeads also demonstrate its practical potential for high-throughput and multiplex suspension molecular assays.

Improvements to an earth observing statistical performance model with applications to LWIR spectral variability

NASA Astrophysics Data System (ADS)

Zhao, Runchen; Ientilucci, Emmett J.

2017-05-01

Hyperspectral remote sensing systems provide spectral data composed of hundreds of narrow spectral bands. Spectral remote sensing systems can be used to identify targets, for example, without physical interaction. Often it is of interested to characterize the spectral variability of targets or objects. The purpose of this paper is to identify and characterize the LWIR spectral variability of targets based on an improved earth observing statistical performance model, known as the Forecasting and Analysis of Spectroradiometric System Performance (FASSP) model. FASSP contains three basic modules including a scene model, sensor model and a processing model. Instead of using mean surface reflectance only as input to the model, FASSP transfers user defined statistical characteristics of a scene through the image chain (i.e., from source to sensor). The radiative transfer model, MODTRAN, is used to simulate the radiative transfer based on user defined atmospheric parameters. To retrieve class emissivity and temperature statistics, or temperature / emissivity separation (TES), a LWIR atmospheric compensation method is necessary. The FASSP model has a method to transform statistics in the visible (ie., ELM) but currently does not have LWIR TES algorithm in place. This paper addresses the implementation of such a TES algorithm and its associated transformation of statistics.

Is Fourier analysis performed by the visual system or by the visual investigator.

PubMed

Ochs, A L

1979-01-01

A numerical Fourier transform was made of the pincushion grid illusion and the spectral components orthogonal to the illusory lines were isolated. Their inverse transform creates a picture of the illusion. The spatial-frequency response of cortical, simple receptive field neurons similarly filters the grid. A complete set of these neurons thus approximates a two-dimensional Fourier analyzer. One cannot conclude, however, that the brain actually uses frequency-domain information to interpret visual images.

Real-time implementation of optimized maximum noise fraction transform for feature extraction of hyperspectral images

NASA Astrophysics Data System (ADS)

Wu, Yuanfeng; Gao, Lianru; Zhang, Bing; Zhao, Haina; Li, Jun

2014-01-01

We present a parallel implementation of the optimized maximum noise fraction (G-OMNF) transform algorithm for feature extraction of hyperspectral images on commodity graphics processing units (GPUs). The proposed approach explored the algorithm data-level concurrency and optimized the computing flow. We first defined a three-dimensional grid, in which each thread calculates a sub-block data to easily facilitate the spatial and spectral neighborhood data searches in noise estimation, which is one of the most important steps involved in OMNF. Then, we optimized the processing flow and computed the noise covariance matrix before computing the image covariance matrix to reduce the original hyperspectral image data transmission. These optimization strategies can greatly improve the computing efficiency and can be applied to other feature extraction algorithms. The proposed parallel feature extraction algorithm was implemented on an Nvidia Tesla GPU using the compute unified device architecture and basic linear algebra subroutines library. Through the experiments on several real hyperspectral images, our GPU parallel implementation provides a significant speedup of the algorithm compared with the CPU implementation, especially for highly data parallelizable and arithmetically intensive algorithm parts, such as noise estimation. In order to further evaluate the effectiveness of G-OMNF, we used two different applications: spectral unmixing and classification for evaluation. Considering the sensor scanning rate and the data acquisition time, the proposed parallel implementation met the on-board real-time feature extraction.

Spectral gamuts and spectral gamut mapping

NASA Astrophysics Data System (ADS)

Rosen, Mitchell R.; Derhak, Maxim W.

2006-01-01

All imaging devices have two gamuts: the stimulus gamut and the response gamut. The response gamut of a print engine is typically described in CIE colorimetry units, a system derived to quantify human color response. More fundamental than colorimetric gamuts are spectral gamuts, based on radiance, reflectance or transmittance units. Spectral gamuts depend on the physics of light or on how materials interact with light and do not involve the human's photoreceptor integration or brain processing. Methods for visualizing a spectral gamut raise challenges as do considerations of how to utilize such a data-set for producing superior color reproductions. Recent work has described a transformation of spectra reduced to 6-dimensions called LabPQR. LabPQR was designed as a hybrid space with three explicit colorimetric axes and three additional spectral reconstruction axes. In this paper spectral gamuts are discussed making use of LabPQR. Also, spectral gamut mapping is considered in light of the colorimetric-spectral duality of the LabPQR space.

Analysis for signal-to-noise ratio of hyper-spectral imaging FTIR interferometer

NASA Astrophysics Data System (ADS)

Li, Xun-niu; Zheng, Wei-jian; Lei, Zheng-gang; Wang, Hai-yang; Fu, Yan-peng

2013-08-01

Signal-to-noise Ratio of hyper-spectral imaging FTIR interferometer system plays a decisive role on the performance of the instrument. It is necessary to analyze them in the development process. Based on the simplified target/background model, the energy transfer model of the LWIR hyper-spectral imaging interferometer has been discussed. The noise equivalent spectral radiance (NESR) and its influencing factors of the interferometer system was analyzed, and the signal-to-noise（SNR） was calculated by using the properties of NESR and incident radiance. In a typical application environment, using standard atmospheric model of USA(1976 COESA) as a background, and set a reasonable target/background temperature difference, and take Michelson spatial modulation Fourier Transform interferometer as an example, the paper had calculated the NESR and the SNR of the interferometer system which using the commercially LWIR cooled FPA and UFPA detector. The system noise sources of the instrument were also analyzed in the paper. The results of those analyses can be used to optimize and pre-estimate the performance of the interferometer system, and analysis the applicable conditions of use different detectors. It has important guiding significance for the LWIR interferometer spectrometer design.

Diffractive shear interferometry for extreme ultraviolet high-resolution lensless imaging

NASA Astrophysics Data System (ADS)

Jansen, G. S. M.; de Beurs, A.; Liu, X.; Eikema, K. S. E.; Witte, S.

2018-05-01

We demonstrate a novel imaging approach and associated reconstruction algorithm for far-field coherent diffractive imaging, based on the measurement of a pair of laterally sheared diffraction patterns. The differential phase profile retrieved from such a measurement leads to improved reconstruction accuracy, increased robustness against noise, and faster convergence compared to traditional coherent diffractive imaging methods. We measure laterally sheared diffraction patterns using Fourier-transform spectroscopy with two phase-locked pulse pairs from a high harmonic source. Using this approach, we demonstrate spectrally resolved imaging at extreme ultraviolet wavelengths between 28 and 35 nm.

ART AND SCIENCE OF IMAGE MAPS.

USGS Publications Warehouse

Kidwell, Richard D.; McSweeney, Joseph A.

1985-01-01

The visual image of reflected light is influenced by the complex interplay of human color discrimination, spatial relationships, surface texture, and the spectral purity of light, dyes, and pigments. Scientific theories of image processing may not always achieve acceptable results as the variety of factors, some psychological, are in part, unpredictable. Tonal relationships that affect digital image processing and the transfer functions used to transform from the continuous-tone source image to a lithographic image, may be interpreted for an insight of where art and science fuse in the production process. The application of art and science in image map production at the U. S. Geological Survey is illustrated and discussed.

Identifying areas of high economic-potential copper mineralization using ASTER data in the Urumieh-Dokhtar Volcanic Belt, Iran

NASA Astrophysics Data System (ADS)

Pour, Amin Beiranvand; Hashim, Mazlan

2012-02-01

This study investigates the application of spectral image processing methods to ASTER data for mapping hydrothermal alteration zones associated with porphyry copper mineralization and related host rock. The study area is located in the southeastern segment of the Urumieh-Dokhtar Volcanic Belt of Iran. This area has been selected because it is a potential zone for exploration of new porphyry copper deposits. Spectral transform approaches, namely principal component analysis, band ratio and minimum noise fraction were used for mapping hydrothermally altered rocks and lithological units at regional scale. Spectral mapping methods, including spectral angle mapper, linear spectral unmixing, matched filtering and mixture tuned matched filtering were applied to differentiate hydrothermal alteration zones associated with porphyry copper mineralization such as phyllic, argillic and propylitic mineral assemblages.Spectral transform methods enhanced hydrothermally altered rocks associated with the known porphyry copper deposits and new identified prospects using shortwave infrared (SWIR) bands of ASTER. These methods showed the discrimination of quartz rich igneous rocks from the magmatic background and the boundary between igneous and sedimentary rocks using the thermal infrared (TIR) bands of ASTER at regional scale. Spectral mapping methods distinguished the sericitically- and argillically-altered rocks (the phyllic and argillic alteration zones) that surrounded by discontinuous to extensive zones of propylitized rocks (the propylitic alteration zone) using SWIR bands of ASTER at both regional and district scales. Linear spectral unmixing method can be best suited for distinguishing specific high economic-potential hydrothermal alteration zone (the phyllic zone) and mineral assemblages using SWIR bands of ASTER. Results have proven to be effective, and in accordance with the results of field surveying, spectral reflectance measurements and X-ray diffraction (XRD) analysis. In conclusion, the image processing methods used can provide cost-effective information to discover possible locations of porphyry copper and epithermal gold mineralization prior to detailed and costly ground investigations. The extraction of spectral information from ASTER data can produce comprehensive and accurate information for copper and gold resource investigations around the world, including those yet to be discovered.

Mach-Zehnder Fourier transform spectrometer for astronomical spectroscopy at submillimeter wavelengths

NASA Astrophysics Data System (ADS)

Naylor, David A.; Gom, Bradley G.; Schofield, Ian; Tompkins, Gregory; Davis, Gary R.

2003-02-01

Astronomical spectroscopy at submillimeter wavelengths holds much promise for fields as diverse as the study of planetary atmospheres, molecular clouds and extragalactic sources. Fourier transform spectrometers (FTS) represent an important class of spectrometers well suited to observations that require broad spectral coverage at intermediate spectral resolution. In this paper we present the design and performance of a novel FTS, which has been developed for use at the James Clerk Maxwell Telescope (JCMT). The design uses two broadband intensity beamsplitters in a Mach-Zehnder configuration, which provide access to all four interferometer ports while maintaining a high and uniform efficiency over a broad spectral range. Since the interferometer processes both polarizations it is twice as efficient as the Martin-Puplett interferometer (MPI). As with the MPI, the spatial separation of the two input ports allows a reference blackbody to be viewed at all times in one port, while continually viewing the astronomical source in the other. Furthermore, by minimizing the size of the optical beam at the beamsplitter, the design is well suited to imaging Fourier transform spectroscopy (IFTS) as evidenced by its selection for the SPIRE instrument on Herschel.

Development of a low-cost, 11 µm spectral domain optical coherence tomography surface profilometry prototype

NASA Astrophysics Data System (ADS)

Suliali, Nyasha J.; Baricholo, Peter; Neethling, Pieter H.; Rohwer, Erich G.

2017-06-01

A spectral-domain Optical Coherence Tomography (OCT) surface profilometry prototype has been developed for the purpose of surface metrology of optical elements. The prototype consists of a light source, spectral interferometer, sample fixture and software currently running on Microsoft® Windows platforms. In this system, a broadband light emitting diode beam is focused into a Michelson interferometer with a plane mirror as its sample fixture. At the interferometer output, spectral interferograms of broadband sources were measured using a Czerny-Turner mount monochromator with a 2048-element complementary metal oxide semiconductor linear array as the detector. The software performs importation and interpolation of interferometer spectra to pre-condition the data for image computation. One dimensional axial OCT images were computed by Fourier transformation of the measured spectra. A first reflection surface profilometry (FRSP) algorithm was then formulated to perform imaging of step-function-surfaced samples. The algorithm re-constructs two dimensional colour-scaled slice images by concatenation of 21 and 13 axial scans to form a 10 mm and 3.0 mm slice respectively. Measured spectral interferograms, computed interference fringe signals and depth reflectivity profiles were comparable to simulations and correlated to displacements of a single reflector linearly translated about the arm null-mismatch point. Surface profile images of a double-step-function-surfaced sample, embedded with inclination and crack detail were plotted with an axial resolution of 11 μm. The surface shape, defects and misalignment relative to the incident beam were detected to the order of a micron, confirming high resolution of the developed system as compared to electro-mechanical surface profilometry techniques.

Exploring the impact of wavelet-based denoising in the classification of remote sensing hyperspectral images

NASA Astrophysics Data System (ADS)

Quesada-Barriuso, Pablo; Heras, Dora B.; Argüello, Francisco

2016-10-01

The classification of remote sensing hyperspectral images for land cover applications is a very intensive topic. In the case of supervised classification, Support Vector Machines (SVMs) play a dominant role. Recently, the Extreme Learning Machine algorithm (ELM) has been extensively used. The classification scheme previously published by the authors, and called WT-EMP, introduces spatial information in the classification process by means of an Extended Morphological Profile (EMP) that is created from features extracted by wavelets. In addition, the hyperspectral image is denoised in the 2-D spatial domain, also using wavelets and it is joined to the EMP via a stacked vector. In this paper, the scheme is improved achieving two goals. The first one is to reduce the classification time while preserving the accuracy of the classification by using ELM instead of SVM. The second one is to improve the accuracy results by performing not only a 2-D denoising for every spectral band, but also a previous additional 1-D spectral signature denoising applied to each pixel vector of the image. For each denoising the image is transformed by applying a 1-D or 2-D wavelet transform, and then a NeighShrink thresholding is applied. Improvements in terms of classification accuracy are obtained, especially for images with close regions in the classification reference map, because in these cases the accuracy of the classification in the edges between classes is more relevant.

Evaluation techniques and metrics for assessment of pan+MSI fusion (pansharpening)

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

2015-05-01

Fusion of broadband panchromatic data with narrow band multispectral data - pansharpening - is a common and often studied problem in remote sensing. Many methods exist to produce data fusion results with the best possible spatial and spectral characteristics, and a number have been commercially implemented. This study examines the output products of 4 commercial implementations with regard to their relative strengths and weaknesses for a set of defined image characteristics and analyst use-cases. Image characteristics used are spatial detail, spatial quality, spectral integrity, and composite color quality (hue and saturation), and analyst use-cases included a variety of object detection and identification tasks. The imagery comes courtesy of the RIT SHARE 2012 collect. Two approaches are used to evaluate the pansharpening methods, analyst evaluation or qualitative measure and image quality metrics or quantitative measures. Visual analyst evaluation results are compared with metric results to determine which metrics best measure the defined image characteristics and product use-cases and to support future rigorous characterization the metrics' correlation with the analyst results. Because pansharpening represents a trade between adding spatial information from the panchromatic image, and retaining spectral information from the MSI channels, the metrics examined are grouped into spatial improvement metrics and spectral preservation metrics. A single metric to quantify the quality of a pansharpening method would necessarily be a combination of weighted spatial and spectral metrics based on the importance of various spatial and spectral characteristics for the primary task of interest. Appropriate metrics and weights for such a combined metric are proposed here, based on the conducted analyst evaluation. Additionally, during this work, a metric was developed specifically focused on assessment of spatial structure improvement relative to a reference image and independent of scene content. Using analysis of Fourier transform images, a measure of high-frequency content is computed in small sub-segments of the image. The average increase in high-frequency content across the image is used as the metric, where averaging across sub-segments combats the scene dependent nature of typical image sharpness techniques. This metric had an improved range of scores, better representing difference in the test set than other common spatial structure metrics.

Broadband hyperspectral coherent anti-Stokes Raman scattering microscopy for stain-free histological imaging with principal component analysis

NASA Astrophysics Data System (ADS)

Xu, Jingjiang; Guo, Baoshan; Wong, Kenneth K. Y.; Tsia, Kevin K.

2014-02-01

Routine procedures in standard histopathology involve laborious steps of tissue processing and staining for final examination. New techniques which can bypass these procedures and thus minimize the tissue handling error would be of great clinical value. Coherent anti-Stokes Raman scattering (CARS) microscopy is an attractive tool for label-free biochemical-specific characterization of biological specimen. However, a vast majority of prior works on CARS (or stimulated Raman scattering (SRS)) bioimaging restricted analyses on a narrowband or well-distinctive Raman spectral signatures. Although hyperspectral SRS/CARS imaging has recently emerged as a better solution to access wider-band spectral information in the image, studies mostly focused on a limited spectral range, e.g. CH-stretching vibration of lipids, or non-biological samples. Hyperspectral image information in the congested fingerprint spectrum generally remains untapped for biological samples. In this regard, we further explore ultrabroadband hyperspectral multiplex (HM-CARS) to perform chemoselective histological imaging with the goal of exploring its utility in stain-free clinical histopathology. Using the supercontinuum Stokes, our system can access the CARS spectral window as wide as >2000cm-1. In order to unravel the congested CARS spectra particularly in the fingerprint region, we first employ a spectral phase-retrieval algorithm based on Kramers-Kronig (KK) transform to minimize the non-resonant background in the CARS spectrum. We then apply principal component analysis (PCA) to identify and map the spatial distribution of different biochemical components in the tissues. We demonstrate chemoselective HM-CARS imaging of a colon tissue section which displays the key cellular structures that correspond well with standard stained-tissue observation.

Spectral analysis method and sample generation for real time visualization of speech

NASA Astrophysics Data System (ADS)

Hobohm, Klaus

A method for translating speech signals into optical models, characterized by high sound discrimination and learnability and designed to provide to deaf persons a feedback towards control of their way of speaking, is presented. Important properties of speech production and perception processes and organs involved in these mechanisms are recalled in order to define requirements for speech visualization. It is established that the spectral representation of time, frequency and amplitude resolution of hearing must be fair and continuous variations of acoustic parameters of speech signal must be depicted by a continuous variation of images. A color table was developed for dynamic illustration and sonograms were generated with five spectral analysis methods such as Fourier transformations and linear prediction coding. For evaluating sonogram quality, test persons had to recognize consonant/vocal/consonant words and an optimized analysis method was achieved with a fast Fourier transformation and a postprocessor. A hardware concept of a real time speech visualization system, based on multiprocessor technology in a personal computer, is presented.

Determination of carotid disease with the application of STFT and CWT methods.

PubMed

Hardalaç, Firat; Yildirim, Hanefi; Serhatlioğlu, Selami

2007-06-01

In this study, Doppler signals were recorded from the output of carotid arteries of 40 subjects and transferred to a personal computer (PC) by using a 16-bit sound card. Doppler difference frequencies were recorded from each of the subjects, and then analyzed by using short-time Fourier transform (STFT) and the continuous wavelet transform (CWT) methods to obtain their sonograms. These sonograms were then used to determine the relationships of applied methods with medical conditions. The sonograms that were obtained by CWT method gave better results for spectral resolution than the STFT method. The sonograms of CWT method offer net envelope and better imaging, so that the measurement of blood flow and brain pressure can be made more accurately. Simultaneously, receiver operating characteristic (ROC) analysis has been conducted for this study and the estimation performance of the spectral resolution for the STFT and CTW has been obtained. The STFT has shown a 80.45% success for the spectral resolution while CTW has shown a 89.90% success.

AGARD Flight Test Techniques Series. Volume 14. Introduction to Flight Test Engineering (Introduction a la Technique d’essais en vol)

DTIC Science & Technology

1995-09-01

path and aircraft attitude and other flight or aircraft parameters • Calculations in the frequency domain ( Fast Fourier Transform) • Data analysis...Signal filtering Image processing of video and radar data Parameter identification Statistical analysis Power spectral density Fast Fourier Transform...airspeeds both fast and slow, altitude, load factor both above and below 1g, centers of gravity (fore and aft), and with system/subsystem failures. Whether

The Effect of Substrate Emissivity on the Spectral Emission of a Hot-Gas Overlayer

DTIC Science & Technology

2015-12-30

unlimited. Unclassified Unlimited Unclassified Unlimited Unclassified Unlimited Unclassified Unlimited 19 Harold D. Ladouceur (202) 767-3558 Fourier ...13 REFERENCES………………………………………………………………………………….………..14 E-1 EXECUTIVE SUMMARY Fourier transform infrared...Raman spectroscopy, ambient x-ray photoelectron spectroscopy, near- infrared thermal imaging, and Fourier transform infrared emission spectroscopy

A compact LWIR hyperspectral system employing a microbolometer array and a variable gap Fabry-Perot interferometer employed as a Fourier transform spectrometer

NASA Astrophysics Data System (ADS)

Lucey, Paul G.; Hinrichs, John L.; Akagi, Jason

2012-06-01

A prototype long wave infrared Fourier transform spectral imaging system using a wedged Fabry-Perot interferometer and a microbolometer array was designed and built. The instrument can be used at both short (cm) and long standoff ranges (infinity focus). Signal to noise ratios are in the several hundred range for 30 C targets. The sensor is compact, fitting in a volume about 12 x12 x 4 inches.

GIFTS SM EDU Level 1B Algorithms

NASA Technical Reports Server (NTRS)

Tian, Jialin; Gazarik, Michael J.; Reisse, Robert A.; Johnson, David G.

2007-01-01

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) SensorModule (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiances using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the GIFTS SM EDU Level 1B algorithms involved in the calibration. The GIFTS Level 1B calibration procedures can be subdivided into four blocks. In the first block, the measured raw interferograms are first corrected for the detector nonlinearity distortion, followed by the complex filtering and decimation procedure. In the second block, a phase correction algorithm is applied to the filtered and decimated complex interferograms. The resulting imaginary part of the spectrum contains only the noise component of the uncorrected spectrum. Additional random noise reduction can be accomplished by applying a spectral smoothing routine to the phase-corrected spectrum. The phase correction and spectral smoothing operations are performed on a set of interferogram scans for both ambient and hot blackbody references. To continue with the calibration, we compute the spectral responsivity based on the previous results, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. We now can estimate the noise equivalent spectral radiance (NESR) from the calibrated ABB and HBB spectra. The correction schemes that compensate for the fore-optics offsets and off-axis effects are also implemented. In the third block, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is designed based on the pixel performance evaluation. Finally, in the fourth block, the single pixel algorithms are applied to the entire FPA.

Multi-Image Registration for an Enhanced Vision System

NASA Technical Reports Server (NTRS)

Hines, Glenn; Rahman, Zia-Ur; Jobson, Daniel; Woodell, Glenn

2002-01-01

An Enhanced Vision System (EVS) utilizing multi-sensor image fusion is currently under development at the NASA Langley Research Center. The EVS will provide enhanced images of the flight environment to assist pilots in poor visibility conditions. Multi-spectral images obtained from a short wave infrared (SWIR), a long wave infrared (LWIR), and a color visible band CCD camera, are enhanced and fused using the Retinex algorithm. The images from the different sensors do not have a uniform data structure: the three sensors not only operate at different wavelengths, but they also have different spatial resolutions, optical fields of view (FOV), and bore-sighting inaccuracies. Thus, in order to perform image fusion, the images must first be co-registered. Image registration is the task of aligning images taken at different times, from different sensors, or from different viewpoints, so that all corresponding points in the images match. In this paper, we present two methods for registering multiple multi-spectral images. The first method performs registration using sensor specifications to match the FOVs and resolutions directly through image resampling. In the second method, registration is obtained through geometric correction based on a spatial transformation defined by user selected control points and regression analysis.

A spectral-structural bag-of-features scene classifier for very high spatial resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Zhao, Bei; Zhong, Yanfei; Zhang, Liangpei

2016-06-01

Land-use classification of very high spatial resolution remote sensing (VHSR) imagery is one of the most challenging tasks in the field of remote sensing image processing. However, the land-use classification is hard to be addressed by the land-cover classification techniques, due to the complexity of the land-use scenes. Scene classification is considered to be one of the expected ways to address the land-use classification issue. The commonly used scene classification methods of VHSR imagery are all derived from the computer vision community that mainly deal with terrestrial image recognition. Differing from terrestrial images, VHSR images are taken by looking down with airborne and spaceborne sensors, which leads to the distinct light conditions and spatial configuration of land cover in VHSR imagery. Considering the distinct characteristics, two questions should be answered: (1) Which type or combination of information is suitable for the VHSR imagery scene classification? (2) Which scene classification algorithm is best for VHSR imagery? In this paper, an efficient spectral-structural bag-of-features scene classifier (SSBFC) is proposed to combine the spectral and structural information of VHSR imagery. SSBFC utilizes the first- and second-order statistics (the mean and standard deviation values, MeanStd) as the statistical spectral descriptor for the spectral information of the VHSR imagery, and uses dense scale-invariant feature transform (SIFT) as the structural feature descriptor. From the experimental results, the spectral information works better than the structural information, while the combination of the spectral and structural information is better than any single type of information. Taking the characteristic of the spatial configuration into consideration, SSBFC uses the whole image scene as the scope of the pooling operator, instead of the scope generated by a spatial pyramid (SP) commonly used in terrestrial image classification. The experimental results show that the whole image as the scope of the pooling operator performs better than the scope generated by SP. In addition, SSBFC codes and pools the spectral and structural features separately to avoid mutual interruption between the spectral and structural features. The coding vectors of spectral and structural features are then concatenated into a final coding vector. Finally, SSBFC classifies the final coding vector by support vector machine (SVM) with a histogram intersection kernel (HIK). Compared with the latest scene classification methods, the experimental results with three VHSR datasets demonstrate that the proposed SSBFC performs better than the other classification methods for VHSR image scenes.

Histopathology mapping of biochemical changes in myocardial infarction by Fourier transform infrared spectral imaging.

PubMed

Yang, Tian T; Weng, Shi F; Zheng, Na; Pan, Qing H; Cao, Hong L; Liu, Liang; Zhang, Hai D; Mu, Da W

2011-04-15

Fourier transform infrared (FTIR) imaging and microspectroscopy have been extensively applied in the identification and investigation of both healthy and diseased tissues. FTIR imaging can be used to determine the biodistribution of several molecules of interest (carbohydrates, lipids, proteins) for tissue analysis, without the need for prior staining of these tissues. Molecular structure data, such as protein secondary structure and collagen triple helix exhibits, can also be obtained from the same analysis. Thus, several histopathological lesions, for example myocardial infarction, can be identified from FTIR-analyzed tissue images, the latter which can allow for more accurate discrimination between healthy tissues and pathological lesions. Accordingly, we propose FTIR imaging as a new tool integrating both molecular and histopathological assessment to investigate the degree of pathological changes in tissues. In this study, myocardial infarction is presented as an illustrative example of the wide potential of FTIR imaging for biomedical applications. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Near-common-path interferometer for imaging Fourier-transform spectroscopy in wide-field microscopy

PubMed Central

Wadduwage, Dushan N.; Singh, Vijay Raj; Choi, Heejin; Yaqoob, Zahid; Heemskerk, Hans; Matsudaira, Paul; So, Peter T. C.

2017-01-01

Imaging Fourier-transform spectroscopy (IFTS) is a powerful method for biological hyperspectral analysis based on various imaging modalities, such as fluorescence or Raman. Since the measurements are taken in the Fourier space of the spectrum, it can also take advantage of compressed sensing strategies. IFTS has been readily implemented in high-throughput, high-content microscope systems based on wide-field imaging modalities. However, there are limitations in existing wide-field IFTS designs. Non-common-path approaches are less phase-stable. Alternatively, designs based on the common-path Sagnac interferometer are stable, but incompatible with high-throughput imaging. They require exhaustive sequential scanning over large interferometric path delays, making compressive strategic data acquisition impossible. In this paper, we present a novel phase-stable, near-common-path interferometer enabling high-throughput hyperspectral imaging based on strategic data acquisition. Our results suggest that this approach can improve throughput over those of many other wide-field spectral techniques by more than an order of magnitude without compromising phase stability. PMID:29392168

Assessment of SPOT-6 optical remote sensing data against GF-1 using NNDiffuse image fusion algorithm

NASA Astrophysics Data System (ADS)

Zhao, Jinling; Guo, Junjie; Cheng, Wenjie; Xu, Chao; Huang, Linsheng

2017-07-01

A cross-comparison method was used to assess the SPOT-6 optical satellite imagery against Chinese GF-1 imagery using three types of indicators: spectral and color quality, fusion effect and identification potential. More specifically, spectral response function (SRF) curves were used to compare the two imagery, showing that the SRF curve shape of SPOT-6 is more like a rectangle compared to GF-1 in blue, green, red and near-infrared bands. NNDiffuse image fusion algorithm was used to evaluate the capability of information conservation in comparison with wavelet transform (WT) and principal component (PC) algorithms. The results show that NNDiffuse fused image has extremely similar entropy vales than original image (1.849 versus 1.852) and better color quality. In addition, the object-oriented classification toolset (ENVI EX) was used to identify greenlands for comparing the effect of self-fusion image of SPOT-6 and inter-fusion image between SPOT-6 and GF-1 based on the NNDiffuse algorithm. The overall accuracy is 97.27% and 76.88%, respectively, showing that self-fused image of SPOT-6 has better identification capability.

A new COmpact hyperSpectral Imaging system (COSI) for UAS

NASA Astrophysics Data System (ADS)

Sima, Aleksandra; Baeck, Pieter-Jan; Delalieux, Stephanie; Livens, Stefan; Blommaert, Joris; Delauré, Bavo; Boonen, Miet

2016-04-01

This presentation gives an overview of the new COmpact hyperSpectral Imaging (COSI) system recently developed at the Flemish Institute for Technological Research (VITO, Belgium) and suitable for multirotor Remotely Piloted Aircraft Systems (RPAS) platforms. The camera is compact and lightweight, with a total mass of less than 500g including: an embedded computer, storage and power distribution unit. Such device miniaturization was possible thanks to the application of linear variable filters technology, in which image lines in the across flight direction correspond to different spectral bands as well as a different location on the ground (frame camera). The scanning motion is required to retrieve the complete spectrum for every point on the ground. The COSI camera captures data in 72 narrow (FWHM: 5nm to 10 nm) bands in the spectral range of 600-900 nm. Such spectral information is highly favourable for vegetation studies, since the main chlorophyll absorption feature centred around 680 nm is measured, as well as, the red-edge region (680 nm to 730 nm) which is often linked to plant stress. The NIR region furthermore reflects the internal plant structure, and is often linked to leaf area index and plant biomass. Next to the high spectral resolution, the COSI imager also provides a very high spatial data resolution i.e. images captured with a 9mm lens at 40m altitude cover a swath of ~40m with a ~2cm ground sampling distance. A dedicated data processing chain transforms the raw images into various information and action maps representing the status of the vegetation health and thus allowing for optimization of the management decisions within agricultural fields. In a number of test flights, hyperspectral COSI imager data were acquired covering diverse environments, e.g.: strawberry fields, natural grassland or pear orchards. Next to the COSI system overview, examples of collected data will be presented together with the results of the spectral data analysis. Lessons learned and an outlook on further improvements will be also shared with the audience.

Beyond MOS and fibers: Optical Fourier-transform Imaging Unit for Cananea Observatory (OFIUCO)

NASA Astrophysics Data System (ADS)

Nieto-Suárez, M. A.; Rosales-Ortega, F. F.; Castillo, E.; García, P.; Escobedo, G.; Sánchez, S. F.; González, J.; Iglesias-Páramo, J.; Mollá, M.; Chávez, M.; Bertone, E.; et al.

2017-11-01

Many physical processes in astronomy are still hampered by the lack of spatial and spectral resolution, and also restricted to the field-of-view (FoV) of current 2D spectroscopy instruments available worldwide. It is due to that, many of the ongoing or proposed studies are based on large-scale imaging and/or spectroscopic surveys. Under this philosophy, large aperture telescopes are dedicated to the study of intrinsically faint and/or distance objects, covering small FoVs, with high spatial resolution, while smaller telescopes are devoted to wide-field explorations. However, future astronomical surveys, should be addressed by acquiring un-biases, spatially resolved, high-quality spectroscopic information for a wide FoV. Therefore, and in order to improve the current instrumental offer in the Observatorio Astrofísico Guillermo Haro (OAGH) in Cananea, Mexico (INAOE); and to explore a possible instrument for the future Telescopio San Pedro Mártir (6.5m), we are currently integrating at INAOE an instrument prototype that will provide us with un-biased wide-field (few arcmin) spectroscopic information, and with the flexibility of operating at different spectral resolutions (R 1-20000), with a spatial resolution limited by seeing, and therefore, to be used in a wide range of astronomical problems. This instrument called OFIUCO: Optical Fourier-transform Imaging Unit for Cananea Observatory, will make use of the Fourier Transform Spectroscopic technique, which has been proved to be feasible in the optical wavelength range (350-1000 nm) with designs such as SITELLE (CFHT). We describe here the basic technical description of a Fourier transform spectrograph with important modifications from previous astronomical versions, as well as the technical advantages and weakness, and the science cases in which this instrument can be implemented.

Examination of Spectral Transformations on Spectral Mixture Analysis

NASA Astrophysics Data System (ADS)

Deng, Y.; Wu, C.

2018-04-01

While many spectral transformation techniques have been applied on spectral mixture analysis (SMA), few study examined their necessity and applicability. This paper focused on exploring the difference between spectrally transformed schemes and untransformed scheme to find out which transformed scheme performed better in SMA. In particular, nine spectrally transformed schemes as well as untransformed scheme were examined in two study areas. Each transformed scheme was tested 100 times using different endmember classes' spectra under the endmember model of vegetation- high albedo impervious surface area-low albedo impervious surface area-soil (V-ISAh-ISAl-S). Performance of each scheme was assessed based on mean absolute error (MAE). Statistical analysis technique, Paired-Samples T test, was applied to test the significance of mean MAEs' difference between transformed and untransformed schemes. Results demonstrated that only NSMA could exceed the untransformed scheme in all study areas. Some transformed schemes showed unstable performance since they outperformed the untransformed scheme in one area but weakened the SMA result in another region.

FPGA design of correlation-based pattern recognition

NASA Astrophysics Data System (ADS)

Jridi, Maher; Alfalou, Ayman

2017-05-01

Optical/Digital pattern recognition and tracking based on optical/digital correlation are a well-known techniques to detect, identify and localize a target object in a scene. Despite the limited number of treatments required by the correlation scheme, computational time and resources are relatively high. The most computational intensive treatment required by the correlation is the transformation from spatial to spectral domain and then from spectral to spatial domain. Furthermore, these transformations are used on optical/digital encryption schemes like the double random phase encryption (DRPE). In this paper, we present a VLSI architecture for the correlation scheme based on the fast Fourier transform (FFT). One interesting feature of the proposed scheme is its ability to stream image processing in order to perform correlation for video sequences. A trade-off between the hardware consumption and the robustness of the correlation can be made in order to understand the limitations of the correlation implementation in reconfigurable and portable platforms. Experimental results obtained from HDL simulations and FPGA prototype have demonstrated the advantages of the proposed scheme.

Preliminary PCA/TT Results on MRO CRISM Multispectral Images

NASA Astrophysics Data System (ADS)

Klassen, David R.; Smith, M. D.

2010-10-01

Mars Reconnaissance Orbiter arrived at Mars in March 2006 and by September had achieved its science-phase orbit with the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) beginning its visible to near-infrared (VIS/NIR) spectral imaging shortly thereafter. One goal of CRISM is to fill in the spatial gaps between the various targeted observations, eventually mapping the entire surface. Due to the large volume of data this would create, the instrument works in a reduced spectral sampling mode creating "multispectral” images. From these data we can create image cubes using 64 wavelengths from 0.410 to 3.923 µm. We present here our analysis of these multispectral mode data products using Principal Components Analysis (PCA) and Target Transformation (TT) [1]. Previous work with ground-based images [2-5] has shown that over an entire visible hemisphere, there are only three to four meaningful components using 32-105 wavelengths over 1.5-4.1 µm the first two are consistent over all temporal scales. The TT retrieved spectral endmembers show nearly the same level of consistency [5]. The preliminary work on the CRISM images cubes implies similar results; three to four significant principal components that are fairly consistent over time. These components are then used in TT to find spectral endmembers which can be used to characterize the surface reflectance for future use in radiative transfer cloud optical depth retrievals. We present here the PCA/TT results comparing the principal components and recovered endmembers from six reconstructed CRISM multi-spectral image cubes. References: [1] Bandfield, J. L., et al. (2000) JGR, 105, 9573. [2] Klassen, D. R. and Bell III, J. F. (2001) BAAS 33, 1069. [3] Klassen, D. R. and Bell III, J. F. (2003) BAAS, 35, 936. [4] Klassen, D. R., Wark, T. J., Cugliotta, C. G. (2005) BAAS, 37, 693. [5] Klassen, D. R. (2009) Icarus, 204, 32.

The MIND PALACE: A Multi-Spectral Imaging and Spectroscopy Database for Planetary Science

NASA Astrophysics Data System (ADS)

Eshelman, E.; Doloboff, I.; Hara, E. K.; Uckert, K.; Sapers, H. M.; Abbey, W.; Beegle, L. W.; Bhartia, R.

2017-12-01

The Multi-Instrument Database (MIND) is the web-based home to a well-characterized set of analytical data collected by a suite of deep-UV fluorescence/Raman instruments built at the Jet Propulsion Laboratory (JPL). Samples derive from a growing body of planetary surface analogs, mineral and microbial standards, meteorites, spacecraft materials, and other astrobiologically relevant materials. In addition to deep-UV spectroscopy, datasets stored in MIND are obtained from a variety of analytical techniques obtained over multiple spatial and spectral scales including electron microscopy, optical microscopy, infrared spectroscopy, X-ray fluorescence, and direct fluorescence imaging. Multivariate statistical analysis techniques, primarily Principal Component Analysis (PCA), are used to guide interpretation of these large multi-analytical spectral datasets. Spatial co-referencing of integrated spectral/visual maps is performed using QGIS (geographic information system software). Georeferencing techniques transform individual instrument data maps into a layered co-registered data cube for analysis across spectral and spatial scales. The body of data in MIND is intended to serve as a permanent, reliable, and expanding database of deep-UV spectroscopy datasets generated by this unique suite of JPL-based instruments on samples of broad planetary science interest.

Hyperspectral interventional imaging for enhanced tissue visualization and discrimination combining band selection methods.

PubMed

Nouri, Dorra; Lucas, Yves; Treuillet, Sylvie

2016-12-01

Hyperspectral imaging is an emerging technology recently introduced in medical applications inasmuch as it provides a powerful tool for noninvasive tissue characterization. In this context, a new system was designed to be easily integrated in the operating room in order to detect anatomical tissues hardly noticed by the surgeon's naked eye. Our LCTF-based spectral imaging system is operative over visible, near- and middle-infrared spectral ranges (400-1700 nm). It is dedicated to enhance critical biological tissues such as the ureter and the facial nerve. We aim to find the best three relevant bands to create a RGB image to display during the intervention with maximal contrast between the target tissue and its surroundings. A comparative study is carried out between band selection methods and band transformation methods. Combined band selection methods are proposed. All methods are compared using different evaluation criteria. Experimental results show that the proposed combined band selection methods provide the best performance with rich information, high tissue separability and short computational time. These methods yield a significant discrimination between biological tissues. We developed a hyperspectral imaging system in order to enhance some biological tissue visualization. The proposed methods provided an acceptable trade-off between the evaluation criteria especially in SWIR spectral band that outperforms the naked eye's capacities.

Experimental geometry for simultaneous beam characterization and sample imaging allowing for pink beam Fourier transform holography or coherent diffractive imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Flewett, Samuel; Eisebitt, Stefan

2011-02-20

One consequence of the self-amplified stimulated emission process used to generate x rays in free electron lasers (FELs) is the intrinsic shot-to-shot variance in the wavelength and temporal coherence. In order to optimize the results from diffractive imaging experiments at FEL sources, it will be advantageous to acquire a means of collecting coherence and spectral information simultaneously with the diffraction pattern from the sample we wish to study. We present a holographic mask geometry, including a grating structure, which can be used to extract both temporal and spatial coherence information alongside the sample scatter from each individual FEL shot andmore » also allows for the real space reconstruction of the sample using either Fourier transform holography or iterative phase retrieval.« less

Flame analysis using image processing techniques

NASA Astrophysics Data System (ADS)

Her Jie, Albert Chang; Zamli, Ahmad Faizal Ahmad; Zulazlan Shah Zulkifli, Ahmad; Yee, Joanne Lim Mun; Lim, Mooktzeng

2018-04-01

This paper presents image processing techniques with the use of fuzzy logic and neural network approach to perform flame analysis. Flame diagnostic is important in the industry to extract relevant information from flame images. Experiment test is carried out in a model industrial burner with different flow rates. Flame features such as luminous and spectral parameters are extracted using image processing and Fast Fourier Transform (FFT). Flame images are acquired using FLIR infrared camera. Non-linearities such as thermal acoustic oscillations and background noise affect the stability of flame. Flame velocity is one of the important characteristics that determines stability of flame. In this paper, an image processing method is proposed to determine flame velocity. Power spectral density (PSD) graph is a good tool for vibration analysis where flame stability can be approximated. However, a more intelligent diagnostic system is needed to automatically determine flame stability. In this paper, flame features of different flow rates are compared and analyzed. The selected flame features are used as inputs to the proposed fuzzy inference system to determine flame stability. Neural network is used to test the performance of the fuzzy inference system.

Robust high-resolution quantification of time signals encoded by in vivo magnetic resonance spectroscopy

NASA Astrophysics Data System (ADS)

Belkić, Dževad; Belkić, Karen

2018-01-01

This paper on molecular imaging emphasizes improving specificity of magnetic resonance spectroscopy (MRS) for early cancer diagnostics by high-resolution data analysis. Sensitivity of magnetic resonance imaging (MRI) is excellent, but specificity is insufficient. Specificity is improved with MRS by going beyond morphology to assess the biochemical content of tissue. This is contingent upon accurate data quantification of diagnostically relevant biomolecules. Quantification is spectral analysis which reconstructs chemical shifts, amplitudes and relaxation times of metabolites. Chemical shifts inform on electronic shielding of resonating nuclei bound to different molecular compounds. Oscillation amplitudes in time signals retrieve the abundance of MR sensitive nuclei whose number is proportional to metabolite concentrations. Transverse relaxation times, the reciprocal of decay probabilities of resonances, arise from spin-spin coupling and reflect local field inhomogeneities. In MRS single voxels are used. For volumetric coverage, multi-voxels are employed within a hybrid of MRS and MRI called magnetic resonance spectroscopic imaging (MRSI). Common to MRS and MRSI is encoding of time signals and subsequent spectral analysis. Encoded data do not provide direct clinical information. Spectral analysis of time signals can yield the quantitative information, of which metabolite concentrations are the most clinically important. This information is equivocal with standard data analysis through the non-parametric, low-resolution fast Fourier transform and post-processing via fitting. By applying the fast Padé transform (FPT) with high-resolution, noise suppression and exact quantification via quantum mechanical signal processing, advances are made, presented herein, focusing on four areas of critical public health importance: brain, prostate, breast and ovarian cancers.

Spectral Target Detection using Schroedinger Eigenmaps

NASA Astrophysics Data System (ADS)

Dorado-Munoz, Leidy P.

Applications of optical remote sensing processes include environmental monitoring, military monitoring, meteorology, mapping, surveillance, etc. Many of these tasks include the detection of specific objects or materials, usually few or small, which are surrounded by other materials that clutter the scene and hide the relevant information. This target detection process has been boosted lately by the use of hyperspectral imagery (HSI) since its high spectral dimension provides more detailed spectral information that is desirable in data exploitation. Typical spectral target detectors rely on statistical or geometric models to characterize the spectral variability of the data. However, in many cases these parametric models do not fit well HSI data that impacts the detection performance. On the other hand, non-linear transformation methods, mainly based on manifold learning algorithms, have shown a potential use in HSI transformation, dimensionality reduction and classification. In target detection, non-linear transformation algorithms are used as preprocessing techniques that transform the data to a more suitable lower dimensional space, where the statistical or geometric detectors are applied. One of these non-linear manifold methods is the Schroedinger Eigenmaps (SE) algorithm that has been introduced as a technique for semi-supervised classification. The core tool of the SE algorithm is the Schroedinger operator that includes a potential term that encodes prior information about the materials present in a scene, and enables the embedding to be steered in some convenient directions in order to cluster similar pixels together. A completely novel target detection methodology based on SE algorithm is proposed for the first time in this thesis. The proposed methodology does not just include the transformation of the data to a lower dimensional space but also includes the definition of a detector that capitalizes on the theory behind SE. The fact that target pixels and those similar pixels are clustered in a predictable region of the low-dimensional representation is used to define a decision rule that allows one to identify target pixels over the rest of pixels in a given image. In addition, a knowledge propagation scheme is used to combine spectral and spatial information as a means to propagate the "potential constraints" to nearby points. The propagation scheme is introduced to reinforce weak connections and improve the separability between most of the target pixels and the background. Experiments using different HSI data sets are carried out in order to test the proposed methodology. The assessment is performed from a quantitative and qualitative point of view, and by comparing the SE-based methodology against two other detection methodologies that use linear/non-linear algorithms as transformations and the well-known Adaptive Coherence/Cosine Estimator (ACE) detector. Overall results show that the SE-based detector outperforms the other two detection methodologies, which indicates the usefulness of the SE transformation in spectral target detection problems.

Continued Development of a Planetary Imaging Fourier Transform Spectrometer (PIFTS)

NASA Technical Reports Server (NTRS)

Sromovsky, L. A.

2002-01-01

This report describes continued efforts to evaluate a breadboard of a Planetary Imaging Fourier Transform Spectrometer (PIFTS). The PIFTS breadboard was developed under prior PIDDP funding. That effort is described in the final report for NASA Grant NAG5-6248 and in two conference papers (Sromovsky et al. 2000; Revercomb et al. 2000). The PIFTS breadboard was designed for near-IR (1-5.2 micrometer imaging of planetary targets with spectral resolving powers of several hundred to several thousand, using an InSb detector array providing at least 64x64 pixels imaging detail. The major focus of the development effort was to combine existing technologies to produce a small and low power design compatible with a very low mass flyable instrument. The objective of this grant (NAG5-10729) was further characterization of the breadboard performance, including intercomparisons with the highly accurate non-imaging Advanced Emitted Radiance Interferometer (AERI) (Revercomb et al. 1994; Best et al. 1997).

Imaging the eye fundus with real-time en-face spectral domain optical coherence tomography

PubMed Central

Bradu, Adrian; Podoleanu, Adrian Gh.

2014-01-01

Real-time display of processed en-face spectral domain optical coherence tomography (SD-OCT) images is important for diagnosis. However, due to many steps of data processing requirements, such as Fast Fourier transformation (FFT), data re-sampling, spectral shaping, apodization, zero padding, followed by software cut of the 3D volume acquired to produce an en-face slice, conventional high-speed SD-OCT cannot render an en-face OCT image in real time. Recently we demonstrated a Master/Slave (MS)-OCT method that is highly parallelizable, as it provides reflectivity values of points at depth within an A-scan in parallel. This allows direct production of en-face images. In addition, the MS-OCT method does not require data linearization, which further simplifies the processing. The computation in our previous paper was however time consuming. In this paper we present an optimized algorithm that can be used to provide en-face MS-OCT images much quicker. Using such an algorithm we demonstrate around 10 times faster production of sets of en-face OCT images than previously obtained as well as simultaneous real-time display of up to 4 en-face OCT images of 200 × 200 pixels2 from the fovea and the optic nerve of a volunteer. We also demonstrate 3D and B-scan OCT images obtained from sets of MS-OCT C-scans, i.e. with no FFT and no intermediate step of generation of A-scans. PMID:24761303

Absorption Mode FT-ICR Mass Spectrometry Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Donald F.; Kilgour, David P.; Konijnenburg, Marco

2013-12-03

Fourier transform ion cyclotron resonance mass spectrometry offers the highest mass resolving power for molecular imaging experiments. This high mass resolving power ensures that closely spaced peaks at the same nominal mass are resolved for proper image generation. Typically higher magnetic fields are used to increase mass resolving power. However, a gain in mass resolving power can also be realized by phase correction of the data for absorption mode display. In addition to mass resolving power, absorption mode offers higher mass accuracy and signal-to-noise ratio over the conventional magnitude mode. Here we present the first use of absorption mode formore » Fourier transform ion cyclotron resonance mass spectrometry imaging. The Autophaser algorithm is used to phase correct each spectrum (pixel) in the image and then these parameters are used by the Chameleon work-flow based data processing software to generate absorption mode ?Datacubes? for image and spectral viewing. Absorption mode reveals new mass and spatial features that are not resolved in magnitude mode and results in improved selected ion image contrast.« less

Development of an Imaging Fourier Transform Spectrometer

DTIC Science & Technology

1986-05-01

during multiple tests or concurrently applying many identical instrument systems to a single test. These difficult, expensive, and time-consuming...processes would introduce AEDC-TR-86-17 uncertainties due to nonstationary sources and instrument instability associated with multiple firings or... multiple instruments. For even moderate spatial, spectral, and temporal resolution, none of the previously mentioned approaches is reasonable. The

Image processing techniques and applications to the Earth Resources Technology Satellite program

NASA Technical Reports Server (NTRS)

Polge, R. J.; Bhagavan, B. K.; Callas, L.

1973-01-01

The Earth Resources Technology Satellite system is studied, with emphasis on sensors, data processing requirements, and image data compression using the Fast Fourier and Hadamard transforms. The ERTS-A system and the fundamentals of remote sensing are discussed. Three user applications (forestry, crops, and rangelands) are selected and their spectral signatures are described. It is shown that additional sensors are needed for rangeland management. An on-board information processing system is recommended to reduce the amount of data transmitted.

Research of generalized wavelet transformations of Haar correctness in remote sensing of the Earth

NASA Astrophysics Data System (ADS)

Kazaryan, Maretta; Shakhramanyan, Mihail; Nedkov, Roumen; Richter, Andrey; Borisova, Denitsa; Stankova, Nataliya; Ivanova, Iva; Zaharinova, Mariana

2017-10-01

In this paper, Haar's generalized wavelet functions are applied to the problem of ecological monitoring by the method of remote sensing of the Earth. We study generalized Haar wavelet series and suggest the use of Tikhonov's regularization method for investigating them for correctness. In the solution of this problem, an important role is played by classes of functions that were introduced and described in detail by I.M. Sobol for studying multidimensional quadrature formulas and it contains functions with rapidly convergent series of wavelet Haar. A theorem on the stability and uniform convergence of the regularized summation function of the generalized wavelet-Haar series of a function from this class with approximate coefficients is proved. The article also examines the problem of using orthogonal transformations in Earth remote sensing technologies for environmental monitoring. Remote sensing of the Earth allows to receive from spacecrafts information of medium, high spatial resolution and to conduct hyperspectral measurements. Spacecrafts have tens or hundreds of spectral channels. To process the images, the device of discrete orthogonal transforms, and namely, wavelet transforms, was used. The aim of the work is to apply the regularization method in one of the problems associated with remote sensing of the Earth and subsequently to process the satellite images through discrete orthogonal transformations, in particular, generalized Haar wavelet transforms. General methods of research. In this paper, Tikhonov's regularization method, the elements of mathematical analysis, the theory of discrete orthogonal transformations, and methods for decoding of satellite images are used. Scientific novelty. The task of processing of archival satellite snapshots (images), in particular, signal filtering, was investigated from the point of view of an incorrectly posed problem. The regularization parameters for discrete orthogonal transformations were determined.

Radiometric and spectral stray light correction for the portable remote imaging spectrometer (PRISM) coastal ocean sensor

NASA Astrophysics Data System (ADS)

Haag, Justin M.; Van Gorp, Byron E.; Mouroulis, Pantazis; Thompson, David R.

2017-09-01

The airborne Portable Remote Imaging Spectrometer (PRISM) instrument is based on a fast (F/1.8) Dyson spectrometer operating at 350-1050 nm and a two-mirror telescope combined with a Teledyne HyViSI 6604A detector array. Raw PRISM data contain electronic and optical artifacts that must be removed prior to radiometric calibration. We provide an overview of the process transforming raw digital numbers to calibrated radiance values. Electronic panel artifacts are first corrected using empirical relationships developed from laboratory data. The instrument spectral response functions (SRF) are reconstructed using a measurement-based optimization technique. Removal of SRF effects from the data improves retrieval of true spectra, particularly in the typically low-signal near-ultraviolet and near-infrared regions. As a final step, radiometric calibration is performed using corrected measurements of an object of known radiance. Implementation of the complete calibration procedure maximizes data quality in preparation for subsequent processing steps, such as atmospheric removal and spectral signature classification.

Accounting for tissue heterogeneity in infrared spectroscopic imaging for accurate diagnosis of thyroid carcinoma subtypes.

PubMed

Martinez-Marin, David; Sreedhar, Hari; Varma, Vishal K; Eloy, Catarina; Sobrinho-Simões, Manuel; Kajdacsy-Balla, André; Walsh, Michael J

2017-07-01

Fourier transform infrared (FT-IR) microscopy was used to image tissue samples from twenty patients diagnosed with thyroid carcinoma. The spectral data were then used to differentiate between follicular thyroid carcinoma and follicular variant of papillary thyroid carcinoma using principle component analysis coupled with linear discriminant analysis and a Naïve Bayesian classifier operating on a set of computed spectral metrics. Classification of patients' disease type was accomplished by using average spectra from a wide region containing follicular cells, colloid, and fibrosis; however, classification of disease state at the pixel level was only possible when the extracted spectra were limited to follicular epithelial cells in the samples, excluding the relatively uninformative areas of fibrosis. The results demonstrate the potential of FT-IR microscopy as a tool to assist in the difficult diagnosis of these subtypes of thyroid cancer, and also highlights the importance of selectively and separately analyzing spectral information from different features of a tissue of interest.

The optical design of a far infrared imaging FTS for SPICA

NASA Astrophysics Data System (ADS)

Pastor, Carmen; Zuluaga, Pablo; Jellema, Willem; González Fernández, Luis Miguel; Belenguer, Tomas; Torres Redondo, Josefina; Kooijman, Peter Paul; Najarro, Francisco; Eggens, Martin; Roelfsema, Peter; Nakagawa, Takao

2014-08-01

This paper describes the optical design of the far infrared imaging spectrometer for the JAXA's SPICA mission. The SAFARI instrument, is a cryogenic imaging Fourier transform spectrometer (iFTS), designed to perform backgroundlimited spectroscopic and photometric imaging in the band 34-210 μm. The all-reflective optical system is highly modular and consists of three main modules; input optics module, interferometer module (FTS) and camera bay optics. A special study has been dedicated to the spectroscopic performance of the instrument, in which the spectral response and interference of the instrument have been modeled, as the FTS mechanism scans over the total desired OPD range.

Multi Spectral Fluorescence Imager (MSFI)

NASA Technical Reports Server (NTRS)

Caron, Allison

2016-01-01

Genetic transformation with in vivo reporter genes for fluorescent proteins can be performed on a variety of organisms to address fundamental biological questions. Model organisms that may utilize an ISS imager include unicellular organisms (Saccharomyces cerevisiae), plants (Arabidopsis thaliana), and invertebrates (Caenorhabditis elegans). The multispectral fluorescence imager (MSFI) will have the capability to accommodate 10 cm x 10 cm Petri plates, various sized multi-well culture plates, and other custom culture containers. Features will include programmable temperature and light cycles, ethylene scrubbing (less than 25 ppb), CO2 control (between 400 ppm and ISS-ambient levels in units of 100 ppm) and sufficient airflow to prevent condensation that would interfere with imaging.

a Preliminary Investigation on Comparison and Transformation of SENTINEL-2 MSI and Landsat 8 Oli

NASA Astrophysics Data System (ADS)

Chen, F.; Lou, S.; Fan, Q.; Li, J.; Wang, C.; Claverie, M.

2018-05-01

A PRELIMINARY INVESTIGATION ON COMPARISON AND TRANSFORMATION OF SENTINEL-2 MSI AND LANDSAT 8 OLI Timely and accurate earth observation with short revisit interval is usually necessary, especially for emergency response. Currently, several new generation sensors provided with similar channel characteristics have been operated onboard different satellite platforms, including Sentinel-2 and Landsat 8. Joint use of the observations by different sensors offers an opportunity to meet the demands for emergency requirements. For example, through the combination of Landsat and Sentinel-2 data, the land can be observed every 2-3 days at medium spatial resolution. However, differences are expected in radiometric values (e.g., channel reflectance) of the corresponding channels between two sensors. Spectral response function (SRF) is taken as an important aspect of sensor settings. Accordingly, between-sensor differences due to SRFs variation need to be quantified and compensated. The comparison of SRFs shows difference (more or less) in channel settings between Sentinel-2 Multi-Spectral Instrument (MSI) and Landsat 8 Operational Land Imager (OLI). Effect of the difference in SRF on corresponding values between MSI and OLI was investigated, mainly in terms of channel reflectance and several derived spectral indices. Spectra samples from ASTER Spectral Library Version 2.0 and Hyperion data archives were used in obtaining channel reflectance simulation of MSI and OLI. Preliminary results show that MSI and OLI are well comparable in several channels with small relative discrepancy (< 5 %), including the Costal Aerosol channel, a NIR (855-875 nm) channel, the SWIR channels, and the Cirrus channel. Meanwhile, for channels covering Blue, Green, Red, and NIR (785-900 nm), the between-sensor differences are significantly presented. Compared with the difference in reflectance of each individual channel, the difference in derived spectral index is more significant. In addition, effectiveness of linear transformation model is not ensured when the target belongs to another spectra collection. If an improper transformation model is selected, the between-sensor discrepancy will even largely increase. In conclusion, improvement in between-sensor consistency is possibly a challenge, through linear transformation based on model(s) generated from other spectra collections.

Semi-Automatic Normalization of Multitemporal Remote Images Based on Vegetative Pseudo-Invariant Features

PubMed Central

Garcia-Torres, Luis; Caballero-Novella, Juan J.; Gómez-Candón, David; De-Castro, Ana Isabel

2014-01-01

A procedure to achieve the semi-automatic relative image normalization of multitemporal remote images of an agricultural scene called ARIN was developed using the following procedures: 1) defining the same parcel of selected vegetative pseudo-invariant features (VPIFs) in each multitemporal image; 2) extracting data concerning the VPIF spectral bands from each image; 3) calculating the correction factors (CFs) for each image band to fit each image band to the average value of the image series; and 4) obtaining the normalized images by linear transformation of each original image band through the corresponding CF. ARIN software was developed to semi-automatically perform the ARIN procedure. We have validated ARIN using seven GeoEye-1 satellite images taken over the same location in Southern Spain from early April to October 2010 at an interval of approximately 3 to 4 weeks. The following three VPIFs were chosen: citrus orchards (CIT), olive orchards (OLI) and poplar groves (POP). In the ARIN-normalized images, the range, standard deviation (s. d.) and root mean square error (RMSE) of the spectral bands and vegetation indices were considerably reduced compared to the original images, regardless of the VPIF or the combination of VPIFs selected for normalization, which demonstrates the method’s efficacy. The correlation coefficients between the CFs among VPIFs for any spectral band (and all bands overall) were calculated to be at least 0.85 and were significant at P = 0.95, indicating that the normalization procedure was comparably performed regardless of the VPIF chosen. ARIN method was designed only for agricultural and forestry landscapes where VPIFs can be identified. PMID:24604031

Higher resolution satellite remote sensing and the impact on image mapping

USGS Publications Warehouse

Watkins, Allen H.; Thormodsgard, June M.

1987-01-01

Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges.The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

A complex guided spectral transform Lanczos method for studying quantum resonance states

DOE PAGES

Yu, Hua-Gen

2014-12-28

A complex guided spectral transform Lanczos (cGSTL) algorithm is proposed to compute both bound and resonance states including energies, widths and wavefunctions. The algorithm comprises of two layers of complex-symmetric Lanczos iterations. A short inner layer iteration produces a set of complex formally orthogonal Lanczos (cFOL) polynomials. They are used to span the guided spectral transform function determined by a retarded Green operator. An outer layer iteration is then carried out with the transform function to compute the eigen-pairs of the system. The guided spectral transform function is designed to have the same wavefunctions as the eigenstates of the originalmore » Hamiltonian in the spectral range of interest. Therefore the energies and/or widths of bound or resonance states can be easily computed with their wavefunctions or by using a root-searching method from the guided spectral transform surface. The new cGSTL algorithm is applied to bound and resonance states of HO₂, and compared to previous calculations.« less

Multi-objective based spectral unmixing for hyperspectral images

NASA Astrophysics Data System (ADS)

Xu, Xia; Shi, Zhenwei

2017-02-01

Sparse hyperspectral unmixing assumes that each observed pixel can be expressed by a linear combination of several pure spectra in a priori library. Sparse unmixing is challenging, since it is usually transformed to a NP-hard l0 norm based optimization problem. Existing methods usually utilize a relaxation to the original l0 norm. However, the relaxation may bring in sensitive weighted parameters and additional calculation error. In this paper, we propose a novel multi-objective based algorithm to solve the sparse unmixing problem without any relaxation. We transform sparse unmixing to a multi-objective optimization problem, which contains two correlative objectives: minimizing the reconstruction error and controlling the endmember sparsity. To improve the efficiency of multi-objective optimization, a population-based randomly flipping strategy is designed. Moreover, we theoretically prove that the proposed method is able to recover a guaranteed approximate solution from the spectral library within limited iterations. The proposed method can directly deal with l0 norm via binary coding for the spectral signatures in the library. Experiments on both synthetic and real hyperspectral datasets demonstrate the effectiveness of the proposed method.

Hyper-spectral Atmospheric Sounding. Appendixes 1

NASA Technical Reports Server (NTRS)

Smith, W. L.; Zhou, D. K.; Revercomb, H. E.; Huang, H. L.; Antonelli, P.; Mango, S. A.

2002-01-01

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) is the first hyper-spectral remote sounding system to be orbited aboard a geosynchronous satellite. The GETS is designed to obtain revolutionary observations of the four dimensional atmospheric temperature, moisture, and wind structure as well as the distribution of the atmospheric trace gases, CO and O3. Although GIFTS will not be orbited until 2006-2008, a glimpse at the its measurement capabilities has been obtained by analyzing data from the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Test-bed-Interferometer (NAST-I) and Aqua satellite Atmospheric Infrared Sounder (AIRS). In this paper we review the GIFTS experiment and empirically assess measurement expectations based on meteorological profiles retrieved from the NAST aircraft and Aqua satellite AIRS spectral radiances.

Use of digital Munsell color space to assist interretation of imaging spectrometer data: Geologic examples from the northern Grapevine Mountains, California and Nevada

NASA Technical Reports Server (NTRS)

Kruse, F. A.; Knepper, D. H., Jr.; Clark, R. N.

1986-01-01

Techniques using Munsell color transformations were developed for reducing 128 channels (or less) of Airborne Imaging Spectrometer (AIS) data to a single color-composite-image suitable for both visual interpretation and digital analysis. Using AIS data acquired in 1984 and 1985, limestone and dolomite roof pendants and sericite-illite and other clay minerals related to alteration were mapped in a quartz monzonite stock in the northern Grapevine Mountains of California and Nevada. Field studies and laboratory spectral measurements verify the mineralogical distributions mapped from the AIS data.

Contrast in Terahertz Images of Archival Documents—Part I: Influence of the Optical Parameters from the Ink and Support

NASA Astrophysics Data System (ADS)

Bardon, Tiphaine; May, Robert K.; Jackson, J. Bianca; Beentjes, Gabriëlle; de Bruin, Gerrit; Taday, Philip F.; Strlič, Matija

2017-04-01

This study aims to objectively inform curators when terahertz time-domain (TD) imaging set in reflection mode is likely to give well-contrasted images of inscriptions in a complex archival document and is a useful non-invasive alternative to current digitisation processes. To this end, the dispersive refractive indices and absorption coefficients from various archival materials are assessed and their influence on contrast in terahertz images from historical documents is explored. Sepia ink and inks produced with bistre or verdigris mixed with a solution of Arabic gum or rabbit skin glue are unlikely to lead to well-contrasted images. However, dispersions of bone black, ivory black, iron gall ink, malachite, lapis lazuli, minium and vermilion are likely to lead to well-contrasted images. Inscriptions written with lamp black, carbon black and graphite give the best imaging results. The characteristic spectral signatures from iron gall ink, minium and vermilion pellets between 5 and 100 cm-1 relate to a ringing effect at late collection times in TD waveforms transmitted through these pellets. The same ringing effect can be probed in waveforms reflected from iron gall, minium and vermilion ink deposits at the surface of a document. Since TD waveforms collected for each scanning pixel can be Fourier-transformed into spectral information, terahertz TD imaging in reflection mode can serve as a hyperspectral imaging tool. However, chemical recognition and mapping of the ink is currently limited by the fact that the morphology of the document influences more the terahertz spectral response of the document than the resonant behaviour of the ink.

Hyperspectral image classification based on local binary patterns and PCANet

NASA Astrophysics Data System (ADS)

Yang, Huizhen; Gao, Feng; Dong, Junyu; Yang, Yang

2018-04-01

Hyperspectral image classification has been well acknowledged as one of the challenging tasks of hyperspectral data processing. In this paper, we propose a novel hyperspectral image classification framework based on local binary pattern (LBP) features and PCANet. In the proposed method, linear prediction error (LPE) is first employed to select a subset of informative bands, and LBP is utilized to extract texture features. Then, spectral and texture features are stacked into a high dimensional vectors. Next, the extracted features of a specified position are transformed to a 2-D image. The obtained images of all pixels are fed into PCANet for classification. Experimental results on real hyperspectral dataset demonstrate the effectiveness of the proposed method.

Enhancing hyperspectral spatial resolution using multispectral image fusion: A wavelet approach

NASA Astrophysics Data System (ADS)

Jazaeri, Amin

High spectral and spatial resolution images have a significant impact in remote sensing applications. Because both spatial and spectral resolutions of spaceborne sensors are fixed by design and it is not possible to further increase the spatial or spectral resolution, techniques such as image fusion must be applied to achieve such goals. This dissertation introduces the concept of wavelet fusion between hyperspectral and multispectral sensors in order to enhance the spectral and spatial resolution of a hyperspectral image. To test the robustness of this concept, images from Hyperion (hyperspectral sensor) and Advanced Land Imager (multispectral sensor) were first co-registered and then fused using different wavelet algorithms. A regression-based fusion algorithm was also implemented for comparison purposes. The results show that the fused images using a combined bi-linear wavelet-regression algorithm have less error than other methods when compared to the ground truth. In addition, a combined regression-wavelet algorithm shows more immunity to misalignment of the pixels due to the lack of proper registration. The quantitative measures of average mean square error show that the performance of wavelet-based methods degrades when the spatial resolution of hyperspectral images becomes eight times less than its corresponding multispectral image. Regardless of what method of fusion is utilized, the main challenge in image fusion is image registration, which is also a very time intensive process. Because the combined regression wavelet technique is computationally expensive, a hybrid technique based on regression and wavelet methods was also implemented to decrease computational overhead. However, the gain in faster computation was offset by the introduction of more error in the outcome. The secondary objective of this dissertation is to examine the feasibility and sensor requirements for image fusion for future NASA missions in order to be able to perform onboard image fusion. In this process, the main challenge of image registration was resolved by registering the input images using transformation matrices of previously acquired data. The composite image resulted from the fusion process remarkably matched the ground truth, indicating the possibility of real time onboard fusion processing.

Outlier and target detection in aerial hyperspectral imagery: a comparison of traditional and percentage occupancy hit or miss transform techniques

NASA Astrophysics Data System (ADS)

Young, Andrew; Marshall, Stephen; Gray, Alison

2016-05-01

The use of aerial hyperspectral imagery for the purpose of remote sensing is a rapidly growing research area. Currently, targets are generally detected by looking for distinct spectral features of the objects under surveillance. For example, a camouflaged vehicle, deliberately designed to blend into background trees and grass in the visible spectrum, can be revealed using spectral features in the near-infrared spectrum. This work aims to develop improved target detection methods, using a two-stage approach, firstly by development of a physics-based atmospheric correction algorithm to convert radiance into re ectance hyperspectral image data and secondly by use of improved outlier detection techniques. In this paper the use of the Percentage Occupancy Hit or Miss Transform is explored to provide an automated method for target detection in aerial hyperspectral imagery.

Quantitative subsurface analysis using frequency modulated thermal wave imaging

NASA Astrophysics Data System (ADS)

Subhani, S. K.; Suresh, B.; Ghali, V. S.

2018-01-01

Quantitative depth analysis of the anomaly with an enhanced depth resolution is a challenging task towards the estimation of depth of the subsurface anomaly using thermography. Frequency modulated thermal wave imaging introduced earlier provides a complete depth scanning of the object by stimulating it with a suitable band of frequencies and further analyzing the subsequent thermal response using a suitable post processing approach to resolve subsurface details. But conventional Fourier transform based methods used for post processing unscramble the frequencies with a limited frequency resolution and contribute for a finite depth resolution. Spectral zooming provided by chirp z transform facilitates enhanced frequency resolution which can further improves the depth resolution to axially explore finest subsurface features. Quantitative depth analysis with this augmented depth resolution is proposed to provide a closest estimate to the actual depth of subsurface anomaly. This manuscript experimentally validates this enhanced depth resolution using non stationary thermal wave imaging and offers an ever first and unique solution for quantitative depth estimation in frequency modulated thermal wave imaging.

A group filter algorithm for sea mine detection

NASA Astrophysics Data System (ADS)

Cobb, J. Tory; An, Myoung; Tolimieri, Richard

2005-06-01

Automatic detection of sea mines in coastal regions is a difficult task due to the highly variable sea bottom conditions present in the underwater environment. Detection systems must be able to discriminate objects which vary in size, shape, and orientation from naturally occurring and man-made clutter. Additionally, these automated systems must be computationally efficient to be incorporated into unmanned underwater vehicle (UUV) sensor systems characterized by high sensor data rates and limited processing abilities. Using noncommutative group harmonic analysis, a fast, robust sea mine detection system is created. A family of unitary image transforms associated to noncommutative groups is generated and applied to side scan sonar image files supplied by Naval Surface Warfare Center Panama City (NSWC PC). These transforms project key image features, geometrically defined structures with orientations, and localized spectral information into distinct orthogonal components or feature subspaces of the image. The performance of the detection system is compared against the performance of an independent detection system in terms of probability of detection (Pd) and probability of false alarm (Pfa).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foxley, Sean, E-mail: sean.foxley@ndcn.ox.ac.uk; Karczmar, Gregory S.; Domowicz, Miriam

Purpose: Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T{sub 2}{sup *}-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflectmore » local anatomy. The resulting information compliments previous studies based on T{sub 2}{sup *} and resonance frequency. Methods: The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm{sup 3} and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16–24 h). Results: High contrast T{sub 2}{sup *}-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at −7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not present at +7.0 Hz and may be specific to white matter anatomy. Moreover, a frequency shift of 6.76 ± 0.55 Hz was measured between the molecular and granular layers of the cerebellum. This shift is demonstrated in corresponding spectra; water peaks from voxels in the molecular and granular layers are consistently 2 bins apart (7.0 Hz, as dictated by the spectral resolution) from one another. Conclusions: High spectral and spatial resolution MR imaging has the potential to accurately measure the changes in the water resonance in small voxels. This information can guide optimization and interpretation of more commonly used, more rapid imaging methods that depend on image contrast produced by local susceptibility gradients. In addition, with improved sampling methods, high spectral and spatial resolution data could be acquired in reasonable run times, and used for in vivo scans to increase sensitivity to variations in local susceptibility.« less

Adaptive coding of MSS imagery. [Multi Spectral band Scanners

NASA Technical Reports Server (NTRS)

Habibi, A.; Samulon, A. S.; Fultz, G. L.; Lumb, D.

1977-01-01

A number of adaptive data compression techniques are considered for reducing the bandwidth of multispectral data. They include adaptive transform coding, adaptive DPCM, adaptive cluster coding, and a hybrid method. The techniques are simulated and their performance in compressing the bandwidth of Landsat multispectral images is evaluated and compared using signal-to-noise ratio and classification consistency as fidelity criteria.

Fourier transform infrared spectroscopic imaging parameters describing acid phosphate substitution in biologic hydroxyapatite.

PubMed

Spevak, Lyudmila; Flach, Carol R; Hunter, Tracey; Mendelsohn, Richard; Boskey, Adele

2013-05-01

Acid phosphate substitution into mineralized tissues is an important determinant of their mechanical properties and their response to treatment. This study identifies and validates Fourier transform infrared spectroscopic imaging (FTIRI) spectral parameters that provide information on the acid phosphate (HPO4) substitution into hydroxyapatite in developing mineralized tissues. Curve fitting and Fourier self-deconvolution were used to identify subband positions in model compounds (with and without HPO4). The intensity of subbands at 1127 and 1110 cm(-1) correlated with the acid phosphate content in these models. Peak height ratios of these subbands to the ν3 vibration at 1096 cm(-1) found in stoichiometric apatite were evaluated in the model compounds and mixtures thereof. FTIRI spectra of bones and teeth at different developmental ages were analyzed using these spectral parameters. Factor analysis (a chemometric technique) was also conducted on the tissue samples and resulted in factor loadings with spectral features corresponding to the HPO4 vibrations described above. Images of both factor correlation coefficients and the peak height ratios 1127/1096 and 1112/1096 cm(-1) demonstrated higher acid phosphate content in younger vs. more mature regions in the same specimen. Maps of the distribution of acid phosphate content will be useful for characterizing the extent of new bone formation, the areas of potential decreased strength, and the effects of therapies such as those used in metabolic bone diseases (osteoporosis, chronic kidney disease) on mineral composition. Because of the wider range of values obtained with the 1127/1096 cm(-1) parameter compared to the 1110/1096 cm(-1) parameter and the smaller scatter in the slope, it is suggested that this ratio should be the parameter of choice.

PISCES High Contrast Integral Field Spectrograph Simulations and Data Reduction Pipeline

NASA Technical Reports Server (NTRS)

Llop Sayson, Jorge Domingo; Memarsadeghi, Nargess; McElwain, Michael W.; Gong, Qian; Perrin, Marshall; Brandt, Timothy; Grammer, Bryan; Greeley, Bradford; Hilton, George; Marx, Catherine

2015-01-01

The PISCES (Prototype Imaging Spectrograph for Coronagraphic Exoplanet Studies) is a lenslet array based integral field spectrograph (IFS) designed to advance the technology readiness of the WFIRST (Wide Field Infrared Survey Telescope)-AFTA (Astrophysics Focused Telescope Assets) high contrast Coronagraph Instrument. We present the end to end optical simulator and plans for the data reduction pipeline (DRP). The optical simulator was created with a combination of the IDL (Interactive Data Language)-based PROPER (optical propagation) library and Zemax (a MatLab script), while the data reduction pipeline is a modified version of the Gemini Planet Imager's (GPI) IDL pipeline. The simulations of the propagation of light through the instrument are based on Fourier transform algorithms. The DRP enables transformation of the PISCES IFS data to calibrated spectral data cubes.

Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM).

PubMed

Gao, Hao; Yu, Hengyong; Osher, Stanley; Wang, Ge

2011-11-01

We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations.

A general spectral transformation simultaneously including a Fourier transformation and a Laplace transformation

NASA Technical Reports Server (NTRS)

Marko, H.

1978-01-01

A general spectral transformation is proposed and described. Its spectrum can be interpreted as a Fourier spectrum or a Laplace spectrum. The laws and functions of the method are discussed in comparison with the known transformations, and a sample application is shown.

Real-time processing for full-range Fourier-domain optical-coherence tomography with zero-filling interpolation using multiple graphic processing units.

PubMed

Watanabe, Yuuki; Maeno, Seiya; Aoshima, Kenji; Hasegawa, Haruyuki; Koseki, Hitoshi

2010-09-01

The real-time display of full-range, 2048?axial pixelx1024?lateral pixel, Fourier-domain optical-coherence tomography (FD-OCT) images is demonstrated. The required speed was achieved by using dual graphic processing units (GPUs) with many stream processors to realize highly parallel processing. We used a zero-filling technique, including a forward Fourier transform, a zero padding to increase the axial data-array size to 8192, an inverse-Fourier transform back to the spectral domain, a linear interpolation from wavelength to wavenumber, a lateral Hilbert transform to obtain the complex spectrum, a Fourier transform to obtain the axial profiles, and a log scaling. The data-transfer time of the frame grabber was 15.73?ms, and the processing time, which includes the data transfer between the GPU memory and the host computer, was 14.75?ms, for a total time shorter than the 36.70?ms frame-interval time using a line-scan CCD camera operated at 27.9?kHz. That is, our OCT system achieved a processed-image display rate of 27.23 frames/s.

Broadband Structural Dynamics: Understanding the Impulse-Response of Structures Across Multiple Length and Time Scales

DTIC Science & Technology

2010-08-18

Spectral domain response calculated • Time domain response obtained through inverse transform Approach 4: WASABI Wavelet Analysis of Structural Anomalies...differences at unity scale! Time Function Transform Apply Spectral Domain Transfer Function Time Function Inverse Transform Transform Transform  mtP

Transformation of light double cones in the human retina: the origin of trichromatism, of 4D-spatiotemporal vision, and of patchwise 4D Fourier transformation in Talbot imaging

NASA Astrophysics Data System (ADS)

Lauinger, Norbert

1997-09-01

The interpretation of the 'inverted' retina of primates as an 'optoretina' (a light cones transforming diffractive cellular 3D-phase grating) integrates the functional, structural, and oscillatory aspects of a cortical layer. It is therefore relevant to consider prenatal developments as a basis of the macro- and micro-geometry of the inner eye. This geometry becomes relevant for the postnatal trichromatic synchrony organization (TSO) as well as the adaptive levels of human vision. It is shown that the functional performances, the trichromatism in photopic vision, the monocular spatiotemporal 3D- and 4D-motion detection, as well as the Fourier optical image transformation with extraction of invariances all become possible. To transform light cones into reciprocal gratings especially the spectral phase conditions in the eikonal of the geometrical optical imaging before the retinal 3D-grating become relevant first, then in the von Laue resp. reciprocal von Laue equation for 3D-grating optics inside the grating and finally in the periodicity of Talbot-2/Fresnel-planes in the near-field behind the grating. It is becoming possible to technically realize -- at least in some specific aspects -- such a cortical optoretina sensor element with its typical hexagonal-concentric structure which leads to these visual functions.

Spectral transform and orthogonality relations for the Kadomtsev-Petviashvili I equation

NASA Astrophysics Data System (ADS)

Boiti, M.; Leon, J. J.-P.; Pempinelli, F.

1989-10-01

We define a new spectral transform r(k, l) of the potential u in the time dependent Schrödinger equation (associated to the KPI equation). Orthogonality relations for the sectionally holomorphic eigenfunctions of the Schrödinger equation are used to express the spectral transform f( k, l) previously introduced by Manakov and Fokas and Ablowitz in terms of r( k, l). The main advantage of the new spectral transform r( k, l) is that its definition does not require to introduce an additional nonanalytic eigenfunction N. Characterization equations for r( k, l) are also obtained.

Design of far-infrared acousto-optic tunable filter based on backward collinear interaction.

PubMed

Voloshinov, Vitaly B; Porokhovnichenko, Dmitriy L; Dyakonov, Evgeniy A

2018-04-10

The paper proposes a design of acousto-optic cell applying backward collinear interaction and acoustic mode transformation in a KRS-5 crystal. This cell may serve as an acousto-optic tunable filter for far-infrared spectral range and is able to operate both with collimated optical beams and with divergent beams forming images. The problem of acoustic mode transformation by wave reflection from the crystal facet away from symmetry planes has been solved. Polarization properties of the backward collinear interaction in optically isotropic media are discussed. Copyright © 2018 Elsevier B.V. All rights reserved.

Application of Fourier analysis to multispectral/spatial recognition

NASA Technical Reports Server (NTRS)

Hornung, R. J.; Smith, J. A.

1973-01-01

One approach for investigating spectral response from materials is to consider spatial features of the response. This might be accomplished by considering the Fourier spectrum of the spatial response. The Fourier Transform may be used in a one-dimensional to multidimensional analysis of more than one channel of data. The two-dimensional transform represents the Fraunhofer diffraction pattern of the image in optics and has certain invariant features. Physically the diffraction pattern contains spatial features which are possibly unique to a given configuration or classification type. Different sampling strategies may be used to either enhance geometrical differences or extract additional features.

From printed color to image appearance: tool for advertising assessment

NASA Astrophysics Data System (ADS)

Bonanomi, Cristian; Marini, Daniele; Rizzi, Alessandro

2012-07-01

We present a methodology to calculate the color appearance of advertising billboards set in indoor and outdoor environments, printed on different types of paper support and viewed under different illuminations. The aim is to simulate the visual appearance of an image printed on a specific support, observed in a certain context and illuminated with a specific source of light. Knowing in advance the visual rendering of an image in different conditions can avoid problems related to its visualization. The proposed method applies a sequence of transformations to convert a four channels image (CMYK) into a spectral one, considering the paper support, then it simulates the chosen illumination, and finally computes an estimation of the appearance.

A Protocol for Using Förster Resonance Energy Transfer (FRET)-force Biosensors to Measure Mechanical Forces across the Nuclear LINC Complex.

PubMed

Arsenovic, Paul T; Bathula, Kranthidhar; Conway, Daniel E

2017-04-11

The LINC complex has been hypothesized to be the critical structure that mediates the transfer of mechanical forces from the cytoskeleton to the nucleus. Nesprin-2G is a key component of the LINC complex that connects the actin cytoskeleton to membrane proteins (SUN domain proteins) in the perinuclear space. These membrane proteins connect to lamins inside the nucleus. Recently, a Förster Resonance Energy Transfer (FRET)-force probe was cloned into mini-Nesprin-2G (Nesprin-TS (tension sensor)) and used to measure tension across Nesprin-2G in live NIH3T3 fibroblasts. This paper describes the process of using Nesprin-TS to measure LINC complex forces in NIH3T3 fibroblasts. To extract FRET information from Nesprin-TS, an outline of how to spectrally unmix raw spectral images into acceptor and donor fluorescent channels is also presented. Using open-source software (ImageJ), images are pre-processed and transformed into ratiometric images. Finally, FRET data of Nesprin-TS is presented, along with strategies for how to compare data across different experimental groups.

Hyperspectral imaging for detection of cholesterol in human skin

NASA Astrophysics Data System (ADS)

Milanič, Matija; Bjorgan, Asgeir; Larsson, Marcus; Marraccini, Paolo; Strömberg, Tomas; Randeberg, Lise L.

2015-03-01

Hypercholesterolemia is characterized by high levels of cholesterol in the blood and is associated with an increased risk of atherosclerosis and coronary heart disease. Early detection of hypercholesterolemia is necessary to prevent onset and progress of cardiovascular disease. Optical imaging techniques might have a potential for early diagnosis and monitoring of hypercholesterolemia. In this study, hyperspectral imaging was investigated for this application. The main aim of the study was to identify spectral and spatial characteristics that can aid identification of hypercholesterolemia in facial skin. The first part of the study involved a numerical simulation of human skin affected by hypercholesterolemia. A literature survey was performed to identify characteristic morphological and physiological parameters. Realistic models were prepared and Monte Carlo simulations were performed to obtain hyperspectral images. Based on the simulations optimal wavelength regions for differentiation between normal and cholesterol rich skin were identified. Minimum Noise Fraction transformation (MNF) was used for analysis. In the second part of the study, the simulations were verified by a clinical study involving volunteers with elevated and normal levels of cholesterol. The faces of the volunteers were scanned by a hyperspectral camera covering the spectral range between 400 nm and 720 nm, and characteristic spectral features of the affected skin were identified. Processing of the images was done after conversion to reflectance and masking of the images. The identified features were compared to the known cholesterol levels of the subjects. The results of this study demonstrate that hyperspectral imaging of facial skin can be a promising, rapid modality for detection of hypercholesterolemia.

Mapping swamp timothy (Cripsis schenoides) seed productivity using spectral values and vegetation indices in managed wetlands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rahilly, P.J.A.; Li, D.; Guo, Q.

2010-01-15

This work examines the potential to predict the seed productivity of a key wetland plant species using spectral reflectance values and spectral vegetation indices. Specifically, the seed productivity of swamp timothy (Cripsis schenoides) was investigated in two wetland ponds, managed for waterfowl habitat, in California's San Joaquin Valley. Spectral reflectance values were obtained and associated spectral vegetation indices (SVI) calculated from two sets of high resolution aerial images (May 11, 2006 and June 9, 2006) and were compared to the collected vegetation data. Vegetation data were collected and analyzed from 156 plots for total aboveground biomass, total aboveground swamp timothymore » biomass, and total swamp timothy seed biomass. The SVI investigated included the Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Transformed Soil Adjusted Vegetation Index (TSAVI), Modified Soil Adjusted Vegetation Index (MSAVI), and Global Environment Monitoring Index (GEMI). We evaluated the correlation of the various SVI with in situ vegetation measurements for linear, quadratic, exponential and power functions. In all cases, the June image provided better predictive capacity relative to May, a result that underscores the importance of timing imagery to coincide with more favorable vegetation maturity. The north pond with the June image using SR and the exponential function (R{sup 2}=0.603) proved to be the best predictor of swamp timothy seed productivity. The June image for the south pond was less predictive, with TSAVI and the exponential function providing the best correlation (R{sup 2}=0.448). This result was attributed to insufficient vegetal cover in the south pond (or a higher percentage of bare soil) due to poor drainage conditions which resulted in a delay in swamp timothy germination. The results of this work suggest that spectral reflectance can be used to estimate seed productivity in managed seasonal wetlands.« less

Superharmonic imaging with chirp coded excitation: filtering spectrally overlapped harmonics.

PubMed

Harput, Sevan; McLaughlan, James; Cowell, David M J; Freear, Steven

2014-11-01

Superharmonic imaging improves the spatial resolution by using the higher order harmonics generated in tissue. The superharmonic component is formed by combining the third, fourth, and fifth harmonics, which have low energy content and therefore poor SNR. This study uses coded excitation to increase the excitation energy. The SNR improvement is achieved on the receiver side by performing pulse compression with harmonic matched filters. The use of coded signals also introduces new filtering capabilities that are not possible with pulsed excitation. This is especially important when using wideband signals. For narrowband signals, the spectral boundaries of the harmonics are clearly separated and thus easy to filter; however, the available imaging bandwidth is underused. Wideband excitation is preferable for harmonic imaging applications to preserve axial resolution, but it generates spectrally overlapping harmonics that are not possible to filter in time and frequency domains. After pulse compression, this overlap increases the range side lobes, which appear as imaging artifacts and reduce the Bmode image quality. In this study, the isolation of higher order harmonics was achieved in another domain by using the fan chirp transform (FChT). To show the effect of excitation bandwidth in superharmonic imaging, measurements were performed by using linear frequency modulated chirp excitation with varying bandwidths of 10% to 50%. Superharmonic imaging was performed on a wire phantom using a wideband chirp excitation. Results were presented with and without applying the FChT filtering technique by comparing the spatial resolution and side lobe levels. Wideband excitation signals achieved a better resolution as expected, however range side lobes as high as -23 dB were observed for the superharmonic component of chirp excitation with 50% fractional bandwidth. The proposed filtering technique achieved >50 dB range side lobe suppression and improved the image quality without affecting the axial resolution.

Spectral interpolation - Zero fill or convolution. [image processing

NASA Technical Reports Server (NTRS)

Forman, M. L.

1977-01-01

Zero fill, or augmentation by zeros, is a method used in conjunction with fast Fourier transforms to obtain spectral spacing at intervals closer than obtainable from the original input data set. In the present paper, an interpolation technique (interpolation by repetitive convolution) is proposed which yields values accurate enough for plotting purposes and which lie within the limits of calibration accuracies. The technique is shown to operate faster than zero fill, since fewer operations are required. The major advantages of interpolation by repetitive convolution are that efficient use of memory is possible (thus avoiding the difficulties encountered in decimation in time FFTs) and that is is easy to implement.

Using Fourier transform IR spectroscopy to analyze biological materials

PubMed Central

Baker, Matthew J; Trevisan, Júlio; Bassan, Paul; Bhargava, Rohit; Butler, Holly J; Dorling, Konrad M; Fielden, Peter R; Fogarty, Simon W; Fullwood, Nigel J; Heys, Kelly A; Hughes, Caryn; Lasch, Peter; Martin-Hirsch, Pierre L; Obinaju, Blessing; Sockalingum, Ganesh D; Sulé-Suso, Josep; Strong, Rebecca J; Walsh, Michael J; Wood, Bayden R; Gardner, Peter; Martin, Francis L

2015-01-01

IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing. PMID:24992094

A discrete polar Stockwell transform for enhanced characterization of tissue structure using MRI.

PubMed

Pridham, Glen; Steenwijk, Martijn D; Geurts, Jeroen J G; Zhang, Yunyan

2018-05-02

The purpose of this study was to present an effective algorithm for computing the discrete polar Stockwell transform (PST), investigate its unique multiscale and multi-orientation features, and explore potentially new applications including denoising and tissue segmentation. We investigated PST responses using both synthetic and MR images. Moreover, we compared the features of PST with both Gabor and Morlet wavelet transforms, and compared the PST with two wavelet approaches for denoising using MRI. Using a synthetic image, we also tested the edge effect of PST through signal-padding. Then, we constructed a partially supervised classifier using radial, marginal PST spectra of T2-weighted MRI, acquired from postmortem brains with multiple sclerosis. The classification involved three histology-verified tissue types: normal appearing white matter (NAWM), lesion, or other, along with 5-fold cross-validation. The PST generated a series of images with varying orientations or rotation-invariant scales. Radial frequencies highlighted image structures of different size, and angular frequencies enhanced structures by orientation. Signal-padding helped suppress boundary artifacts but required attention to incidental artifacts. In comparison, the Gabor transform produced more redundant images and the wavelet spectra appeared less spatially smooth than the PST. In addition, the PST demonstrated lower root-mean-square errors than other transforms in denoising and achieved a 93% accuracy for NAWM pixels (296/317), and 88% accuracy for lesion pixels (165/188) in MRI segmentation. The PST is a unique local spectral density-assessing tool which is sensitive to both structure orientations and scales. This may facilitate multiple new applications including advanced characterization of tissue structure in standard MRI. © 2018 International Society for Magnetic Resonance in Medicine.

Double Fourier analysis for Emotion Identification in Voiced Speech

NASA Astrophysics Data System (ADS)

Sierra-Sosa, D.; Bastidas, M.; Ortiz P., D.; Quintero, O. L.

2016-04-01

We propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech. Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions. A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds. Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions. Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it. Finally features related with emotions in voiced speech are extracted and presented.

An algorithm for retrieving rock-desertification from multispectral remote sensing images

NASA Astrophysics Data System (ADS)

Xia, Xueqi; Tian, Qingjiu; Liao, Yan

2009-06-01

Rock-desertification is a typical environmental and ecological problem in Southwest China. As remote sensing is an important means of monitoring spatial variation of rock-desertification, a method is developed for measurement and information retrieval of rock-desertification from multi-spectral high-resolution remote sensing images. MNF transform is applied to 4-band IKONOS multi-spectral remotely sensed data to reduce the number of spectral dimensions to three. In the 3-demension endmembers are extracted and analyzed. It is found that various vegetations group into a line defined as "vegetation line", in which "dark vegetations", such as coniferous forest and broadleaf forest, continuously change to "bright vegetations", such as grasses. It is presumed that is caused by deferent proportion of shadow mixed in leaves or branches in various types of vegetation. Normalized distance between the endmember of rocks and the vegetation line is defined as Geometric Rock-desertification Index (GRI), which was used to scale rock-desertification. The case study with ground truth validation in Puding, Guizhou province showed successes and the advantages of this method.

Simulating the WFIRST coronagraph integral field spectrograph

NASA Astrophysics Data System (ADS)

Rizzo, Maxime J.; Groff, Tyler D.; Zimmermann, Neil T.; Gong, Qian; Mandell, Avi M.; Saxena, Prabal; McElwain, Michael W.; Roberge, Aki; Krist, John; Riggs, A. J. Eldorado; Cady, Eric J.; Mejia Prada, Camilo; Brandt, Timothy; Douglas, Ewan; Cahoy, Kerri

2017-09-01

A primary goal of direct imaging techniques is to spectrally characterize the atmospheres of planets around other stars at extremely high contrast levels. To achieve this goal, coronagraphic instruments have favored integral field spectrographs (IFS) as the science cameras to disperse the entire search area at once and obtain spectra at each location, since the planet position is not known a priori. These spectrographs are useful against confusion from speckles and background objects, and can also help in the speckle subtraction and wavefront control stages of the coronagraphic observation. We present a software package, the Coronagraph and Rapid Imaging Spectrograph in Python (crispy) to simulate the IFS of the WFIRST Coronagraph Instrument (CGI). The software propagates input science cubes using spatially and spectrally resolved coronagraphic focal plane cubes, transforms them into IFS detector maps and ultimately reconstructs the spatio-spectral input scene as a 3D datacube. Simulated IFS cubes can be used to test data extraction techniques, refine sensitivity analyses and carry out design trade studies of the flight CGI-IFS instrument. crispy is a publicly available Python package and can be adapted to other IFS designs.

Wide-field spectral imaging of human ovary autofluorescence and oncologic diagnosis via previously collected probe data

NASA Astrophysics Data System (ADS)

Renkoski, Timothy E.; Hatch, Kenneth D.; Utzinger, Urs

2012-03-01

With no sufficient screening test for ovarian cancer, a method to evaluate the ovarian disease state quickly and nondestructively is needed. The authors have applied a wide-field spectral imager to freshly resected ovaries of 30 human patients in a study believed to be the first of its magnitude. Endogenous fluorescence was excited with 365-nm light and imaged in eight emission bands collectively covering the 400- to 640-nm range. Linear discriminant analysis was used to classify all image pixels and generate diagnostic maps of the ovaries. Training the classifier with previously collected single-point autofluorescence measurements of a spectroscopic probe enabled this novel classification. The process by which probe-collected spectra were transformed for comparison with imager spectra is described. Sensitivity of 100% and specificity of 51% were obtained in classifying normal and cancerous ovaries using autofluorescence data alone. Specificity increased to 69% when autofluorescence data were divided by green reflectance data to correct for spatial variation in tissue absorption properties. Benign neoplasm ovaries were also found to classify as nonmalignant using the same algorithm. Although applied ex vivo, the method described here appears useful for quick assessment of cancer presence in the human ovary.

A Panchromatic Imaging Fourier Transform Spectrometer for the NASA Geostationary Coastal and Air Pollution Events Mission

NASA Technical Reports Server (NTRS)

Wu, Yen-Hung; Key, Richard; Sander, Stanley; Blavier, Jean-Francois; Rider, David

2011-01-01

This paper summarizes the design and development of the Panchromatic Imaging Fourier Transform Spectrometer (PanFTS) for the NASA Geostationary Coastal and Air Pollution Events (GEO-CAPE) Mission. The PanFTS instrument will advance the understanding of the global climate and atmospheric chemistry by measuring spectrally resolved outgoing thermal and reflected solar radiation. With continuous spectral coverage from the near-ultraviolet through the thermal infrared, this instrument is designed to measure pollutants, greenhouse gases, and aerosols as called for by the U.S. National Research Council Decadal Survey; Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond1. The PanFTS instrument is a hybrid instrument based on spectrometers like the Tropospheric Emissions Spectrometer (TES) that measures thermal emission, and those like the Orbiting Carbon Observatory (OCO), and the Ozone Monitoring Instrument (OMI) that measure scattered solar radiation. Simultaneous measurements over the broad spectral range from IR to UV is accomplished by a two sided interferometer with separate optical trains and detectors for the ultraviolet-visible and infrared spectral domains. This allows each side of the instrument to be independently optimized for its respective spectral domain. The overall interferometer design is compact because the two sides share a single high precision cryogenic optical path difference mechanism (OPDM) and metrology laser as well as a number of other instrument systems including the line-of-sight pointing mirror, the data management system, thermal control system, electrical system, and the mechanical structure. The PanFTS breadboard instrument has been tested in the laboratory and demonstrated the basic functionality for simultaneous measurements in the visible and infrared. It is set to begin operations in the field at the California Laboratory for Atmospheric Remote Sensing (CLARS) observatory on Mt. Wilson measuring the atmospheric chemistry across the Los Angeles basin. Development has begun on a flight size PanFTS engineering model (EM) that addresses all critical scaling issues and demonstrates operation over the full spectral range of the flight instrument which will show the PanFTS instrument design is mature.

Spectral transformation of ASTER and Landsat TM bands for lithological mapping of Soghan ophiolite complex, south Iran

NASA Astrophysics Data System (ADS)

Pournamdari, Mohsen; Hashim, Mazlan; Pour, Amin Beiranvand

2014-08-01

Spectral transformation methods, including correlation coefficient (CC) and Optimum Index Factor (OIF), band ratio (BR) and principal component analysis (PCA) were applied to ASTER and Landsat TM bands for lithological mapping of Soghan ophiolitic complex in south of Iran. The results indicated that the methods used evidently showed superior outputs for detecting lithological units in ophiolitic complexes. CC and OIF methods were used to establish enhanced Red-Green-Blue (RGB) color combination bands for discriminating lithological units. A specialized band ratio (4/1, 4/5, 4/7 in RGB) was developed using ASTER bands to differentiate lithological units in ophiolitic complexes. The band ratio effectively detected serpentinite dunite as host rock of chromite ore deposits from surrounding lithological units in the study area. Principal component images derived from first three bands of ASTER and Landsat TM produced well results for lithological mapping applications. ASTER bands contain improved spectral characteristics and higher spatial resolution for detecting serpentinite dunite in ophiolitic complexes. The developed approach used in this study offers great potential for lithological mapping using ASTER and Landsat TM bands, which contributes in economic geology for prospecting chromite ore deposits associated with ophiolitic complexes.

SITELLE: a wide-field imaging Fourier transform spectrometer for the Canada-France-Hawaii Telescope

NASA Astrophysics Data System (ADS)

Drissen, L.; Bernier, A.-P.; Rousseau-Nepton, L.; Alarie, A.; Robert, C.; Joncas, G.; Thibault, S.; Grandmont, F.

2010-07-01

We describe the concept of a new instrument for the Canada-France-Hawaii telescope (CFHT), SITELLE (Spectromètre Imageur à Transformée de Fourier pour l'Etude en Long et en Large de raies d'Emission), as well as a science case and a technical study of its preliminary design. SITELLE will be an imaging Fourier transform spectrometer capable of obtaining the visible (350 nm - 950 nm) spectrum of every source of light in a field of view of 15 arcminutes, with 100% spatial coverage and a spectral resolution ranging from R = 1 (deep panchromatic image) to R = 104 (for gas dynamics). SITELLE will cover a field of view 100 to 1000 times larger than traditional integral field spectrographs, such as GMOS-IFU on Gemini or the future MUSE on the VLT. It is a legacy from BEAR, the first imaging FTS installed on the CFHT and the direct successor of SpIOMM, a similar instrument attached to the 1.6-m telescope of the Observatoire du Mont-Mégantic in Québec. SITELLE will be used to study the structure and kinematics of HII regions and ejecta around evolved stars in the Milky Way, emission-line stars in clusters, abundances in nearby gas-rich galaxies, and the star formation rate in distant galaxies.

Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer's disease.

PubMed

Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

2016-07-01

Computer based diagnosis of Alzheimer's disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer's disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn; Moin, Aisha; Srivastava, Anuja

Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Componentmore » Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).« less

Optimal attributes for the object based detection of giant reed in riparian habitats: A comparative study between Airborne High Spatial Resolution and WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Fernandes, Maria Rosário; Aguiar, Francisca C.; Silva, João M. N.; Ferreira, Maria Teresa; Pereira, José M. C.

2014-10-01

Giant reed is an aggressive invasive plant of riparian ecosystems in many sub-tropical and warm-temperate regions, including Mediterranean Europe. In this study we tested a set of geometric, spectral and textural attributes in an object based image analysis (OBIA) approach to map giant reed invasions in riparian habitats. Bagging Classification and Regression Tree were used to select the optimal attributes and to build the classification rules sets. Mapping accuracy was performed using landscape metrics and the Kappa coefficient to compare the topographical and geometric similarity between the giant reed patches obtained with the OBIA map and with a validation map derived from on-screen digitizing. The methodology was applied in two high spatial resolution images: an airborne multispectral imagery and the newly WorldView-2 imagery. A temporal coverage of the airborne multispectral images was radiometrically calibrated with the IR-Mad transformation and used to assess the influence of the phenological variability of the invader. We found that optimal attributes for giant reed OBIA detection are a combination of spectral, geometric and textural information, with different scoring selection depending on the spectral and spatial characteristics of the imagery. WorldView-2 showed higher mapping accuracy (Kappa coefficient of 77%) and spectral attributes, including the newly yellow band, were preferentially selected, although a tendency to overestimate the total invaded area, due to the low spatial resolution (2 m of pixel size vs. 50 cm) was observed. When airborne images were used, geometric attributes were primarily selected and a higher spatial detail of the invasive patches was obtained, due to the higher spatial resolution. However, in highly heterogeneous landscapes, the low spectral resolution of the airborne images (4 bands instead of the 8 of WorldView-2) reduces the capability to detect giant reed patches. Giant reed displays peculiar spectral and geometric traits, at leaf, canopy and stand level, which makes the OBIA approach a very suitable technique for management purposes.

Two-harmonic complex spectral-domain optical coherence tomography using achromatic sinusoidal phase modulation

NASA Astrophysics Data System (ADS)

Lu, Sheng-Hua; Huang, Siang-Ru; Chou, Che-Chung

2018-03-01

We resolve the complex conjugate ambiguity in spectral-domain optical coherence tomography (SD-OCT) by using achromatic two-harmonic method. Unlike previous researches, the optical phase of the fiber interferometer is modulated by an achromatic phase shifter based on an optical delay line. The achromatic phase modulation leads to a wavelength-independent scaling coefficient for the two harmonics. Dividing the mean absolute value of the first harmonic by that of the second harmonic in a B-scan interferogram directly gives the scaling coefficient. It greatly simplifies the determination of the magnitude ratio between the two harmonics without the need of third harmonic and cumbersome iterative calculations. The inverse fast Fourier transform of the complex-valued interferogram constructed with the scaling coefficient, first and second harmonics yields a full-range OCT image. Experimental results confirm the effectiveness of the proposed achromatic two-harmonic technique for suppressing the mirror artifacts in SD-OCT images.

Determining crop residue type and class using satellite acquired data. M.S. Thesis Progress Report, Jun. 1990

NASA Technical Reports Server (NTRS)

Zhuang, Xin

1990-01-01

LANDSAT Thematic Mapper (TM) data for March 23, 1987 with accompanying ground truth data for the study area in Miami County, IN were used to determine crop residue type and class. Principle components and spectral ratioing transformations were applied to the LANDSAT TM data. One graphic information system (GIS) layer of land ownership was added to each original image as the eighth band of data in an attempt to improve classification. Maximum likelihood, minimum distance, and neural networks were used to classify the original, transformed, and GIS-enhanced remotely sensed data. Crop residues could be separated from one another and from bare soil and other biomass. Two types of crop residue and four classes were identified from each LANDSAT TM image. The maximum likelihood classifier performed the best classification for each original image without need of any transformation. The neural network classifier was able to improve the classification by incorporating a GIS-layer of land ownership as an eighth band of data. The maximum likelihood classifier was unable to consider this eighth band of data and thus, its results could not be improved by its consideration.

Fluorescence lifetime imaging and Fourier transform infrared spectroscopy of Michelangelo's David.

PubMed

Comelli, Daniela; Valentini, Gianluca; Cubeddu, Rinaldo; Toniolo, Lucia

2005-09-01

We developed a combined procedure for the analysis of works of art based on a portable system for fluorescence imaging integrated with analytical measurements on microsamples. The method allows us to localize and identify organic and inorganic compounds present on the surface of artworks. The fluorescence apparatus measures the temporal and spectral features of the fluorescence emission, excited by ultraviolet (UV) laser pulses. The kinetic of the emission is studied through a fluorescence lifetime imaging system, while an optical multichannel analyzer measures the fluorescence spectra of selected points. The chemical characterization of the compounds present on the artistic surfaces is then performed by means of analytical measurements on microsamples collected with the assistance of the fluorescence maps. The previous concepts have been successfully applied to study the contaminants on the surface of Michelangelo's David. The fluorescence analysis combined with Fourier transform infrared (FT-IR) measurements revealed the presence of beeswax, which permeates most of the statue surface, and calcium oxalate deposits mainly arranged in vertical patterns and related to rain washing.

HMM for hyperspectral spectrum representation and classification with endmember entropy vectors

NASA Astrophysics Data System (ADS)

Arabi, Samir Y. W.; Fernandes, David; Pizarro, Marco A.

2015-10-01

The Hyperspectral images due to its good spectral resolution are extensively used for classification, but its high number of bands requires a higher bandwidth in the transmission data, a higher data storage capability and a higher computational capability in processing systems. This work presents a new methodology for hyperspectral data classification that can work with a reduced number of spectral bands and achieve good results, comparable with processing methods that require all hyperspectral bands. The proposed method for hyperspectral spectra classification is based on the Hidden Markov Model (HMM) associated to each Endmember (EM) of a scene and the conditional probabilities of each EM belongs to each other EM. The EM conditional probability is transformed in EM vector entropy and those vectors are used as reference vectors for the classes in the scene. The conditional probability of a spectrum that will be classified is also transformed in a spectrum entropy vector, which is classified in a given class by the minimum ED (Euclidian Distance) among it and the EM entropy vectors. The methodology was tested with good results using AVIRIS spectra of a scene with 13 EM considering the full 209 bands and the reduced spectral bands of 128, 64 and 32. For the test area its show that can be used only 32 spectral bands instead of the original 209 bands, without significant loss in the classification process.

Topics In Chemical Instrumentation: Fourier Transformations for Chemists Part I. Introduction to the Fourier Transform.

ERIC Educational Resources Information Center

Glasser, L.

1987-01-01

This paper explores how Fourier Transform (FT) mimics spectral transformation, how this property can be exploited to advantage in spectroscopy, and how the FT can be used in data treatment. A table displays a number of important FT serial/spectral pairs related by Fourier Transformations. A bibliography and listing of computer software related to…

Mid-IR Spectral Investigation of Normal and Malignant Breast and Cervical Tissue Samples Using a Quantum Cascade Laser-Based Microscope

NASA Astrophysics Data System (ADS)

Haugen, Paul

Mid-infrared (MIR) spectroscopy has been a tool used to identify specific features of normal and malignant tissue samples by utilizing MIR characteristics, specifically in the "fingerprint" region. The fingerprint region is a biologically significant spectral region typically identified between 1500 and 500 cm-1. MIR spectroscopy can be used to study molecular changes and variations occurring in samples, which can then be used to fingerprint specific spectral characteristics and biomarkers in order to categorize the specimens. The most common instruments currently used in this analysis are Fourier transform infrared (FTIR) spectrometers, although properties inherent in these instruments, such as slow data collection time and an inability to specify sample location for the spectral data collection, have placed a ceiling on the clinical practicality of their use for specimen classification and identification. In this thesis, we use a prototype of an infrared hyperspectral imaging microscopy platform based around tunable quantum cascade laser (QCL) technology that has a spectral coverage from 1800-900 cm-1. The quantum cascade lasers are coupled with a series of MIR refractive objectives and an uncooled microbolometer camera. The speed of spectral imaging improves to 30 frames per second, and the high magnification objective has a 1.34 microm pixel resolution with a 0.70 numerical aperture and 4.3 microm spatial resolution. We are able to specify data collection at specific discrete wavelengths as opposed to the full spectrum, which improves the data collection time and de-clutters the data for analysis expediency. Finally, we perform spectral imaging real-time, which aides in selecting precise regions of interest on the target sample. This thesis demonstrates the advantages of exploiting the capabilities of the QCL microscope to advance MIR spectroscopy in the identification of distinguishing traits of normal and malignant breast and cervical tissue samples.

Microfluidic Approaches to Synchrotron Radiation-Based Fourier Transform Infrared (SR-FTIR) Spectral Microscopy of Living Biosystems

PubMed Central

Loutherback, Kevin; Birarda, Giovanni; Chen, Liang; Holman, Hoi-Ying N.

2016-01-01

A long-standing desire in biological and biomedical sciences is to be able to probe cellular chemistry as biological processes are happening inside living cells. Synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectral microscopy is a label-free and nondestructive analytical technique that can provide spatiotemporal distributions and relative abundances of biomolecules of a specimen by their characteristic vibrational modes. Despite great progress in recent years, SR-FTIR imaging of living biological systems remains challenging because of the demanding requirements on environmental control and strong infrared absorption of water. To meet this challenge, microfluidic devices have emerged as a method to control the water thickness while providing a hospitable environment to measure cellular processes and responses over many hours or days. This paper will provide an overview of microfluidic device development for SR-FTIR imaging of living biological systems, provide contrast between the various techniques including closed and open-channel designs, and discuss future directions of development within this area. Even as the fundamental science and technological demonstrations develop, other ongoing issues must be addressed; for example, choosing applications whose experimental requirements closely match device capabilities, and developing strategies to efficiently complete the cycle of development. These will require imagination, ingenuity and collaboration. PMID:26732243

Microfluidic approaches to synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectral microscopy of living biosystems

DOE PAGES

Loutherback, Kevin; Birarda, Giovanni; Chen, Liang; ...

2016-02-15

A long-standing desire in biological and biomedical sciences is to be able to probe cellular chemistry as biological processes are happening inside living cells. Synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectral microscopy is a label-free and nondestructive analytical technique that can provide spatiotemporal distributions and relative abundances of biomolecules of a specimen by their characteristic vibrational modes. Despite great progress in recent years, SR-FTIR imaging of living biological systems remains challenging because of the demanding requirements on environmental control and strong infrared absorption of water. To meet this challenge, microfluidic devices have emerged as a method to control the watermore » thickness while providing a hospitable environment to measure cellular processes and responses over many hours or days. This paper will provide an overview of microfluidic device development for SR-FTIR imaging of living biological systems, provide contrast between the various techniques including closed and open-channel designs, and discuss future directions of development within this area. Even as the fundamental science and technological demonstrations develop, other ongoing issues must be addressed; for example, choosing applications whose experimental requirements closely match device capabilities, and developing strategies to efficiently complete the cycle of development. These will require imagination, ingenuity and collaboration.« less

Microfluidic approaches to synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectral microscopy of living biosystems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loutherback, Kevin; Birarda, Giovanni; Chen, Liang

A long-standing desire in biological and biomedical sciences is to be able to probe cellular chemistry as biological processes are happening inside living cells. Synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectral microscopy is a label-free and nondestructive analytical technique that can provide spatiotemporal distributions and relative abundances of biomolecules of a specimen by their characteristic vibrational modes. Despite great progress in recent years, SR-FTIR imaging of living biological systems remains challenging because of the demanding requirements on environmental control and strong infrared absorption of water. To meet this challenge, microfluidic devices have emerged as a method to control the watermore » thickness while providing a hospitable environment to measure cellular processes and responses over many hours or days. This paper will provide an overview of microfluidic device development for SR-FTIR imaging of living biological systems, provide contrast between the various techniques including closed and open-channel designs, and discuss future directions of development within this area. Even as the fundamental science and technological demonstrations develop, other ongoing issues must be addressed; for example, choosing applications whose experimental requirements closely match device capabilities, and developing strategies to efficiently complete the cycle of development. These will require imagination, ingenuity and collaboration.« less

Diffractive centrosymmetric 3D-transmission phase gratings positioned at the image plane of optical systems transform lightlike 4D-WORLD as tunable resonators into spectral metrics...

NASA Astrophysics Data System (ADS)

Lauinger, Norbert

1999-08-01

Diffractive 3D phase gratings of spherical scatterers dense in hexagonal packing geometry represent adaptively tunable 4D-spatiotemporal filters with trichromatic resonance in visible spectrum. They are described in the (lambda) - chromatic and the reciprocal (nu) -aspects by reciprocal geometric translations of the lightlike Pythagoras theorem, and by the direction cosine for double cones. The most elementary resonance condition in the lightlike Pythagoras theorem is given by the transformation of the grating constants gx, gy, gz of the hexagonal 3D grating to (lambda) h1h2h3 equals (lambda) 111 with cos (alpha) equals 0.5. Through normalization of the chromaticity in the von Laue-interferences to (lambda) 111, the (nu) (lambda) equals (lambda) h1h2h3/(lambda) 111-factor of phase velocity becomes the crucial resonance factor, the 'regulating device' of the spatiotemporal interaction between 3D grating and light, space and time. In the reciprocal space equal/unequal weights and times in spectral metrics result at positions of interference maxima defined by hyperbolas and circles. A database becomes built up by optical interference for trichromatic image preprocessing, motion detection in vector space, multiple range data analysis, patchwide multiple correlations in the spatial frequency spectrum, etc.

Field Dislocation Mechanics for heterogeneous elastic materials: A numerical spectral approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Djaka, Komlan Senam; Villani, Aurelien; Taupin, Vincent

Spectral methods using Fast Fourier Transform (FFT) algorithms have recently seen a surge in interest in the mechanics of materials community. The present work addresses the critical question of determining accurate local mechanical fields using FFT methods without artificial fluctuations arising from materials and defects induced discontinuities. Precisely, this work introduces a numerical approach based on intrinsic discrete Fourier transforms for the simultaneous treatment of material discontinuities arising from the presence of dislocations and from elastic stiffness heterogeneities. To this end, the elasto-static equations of the field dislocation mechanics theory for periodic heterogeneous materials are numerically solved with FFT inmore » the case of dislocations in proximity of inclusions of varying stiffness. An optimal intrinsic discrete Fourier transform method is sought based on two distinct schemes. A centered finite difference scheme for differential rules are used for numerically solving the Poisson-type equation in the Fourier space, while centered finite differences on a rotated grid is chosen for the computation of the modified Fourier–Green’s operator associated with the Lippmann–Schwinger-type equation. By comparing different methods with analytical solutions for an edge dislocation in a composite material, it is found that the present spectral method is accurate, devoid of any numerical oscillation, and efficient even for an infinite phase elastic contrast like a hole embedded in a matrix containing a dislocation. The present FFT method is then used to simulate physical cases such as the elastic fields of dislocation dipoles located near the matrix/inclusion interface in a 2D composite material and the ones due to dislocation loop distributions surrounding cubic inclusions in 3D composite material. In these configurations, the spectral method allows investigating accurately the elastic interactions and image stresses due to dislocation fields in the presence of elastic inhomogeneities.« less

Field Dislocation Mechanics for heterogeneous elastic materials: A numerical spectral approach

DOE PAGES

Djaka, Komlan Senam; Villani, Aurelien; Taupin, Vincent; ...

2017-03-01

Spectral methods using Fast Fourier Transform (FFT) algorithms have recently seen a surge in interest in the mechanics of materials community. The present work addresses the critical question of determining accurate local mechanical fields using FFT methods without artificial fluctuations arising from materials and defects induced discontinuities. Precisely, this work introduces a numerical approach based on intrinsic discrete Fourier transforms for the simultaneous treatment of material discontinuities arising from the presence of dislocations and from elastic stiffness heterogeneities. To this end, the elasto-static equations of the field dislocation mechanics theory for periodic heterogeneous materials are numerically solved with FFT inmore » the case of dislocations in proximity of inclusions of varying stiffness. An optimal intrinsic discrete Fourier transform method is sought based on two distinct schemes. A centered finite difference scheme for differential rules are used for numerically solving the Poisson-type equation in the Fourier space, while centered finite differences on a rotated grid is chosen for the computation of the modified Fourier–Green’s operator associated with the Lippmann–Schwinger-type equation. By comparing different methods with analytical solutions for an edge dislocation in a composite material, it is found that the present spectral method is accurate, devoid of any numerical oscillation, and efficient even for an infinite phase elastic contrast like a hole embedded in a matrix containing a dislocation. The present FFT method is then used to simulate physical cases such as the elastic fields of dislocation dipoles located near the matrix/inclusion interface in a 2D composite material and the ones due to dislocation loop distributions surrounding cubic inclusions in 3D composite material. In these configurations, the spectral method allows investigating accurately the elastic interactions and image stresses due to dislocation fields in the presence of elastic inhomogeneities.« less

Hyperspectral imaging with wavelet transform for classification of colon tissue biopsy samples

NASA Astrophysics Data System (ADS)

Masood, Khalid

2008-08-01

Automatic classification of medical images is a part of our computerised medical imaging programme to support the pathologists in their diagnosis. Hyperspectral data has found its applications in medical imagery. Its usage is increasing significantly in biopsy analysis of medical images. In this paper, we present a histopathological analysis for the classification of colon biopsy samples into benign and malignant classes. The proposed study is based on comparison between 3D spectral/spatial analysis and 2D spatial analysis. Wavelet textural features in the wavelet domain are used in both these approaches for classification of colon biopsy samples. Experimental results indicate that the incorporation of wavelet textural features using a support vector machine, in 2D spatial analysis, achieve best classification accuracy.

Multispectral image sharpening using a shift-invariant wavelet transform and adaptive processing of multiresolution edges

USGS Publications Warehouse

Lemeshewsky, G.P.; Rahman, Z.-U.; Schowengerdt, R.A.; Reichenbach, S.E.

2002-01-01

Enhanced false color images from mid-IR, near-IR (NIR), and visible bands of the Landsat thematic mapper (TM) are commonly used for visually interpreting land cover type. Described here is a technique for sharpening or fusion of NIR with higher resolution panchromatic (Pan) that uses a shift-invariant implementation of the discrete wavelet transform (SIDWT) and a reported pixel-based selection rule to combine coefficients. There can be contrast reversals (e.g., at soil-vegetation boundaries between NIR and visible band images) and consequently degraded sharpening and edge artifacts. To improve performance for these conditions, I used a local area-based correlation technique originally reported for comparing image-pyramid-derived edges for the adaptive processing of wavelet-derived edge data. Also, using the redundant data of the SIDWT improves edge data generation. There is additional improvement because sharpened subband imagery is used with the edge-correlation process. A reported technique for sharpening three-band spectral imagery used forward and inverse intensity, hue, and saturation transforms and wavelet-based sharpening of intensity. This technique had limitations with opposite contrast data, and in this study sharpening was applied to single-band multispectral-Pan image pairs. Sharpening used simulated 30-m NIR imagery produced by degrading the spatial resolution of a higher resolution reference. Performance, evaluated by comparison between sharpened and reference image, was improved when sharpened subband data were used with the edge correlation.

Hybrid single-source online Fourier transform coherent anti-Stokes Raman scattering/optical coherence tomography.

PubMed

Kamali, Tschackad; Považay, Boris; Kumar, Sunil; Silberberg, Yaron; Hermann, Boris; Werkmeister, René; Drexler, Wolfgang; Unterhuber, Angelika

2014-10-01

We demonstrate a multimodal optical coherence tomography (OCT) and online Fourier transform coherent anti-Stokes Raman scattering (FTCARS) platform using a single sub-12 femtosecond (fs) Ti:sapphire laser enabling simultaneous extraction of structural and chemical ("morphomolecular") information of biological samples. Spectral domain OCT prescreens the specimen providing a fast ultrahigh (4×12  μm axial and transverse) resolution wide field morphologic overview. Additional complementary intrinsic molecular information is obtained by zooming into regions of interest for fast label-free chemical mapping with online FTCARS spectroscopy. Background-free CARS is based on a Michelson interferometer in combination with a highly linear piezo stage, which allows for quick point-to-point extraction of CARS spectra in the fingerprint region in less than 125 ms with a resolution better than 4  cm(-1) without the need for averaging. OCT morphology and CARS spectral maps indicating phosphate and carbonate bond vibrations from human bone samples are extracted to demonstrate the performance of this hybrid imaging platform.

Micro modules for mobile shape, color and spectral imaging with smartpads in industry, biology and medicine

NASA Astrophysics Data System (ADS)

Hofmann, Dietrich; Dittrich, Paul-Gerald; Düntsch, Eric; Kraus, Daniel

2014-02-01

Aim of the paper is the demonstration of a paradigm shift in shape, color and spectral measurements in industry, biology and medicine as well as in measurement education and training. Innovative hardware apps (hwapps) and software apps (swapps) with smartpads are fundamental enablers for the transformation from conventional stationary working places towards innovative mobile working places with in-field measurements and point-of-care (POC) diagnostics. Mobile open online courses (MOOCs) are transforming the study habits. Practical examples for the application of innovative photonic micro shapemeters, colormeters and spectrometers will be given. The innovative approach opens so far untapped enormous markets for measurement science, engineering and training. These innovative working conditions will be fast accepted due to their convenience, reliability and affordability. A highly visible advantage of smartpads is the huge number of their distribution, their worldwide connectivity via Internet and cloud services, the standardized interfaces like USB and HDMI and the experienced capabilities of their users for practical operations, learned with their private smartpads.

Laser induced periodic surface structuring on Si by temporal shaped femtosecond pulses.

PubMed

Almeida, G F B; Martins, R J; Otuka, A J G; Siqueira, J P; Mendonca, C R

2015-10-19

We investigated the effect of temporal shaped femtosecond pulses on silicon laser micromachining. By using sinusoidal spectral phases, pulse trains composed of sub-pulses with distinct temporal separations were generated and applied to the silicon surface to produce Laser Induced Periodic Surface Structures (LIPSS). The LIPSS obtained with different sub-pulse separation were analyzed by comparing the intensity of the two-dimensional fast Fourier Transform (2D-FFT) of the AFM images of the ripples (LIPSS). It was observed that LIPSS amplitude is more emphasized for the pulse train with sub-pulses separation of 128 fs, even when compared with the Fourier transform limited pulse. By estimating the carrier density achieved at the end of each pulse train, we have been able to interpret our results with the Sipe-Drude model, that predicts that LIPSS efficacy is higher for a specific induced carrier density. Hence, our results indicate that temporal shaping of the excitation pulse, performed by spectral phase modulation, can be explored in fs-laser microstructuring.

ORBS: A reduction software for SITELLE and SpiOMM data

NASA Astrophysics Data System (ADS)

Martin, Thomas

2014-09-01

ORBS merges, corrects, transforms and calibrates interferometric data cubes and produces a spectral cube of the observed region for analysis. It is a fully automatic data reduction software for use with SITELLE (installed at the Canada-France-Hawaii Telescope) and SpIOMM (a prototype attached to the Observatoire du Mont Mégantic); these imaging Fourier transform spectrometers obtain a hyperspectral data cube which samples a 12 arc-minutes field of view into 4 millions of visible spectra. ORBS is highly parallelized; its core classes (ORB) have been designed to be used in a suite of softwares for data analysis (ORCS and OACS), data simulation (ORUS) and data acquisition (IRIS).

A High Performance Image Data Compression Technique for Space Applications

NASA Technical Reports Server (NTRS)

Yeh, Pen-Shu; Venbrux, Jack

2003-01-01

A highly performing image data compression technique is currently being developed for space science applications under the requirement of high-speed and pushbroom scanning. The technique is also applicable to frame based imaging data. The algorithm combines a two-dimensional transform with a bitplane encoding; this results in an embedded bit string with exact desirable compression rate specified by the user. The compression scheme performs well on a suite of test images acquired from spacecraft instruments. It can also be applied to three-dimensional data cube resulting from hyper-spectral imaging instrument. Flight qualifiable hardware implementations are in development. The implementation is being designed to compress data in excess of 20 Msampledsec and support quantization from 2 to 16 bits. This paper presents the algorithm, its applications and status of development.

A Multispectral Image Creating Method for a New Airborne Four-Camera System with Different Bandpass Filters

PubMed Central

Li, Hanlun; Zhang, Aiwu; Hu, Shaoxing

2015-01-01

This paper describes an airborne high resolution four-camera multispectral system which mainly consists of four identical monochrome cameras equipped with four interchangeable bandpass filters. For this multispectral system, an automatic multispectral data composing method was proposed. The homography registration model was chosen, and the scale-invariant feature transform (SIFT) and random sample consensus (RANSAC) were used to generate matching points. For the difficult registration problem between visible band images and near-infrared band images in cases lacking manmade objects, we presented an effective method based on the structural characteristics of the system. Experiments show that our method can acquire high quality multispectral images and the band-to-band alignment error of the composed multiple spectral images is less than 2.5 pixels. PMID:26205264

Composite multi-lobe descriptor for cross spectral face recognition: matching active IR to visible light images

NASA Astrophysics Data System (ADS)

Cao, Zhicheng; Schmid, Natalia A.

2015-05-01

Matching facial images across electromagnetic spectrum presents a challenging problem in the field of biometrics and identity management. An example of this problem includes cross spectral matching of active infrared (IR) face images or thermal IR face images against a dataset of visible light images. This paper describes a new operator named Composite Multi-Lobe Descriptor (CMLD) for facial feature extraction in cross spectral matching of near-infrared (NIR) or short-wave infrared (SWIR) against visible light images. The new operator is inspired by the design of ordinal measures. The operator combines Gaussian-based multi-lobe kernel functions, Local Binary Pattern (LBP), generalized LBP (GLBP) and Weber Local Descriptor (WLD) and modifies them into multi-lobe functions with smoothed neighborhoods. The new operator encodes both the magnitude and phase responses of Gabor filters. The combining of LBP and WLD utilizes both the orientation and intensity information of edges. Introduction of multi-lobe functions with smoothed neighborhoods further makes the proposed operator robust against noise and poor image quality. Output templates are transformed into histograms and then compared by means of a symmetric Kullback-Leibler metric resulting in a matching score. The performance of the multi-lobe descriptor is compared with that of other operators such as LBP, Histogram of Oriented Gradients (HOG), ordinal measures, and their combinations. The experimental results show that in many cases the proposed method, CMLD, outperforms the other operators and their combinations. In addition to different infrared spectra, various standoff distances from close-up (1.5 m) to intermediate (50 m) and long (106 m) are also investigated in this paper. Performance of CMLD is evaluated for of each of the three cases of distances.

SpIOMM and SITELLE: Wide-field Imaging FTS for the Study of Galaxy Evolution

NASA Astrophysics Data System (ADS)

Drissen, Laurent; Bernier, Anne-Pier; Robert, Carmelle; Robert

2011-12-01

SpIOMM, a wide-field Imaging Fourier Transform Spectrometer attached to the Mont Mégantic 1.6-m telescope, is capable of obtaining the visible spectrum of every source of light in a 12 arcminute field of view, with a spectral resolution ranging from R = 1 (wide-band image) to R = 25 000, resulting in 1.7 million spectra with a spatial resolution of one arcsecond. SITELLE will be a similar instrument attached to the Canada-France-Hawaii telescope, and will be in operation in early 2013. We present a short description of these instruments and illustrate their capabilities to study nearby galaxies with the results of a data cube of M51.

Theory of the amplitude-phase retrieval in any linear-transform system and its applications

NASA Astrophysics Data System (ADS)

Yang, Guozhen; Gu, Ben-Yuan; Dong, Bi-Zhen

1992-12-01

This paper is a summary of the theory of the amplitude-phase retrieval problem in any linear transform system and its applications based on our previous works in the past decade. We describe the general statement on the amplitude-phase retrieval problem in an imaging system and derive a set of equations governing the amplitude-phase distribution in terms of the rigorous mathematical derivation. We then show that, by using these equations and an iterative algorithm, a variety of amplitude-phase problems can be successfully handled. We carry out the systematic investigations and comprehensive numerical calculations to demonstrate the utilization of this new algorithm in various transform systems. For instance, we have achieved the phase retrieval from two intensity measurements in an imaging system with diffraction loss (non-unitary transform), both theoretically and experimentally, and the recovery of model real image from its Hartley-transform modulus only in one and two dimensional cases. We discuss the achievement of the phase retrieval problem from a single intensity only based on the sampling theorem and our algorithm. We also apply this algorithm to provide an optimal design of the phase-adjusted plate for a phase-adjustment focusing laser accelerator and a design approach of single phase-only element for implementing optical interconnect. In order to closely simulate the really measured data, we examine the reconstruction of image from its spectral modulus corrupted by a random noise in detail. The results show that the convergent solution can always be obtained and the quality of the recovered image is satisfactory. We also indicated the relationship and distinction between our algorithm and the original Gerchberg- Saxton algorithm. From these studies, we conclude that our algorithm shows great capability to deal with the comprehensive phase-retrieval problems in the imaging system and the inverse problem in solid state physics. It may open a new way to solve important inverse source problems extensively appearing in physics.

Eliminating time dispersion from seismic wave modeling

NASA Astrophysics Data System (ADS)

Koene, Erik F. M.; Robertsson, Johan O. A.; Broggini, Filippo; Andersson, Fredrik

2018-04-01

We derive an expression for the error introduced by the second-order accurate temporal finite-difference (FD) operator, as present in the FD, pseudospectral and spectral element methods for seismic wave modeling applied to time-invariant media. The `time-dispersion' error speeds up the signal as a function of frequency and time step only. Time dispersion is thus independent of the propagation path, medium or spatial modeling error. We derive two transforms to either add or remove time dispersion from synthetic seismograms after a simulation. The transforms are compared to previous related work and demonstrated on wave modeling in acoustic as well as elastic media. In addition, an application to imaging is shown. The transforms enable accurate computation of synthetic seismograms at reduced cost, benefitting modeling applications in both exploration and global seismology.

Study on identifying deciduous forest by the method of feature space transformation

NASA Astrophysics Data System (ADS)

Zhang, Xuexia; Wu, Pengfei

2009-10-01

The thematic remotely sensed information extraction is always one of puzzling nuts which the remote sensing science faces, so many remote sensing scientists devotes diligently to this domain research. The methods of thematic information extraction include two kinds of the visual interpretation and the computer interpretation, the developing direction of which is intellectualization and comprehensive modularization. The paper tries to develop the intelligent extraction method of feature space transformation for the deciduous forest thematic information extraction in Changping district of Beijing city. The whole Chinese-Brazil resources satellite images received in 2005 are used to extract the deciduous forest coverage area by feature space transformation method and linear spectral decomposing method, and the result from remote sensing is similar to woodland resource census data by Chinese forestry bureau in 2004.

Infrared Microtransmission And Microreflectance Of Biological Systems

NASA Astrophysics Data System (ADS)

Hill, Steve L.; Krishnan, K.; Powell, Jay R.

1989-12-01

The infrared microsampling technique has been successfully applied to a variety of biological systems. A microtomed tissue section may be prepared to permit both visual and infrared discrimination. Infrared structural information may be obtained for a single cell, and computer-enhanced images of tissue specimens may be calculated from spectral map data sets. An analysis of a tissue section anomaly may gg suest eitherprotein compositional differences or a localized concentration of foreign matterp. Opaque biological materials such as teeth, gallstones, and kidney stones may be analyzed by microreflectance spectroscop. Absorption anomalies due to specular dispersion are corrected with the Kraymers-Kronig transformation. Corrected microreflectance spectra may contribute to compositional analysis and correlate diseased-related spectral differences to visual specimen anomalies.

Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain

PubMed Central

Lin, Fa-Hsuan; Witzel, Thomas; Hämäläinen, Matti S.; Dale, Anders M.; Belliveau, John W.; Stufflebeam, Steven M.

2010-01-01

This paper presents a computationally efficient source estimation algorithm that localizes cortical oscillations and their phase relationships. The proposed method employs wavelet-transformed magnetoencephalography (MEG) data and uses anatomical MRI to constrain the current locations to the cortical mantle. In addition, the locations of the sources can be further confined with the help of functional MRI (fMRI) data. As a result, we obtain spatiotemporal maps of spectral power and phase relationships. As an example, we show how the phase locking value (PLV), that is, the trial-by-trial phase relationship between the stimulus and response, can be imaged on the cortex. We apply the method to spontaneous, evoked, and driven cortical oscillations measured with MEG. We test the method of combining MEG, structural MRI, and fMRI using simulated cortical oscillations along Heschl’s gyrus (HG). We also analyze sustained auditory gamma-band neuromagnetic fields from MEG and fMRI measurements. Our results show that combining the MEG recording with fMRI improves source localization for the non-noise-normalized wavelet power. In contrast, noise-normalized spectral power or PLV localization may not benefit from the fMRI constraint. We show that if the thresholds are not properly chosen, noise-normalized spectral power or PLV estimates may contain false (phantom) sources, independent of the inclusion of the fMRI prior information. The proposed algorithm can be used for evoked MEG/EEG and block-designed or event-related fMRI paradigms, or for spontaneous MEG data sets. Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain can provide further understanding of large-scale neural activity and communication between different brain regions. PMID:15488408

Automated processing of label-free Raman microscope images of macrophage cells with standardized regression for high-throughput analysis.

PubMed

Milewski, Robert J; Kumagai, Yutaro; Fujita, Katsumasa; Standley, Daron M; Smith, Nicholas I

2010-11-19

Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively. We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest. The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without compromise in image quality or information loss in associated spectra. These results motivate further use of label free microscopy techniques in real-time imaging of live immune cells.

Microspectroscopy of spectral biomarkers associated with human corneal stem cells

PubMed Central

Nakamura, Takahiro; Kelly, Jemma G.; Trevisan, Júlio; Cooper, Leanne J.; Bentley, Adam J.; Carmichael, Paul L.; Scott, Andrew D.; Cotte, Marine; Susini, Jean; Martin-Hirsch, Pierre L.; Kinoshita, Shigeru; Martin, Francis L.

2010-01-01

Purpose Synchrotron-based radiation (SRS) Fourier-transform infrared (FTIR) microspectroscopy potentially provides novel biomarkers of the cell differentiation process. Because such imaging gives a “biochemical-cell fingerprint” through a cell-sized aperture, we set out to determine whether distinguishing chemical entities associated with putative stem cells (SCs), transit-amplifying (TA) cells, or terminally-differentiated (TD) cells could be identified in human corneal epithelium. Methods Desiccated cryosections (10 μm thick) of cornea on barium fluoride infrared transparent windows were interrogated using SRS FTIR microspectroscopy. Infrared analysis was performed through the acquisition of point spectra or image maps. Results Point spectra were subjected to principal component analysis (PCA) to identify distinguishing chemical entities. Spectral image maps to highlight SCs, TA cells, and TD cells of the cornea were then generated. Point spectrum analysis using PCA highlighted remarkable segregation between the three cell classes. Discriminating chemical entities were associated with several spectral differences over the DNA/RNA (1,425–900 cm−1) and protein/lipid (1,800–1480 cm−1) regions. Prominent biomarkers of SCs compared to TA cells and/or TD cells were 1,040 cm−1, 1,080 cm−1, 1,107 cm−1, 1,225 cm−1, 1,400 cm−1, 1,525 cm−1, 1,558 cm−1, and 1,728 cm−1. Chemical entities associated with DNA/RNA conformation (1,080 cm−1 and 1,225 cm−1) were associated with SCs, whereas protein/lipid biochemicals (1,558 cm−1 and 1,728 cm−1) most distinguished TA cells and TD cells. Conclusions SRS FTIR microspectroscopy can be employed to identify differential spectral biomarkers of SCs, TA cells, and/or TD cells in human cornea. This nondestructive imaging technology is a novel approach to characterizing SCs in situ. PMID:20520745

Joint Dictionary Learning for Multispectral Change Detection.

PubMed

Lu, Xiaoqiang; Yuan, Yuan; Zheng, Xiangtao

2017-04-01

Change detection is one of the most important applications of remote sensing technology. It is a challenging task due to the obvious variations in the radiometric value of spectral signature and the limited capability of utilizing spectral information. In this paper, an improved sparse coding method for change detection is proposed. The intuition of the proposed method is that unchanged pixels in different images can be well reconstructed by the joint dictionary, which corresponds to knowledge of unchanged pixels, while changed pixels cannot. First, a query image pair is projected onto the joint dictionary to constitute the knowledge of unchanged pixels. Then reconstruction error is obtained to discriminate between the changed and unchanged pixels in the different images. To select the proper thresholds for determining changed regions, an automatic threshold selection strategy is presented by minimizing the reconstruction errors of the changed pixels. Adequate experiments on multispectral data have been tested, and the experimental results compared with the state-of-the-art methods prove the superiority of the proposed method. Contributions of the proposed method can be summarized as follows: 1) joint dictionary learning is proposed to explore the intrinsic information of different images for change detection. In this case, change detection can be transformed as a sparse representation problem. To the authors' knowledge, few publications utilize joint learning dictionary in change detection; 2) an automatic threshold selection strategy is presented, which minimizes the reconstruction errors of the changed pixels without the prior assumption of the spectral signature. As a result, the threshold value provided by the proposed method can adapt to different data due to the characteristic of joint dictionary learning; and 3) the proposed method makes no prior assumption of the modeling and the handling of the spectral signature, which can be adapted to different data.

Final design of SITELLE: a wide-field imaging Fourier transform spectrometer for the Canada-France-Hawaii Telescope

NASA Astrophysics Data System (ADS)

Grandmont, F.; Drissen, L.; Mandar, Julie; Thibault, S.; Baril, Marc

2012-09-01

We report here on the current status of SITELLE, an imaging Fourier transform spectrometer to be installed on the Canada-France Hawaii Telescope in 2013. SITELLE is an Integral Field Unit (IFU) spectrograph capable of obtaining the visible (350 nm - 900 nm) spectrum of every pixel of a 2k x 2k CCD imaging a field of view of 11 x 11 arcminutes, with 100% spatial coverage and a spectral resolution ranging from R = 1 (deep panchromatic image) to R < 104 (for gas dynamics). SITELLE will cover a field of view 100 to 1000 times larger than traditional IFUs, such as GMOS-IFU on Gemini or the upcoming MUSE on the VLT. SITELLE follows on the legacy of BEAR, an imaging conversion of the CFHT FTS and the direct successor of SpIOMM, a similar instrument attached to the 1.6-m telescope of the Observatoire du Mont-Mégantic in Québec. SITELLE will be used to study the structure and kinematics of HII regions and ejecta around evolved stars in the Milky Way, emission-line stars in clusters, abundances in nearby gas-rich galaxies, and the star formation rate in distant galaxies.

Optimum thermal infrared bands for mapping general rock type and temperature from space

NASA Technical Reports Server (NTRS)

Holmes, Q. A.; Nueesch, D. R.; Vincent, R. K.

1980-01-01

A study was carried out to determine quantitatively the number and location of spectral bands required to perform general rock type discrimination from spaceborne imaging sensors using only thermal infrared measurements. Beginning with laboratory spectra collected under idealized conditions from relatively well-characterized homogeneous samples, a radiative transfer model was used to transform ground exitance values into the corresponding spectral radiance at the top of the atmosphere. Taking sensor noise into account, analysis of these data revealed that three 1 micron wide spectral bands would permit independent estimations of rock type and sample temperature from a satellite infrared multispectral scanner. This study, which ignores the mixing of terrain elements within the instantaneous field of view of a satellite scanner, indicates that the location of three spectral bands at 8.1-9.1, 9.5-10.5, and 11.0-12.0 microns, and the employment of appropriate preprocessing to minimize atmospheric effects makes it possible to predict general rock type and temperature for a variety of atmospheric states and temperatures.

Optimum thermal infrared bands for mapping general rock type and temperature from space

NASA Technical Reports Server (NTRS)

Holmes, Q. A.; Nuesch, D. R.

1978-01-01

A study was carried out to determine quantitatively the number and locations of spectral bands required to perform general rock-type discrimination from spaceborne imaging sensors using only thermal infrared measurements. Beginning with laboratory spectra collected under idealized conditions from relatively well characterized, homogeneous samples, a radiative transfer model was employed to transform ground exitance values into the corresponding spectral radiance at the top of the atmosphere. Taking sensor noise into account analysis of these data revealed that three 1 micrometer wide spectral bands would permit independent estimators of rock-type and sample temperature from a satellite infrared multispectral scanner. This study, indicates that the location of three spectral bands at 8.1-9.1 micrometers, 9.5-10.5 micrometers and 11.0-12.0 micrometers, and the employment of appropriate preprocessing to minimize atmospheric effects makes it possible to predict general rock-type and temperature for a variety of atmospheric states and temperatures.

Canopy reflectance related to marsh dieback onset and progression in Coastal Louisiana

USGS Publications Warehouse

Ramsey, Elijah W.; Rangoonwala, A.

2006-01-01

In this study, we extended previous work linking leaf spectral changes, dieback onset, and progression of Spartina alterniflora marshes to changes in site-specific canopy reflectance spectra. First, we obtained canopy reflectance spectra (approximately 20 m ground resolution) from the marsh sites occupied during the leaf spectral analyses and from additional sites exhibiting visual signs of dieback. Subsequently, the canopy spectra were analyzed at two spectral scales: the first scale corresponded to whole-spectra sensors, such as the NASA Earth Observing-1 (EO-1) Hyperion, and the second scale corresponded to broadband spectral sensors, such as the EO-1 Advanced Land Imager and the Landsat Enhanced Thematic Mapper. In the whole-spectra analysis, spectral indicators were generated from the whole canopy spectra (about 400 nm to 1,000 nm) by extracting typical dead and healthy marsh spectra, and subsequently using them to determine the percent composition of all canopy reflectance spectra. Percent compositions were then used to classify canopy spectra at each field site into groups exhibiting similar levels of dieback progression ranging from relatively healthy to completely dead. In the broadband reflectance analysis, blue, green, red, red-edge, and near infrared (NIR) spectral bands and NIR/green and NIR/red transforms were extracted from the canopy spectra. Spectral band and band transform indicators of marsh dieback and progression were generated by relating them to marsh status indicators derived from classifications of the 35 mm slides collected at the same time as the canopy reflectance recordings. The whole spectra and broadband spectral indicators were both able to distinguish (a) healthy marsh, (b) live marsh impacted by dieback, and (c) dead marsh, and they both provided some discrimination of dieback progression. Whole-spectra resolution sensors like the EO-1 Hyperion, however, offered an enhanced ability to categorize dieback progression. ?? 2006 American Society for Photogrammetry and Remote Sensing.

Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis

PubMed Central

Zhang, Xue-Xi; Yin, Jian-Hua; Mao, Zhi-Hua; Xia, Yang

2015-01-01

Abstract. Fourier transform infrared imaging (FTIRI) combined with chemometrics algorithm has strong potential to obtain complex chemical information from biology tissues. FTIRI and partial least squares-discriminant analysis (PLS-DA) were used to differentiate healthy and osteoarthritic (OA) cartilages for the first time. A PLS model was built on the calibration matrix of spectra that was randomly selected from the FTIRI spectral datasets of healthy and lesioned cartilage. Leave-one-out cross-validation was performed in the PLS model, and the fitting coefficient between actual and predicted categorical values of the calibration matrix reached 0.95. In the calibration and prediction matrices, the successful identifying percentages of healthy and lesioned cartilage spectra were 100% and 90.24%, respectively. These results demonstrated that FTIRI combined with PLS-DA could provide a promising approach for the categorical identification of healthy and OA cartilage specimens. PMID:26057029

Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis.

PubMed

Zhang, Xue-Xi; Yin, Jian-Hua; Mao, Zhi-Hua; Xia, Yang

2015-06-01

Fourier transform infrared imaging (FTIRI) combined with chemometrics algorithm has strong potential to obtain complex chemical information from biology tissues. FTIRI and partial least squares-discriminant analysis (PLS-DA) were used to differentiate healthy and osteoarthritic (OA) cartilages for the first time. A PLS model was built on the calibration matrix of spectra that was randomly selected from the FTIRI spectral datasets of healthy and lesioned cartilage. Leave-one-out cross-validation was performed in the PLS model, and the fitting coefficient between actual and predicted categorical values of the calibration matrix reached 0.95. In the calibration and prediction matrices, the successful identifying percentages of healthy and lesioned cartilage spectra were 100% and 90.24%, respectively. These results demonstrated that FTIRI combined with PLS-DA could provide a promising approach for the categorical identification of healthy and OA cartilage specimens.

Imaging open-path Fourier transform infrared spectrometer for 3D cloud profiling

NASA Astrophysics Data System (ADS)

Rentz Dupuis, Julia; Mansur, David J.; Vaillancourt, Robert; Carlson, David; Evans, Thomas; Schundler, Elizabeth; Todd, Lori; Mottus, Kathleen

2010-04-01

OPTRA has developed an imaging open-path Fourier transform infrared (I-OP-FTIR) spectrometer for 3D profiling of chemical and biological agent simulant plumes released into test ranges and chambers. An array of I-OP-FTIR instruments positioned around the perimeter of the test site, in concert with advanced spectroscopic algorithms, enables real time tomographic reconstruction of the plume. The approach is intended as a referee measurement for test ranges and chambers. This Small Business Technology Transfer (STTR) effort combines the instrumentation and spectroscopic capabilities of OPTRA, Inc. with the computed tomographic expertise of the University of North Carolina, Chapel Hill. In this paper, we summarize the design and build and detail system characterization and test of a prototype I-OP-FTIR instrument. System characterization includes radiometric performance and spectral resolution. Results from a series of tomographic reconstructions of sulfur hexafluoride plumes in a laboratory setting are also presented.

Usability of multiangular imaging spectroscopy data for analysis of vegetation canopy shadow fraction in boreal forest

NASA Astrophysics Data System (ADS)

Markiet, Vincent; Perheentupa, Viljami; Mõttus, Matti; Hernández-Clemente, Rocío

2016-04-01

Imaging spectroscopy is a remote sensing technology which records continuous spectral data at a very high (better than 10 nm) resolution. Such spectral images can be used to monitor, for example, the photosynthetic activity of vegetation. Photosynthetic activity is dependent on varying light conditions and varies within the canopy. To measure this variation we need very high spatial resolution data with resolution better than the dominating canopy element size (e.g., tree crown in a forest canopy). This is useful, e.g., for detecting photosynthetic downregulation and thus plant stress. Canopy illumination conditions are often quantified using the shadow fraction: the fraction of visible foliage which is not sunlit. Shadow fraction is known to depend on view angle (e.g., hot spot images have very low shadow fraction). Hence, multiple observation angles potentially increase the range of shadow fraction in the imagery in high spatial resolution imaging spectroscopy data. To investigate the potential of multi-angle imaging spectroscopy in investigating canopy processes which vary with shadow fraction, we obtained a unique multiangular airborne imaging spectroscopy data for the Hyytiälä forest research station located in Finland (61° 50'N, 24° 17'E) in July 2015. The main tree species are Norway spruce (Picea abies L. karst), Scots pine (Pinus sylvestris L.) and birch (Betula pubescens Ehrh., Betula pendula Roth). We used an airborne hyperspectral sensor AISA Eagle II (Specim - Spectral Imaging Ltd., Finland) mounted on a tilting platform. The tilting platform allowed us to measure at nadir and approximately 35 degrees off-nadir. The hyperspectral sensor has a 37.5 degrees field of view (FOV), 0.6m pixel size, 128 spectral bands with an average spectral bandwidth of 4.6nm and is sensitive in the 400-1000 nm spectral region. The airborne data was radiometrically, atmospherically and geometrically processed using the Parge and Atcor software (Re Se applications Schläpfer, Switzerland). However, even after meticulous geolocation, the canopy elements (needles) seen from the three view angles were different: at each overpass, different parts of the same crowns were observed. To overcome this, we used a 200m x 200m test site covered with pure pine stands. We assumed that for sunlit, shaded and understory spectral signatures are independent of viewing direction to the accuracy of a constant BRDF factor. Thus, we compared the spectral signatures for sunlit and shaded canopy and understory obtained for each view direction. We selected visually six hundred of the brightest and darkest canopy pixels. Next, we performed a minimum noise fraction (MNF) transformation, created a pixel purity index (PPI) and used Envi's n-D scatterplot to determine pure spectral signatures for the two classes. The pure endmembers for different view angles were compared to determine the BRDF factor and to analyze its spectral invariance. We demonstrate the compatibility of multi-angle data with high spatial resolution data. In principle, both carry similar information on structured (non-flat) targets thus as a vegetation canopy. Nevertheless, multiple view angles helped us to extend the range of shadow fraction in the images. Also, correct separation of shaded crown and shaded understory pixels remains a challenge.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillion, D.

This code enables one to display, take line-outs on, and perform various transformations on an image created by an array of integer*2 data. Uncompressed eight-bit TIFF files created on either the Macintosh or the IBM PC may also be read in and converted to a 16 bit signed integer image. This code is designed to handle all the formats used for PDS (photo-densitometer) files at the Lawrence Livermore National Laboratory. These formats are all explained by the application code. The image may be zoomed infinitely and the gray scale mapping can be easily changed. Line-outs may be horizontal or verticalmore » with arbitrary width, angled with arbitrary end points, or taken along any path. This code is usually used to examine spectrograph data. Spectral lines may be identified and a polynomial fit from position to wavelength may be found. The image array can be remapped so that the pixels all have the same change of lambda width. It is not necessary to do this, however. Lineouts may be printed, saved as Cricket tab-delimited files, or saved as PICT2 files. The plots may be linear, semilog, or logarithmic with nice values and proper scientific notation. Typically, spectral lines are curved.« less

Exploiting spectral content for image segmentation in GPR data

NASA Astrophysics Data System (ADS)

Wang, Patrick K.; Morton, Kenneth D., Jr.; Collins, Leslie M.; Torrione, Peter A.

2011-06-01

Ground-penetrating radar (GPR) sensors provide an effective means for detecting changes in the sub-surface electrical properties of soils, such as changes indicative of landmines or other buried threats. However, most GPR-based pre-screening algorithms only localize target responses along the surface of the earth, and do not provide information regarding an object's position in depth. As a result, feature extraction algorithms are forced to process data from entire cubes of data around pre-screener alarms, which can reduce feature fidelity and hamper performance. In this work, spectral analysis is investigated as a method for locating subsurface anomalies in GPR data. In particular, a 2-D spatial/frequency decomposition is applied to pre-screener flagged GPR B-scans. Analysis of these spatial/frequency regions suggests that aspects (e.g. moments, maxima, mode) of the frequency distribution of GPR energy can be indicative of the presence of target responses. After translating a GPR image to a function of the spatial/frequency distributions at each pixel, several image segmentation approaches can be applied to perform segmentation in this new transformed feature space. To illustrate the efficacy of the approach, a performance comparison between feature processing with and without the image segmentation algorithm is provided.

SPECTRAL SMILE CORRECTION IN CRISM HYPERSPECTRAL IMAGES

NASA Astrophysics Data System (ADS)

Ceamanos, X.; Doute, S.

2009-12-01

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is affected by a common artifact in "push-broom" sensors, the so-called "spectral smile". As a consequence, both central wavelength and spectral width of the spectral response vary along the across-track dimension, thus giving rise to a shifting and smoothing of spectra (see Fig. 1 (left)). In fact, both effects are greater for spectra on the edges, while they are minimum for data acquired by central detectors, the so-called "sweet spot". The prior artifacts become particularly critical for Martian observations which contain steep spectra such as CO2 ice-rich polar images. Fig. 1 (right) shows the horizontal brightness gradient which appears in every band corresponding to a steep portion of spectra. The correction of CRISM spectral smile is addressed using a two-step method which aims at modifying data sensibly in order to mimic the optimal CRISM response. First, all spectra, which are previously interpolated by cubic splines, are resampled to the "sweet spot" wavelengths in order to overcome the spectra shift. Secondly, the non-uniform spectral width is overcome by mimicking an increase of spectral resolution thanks to a spectral sharpening. In order to minimize noise, only bands particularly suffering from smile are selected. First, bands corresponding to the outliers of the Minimum Noise Transformation (MNF) eigenvector, which corresponds to the MNF band related to smile (MNF-smile), are selected. Then, a spectral neighborhood Θi, which takes into account the local spectral convexity or concavity, is defined for every selected band in order to maximize spectral shape preservation. The proposed sharpening technique takes into account both the instrument parameters and the observed spectra. First, every reflectance value belonging to a Θi is reevaluated by a sharpening which depends on a ratio of the spectral width of the current detector and the "sweet spot" one. Then, the optimal degree of sharpening for every Θi is determined thanks to a loop of sharpening procedures, which is assessed by the examination of an estimation of the smile energy (the MNF-smile eigenvalue). As a matter of fact, a higher sharpening is performed on Θi as long as the smile energy decreases. Experiments on CRISM data show remarkable results regarding the decrease of smile energy (up to 80%) and the spectral shape preservation. In fact, initial smile-affected spectra do no longer show shifting nor smoothing (see Fig. 2). Line-averaged spectra and band 155 of FRT5AE3_07 showing spectral smile effects Line-averaged spectra and band 155 of smile-corrected FRT5AE3_07

Classification and Recognition of Tomb Information in Hyperspectral Image

NASA Astrophysics Data System (ADS)

Gu, M.; Lyu, S.; Hou, M.; Ma, S.; Gao, Z.; Bai, S.; Zhou, P.

2018-04-01

There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or true colour camera. In order to classify and identify materials in ancient tomb effectively, this paper applied hyperspectral imaging technology to archaeological research of ancient tomb in Shanxi province. Firstly, the feature bands including the main information at the bottom of the ancient tomb are selected by the Principal Component Analysis (PCA) transformation to realize the data dimension. Then, the image classification was performed using Support Vector Machine (SVM) based on feature bands. Finally, the material at the bottom of ancient tomb is identified by spectral analysis and spectral matching. The results show that SVM based on feature bands can not only ensure the classification accuracy, but also shorten the data processing time and improve the classification efficiency. In the material identification, it is found that the same matter identified in the visible light is actually two different substances. This research result provides a new reference and research idea for archaeological work.

A statistical evaluation of spectral fingerprinting methods using analysis of variance and principal component analysis

USDA-ARS?s Scientific Manuscript database

Six methods were compared with respect to spectral fingerprinting of a well-characterized series of broccoli samples. Spectral fingerprints were acquired for finely-powdered solid samples using Fourier transform-infrared (IR) and Fourier transform-near infrared (NIR) spectrometry and for aqueous met...

Detection of hypercholesterolemia using hyperspectral imaging of human skin

NASA Astrophysics Data System (ADS)

Milanic, Matija; Bjorgan, Asgeir; Larsson, Marcus; Strömberg, Tomas; Randeberg, Lise L.

2015-07-01

Hypercholesterolemia is characterized by high blood levels of cholesterol and is associated with increased risk of atherosclerosis and cardiovascular disease. Xanthelasma is a subcutaneous lesion appearing in the skin around the eyes. Xanthelasma is related to hypercholesterolemia. Identifying micro-xanthelasma can thereforeprovide a mean for early detection of hypercholesterolemia and prevent onset and progress of disease. The goal of this study was to investigate spectral and spatial characteristics of hypercholesterolemia in facial skin. Optical techniques like hyperspectral imaging (HSI) might be a suitable tool for such characterization as it simultaneously provides high resolution spatial and spectral information. In this study a 3D Monte Carlo model of lipid inclusions in human skin was developed to create hyperspectral images in the spectral range 400-1090 nm. Four lesions with diameters 0.12-1.0 mm were simulated for three different skin types. The simulations were analyzed using three algorithms: the Tissue Indices (TI), the two layer Diffusion Approximation (DA), and the Minimum Noise Fraction transform (MNF). The simulated lesions were detected by all methods, but the best performance was obtained by the MNF algorithm. The results were verified using data from 11 volunteers with known cholesterol levels. The face of the volunteers was imaged by a LCTF system (400- 720 nm), and the images were analyzed using the previously mentioned algorithms. The identified features were then compared to the known cholesterol levels of the subjects. Significant correlation was obtained for the MNF algorithm only. This study demonstrates that HSI can be a promising, rapid modality for detection of hypercholesterolemia.

MOVING BEYOND COLOR: THE CASE FOR MULTISPECTRAL IMAGING IN BRIGHTFIELD PATHOLOGY.

PubMed

Cukierski, William J; Qi, Xin; Foran, David J

2009-01-01

A multispectral camera is capable of imaging a histologic slide at narrow bandwidths over the range of the visible spectrum. While several uses for multispectral imaging (MSI) have been demonstrated in pathology [1, 2], there is no unified consensus over when and how MSI might benefit automated analysis [3, 4]. In this work, we use a linear-algebra framework to investigate the relationship between the spectral image and its standard-image counterpart. The multispectral "cube" is treated as an extension of a traditional image in a high-dimensional color space. The concept of metamers is introduced and used to derive regions of the visible spectrum where MSI may provide an advantage. Furthermore, histological stains which are amenable to analysis by MSI are reported. We show the Commission internationale de l'éclairage (CIE) 1931 transformation from spectrum to color is non-neighborhood preserving. Empirical results are demonstrated on multispectral images of peripheral blood smears.

Video Toroid Cavity Imager

DOEpatents

Gerald, II, Rex E.; Sanchez, Jairo; Rathke, Jerome W.

2004-08-10

A video toroid cavity imager for in situ measurement of electrochemical properties of an electrolytic material sample includes a cylindrical toroid cavity resonator containing the sample and employs NMR and video imaging for providing high-resolution spectral and visual information of molecular characteristics of the sample on a real-time basis. A large magnetic field is applied to the sample under controlled temperature and pressure conditions to simultaneously provide NMR spectroscopy and video imaging capabilities for investigating electrochemical transformations of materials or the evolution of long-range molecular aggregation during cooling of hydrocarbon melts. The video toroid cavity imager includes a miniature commercial video camera with an adjustable lens, a modified compression coin cell imager with a fiat circular principal detector element, and a sample mounted on a transparent circular glass disk, and provides NMR information as well as a video image of a sample, such as a polymer film, with micrometer resolution.

Quantitative methods and detection techniques in hyperspectral imaging involving medical and other applications

NASA Astrophysics Data System (ADS)

Roy, Ankita

2007-12-01

This research using Hyperspectral imaging involves recognizing targets through spatial and spectral matching and spectral un-mixing of data ranging from remote sensing to medical imaging kernels for clinical studies based on Hyperspectral data-sets generated using the VFTHSI [Visible Fourier Transform Hyperspectral Imager], whose high resolution Si detector makes the analysis achievable. The research may be broadly classified into (I) A Physically Motivated Correlation Formalism (PMCF), which places both spatial and spectral data on an equivalent mathematical footing in the context of a specific Kernel and (II) An application in RF plasma specie detection during carbon nanotube growing process. (III) Hyperspectral analysis for assessing density and distribution of retinopathies like age related macular degeneration (ARMD) and error estimation enabling the early recognition of ARMD, which is treated as an ill-conditioned inverse imaging problem. The broad statistical scopes of this research are two fold-target recognition problems and spectral unmixing problems. All processes involve experimental and computational analysis of Hyperspectral data sets is presented, which is based on the principle of a Sagnac Interferometer, calibrated to obtain high SNR levels. PMCF computes spectral/spatial/cross moments and answers the question of how optimally the entire hypercube should be sampled and finds how many spatial-spectral pixels are required precisely for a particular target recognition. Spectral analysis of RF plasma radicals, typically Methane plasma and Argon plasma using VFTHSI has enabled better process monitoring during growth of vertically aligned multi-walled carbon nanotubes by instant registration of the chemical composition or density changes temporally, which is key since a significant correlation can be found between plasma state and structural properties. A vital focus of this dissertation is towards medical Hyperspectral imaging applied to retinopathies like age related macular degeneration targets taken with a Fundus imager, which is akin to the VFTHSI. Detection of the constituent components in the diseased hyper-pigmentation area is also computed. The target or reflectance matrix is treated as a highly ill-conditioned spectral un-mixing problem, to which methodologies like inverse techniques, principal component analysis (PCA) and receiver operating curves (ROC) for precise spectral recognition of infected area. The region containing ARMD was easily distinguishable from the spectral mesh plots over the entire band-pass area. Once the location was detected the PMCF coefficients were calculated by cross correlating a target of normal oxygenated retina with the deoxygenated one. The ROCs generated using PMCF shows 30% higher detection probability with improved accuracy than ROCs based on Spectral Angle Mapper (SAM). By spectral unmixing methods, the important endmembers/carotenoids of the MD pigment were found to be Xanthophyl and lutein, while beta-carotene which showed a negative correlation in the unconstrained inverse problem is a supplement given to ARMD patients to prevent the disease and does not occur in the eye. Literature also shows degeneration of meso-zeaxanthin. Ophthalmologists may assert the presence of ARMD and commence the diagnosis process if the Xanthophyl pigment have degenerated 89.9%, while the lutein has decayed almost 80%, as found deduced computationally. This piece of current research takes it to the next level of precise investigation in the continuing process of improved clinical findings by correlating the microanatomy of the diseased fovea and shows promise of an early detection of this disease.

A Sagnac Fourier spectrometer

DOE PAGES

Lenzner, Matthias; Diels, Jean -Claude

2017-03-09

A spectrometer based on a Sagnac interferometer, where one of the mirrors is replaced by a transmission grating, is introduced. Since the action of a transmission grating is reversible, both directions experience the same diffraction at a given wavelength. At the output, the crossed wavefronts are imaged onto a camera, where their Fizeau fringe pattern is recorded. Each spectral element produces a unique spatial frequency, hence the Fourier transform of the recorded interferogram contains the spectrum. Since the grating is tuned to place zero spatial frequency at a selected wavelength, the adjoining spectrum is heterodyned with respect to this wavelength.more » This spectrum can then be discriminated at a high spectral resolution from relatively low spatial frequencies. The spectrometer can be designed without moving parts for a relatively narrow spectral range or with a rotatable grating. As a result, the latter version bears the potential to be calibrated without a calibrated light source.« less

A Sagnac Fourier spectrometer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lenzner, Matthias; Diels, Jean -Claude

A spectrometer based on a Sagnac interferometer, where one of the mirrors is replaced by a transmission grating, is introduced. Since the action of a transmission grating is reversible, both directions experience the same diffraction at a given wavelength. At the output, the crossed wavefronts are imaged onto a camera, where their Fizeau fringe pattern is recorded. Each spectral element produces a unique spatial frequency, hence the Fourier transform of the recorded interferogram contains the spectrum. Since the grating is tuned to place zero spatial frequency at a selected wavelength, the adjoining spectrum is heterodyned with respect to this wavelength.more » This spectrum can then be discriminated at a high spectral resolution from relatively low spatial frequencies. The spectrometer can be designed without moving parts for a relatively narrow spectral range or with a rotatable grating. As a result, the latter version bears the potential to be calibrated without a calibrated light source.« less

Wide-field spectral imaging of human ovary autofluorescence and oncologic diagnosis via previously collected probe data

PubMed Central

Hatch, Kenneth D.

2012-01-01

Abstract. With no sufficient screening test for ovarian cancer, a method to evaluate the ovarian disease state quickly and nondestructively is needed. The authors have applied a wide-field spectral imager to freshly resected ovaries of 30 human patients in a study believed to be the first of its magnitude. Endogenous fluorescence was excited with 365-nm light and imaged in eight emission bands collectively covering the 400- to 640-nm range. Linear discriminant analysis was used to classify all image pixels and generate diagnostic maps of the ovaries. Training the classifier with previously collected single-point autofluorescence measurements of a spectroscopic probe enabled this novel classification. The process by which probe-collected spectra were transformed for comparison with imager spectra is described. Sensitivity of 100% and specificity of 51% were obtained in classifying normal and cancerous ovaries using autofluorescence data alone. Specificity increased to 69% when autofluorescence data were divided by green reflectance data to correct for spatial variation in tissue absorption properties. Benign neoplasm ovaries were also found to classify as nonmalignant using the same algorithm. Although applied ex vivo, the method described here appears useful for quick assessment of cancer presence in the human ovary. PMID:22502561

3D modeling to characterize lamina cribrosa surface and pore geometries using in vivo images from normal and glaucomatous eyes

PubMed Central

Sredar, Nripun; Ivers, Kevin M.; Queener, Hope M.; Zouridakis, George; Porter, Jason

2013-01-01

En face adaptive optics scanning laser ophthalmoscope (AOSLO) images of the anterior lamina cribrosa surface (ALCS) represent a 2D projected view of a 3D laminar surface. Using spectral domain optical coherence tomography images acquired in living monkey eyes, a thin plate spline was used to model the ALCS in 3D. The 2D AOSLO images were registered and projected onto the 3D surface that was then tessellated into a triangular mesh to characterize differences in pore geometry between 2D and 3D images. Following 3D transformation of the anterior laminar surface in 11 normal eyes, mean pore area increased by 5.1 ± 2.0% with a minimal change in pore elongation (mean change = 0.0 ± 0.2%). These small changes were due to the relatively flat laminar surfaces inherent in normal eyes (mean radius of curvature = 3.0 ± 0.5 mm). The mean increase in pore area was larger following 3D transformation in 4 glaucomatous eyes (16.2 ± 6.0%) due to their more steeply curved laminar surfaces (mean radius of curvature = 1.3 ± 0.1 mm), while the change in pore elongation was comparable to that in normal eyes (−0.2 ± 2.0%). This 3D transformation and tessellation method can be used to better characterize and track 3D changes in laminar pore and surface geometries in glaucoma. PMID:23847739

Hazardous gas detection for FTIR-based hyperspectral imaging system using DNN and CNN

NASA Astrophysics Data System (ADS)

Kim, Yong Chan; Yu, Hyeong-Geun; Lee, Jae-Hoon; Park, Dong-Jo; Nam, Hyun-Woo

2017-10-01

Recently, a hyperspectral imaging system (HIS) with a Fourier Transform InfraRed (FTIR) spectrometer has been widely used due to its strengths in detecting gaseous fumes. Even though numerous algorithms for detecting gaseous fumes have already been studied, it is still difficult to detect target gases properly because of atmospheric interference substances and unclear characteristics of low concentration gases. In this paper, we propose detection algorithms for classifying hazardous gases using a deep neural network (DNN) and a convolutional neural network (CNN). In both the DNN and CNN, spectral signal preprocessing, e.g., offset, noise, and baseline removal, are carried out. In the DNN algorithm, the preprocessed spectral signals are used as feature maps of the DNN with five layers, and it is trained by a stochastic gradient descent (SGD) algorithm (50 batch size) and dropout regularization (0.7 ratio). In the CNN algorithm, preprocessed spectral signals are trained with 1 × 3 convolution layers and 1 × 2 max-pooling layers. As a result, the proposed algorithms improve the classification accuracy rate by 1.5% over the existing support vector machine (SVM) algorithm for detecting and classifying hazardous gases.

Recent applications of hyperspectral imaging in microbiology.

PubMed

Gowen, Aoife A; Feng, Yaoze; Gaston, Edurne; Valdramidis, Vasilis

2015-05-01

Hyperspectral chemical imaging (HSI) is a broad term encompassing spatially resolved spectral data obtained through a variety of modalities (e.g. Raman scattering, Fourier transform infrared microscopy, fluorescence and near-infrared chemical imaging). It goes beyond the capabilities of conventional imaging and spectroscopy by obtaining spatially resolved spectra from objects at spatial resolutions varying from the level of single cells up to macroscopic objects (e.g. foods). In tandem with recent developments in instrumentation and sampling protocols, applications of HSI in microbiology have increased rapidly. This article gives a brief overview of the fundamentals of HSI and a comprehensive review of applications of HSI in microbiology over the past 10 years. Technical challenges and future perspectives for these techniques are also discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

Predictive spectroscopy and chemical imaging based on novel optical systems

NASA Astrophysics Data System (ADS)

Nelson, Matthew Paul

1998-10-01

This thesis describes two futuristic optical systems designed to surpass contemporary spectroscopic methods for predictive spectroscopy and chemical imaging. These systems are advantageous to current techniques in a number of ways including lower cost, enhanced portability, shorter analysis time, and improved S/N. First, a novel optical approach to predicting chemical and physical properties based on principal component analysis (PCA) is proposed and evaluated. A regression vector produced by PCA is designed into the structure of a set of paired optical filters. Light passing through the paired filters produces an analog detector signal directly proportional to the chemical/physical property for which the regression vector was designed. Second, a novel optical system is described which takes a single-shot approach to chemical imaging with high spectroscopic resolution using a dimension-reduction fiber-optic array. Images are focused onto a two- dimensional matrix of optical fibers which are drawn into a linear distal array with specific ordering. The distal end is imaged with a spectrograph equipped with an ICCD camera for spectral analysis. Software is used to extract the spatial/spectral information contained in the ICCD images and deconvolute them into wave length-specific reconstructed images or position-specific spectra which span a multi-wavelength space. This thesis includes a description of the fabrication of two dimension-reduction arrays as well as an evaluation of the system for spatial and spectral resolution, throughput, image brightness, resolving power, depth of focus, and channel cross-talk. PCA is performed on the images by treating rows of the ICCD images as spectra and plotting the scores of each PC as a function of reconstruction position. In addition, iterative target transformation factor analysis (ITTFA) is performed on the spectroscopic images to generate ``true'' chemical maps of samples. Univariate zero-order images, univariate first-order spectroscopic images, bivariate first-order spectroscopic images, and multivariate first-order spectroscopic images of the temporal development of laser-induced plumes are presented and interpreted. Reconstructed chemical images generated using bivariate and trivariate wavelength techniques, bimodal and trimodal PCA methods, and bimodal and trimodal ITTFA approaches are also included.

Mapping Chinese tallow with color-infrared photography

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, G.A.; Sapkota, S.K.; Seeger, E.B.; Martella, K.D.

2002-01-01

Airborne color-infrared photography (CIR) (1:12,000 scale) was used to map localized occurrences of the widespread and aggressive Chinese tallow (Sapium sebiferum), an invasive species. Photography was collected during senescence when Chinese tallow's bright red leaves presented a high spectral contrast within the native bottomland hardwood and upland forests and marsh land-cover types. Mapped occurrences were conservative because not all senescing tallow leaves are bright red simultaneously. To simulate low spectral but high spatial resolution satellite/airborne image and digital video data, the CIR photography was transformed into raster images at spatial resolutions approximating 0.5 in and 1.0 m. The image data were then spectrally classified for the occurrence of bright red leaves associated with senescing Chinese tallow. Classification accuracies were greater than 95 percent at both spatial resolutions. There was no significant difference in either forest in the detection of tallow or inclusion of non-tallow trees associated with the two spatial resolutions. In marshes, slightly more tallow occurrences were mapped with the lower spatial resolution, but there were also more misclassifications of native land covers as tallow. Combining all land covers, there was no difference at detecting tallow occurrences (equal omission errors) between the two resolutions, but the higher spatial resolution was associated with less inclusion of non-tallow land covers as tallow (lower commission error). Overall, these results confirm that high spatial (???1 m) but low spectral resolution remote sensing data can be used for mapping Chinese tallow trees in dominant environments found in coastal and adjacent upland landscapes.

Utilizing spatial and spectral features of photoacoustic imaging for ovarian cancer detection and diagnosis

NASA Astrophysics Data System (ADS)

Li, Hai; Kumavor, Patrick; Salman Alqasemi, Umar; Zhu, Quing

2015-01-01

A composite set of ovarian tissue features extracted from photoacoustic spectral data, beam envelope, and co-registered ultrasound and photoacoustic images are used to characterize malignant and normal ovaries using logistic and support vector machine (SVM) classifiers. Normalized power spectra were calculated from the Fourier transform of the photoacoustic beamformed data, from which the spectral slopes and 0-MHz intercepts were extracted. Five features were extracted from the beam envelope and another 10 features were extracted from the photoacoustic images. These 17 features were ranked by their p-values from t-tests on which a filter type of feature selection method was used to determine the optimal feature number for final classification. A total of 169 samples from 19 ex vivo ovaries were randomly distributed into training and testing groups. Both classifiers achieved a minimum value of the mean misclassification error when the seven features with lowest p-values were selected. Using these seven features, the logistic and SVM classifiers obtained sensitivities of 96.39±3.35% and 97.82±2.26%, and specificities of 98.92±1.39% and 100%, respectively, for the training group. For the testing group, logistic and SVM classifiers achieved sensitivities of 92.71±3.55% and 92.64±3.27%, and specificities of 87.52±8.78% and 98.49±2.05%, respectively.

Connecting complexity with spectral entropy using the Laplace transformed solution to the fractional diffusion equation

NASA Astrophysics Data System (ADS)

Liang, Yingjie; Chen, Wen; Magin, Richard L.

2016-07-01

Analytical solutions to the fractional diffusion equation are often obtained by using Laplace and Fourier transforms, which conveniently encode the order of the time and the space derivatives (α and β) as non-integer powers of the conjugate transform variables (s, and k) for the spectral and the spatial frequencies, respectively. This study presents a new solution to the fractional diffusion equation obtained using the Laplace transform and expressed as a Fox's H-function. This result clearly illustrates the kinetics of the underlying stochastic process in terms of the Laplace spectral frequency and entropy. The spectral entropy is numerically calculated by using the direct integration method and the adaptive Gauss-Kronrod quadrature algorithm. Here, the properties of spectral entropy are investigated for the cases of sub-diffusion and super-diffusion. We find that the overall spectral entropy decreases with the increasing α and β, and that the normal or Gaussian case with α = 1 and β = 2, has the lowest spectral entropy (i.e., less information is needed to describe the state of a Gaussian process). In addition, as the neighborhood over which the entropy is calculated increases, the spectral entropy decreases, which implies a spatial averaging or coarse graining of the material properties. Consequently, the spectral entropy is shown to provide a new way to characterize the temporal correlation of anomalous diffusion. Future studies should be designed to examine changes of spectral entropy in physical, chemical and biological systems undergoing phase changes, chemical reactions and tissue regeneration.

Performance of the Fourier transform spectrometer (FTS) for FIS onboard ASTRO-F

NASA Astrophysics Data System (ADS)

Murakami, Noriko; Kawada, Mitsunobu; Takahashi, Hidenori; Ozawa, Keita; Imamura, Tetsuo; Shibai, Hiroshi; Nakagawa, Takao

2004-10-01

We have developed the imaging Fourier Transform Spectrometer (FTS) for the FIS (Far-Infrared Surveyor) onboard the ASTRO-F satellite. A Martin-Puplett interferometer is adopted to achieve high optical efficiency in a wide wavelength range. The total optical efficiency of this spectrometer is achieved 40-80% of the ideal value which is 25% of the incident flux. The wavelength range of 50-200μm is covered with two kinds of detector; the monolithic Ge:Ga photoconductor array for short wavelength (50-110μm) and the stressed Ge:Ga photoconductor array for long wavelength (110-200μm). The spectral resolution expected from the maximum optical path difference is 0.18cm-1. In order to evaluate the spectral resolution of the FTS, we measured absorption lines of H2O in atmosphere using the optics of the FTS with a bolometer at the room temperature. The measured line widths are consistent with the expected instrumental resolution of 0.18 cm-1. Some spectral measurements at the cryogenic temperature were carried out by using cold blackbody sources whose temperatures are controlled in a range from 20 to 50 K. The derived spectra considering with the spectral response of the system are consistent with expected ones. Spectroscopic observations with the FTS will provide a lot of astronomical information; SED of galaxies detected in the all sky survey and the physical diagnostics of the interstellar matter by using the excited atomic or molecular lines.

Spectral ballistic imaging: a novel technique for viewing through turbid or obstructing media.

PubMed

Granot, Er'el; Sternklar, Shmuel

2003-08-01

We propose a new method for viewing through turbid or obstructing media. The medium is illuminated with a modulated cw laser and the amplitude and phase of the transmitted (or reflected) signal is measured. This process takes place for a set of wavelengths in a certain wide band. In this way we acquire the Fourier transform of the temporal output. With this information we can reconstruct the temporal shape of the transmitted signal by computing the inverse transform. The proposed method benefits from the advantages of the first-light technique: high resolution, simple algorithms, insensitivity to boundary condition, etc., without suffering from its main deficiencies: complex and expensive equipment.

Thermal Texture Generation and 3d Model Reconstruction Using SFM and Gan

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Mizginov, V. A.

2018-05-01

Realistic 3D models with textures representing thermal emission of the object are widely used in such fields as dynamic scene analysis, autonomous driving, and video surveillance. Structure from Motion (SfM) methods provide a robust approach for the generation of textured 3D models in the visible range. Still, automatic generation of 3D models from the infrared imagery is challenging due to an absence of the feature points and low sensor resolution. Recent advances in Generative Adversarial Networks (GAN) have proved that they can perform complex image-to-image transformations such as a transformation of day to night and generation of imagery in a different spectral range. In this paper, we propose a novel method for generation of realistic 3D models with thermal textures using the SfM pipeline and GAN. The proposed method uses visible range images as an input. The images are processed in two ways. Firstly, they are used for point matching and dense point cloud generation. Secondly, the images are fed into a GAN that performs the transformation from the visible range to the thermal range. We evaluate the proposed method using real infrared imagery captured with a FLIR ONE PRO camera. We generated a dataset with 2000 pairs of real images captured in thermal and visible range. The dataset is used to train the GAN network and to generate 3D models using SfM. The evaluation of the generated 3D models and infrared textures proved that they are similar to the ground truth model in both thermal emissivity and geometrical shape.

Asymmetric optical image encryption using Kolmogorov phase screens and equal modulus decomposition

NASA Astrophysics Data System (ADS)

Kumar, Ravi; Bhaduri, Basanta; Quan, Chenggen

2017-11-01

An asymmetric technique for optical image encryption is proposed using Kolmogorov phase screens (KPSs) and equal modulus decomposition (EMD). The KPSs are generated using the power spectral density of Kolmogorov turbulence. The input image is first randomized and then Fresnel propagated with distance d. Further, the output in the Fresnel domain is modulated with a random phase mask, and the gyrator transform (GT) of the modulated image is obtained with an angle α. The EMD is operated on the GT spectrum to get the complex images, Z1 and Z2. Among these, Z2 is reserved as a private key for decryption and Z1 is propagated through a medium consisting of four KPSs, located at specified distances, to get the final encrypted image. The proposed technique provides a large set of security keys and is robust against various potential attacks. Numerical simulation results validate the effectiveness and security of the proposed technique.

Digital Signal Processing Techniques for the GIFTS SM EDU

NASA Technical Reports Server (NTRS)

Tian, Jialin; Reisse, Robert A.; Gazarik, Michael J.

2007-01-01

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiance using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three Focal Plane Arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes several digital signal processing (DSP) techniques involved in the development of the calibration model. In the first stage, the measured raw interferograms must undergo a series of processing steps that include filtering, decimation, and detector nonlinearity correction. The digital filtering is achieved by employing a linear-phase even-length FIR complex filter that is designed based on the optimum equiripple criteria. Next, the detector nonlinearity effect is compensated for using a set of pre-determined detector response characteristics. In the next stage, a phase correction algorithm is applied to the decimated interferograms. This is accomplished by first estimating the phase function from the spectral phase response of the windowed interferogram, and then correcting the entire interferogram based on the estimated phase function. In the calibration stage, we first compute the spectral responsivity based on the previous results and the ideal Planck blackbody spectra at the given temperatures, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. In the post-calibration stage, we estimate the Noise Equivalent Spectral Radiance (NESR) from the calibrated ABB and HBB spectra. The NESR is generally considered as a measure of the instrument noise performance, and can be estimated as the standard deviation of calibrated radiance spectra from multiple scans. To obtain an estimate of the FPA performance, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is developed based on the pixel performance evaluation. This would allow us to perform the calibration procedures on a random pixel population that is a good statistical representation of the entire FPA. The design and implementation of each individual component will be discussed in details.

In-flight control and communication architecture of the GLORIA imaging limb sounder on atmospheric research aircraft

NASA Astrophysics Data System (ADS)

Kretschmer, E.; Bachner, M.; Blank, J.; Dapp, R.; Ebersoldt, A.; Friedl-Vallon, F.; Guggenmoser, T.; Gulde, T.; Hartmann, V.; Lutz, R.; Maucher, G.; Neubert, T.; Oelhaf, H.; Preusse, P.; Schardt, G.; Schmitt, C.; Schönfeld, A.; Tan, V.

2015-06-01

The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA), a Fourier-transform-spectrometer-based limb spectral imager, operates on high-altitude research aircraft to study the transit region between the troposphere and the stratosphere. It is one of the most sophisticated systems to be flown on research aircraft in Europe, requiring constant monitoring and human intervention in addition to an automation system. To ensure proper functionality and interoperability on multiple platforms, a flexible control and communication system was laid out. The architectures of the communication system as well as the protocols used are reviewed. The integration of this architecture in the automation process as well as the scientific campaign flight application context are discussed.

In-flight control and communication architecture of the GLORIA imaging limb-sounder on atmospheric research aircraft

NASA Astrophysics Data System (ADS)

Kretschmer, E.; Bachner, M.; Blank, J.; Dapp, R.; Ebersoldt, A.; Friedl-Vallon, F.; Guggenmoser, T.; Gulde, T.; Hartmann, V.; Lutz, R.; Maucher, G.; Neubert, T.; Oelhaf, H.; Preusse, P.; Schardt, G.; Schmitt, C.; Schönfeld, A.; Tan, V.

2015-02-01

The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA), a Fourier transform spectrometer based limb spectral imager, operates on high-altitude research aircraft to study the transit region between the troposphere and the stratosphere. It is one of the most sophisticated systems to be flown on research aircraft in Europe, requiring constant monitoring and human intervention in addition to an automation system. To ensure proper functionality and interoperability on multiple platforms, a flexible control and communication system was laid out. The architectures of the communication system as well as the protocols used are reviewed. The integration of this architecture in the automation process as well as the scientific campaign flight application context are discussed.

Hyperspectral Imagers for the Study of Massive Star Nebulae

NASA Astrophysics Data System (ADS)

Drissen, L.; Alarie, A.; Martin, T.; Spiomm/Sitelle Team

2012-12-01

We present two wide-field imaging Fourier transform spectrometers built by our team to study the interstellar medium around massive stars in the Milky Way and nearby galaxies. SpIOMM, attached to the Mont Mégantic 1.6-m telescope, is capable of obtaining the visible spectrum of every source of light in a 12 arcminute field of view, with a spectral resolution ranging from R = 1 (wide-band image) to R = 25 000, resulting in about a million spectra with a spatial resolution of one arcsecond. SITELLE will be a similar instrument attached to the Canada-France-Hawaii telescope, and will be in operation in early 2013. We illustrate SpIOMM's capabilities to study the interactions between massive stars and their environment.

Improving multispectral satellite image compression using onboard subpixel registration

NASA Astrophysics Data System (ADS)

Albinet, Mathieu; Camarero, Roberto; Isnard, Maxime; Poulet, Christophe; Perret, Jokin

2013-09-01

Future CNES earth observation missions will have to deal with an ever increasing telemetry data rate due to improvements in resolution and addition of spectral bands. Current CNES image compressors implement a discrete wavelet transform (DWT) followed by a bit plane encoding (BPE) but only on a mono spectral basis and do not profit from the multispectral redundancy of the observed scenes. Recent CNES studies have proven a substantial gain on the achievable compression ratio, +20% to +40% on selected scenarios, by implementing a multispectral compression scheme based on a Karhunen Loeve transform (KLT) followed by the classical DWT+BPE. But such results can be achieved only on perfectly registered bands; a default of registration as low as 0.5 pixel ruins all the benefits of multispectral compression. In this work, we first study the possibility to implement a multi-bands subpixel onboard registration based on registration grids generated on-the-fly by the satellite attitude control system and simplified resampling and interpolation techniques. Indeed bands registration is usually performed on ground using sophisticated techniques too computationally intensive for onboard use. This fully quantized algorithm is tuned to meet acceptable registration performances within stringent image quality criteria, with the objective of onboard real-time processing. In a second part, we describe a FPGA implementation developed to evaluate the design complexity and, by extrapolation, the data rate achievable on a spacequalified ASIC. Finally, we present the impact of this approach on the processing chain not only onboard but also on ground and the impacts on the design of the instrument.

[Research on improving spectrum resolution of optimized Wollaston prism array].

PubMed

Zhang, Peng; Wang, Jian-Rong; Zhang, Guo-Chen; Hou, Wen

2011-11-01

In order to not affect the image quality of interference fringes on the basis of the structure by increasing the structure angle of Wollaston prism to improve spectrum resolution, the authors optimized the structure of Wollaston prism. Calculating the function of the splitting angle and the structure angle, analysis indicated that taking the isosceles triangle prism with the same nature of the second wedge-shaped prism after the Wollaston prism, which makes the o and e light parallel to the optical axis, and alpha=0 degrees, the imaging interference fringes are no longer affected by changes in the splitting angle. Several optimized Wollaston prisms were made as an array to improve the spectral resolution. Experiments used traditional and optimized Wollaston prism array to detect the spectrum of the 980 nm laser. Experimental data showed that using optimized Wollaston prism array gets a clearer contrast of interference fringes, and the spectral data with Fourier transform are more accurate with DSP.

An Accurate Method for Measuring Airplane-Borne Conformal Antenna's Radar Cross Section

NASA Astrophysics Data System (ADS)

Guo, Shuxia; Zhang, Lei; Wang, Yafeng; Hu, Chufeng

2016-09-01

The airplane-borne conformal antenna attaches itself tightly with the airplane skin, so the conventional measurement method cannot determine the contribution of the airplane-borne conformal antenna to its radar cross section (RCS). This paper uses the 2D microwave imaging to isolate and extract the distribution of the reflectivity of the airplane-borne conformal antenna. It obtains the 2D spatial spectra of the conformal antenna through the wave spectral transform between the 2D spatial image and the 2D spatial spectrum. After the interpolation from the rectangular coordinate domain to the polar coordinate domain, the spectral domain data for the variation of the scatter of the conformal antenna with frequency and angle is obtained. The experimental results show that the measurement method proposed in this paper greatly enhances the airplane-borne conformal antenna's RCS measurement accuracy, essentially eliminates the influences caused by the airplane skin and more accurately reveals the airplane-borne conformal antenna's RCS scatter properties.

Hyperspectral imaging of water quality - past applications and future directions.

NASA Astrophysics Data System (ADS)

Ross, M. R. V.; Pavelsky, T.

2017-12-01

Inland waters control the delivery of sediment, carbon, and nutrients from land to ocean by transforming, depositing, and transporting constituents downstream. However, the dominant in situ conditions that control these processes are poorly constrained, especially at larger spatial scales. Hyperspectral imaging, a remote sensing technique that uses reflectance in hundreds of narrow spectral bands, can be used to estimate water quality parameters like sediment and carbon concentration over larger water bodies. Here, we review methods and applications for using hyperspectral imagery to generate near-surface two-dimensional models of water quality in lakes and rivers. Further, we show applications using newly available data from the National Ecological Observation Network aerial observation platform in the Black Warrior and Tombigbee Rivers, Alabama. We demonstrate large spatial variation in chlorophyll, colored dissolved organic matter, and turbidity in each river and uneven mixing of water quality constituents for several kilometers. Finally, we demonstrate some novel techniques using hyperspectral imagery to deconvolve dissolved organic matter spectral signatures to specific organic matter components.

ICER-3D Hyperspectral Image Compression Software

NASA Technical Reports Server (NTRS)

Xie, Hua; Kiely, Aaron; Klimesh, matthew; Aranki, Nazeeh

2010-01-01

Software has been developed to implement the ICER-3D algorithm. ICER-3D effects progressive, three-dimensional (3D), wavelet-based compression of hyperspectral images. If a compressed data stream is truncated, the progressive nature of the algorithm enables reconstruction of hyperspectral data at fidelity commensurate with the given data volume. The ICER-3D software is capable of providing either lossless or lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The compression algorithm, which was derived from the ICER image compression algorithm, includes wavelet-transform, context-modeling, and entropy coding subalgorithms. The 3D wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of sets of hyperspectral image data, while facilitating elimination of spectral ringing artifacts, using a technique summarized in "Improving 3D Wavelet-Based Compression of Spectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. Correlation is further exploited by a context-modeling subalgorithm, which exploits spectral dependencies in the wavelet-transformed hyperspectral data, using an algorithm that is summarized in "Context Modeler for Wavelet Compression of Hyperspectral Images" (NPO-43239), which follows this article. An important feature of ICER-3D is a scheme for limiting the adverse effects of loss of data during transmission. In this scheme, as in the similar scheme used by ICER, the spatial-frequency domain is partitioned into rectangular error-containment regions. In ICER-3D, the partitions extend through all the wavelength bands. The data in each partition are compressed independently of those in the other partitions, so that loss or corruption of data from any partition does not affect the other partitions. Furthermore, because compression is progressive within each partition, when data are lost, any data from that partition received prior to the loss can be used to reconstruct that partition at lower fidelity. By virtue of the compression improvement it achieves relative to previous means of onboard data compression, this software enables (1) increased return of hyperspectral scientific data in the presence of limits on the rates of transmission of data from spacecraft to Earth via radio communication links and/or (2) reduction in spacecraft radio-communication power and/or cost through reduction in the amounts of data required to be downlinked and stored onboard prior to downlink. The software is also suitable for compressing hyperspectral images for ground storage or archival purposes.

Development and application of Fourier-transform infrared chemical imaging of tumour in human tissue.

PubMed

Petter, C H; Heigl, N; Rainer, M; Bakry, R; Pallua, J; Bonn, G K; Huck, C W

2009-01-01

Fourier-transform infrared (FT-IR) based mapping and imaging is a fast emerging technology which is being increasingly applied to investigate tissues in the high-throughput mode. The high resolution close to the cellular level, the possibility to determine the bio-distribution of molecules of interest (proteins, peptides, lipids, carbohydrates) without any pre-treatment and the offer to yield molecular structure information have brought evidence that this technique allows to gain new insights in cancer pathology. Thus, several individual mainly protein and peptide cancer markers ("biomarkers") can be identified from FT-IR tissue images, enabling accurate discrimination between healthy and tumour areas. Optimal data acquisition (spatial resolution, spectral resolution, signal to noise ratio), classification, and validation are necessary to establish practical protocols that can be translated to the qualitative and quantitative clinical routine analysis. Thereby, the development of modern fast infrared imaging systems has strongly supported its acceptance in clinical histopathology. In this review, the necessity of analysis based on global cancer statistics, instrumental setups and developments, experimental state of the art are summarised and applications to investigate different kinds of cancer (e.g., prostate, breast, cervical, colon, oral cavity) are shown and discussed in detail.

Automated thematic mapping and change detection of ERTS-A images. [digital interpretation of Arizona imagery

NASA Technical Reports Server (NTRS)

Gramenopoulos, N. (Principal Investigator)

1973-01-01

The author has identified the following significant results. For the recognition of terrain types, spatial signatures are developed from the diffraction patterns of small areas of ERTS-1 images. This knowledge is exploited for the measurements of a small number of meaningful spatial features from the digital Fourier transforms of ERTS-1 image cells containing 32 x 32 picture elements. Using these spatial features and a heuristic algorithm, the terrain types in the vicinity of Phoenix, Arizona were recognized by the computer with a high accuracy. Then, the spatial features were combined with spectral features and using the maximum likelihood criterion the recognition accuracy of terrain types increased substantially. It was determined that the recognition accuracy with the maximum likelihood criterion depends on the statistics of the feature vectors. Nonlinear transformations of the feature vectors are required so that the terrain class statistics become approximately Gaussian. It was also determined that for a given geographic area the statistics of the classes remain invariable for a period of a month but vary substantially between seasons.

On Hilbert-Huang Transform Based Synthesis of a Signal Contaminated by Radio Frequency Interference or Fringes

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Shiri, Ron S.; Vootukuru, Meg; Coletti, Alessandro

2015-01-01

Norden E. Huang et al. had proposed and published the Hilbert-Huang Transform (HHT) concept correspondently in 1996, 1998. The HHT is a novel method for adaptive spectral analysis of non-linear and non-stationary signals. The HHT comprises two components: - the Huang Empirical Mode Decomposition (EMD), resulting in an adaptive data-derived basis of Intrinsic Mode functions (IMFs), and the Hilbert Spectral Analysis (HSA1) based on the Hilbert Transform for 1-dimension (1D) applied to the EMD IMF's outcome. Although paper describes the HHT concept in great depth, it does not contain all needed methodology to implement the HHT computer code. In 2004, Semion Kizhner and Karin Blank implemented the reference digital HHT real-time data processing system for 1D (HHT-DPS Version 1.4). The case for 2-Dimension (2D) (HHT2) proved to be difficult due to the computational complexity of EMD for 2D (EMD2) and absence of a suitable Hilbert Transform for 2D spectral analysis (HSA2). The real-time EMD2 and HSA2 comprise the real-time HHT2. Kizhner completed the real-time EMD2 and the HSA2 reference digital implementations respectively in 2013 & 2014. Still, the HHT2 outcome synthesis remains an active research area. This paper presents the initial concepts and preliminary results of HHT2-based synthesis and its application to processing of signals contaminated by Radio-Frequency Interference (RFI), as well as optical systems' fringe detection and mitigation at design stage. The Soil Moisture Active Passive (SMAP mission (SMAP) carries a radiometer instrument that measures Earth soil moisture at L1 frequency (1.4 GHz polarimetric - H, V, 3rd and 4th Stokes parameters). There is abundant RFI at L1 and because soil moisture is a strategic parameter, it is important to be able to recover the RFI-contaminated measurement samples (15% of telemetry). State-of-the-art only allows RFI detection and removes RFI-contaminated measurements. The HHT-based analysis and synthesis facilitates recovery of measurements contaminated by all kinds of RFI, including jamming [7-8]. The fringes are inherent in optical systems and multi-layer complex contour expensive coatings are employed to remove the unwanted fringes. HHT2-based analysis allows test image decomposition to analyze and detect fringes, and HHT2-based synthesis of useful image.

Multispectral code excited linear prediction coding and its application in magnetic resonance images.

PubMed

Hu, J H; Wang, Y; Cahill, P T

1997-01-01

This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256x256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously.

Infrared micro-spectral imaging: distinction of tissue types in axillary lymph node histology

PubMed Central

Bird, Benjamin; Miljkovic, Milos; Romeo, Melissa J; Smith, Jennifer; Stone, Nicholas; George, Michael W; Diem, Max

2008-01-01

Background Histopathologic evaluation of surgical specimens is a well established technique for disease identification, and has remained relatively unchanged since its clinical introduction. Although it is essential for clinical investigation, histopathologic identification of tissues remains a time consuming and subjective technique, with unsatisfactory levels of inter- and intra-observer discrepancy. A novel approach for histological recognition is to use Fourier Transform Infrared (FT-IR) micro-spectroscopy. This non-destructive optical technique can provide a rapid measurement of sample biochemistry and identify variations that occur between healthy and diseased tissues. The advantage of this method is that it is objective and provides reproducible diagnosis, independent of fatigue, experience and inter-observer variability. Methods We report a method for analysing excised lymph nodes that is based on spectral pathology. In spectral pathology, an unstained (fixed or snap frozen) tissue section is interrogated by a beam of infrared light that samples pixels of 25 μm × 25 μm in size. This beam is rastered over the sample, and up to 100,000 complete infrared spectra are acquired for a given tissue sample. These spectra are subsequently analysed by a diagnostic computer algorithm that is trained by correlating spectral and histopathological features. Results We illustrate the ability of infrared micro-spectral imaging, coupled with completely unsupervised methods of multivariate statistical analysis, to accurately reproduce the histological architecture of axillary lymph nodes. By correlating spectral and histopathological features, a diagnostic algorithm was trained that allowed both accurate and rapid classification of benign and malignant tissues composed within different lymph nodes. This approach was successfully applied to both deparaffinised and frozen tissues and indicates that both intra-operative and more conventional surgical specimens can be diagnosed by this technique. Conclusion This paper provides strong evidence that automated diagnosis by means of infrared micro-spectral imaging is possible. Recent investigations within the author's laboratory upon lymph nodes have also revealed that cancers from different primary tumours provide distinctly different spectral signatures. Thus poorly differentiated and hard-to-determine cases of metastatic invasion, such as micrometastases, may additionally be identified by this technique. Finally, we differentiate benign and malignant tissues composed within axillary lymph nodes by completely automated methods of spectral analysis. PMID:18759967

Spectral feature design in high dimensional multispectral data

NASA Technical Reports Server (NTRS)

Chen, Chih-Chien Thomas; Landgrebe, David A.

1988-01-01

The High resolution Imaging Spectrometer (HIRIS) is designed to acquire images simultaneously in 192 spectral bands in the 0.4 to 2.5 micrometers wavelength region. It will make possible the collection of essentially continuous reflectance spectra at a spectral resolution sufficient to extract significantly enhanced amounts of information from return signals as compared to existing systems. The advantages of such high dimensional data come at a cost of increased system and data complexity. For example, since the finer the spectral resolution, the higher the data rate, it becomes impractical to design the sensor to be operated continuously. It is essential to find new ways to preprocess the data which reduce the data rate while at the same time maintaining the information content of the high dimensional signal produced. Four spectral feature design techniques are developed from the Weighted Karhunen-Loeve Transforms: (1) non-overlapping band feature selection algorithm; (2) overlapping band feature selection algorithm; (3) Walsh function approach; and (4) infinite clipped optimal function approach. The infinite clipped optimal function approach is chosen since the features are easiest to find and their classification performance is the best. After the preprocessed data has been received at the ground station, canonical analysis is further used to find the best set of features under the criterion that maximal class separability is achieved. Both 100 dimensional vegetation data and 200 dimensional soil data were used to test the spectral feature design system. It was shown that the infinite clipped versions of the first 16 optimal features had excellent classification performance. The overall probability of correct classification is over 90 percent while providing for a reduced downlink data rate by a factor of 10.

Research on remote sensing identification of rural abandoned homesteads using multiparameter characteristics method

NASA Astrophysics Data System (ADS)

Xu, Saiping; Zhao, Qianjun; Yin, Kai; Cui, Bei; Zhang, Xiupeng

2016-10-01

Hollow village is a special phenomenon in the process of urbanization in China, which causes the waste of land resources. Therefore, it's imminent to carry out the hollow village recognition and renovation. However, there are few researches on the remote sensing identification of hollow village. In this context, in order to recognize the abandoned homesteads by remote sensing technique, the experiment was carried out as follows. Firstly, Gram-Schmidt transform method was utilized to complete the image fusion between multi-spectral images and panchromatic image of WorldView-2. Then the fusion images were made edge enhanced by high pass filtering. The multi-resolution segmentation and spectral difference segmentation were carried out to obtain the image objects. Secondly, spectral characteristic parameters were calculated, such as the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), the normalized difference Soil index (NDSI) etc. The shape feature parameters were extracted, such as Area, Length/Width Ratio and Rectangular Fit etc.. Thirdly, the SEaTH algorithm was used to determine the thresholds and optimize the feature space. Furthermore, the threshold classification method and the random forest classifier were combined, and the appropriate amount of samples were selected to train the classifier in order to determine the important feature parameters and the best classifier parameters involved in classification. Finally, the classification results was verified by computing the confusion matrix. The classification results were continuous and the phenomenon of salt and pepper using pixel classification was avoided effectively. In addition, the results showed that the extracted Abandoned Homesteads were in complete shapes, which could be distinguished from those confusing classes such as Homestead in Use and Roads.

Observation of SO2 degassing at Stromboli volcano using a hyperspectral thermal infrared imager

NASA Astrophysics Data System (ADS)

Smekens, Jean-François; Gouhier, Mathieu

2018-05-01

Thermal infrared (TIR) imaging is a common tool for the monitoring of volcanic activity. Broadband cameras with increasing sampling frequency give great insight into the physical processes taking place during effusive and explosive event, while Fourier transform infrared (FTIR) methods provide high resolution spectral information used to assess the composition of volcanic gases but are often limited to a single point of interest. Continuing developments in detector technology have given rise to a new class of hyperspectral imagers combining the advantages of both approaches. In this work, we present the results of our observations of volcanic activity at Stromboli volcano with a ground-based imager, the Telops Hyper-Cam LW, when used to detect emissions of sulfur dioxide (SO2) produced at the vent, with data acquired at Stromboli volcano (Italy) in early October of 2015. We have developed an innovative technique based on a curve-fitting algorithm to quickly extract spectral information from high-resolution datasets, allowing fast and reliable identification of SO2. We show in particular that weak SO2 emissions, such as inter-eruptive gas puffing, can be easily detected using this technology, even with poor weather conditions during acquisition (e.g., high relative humidity, presence of fog and/or ash). Then, artificially reducing the spectral resolution of the instrument, we recreated a variety of commonly used multispectral configurations to examine the efficiency of four qualitative SO2 indicators based on simple Brightness Temperature Difference (BTD). Our results show that quickly changing conditions at the vent - including but not limited to the presence of summit fog - render the establishment of meaningful thresholds for BTD indicators difficult. Building on those results, we propose recommendations on the use of multispectral imaging for SO2 monitoring and routine measurements from ground-based instruments.

A Fourier Transform Infrared Spectroscopy Analysis of Carious Dentin from Transparent Zone to Normal Zone

PubMed Central

Liu, Y.; Yao, X.; Liu, Y.W.; Wang, Y.

2015-01-01

It is well known that caries invasion leads to the differentiation of dentin into zones with altered composition, collagen integrity and mineral identity. However, understanding of these changes from the fundamental perspective of molecular structure has been lacking so far. In light of this, the present work aims to utilize Fourier transform infrared spectroscopy (FTIR) to directly extract molecular information regarding collagen's and hydroxyapatite's structural changes as dentin transitions from the transparent zone (TZ) into the normal zone (NZ). Unembedded ultrathin dentin films were sectioned from carious teeth, and an FTIR imaging system was used to obtain spatially resolved FTIR spectra. According to the mineral-to-matrix ratio image generated from large-area low-spectral-resolution scan, the TZ, the NZ and the intermediate subtransparent zone (STZ) were identified. High-spectral-resolution spectra were taken from each zone and subsequently examined with regard to mineral content, carbonate distribution, collagen denaturation and carbonate substitution patterns. The integrity of collagen's triple helical structure was also evaluated based on spectra collected from demineralized dentin films of selected teeth. The results support the argument that STZ is the real sclerotic layer, and they corroborate the established knowledge that collagen in TZ is hardly altered and therefore should be reserved for reparative purposes. Moreover, the close resemblance between the STZ and the NZ in terms of carbonate content, and that between the STZ and the TZ in terms of being A-type carbonate-rich, suggest that the mineral that initially occludes dentin tubules is hydroxyapatite newly generated from odontoblastic activities, which is then transformed into whitlockite in the demineralization/remineralization process as caries progresses. PMID:24556607

A Fourier transform infrared spectroscopy analysis of carious dentin from transparent zone to normal zone.

PubMed

Liu, Y; Yao, X; Liu, Y W; Wang, Y

2014-01-01

It is well known that caries invasion leads to the differentiation of dentin into zones with altered composition, collagen integrity and mineral identity. However, understanding of these changes from the fundamental perspective of molecular structure has been lacking so far. In light of this, the present work aims to utilize Fourier transform infrared spectroscopy (FTIR) to directly extract molecular information regarding collagen's and hydroxyapatite's structural changes as dentin transitions from the transparent zone (TZ) into the normal zone (NZ). Unembedded ultrathin dentin films were sectioned from carious teeth, and an FTIR imaging system was used to obtain spatially resolved FTIR spectra. According to the mineral-to-matrix ratio image generated from large-area low-spectral-resolution scan, the TZ, the NZ and the intermediate subtransparent zone (STZ) were identified. High-spectral-resolution spectra were taken from each zone and subsequently examined with regard to mineral content, carbonate distribution, collagen denaturation and carbonate substitution patterns. The integrity of collagen's triple helical structure was also evaluated based on spectra collected from demineralized dentin films of selected teeth. The results support the argument that STZ is the real sclerotic layer, and they corroborate the established knowledge that collagen in TZ is hardly altered and therefore should be reserved for reparative purposes. Moreover, the close resemblance between the STZ and the NZ in terms of carbonate content, and that between the STZ and the TZ in terms of being A-type carbonate-rich, suggest that the mineral that initially occludes dentin tubules is hydroxyapatite newly generated from odontoblastic activities, which is then transformed into whitlockite in the demineralization/remineralization process as caries progresses. © 2014 S. Karger AG, Basel.

Spectral analysis using the CCD Chirp Z-transform

NASA Technical Reports Server (NTRS)

Eversole, W. L.; Mayer, D. J.; Bosshart, P. W.; Dewit, M.; Howes, C. R.; Buss, D. D.

1978-01-01

The charge coupled device (CCD) Chirp Z transformation (CZT) spectral analysis techniques were reviewed and results on state-of-the-art CCD CZT technology are presented. The CZT algorithm was examined and the advantages of CCD implementation are discussed. The sliding CZT which is useful in many spectral analysis applications is described, and the performance limitations of the CZT are studied.

Spectral analysis for GNSS coordinate time series using chirp Fourier transform

NASA Astrophysics Data System (ADS)

Feng, Shengtao; Bo, Wanju; Ma, Qingzun; Wang, Zifan

2017-12-01

Spectral analysis for global navigation satellite system (GNSS) coordinate time series provides a principal tool to understand the intrinsic mechanism that affects tectonic movements. Spectral analysis methods such as the fast Fourier transform, Lomb-Scargle spectrum, evolutionary power spectrum, wavelet power spectrum, etc. are used to find periodic characteristics in time series. Among spectral analysis methods, the chirp Fourier transform (CFT) with less stringent requirements is tested with synthetic and actual GNSS coordinate time series, which proves the accuracy and efficiency of the method. With the length of series only limited to even numbers, CFT provides a convenient tool for windowed spectral analysis. The results of ideal synthetic data prove CFT accurate and efficient, while the results of actual data show that CFT is usable to derive periodic information from GNSS coordinate time series.

Estimation of spectral kurtosis

NASA Astrophysics Data System (ADS)

Sutawanir

2017-03-01

Rolling bearings are the most important elements in rotating machinery. Bearing frequently fall out of service for various reasons: heavy loads, unsuitable lubrications, ineffective sealing. Bearing faults may cause a decrease in performance. Analysis of bearing vibration signals has attracted attention in the field of monitoring and fault diagnosis. Bearing vibration signals give rich information for early detection of bearing failures. Spectral kurtosis, SK, is a parameter in frequency domain indicating how the impulsiveness of a signal varies with frequency. Faults in rolling bearings give rise to a series of short impulse responses as the rolling elements strike faults, SK potentially useful for determining frequency bands dominated by bearing fault signals. SK can provide a measure of the distance of the analyzed bearings from a healthy one. SK provides additional information given by the power spectral density (psd). This paper aims to explore the estimation of spectral kurtosis using short time Fourier transform known as spectrogram. The estimation of SK is similar to the estimation of psd. The estimation falls in model-free estimation and plug-in estimator. Some numerical studies using simulations are discussed to support the methodology. Spectral kurtosis of some stationary signals are analytically obtained and used in simulation study. Kurtosis of time domain has been a popular tool for detecting non-normality. Spectral kurtosis is an extension of kurtosis in frequency domain. The relationship between time domain and frequency domain analysis is establish through power spectrum-autocovariance Fourier transform. Fourier transform is the main tool for estimation in frequency domain. The power spectral density is estimated through periodogram. In this paper, the short time Fourier transform of the spectral kurtosis is reviewed, a bearing fault (inner ring and outer ring) is simulated. The bearing response, power spectrum, and spectral kurtosis are plotted to visualize the pattern of each fault. Keywords: frequency domain Fourier transform, spectral kurtosis, bearing fault

Multimodal Spectral Imaging of Cells Using a Transmission Diffraction Grating on a Light Microscope

PubMed Central

Isailovic, Dragan; Xu, Yang; Copus, Tyler; Saraswat, Suraj; Nauli, Surya M.

2011-01-01

A multimodal methodology for spectral imaging of cells is presented. The spectral imaging setup uses a transmission diffraction grating on a light microscope to concurrently record spectral images of cells and cellular organelles by fluorescence, darkfield, brightfield, and differential interference contrast (DIC) spectral microscopy. Initially, the setup was applied for fluorescence spectral imaging of yeast and mammalian cells labeled with multiple fluorophores. Fluorescence signals originating from fluorescently labeled biomolecules in cells were collected through triple or single filter cubes, separated by the grating, and imaged using a charge-coupled device (CCD) camera. Cellular components such as nuclei, cytoskeleton, and mitochondria were spatially separated by the fluorescence spectra of the fluorophores present in them, providing detailed multi-colored spectral images of cells. Additionally, the grating-based spectral microscope enabled measurement of scattering and absorption spectra of unlabeled cells and stained tissue sections using darkfield and brightfield or DIC spectral microscopy, respectively. The presented spectral imaging methodology provides a readily affordable approach for multimodal spectral characterization of biological cells and other specimens. PMID:21639978

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smallwood, D.O.

In a previous paper Smallwood and Paez (1991) showed how to generate realizations of partially coherent stationary normal time histories with a specified cross-spectral density matrix. This procedure is generalized for the case of multiple inputs with a specified cross-spectral density function and a specified marginal probability density function (pdf) for each of the inputs. The specified pdfs are not required to be Gaussian. A zero memory nonlinear (ZMNL) function is developed for each input to transform a Gaussian or normal time history into a time history with a specified non-Gaussian distribution. The transformation functions have the property that amore » transformed time history will have nearly the same auto spectral density as the original time history. A vector of Gaussian time histories are then generated with the specified cross-spectral density matrix. These waveforms are then transformed into the required time history realizations using the ZMNL function.« less

Interpretation of AIS Images of Cuprite, Nevada Using Constraints of Spectral Mixtures

NASA Technical Reports Server (NTRS)

Smith, M. O.; Adams, J. B.

1985-01-01

A technique is outlined that tests the hypothesis Airborne Imaging Spectrometer (AIS) image spectra are produced by mixtures of surface materials. This technique allows separation of AIS images into concentration images of spectral endmembers (e.g., surface materials causing spectral variation). Using a spectral reference library it was possible to uniquely identify these spectral endmembers with respect to the reference library and to calibrate the AIS images.

A novel method to detect shadows on multispectral images

NASA Astrophysics Data System (ADS)

Daǧlayan Sevim, Hazan; Yardımcı ćetin, Yasemin; Özışık Başkurt, Didem

2016-10-01

Shadowing occurs when the direct light coming from a light source is obstructed by high human made structures, mountains or clouds. Since shadow regions are illuminated only by scattered light, true spectral properties of the objects are not observed in such regions. Therefore, many object classification and change detection problems utilize shadow detection as a preprocessing step. Besides, shadows are useful for obtaining 3D information of the objects such as estimating the height of buildings. With pervasiveness of remote sensing images, shadow detection is ever more important. This study aims to develop a shadow detection method on multispectral images based on the transformation of C1C2C3 space and contribution of NIR bands. The proposed method is tested on Worldview-2 images covering Ankara, Turkey at different times. The new index is used on these 8-band multispectral images with two NIR bands. The method is compared with methods in the literature.

Electromagnetic Vortex-Based Radar Imaging Using a Single Receiving Antenna: Theory and Experimental Results

PubMed Central

Yuan, Tiezhu; Wang, Hongqiang; Cheng, Yongqiang; Qin, Yuliang

2017-01-01

Radar imaging based on electromagnetic vortex can achieve azimuth resolution without relative motion. The present paper investigates this imaging technique with the use of a single receiving antenna through theoretical analysis and experimental results. Compared with the use of multiple receiving antennas, the echoes from a single receiver cannot be used directly for image reconstruction using Fourier method. The reason is revealed by using the point spread function. An additional phase is compensated for each mode before imaging process based on the array parameters and the elevation of the targets. A proof-of-concept imaging system based on a circular phased array is created, and imaging experiments of corner-reflector targets are performed in an anechoic chamber. The azimuthal image is reconstructed by the use of Fourier transform and spectral estimation methods. The azimuth resolution of the two methods is analyzed and compared through experimental data. The experimental results verify the principle of azimuth resolution and the proposed phase compensation method. PMID:28335487

Calibrated infrared ground/air radiometric spectrometer

NASA Astrophysics Data System (ADS)

Silk, J. K.; Schildkraut, Elliot Robert; Bauldree, Russell S.; Goodrich, Shawn M.

1996-06-01

The calibrated infrared ground/air radiometric spectrometer (CIGARS) is a new high performance, multi-purpose, multi- platform Fourier transform spectrometer (FPS) sensor. It covers the waveband from 0.2 to 12 micrometer, has spectral resolution as fine as 0.3 cm-1, and records over 100 spectra per second. Two CIGARS units are being used for observations of target signatures in the air or on the ground from fixed or moving platforms, including high performance jet aircraft. In this paper we describe the characteristics and capabilities of the CIGARS sensor, which uses four interchangeable detector modules (Si, InGaAs, InSb, and HgCdTe) and two optics modules, with internal calibration. The data recording electronics support observations of transient events, even without precise information on the timing of the event. We present test and calibration data on the sensitivity, spectral resolution, stability, and spectral rate of CIGARS, and examples of in- flight observations of real targets. We also discuss plans for adapting CIGARS for imaging spectroscopy observations, with simultaneous spectral and spatial data, by replacing the existing detectors with a focal plane array (FPA).

Characterization of Interfacial Chemistry of Adhesive/Dentin Bond Using FTIR Chemical Imaging With Univariate and Multivariate Data Processing

PubMed Central

Wang, Yong; Yao, Xiaomei; Parthasarathy, Ranganathan

2008-01-01

Fourier transform infrared (FTIR) chemical imaging can be used to investigate molecular chemical features of the adhesive/dentin interfaces. However, the information is not straightforward, and is not easily extracted. The objective of this study was to use multivariate analysis methods, principal component analysis and fuzzy c-means clustering, to analyze spectral data in comparison with univariate analysis. The spectral imaging data collected from both the adhesive/healthy dentin and adhesive/caries-affected dentin specimens were used and compared. The univariate statistical methods such as mapping of intensities of specific functional group do not always accurately identify functional group locations and concentrations due to more or less band overlapping in adhesive and dentin. Apart from the ease with which information can be extracted, multivariate methods highlight subtle and often important changes in the spectra that are difficult to observe using univariate methods. The results showed that the multivariate methods gave more satisfactory, interpretable results than univariate methods and were conclusive in showing that they can discriminate and classify differences between healthy dentin and caries-affected dentin within the interfacial regions. It is demonstrated that the multivariate FTIR imaging approaches can be used in the rapid characterization of heterogeneous, complex structure. PMID:18980198

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillion, D.

This code enables one to display, take line-outs on, and perform various transformations on an image created by an array of integer*2 data. Uncompressed eight-bit TIFF files created on either the Macintosh or the IBM PC may also be read in and converted to a 16 bit signed integer image. This code is designed to handle all the formates used for PDS (photo-densitometer) files at the Lawrence Livermore National Laboratory. These formats are all explained by the application code. The image may be zoomed infinitely and the gray scale mapping can be easily changed. Line-outs may be horizontal or verticalmore » with arbitrary width, angled with arbitrary end points, or taken along any path. This code is usually used to examine spectrograph data. Spectral lines may be identified and a polynomial fit from position to wavelength may be found. The image array can be remapped so that the pixels all have the same change of lambda width. It is not necessary to do this, however. Lineouts may be printed, saved as Cricket tab-delimited files, or saved as PICT2 files. The plots may be linear, semilog, or logarithmic with nice values and proper scientific notation. Typically, spectral lines are curved. By identifying points on these lines and fitting their shapes by polyn.« less

Combined use of quantitative ED-EPMA, Raman microspectrometry, and ATR-FTIR imaging techniques for the analysis of individual particles.

PubMed

Jung, Hae-Jin; Eom, Hyo-Jin; Kang, Hyun-Woo; Moreau, Myriam; Sobanska, Sophie; Ro, Chul-Un

2014-08-21

In this work, quantitative energy-dispersive electron probe X-ray microanalysis (ED-EPMA) (called low-Z particle EPMA), Raman microspectrometry (RMS), and attenuated total reflectance Fourier transform infrared spectroscopic (ATR-FTIR) imaging were applied in combination for the analysis of the same individual airborne particles for the first time. After examining individual particles of micrometer size by low-Z particle EPMA, consecutive examinations by RMS and ATR-FTIR imaging of the same individual particles were then performed. The relocation of the same particles on Al or Ag foils was successfully carried out among the three standalone instruments for several standard samples and an indoor airborne particle sample, resulting in the successful acquisition of quality spectral data from the three single-particle analytical techniques. The combined application of the three techniques to several different standard particles confirmed that those techniques provided consistent and complementary chemical composition information on the same individual particles. Further, it was clearly demonstrated that the three different types of spectral and imaging data from the same individual particles in an indoor aerosol sample provided richer information on physicochemical characteristics of the particle ensemble than that obtainable by the combined use of two single-particle analytical techniques.

Identification of coffee bean varieties using hyperspectral imaging: influence of preprocessing methods and pixel-wise spectra analysis.

PubMed

Zhang, Chu; Liu, Fei; He, Yong

2018-02-01

Hyperspectral imaging was used to identify and to visualize the coffee bean varieties. Spectral preprocessing of pixel-wise spectra was conducted by different methods, including moving average smoothing (MA), wavelet transform (WT) and empirical mode decomposition (EMD). Meanwhile, spatial preprocessing of the gray-scale image at each wavelength was conducted by median filter (MF). Support vector machine (SVM) models using full sample average spectra and pixel-wise spectra, and the selected optimal wavelengths by second derivative spectra all achieved classification accuracy over 80%. Primarily, the SVM models using pixel-wise spectra were used to predict the sample average spectra, and these models obtained over 80% of the classification accuracy. Secondly, the SVM models using sample average spectra were used to predict pixel-wise spectra, but achieved with lower than 50% of classification accuracy. The results indicated that WT and EMD were suitable for pixel-wise spectra preprocessing. The use of pixel-wise spectra could extend the calibration set, and resulted in the good prediction results for pixel-wise spectra and sample average spectra. The overall results indicated the effectiveness of using spectral preprocessing and the adoption of pixel-wise spectra. The results provided an alternative way of data processing for applications of hyperspectral imaging in food industry.

Prospects for the design of an ultraviolet imaging Fourier transform spectrometer

NASA Astrophysics Data System (ADS)

Lemaire, Philippe

2017-11-01

Recent results from solar observations in the far and extremeultraviolet (FUV/EUV) obtained from SOHO (SOlar and Heliospheric Observatory) and TRACE (Transition Region Camera) show the extreme variability of the solar atmosphere. Within the limited resolution of the instruments (1-2 arcseconds) horizontal and vertical velocities up-to 100 to 400 km s-1 have been measured. With an horizontal velocity of 100 km s-1 an one arsecond structure crosses the one arcsecond slit width of a classical slit spectrometer in less than 10 seconds. In the future, with higher angular resolution (e.g. 0.1 arcsecond), the capability to study small structures will be greatly reduced by a classical slit spectrometer. To be able to characterize the small scale solar atmospheric structures formed in the 104 K to 106 K temperature range (which emit in the 30 to 180 nm wavelength range) a spectrometer without slit (or with wide slit) is required. At the same time to obtain an accurate measurement of the doppler velocity an high spectral resolution is needed. The two requirements, high spectral resolution and large slit, are difficult to be simultaneously fulfilled with a classical slit spectrometer within the limited volume of a space instrumentation. Also, we propose to use an Imaging Fourier Transform Spectrometer (IFTS) to provide simultaneously a bidimensionnal field and an accurate determination of line profiles and positions. The development of Fourier Transform Spectrometers (FTS), although popular in the infrared, has been very limited in the UV/FUV by the lack of very high quality beam splitter. Since 10 years, the use of diffraction gratings as beam splitters has been suggested and few intruments have been built ([Chak 94]; [Clea 92]; [File 00]). These instruments illustrate some applications in the new wavelength domain opened by using a beam splitter grating, but do not yet provide the full capabilities of an FTS. In this paper we present several optical schemes which can provide the full capabilities of a complete IFTS in the FUV/EUV spectral range.

Digital algorithm for dispersion correction in optical coherence tomography for homogeneous and stratified media.

PubMed

Marks, Daniel L; Oldenburg, Amy L; Reynolds, J Joshua; Boppart, Stephen A

2003-01-10

The resolution of optical coherence tomography (OCT) often suffers from blurring caused by material dispersion. We present a numerical algorithm for computationally correcting the effect of material dispersion on OCT reflectance data for homogeneous and stratified media. This is experimentally demonstrated by correcting the image of a polydimethyl siloxane microfludic structure and of glass slides. The algorithm can be implemented using the fast Fourier transform. With broad spectral bandwidths and highly dispersive media or thick objects, dispersion correction becomes increasingly important.

Digital Algorithm for Dispersion Correction in Optical Coherence Tomography for Homogeneous and Stratified Media

NASA Astrophysics Data System (ADS)

Marks, Daniel L.; Oldenburg, Amy L.; Reynolds, J. Joshua; Boppart, Stephen A.

2003-01-01

The resolution of optical coherence tomography (OCT) often suffers from blurring caused by material dispersion. We present a numerical algorithm for computationally correcting the effect of material dispersion on OCT reflectance data for homogeneous and stratified media. This is experimentally demonstrated by correcting the image of a polydimethyl siloxane microfludic structure and of glass slides. The algorithm can be implemented using the fast Fourier transform. With broad spectral bandwidths and highly dispersive media or thick objects, dispersion correction becomes increasingly important.

A practical approach to spectral calibration of short wavelength infrared hyper-spectral imaging systems

NASA Astrophysics Data System (ADS)

Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2010-02-01

Near-infrared spectroscopy is a promising, rapidly developing, reliable and noninvasive technique, used extensively in the biomedicine and in pharmaceutical industry. With the introduction of acousto-optic tunable filters (AOTF) and highly sensitive InGaAs focal plane sensor arrays, real-time high resolution hyper-spectral imaging has become feasible for a number of new biomedical in vivo applications. However, due to the specificity of the AOTF technology and lack of spectral calibration standardization, maintaining long-term stability and compatibility of the acquired hyper-spectral images across different systems is still a challenging problem. Efficiently solving both is essential as the majority of methods for analysis of hyper-spectral images relay on a priori knowledge extracted from large spectral databases, serving as the basis for reliable qualitative or quantitative analysis of various biological samples. In this study, we propose and evaluate fast and reliable spectral calibration of hyper-spectral imaging systems in the short wavelength infrared spectral region. The proposed spectral calibration method is based on light sources or materials, exhibiting distinct spectral features, which enable robust non-rigid registration of the acquired spectra. The calibration accounts for all of the components of a typical hyper-spectral imaging system such as AOTF, light source, lens and optical fibers. The obtained results indicated that practical, fast and reliable spectral calibration of hyper-spectral imaging systems is possible, thereby assuring long-term stability and inter-system compatibility of the acquired hyper-spectral images.

Spectral analysis using CCDs

NASA Technical Reports Server (NTRS)

Hewes, C. R.; Brodersen, R. W.; De Wit, M.; Buss, D. D.

1976-01-01

Charge-coupled devices (CCDs) are ideally suited for performing sampled-data transversal filtering operations in the analog domain. Two algorithms have been identified for performing spectral analysis in which the bulk of the computation can be performed in a CCD transversal filter; the chirp z-transform and the prime transform. CCD implementation of both these transform algorithms is presented together with performance data and applications.

Standardized Digital Colposcopy with Dynamic Spectral Imaging for Conservative Patient Management.

PubMed

Kaufmann, Angelika; Founta, Christina; Papagiannakis, Emmanouil; Naik, Raj; Fisher, Ann

2017-01-01

Colposcopy is subjective and management of young patients with high-grade disease is challenging, as treatments may impair subsequent pregnancies and adversely affect obstetric outcomes. Conservative management of selected patients is becoming more popular amongst clinicians; however it requires accurate assessment and documentation. Novel adjunctive technologies for colposcopy could improve patient care and help individualize management decisions by introducing standardization, increasing sensitivity, and improving documentation. A nulliparous 27-year-old woman planning pregnancy underwent colposcopy following high-grade cytology. The colposcopic impression was of low-grade changes, whilst the Dynamic Spectral Imaging (DSI) map of the cervix suggested potential high-grade. A DSI-directed biopsy confirmed CIN2. At follow-up, both colposcopy and DSI were suggestive of low-grade disease only, and image comparison confirmed the absence of previously present acetowhite epithelium areas. Histology of the transformation zone following excisional treatment, as per patient's choice, showed no high-grade changes. Digital colposcopy with DSI mapping helps standardize colposcopic examinations, increase diagnostic accuracy, and monitor cervical changes over time, improving patient care. When used for longitudinal tracking of disease and when it confirms a negative colposcopy, it can help towards avoiding overtreatment and hence decrease morbidity related to cervical excision.

First imaging Fourier-transform spectral measurements of detonation in an internal combustion engine

NASA Astrophysics Data System (ADS)

Gross, Kevin C.; Borel, Chris; White, Allen; Sakai, Stephen; DeVasher, Rebecca; Perram, Glen P.

2010-08-01

The Telops Hyper-Cam midwave (InSb 1.5-5.5μm) imaging Fourier-transformspectrometer (IFTS) observed repeated detonations in an ethanol-powered internal combustion (IC) engine. The IC engine is aMegatech Corporation MEG 150 with a 1in. bore, 4in. stroke, and a compression ratio of 3 : 1. The IC combustion cylinder is made from sapphire permitting observation in the visible and infrared. From a distance of 3m, the IFTS imaged the combustion cylinder on a 64×32 pixel array with each pixel covering a 0.1×0.1cm2 area. More than 14,000 interferograms were collected at a rate of 16Hz. The maximum optical path difference of the interferograms was 0.017cm corresponding to an unapodized spectral resolution of 36cm-1. Engine speed was varied between 600-1200RPM to de-correlate the observation time scale from the occurrence of detonations. A method is devised to process the ensemble of interferograms which takes advantage of the DC component so that the time history of the combustion spectrum can be recovered at each pixel location. Preliminary results of this analysis will be presented.

A Fast Variant of 1H Spectroscopic U-FLARE Imaging Using Adjusted Chemical Shift Phase Encoding

NASA Astrophysics Data System (ADS)

Ebel, Andreas; Dreher, Wolfgang; Leibfritz, Dieter

2000-02-01

So far, fast spectroscopic imaging (SI) using the U-FLARE sequence has provided metabolic maps indirectly via Fourier transformation (FT) along the chemical shift (CS) dimension and subsequent peak integration. However, a large number of CS encoding steps Nω is needed to cover the spectral bandwidth and to achieve sufficient spectral resolution for peak integration even if the number of resonance lines is small compared to Nω and even if only metabolic images are of interest and not the spectra in each voxel. Other reconstruction algorithms require extensive prior knowledge, starting values, and/or model functions. An adjusted CS phase encoding scheme (APE) can be used to overcome these drawbacks. It incorporates prior knowledge only about the resonance frequencies present in the sample. Thus, Nω can be reduced by a factor of 4 for many 1H in vivo studies while no spectra have to be reconstructed, and no additional user interaction, prior knowledge, starting values, or model function are required. Phantom measurements and in vivo experiments on rat brain have been performed at 4.7 T to test the feasibility of the method for proton SI.

Signal processing in an acousto-optical spectral colorimeter

NASA Astrophysics Data System (ADS)

Emeljanov, Sergey P.; Kludzin, Victor V.; Kochin, Leonid B.; Medvedev, Sergey V.; Polosin, Lev L.; Sokolov, Vladimir K.

2002-02-01

The algorithms of spectrometer signals processing in the acousto-optical spectral colorimeter, proposed earlier are discussed. This processing is directional on distortion elimination of an optical system spectral characteristics and photoelectric transformations, and also for calculation of tristimulus coefficients X,Y,Z in an international colorimetric system of a CIE - 31 and transformation them in coordinates of recommended CIE uniform contrast systems LUV and LAB.

Oil Spill Detection along the Gulf of Mexico Coastline based on Airborne Imaging Spectrometer Data

NASA Astrophysics Data System (ADS)

Arslan, M. D.; Filippi, A. M.; Guneralp, I.

2013-12-01

The Deepwater Horizon oil spill in the Gulf of Mexico between April and July 2010 demonstrated the importance of synoptic oil-spill monitoring in coastal environments via remote-sensing methods. This study focuses on terrestrial oil-spill detection and thickness estimation based on hyperspectral images acquired along the coastline of the Gulf of Mexico. We use AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) imaging spectrometer data collected over Bay Jimmy and Wilkinson Bay within Barataria Bay, Louisiana, USA during September 2010. We also employ field-based observations of the degree of oil accumulation along the coastline, as well as in situ measurements from the literature. As part of our proposed spectroscopic approach, we operate on atmospherically- and geometrically-corrected hyperspectral AVIRIS data to extract image-derived endmembers via Minimum Noise Fraction transform, Pixel Purity Index-generation, and n-dimensional visualization. Extracted endmembers are then used as input to endmember-mapping algorithms to yield fractional-abundance images and crisp classification images. We also employ Multiple Endmember Spectral Mixture Analysis (MESMA) for oil detection and mapping in order to enable the number and types of endmembers to vary on a per-pixel basis, in contast to simple Spectral Mixture Analysis (SMA). MESMA thus better allows accounting for spectral variabiltiy of oil (e.g., due to varying oil thicknesses, states of degradation, and the presence of different oil types, etc.) and other materials, including soils and salt marsh vegetation of varying types, which may or may not be affected by the oil spill. A decision-tree approach is also utilized for comparison. Classification results do indicate that MESMA provides advantageous capabilities for mapping several oil-thickness classes for affected vegetation and soils along the Gulf of Mexico coastline, relative to the conventional approaches tested. Oil thickness-mapping results from MESMA and the decision tree demonstrate that such products can be accurately generated in complex coastal enviroments.

Beyond MOS and Fibers: Wide-FoV Imaging Fourier Transform Spectroscopy - an Instrumentation Proposal for the Present and Future Mexican Telescopes

NASA Astrophysics Data System (ADS)

Rosales-Ortega, F. F.; Castillo, E.; Sánchez, S. F.; Iglesias-Páramo, J.; Mollá, J. I. M.; Chávez, M.

2016-10-01

In order to extend the current suite of instruments offered in the Observatorio Astrofísico Guillermo Haro (OAGH) in Cananea, Mexico (INAOE), and to explore a second-generation instrument for the future 6.5 m Telescopio San Pedro Martir (TSPM), we propose a prototype instrument that will provide un-biased wide-field (few arcmin) spectroscopic information, with the flexibility of operating at different spectral resolutions (R˜1-104), with a spatial resolution limited by seeing, and therefore to be used in a wide range of astronomical problems. This instrument will make use of the Fourier Transform Spectroscopy technique, which has been proved to be feasible in the optical wavelength range. Here we give the basic technical description of a Fourier transform spectrograph, as well as the technical advantages and weaknesses, and the science cases in which this instrument can be implemented.

Digital techniques for ULF wave polarization analysis

NASA Technical Reports Server (NTRS)

Arthur, C. W.

1979-01-01

Digital power spectral and wave polarization analysis are powerful techniques for studying ULF waves in the earth's magnetosphere. Four different techniques for using the spectral matrix to perform such an analysis have been presented in the literature. Three of these techniques are similar in that they require transformation of the spectral matrix to the principal axis system prior to performing the polarization analysis. The differences in the three techniques lie in the manner in which determine this transformation. A comparative study of these three techniques using both simulated and real data has shown them to be approximately equal in quality of performance. The fourth technique does not require transformation of the spectral matrix. Rather, it uses the measured spectral matrix and state vectors for a desired wave type to design a polarization detector function in the frequency domain. The design of various detector functions and their application to both simulated and real data will be presented.

Gauge transformations for twisted spectral triples

NASA Astrophysics Data System (ADS)

Landi, Giovanni; Martinetti, Pierre

2018-05-01

It is extended to twisted spectral triples the fluctuations of the metric as bounded perturbations of the Dirac operator that arises when a spectral triple is exported between Morita equivalent algebras, as well as gauge transformations which are obtained by the action of the unitary endomorphisms of the module implementing the Morita equivalence. It is firstly shown that the twisted-gauged Dirac operators, previously introduced to generate an extra scalar field in the spectral description of the standard model of elementary particles, in fact follow from Morita equivalence between twisted spectral triples. The law of transformation of the gauge potentials turns out to be twisted in a natural way. In contrast with the non-twisted case, twisted fluctuations do not necessarily preserve the self-adjointness of the Dirac operator. For a self-Morita equivalence, conditions are obtained in order to maintain self-adjointness that are solved explicitly for the minimal twist of a Riemannian manifold.

The demodulated band transform

PubMed Central

Kovach, Christopher K.; Gander, Phillip E.

2016-01-01

Background Windowed Fourier decompositions (WFD) are widely used in measuring stationary and non-stationary spectral phenomena and in describing pairwise relationships among multiple signals. Although a variety of WFDs see frequent application in electrophysiological research, including the short-time Fourier transform, continuous wavelets, band-pass filtering and multitaper-based approaches, each carries certain drawbacks related to computational efficiency and spectral leakage. This work surveys the advantages of a WFD not previously applied in electrophysiological settings. New Methods A computationally efficient form of complex demodulation, the demodulated band transform (DBT), is described. Results DBT is shown to provide an efficient approach to spectral estimation with minimal susceptibility to spectral leakage. In addition, it lends itself well to adaptive filtering of non-stationary narrowband noise. Comparison with existing methods A detailed comparison with alternative WFDs is offered, with an emphasis on the relationship between DBT and Thomson's multitaper. DBT is shown to perform favorably in combining computational efficiency with minimal introduction of spectral leakage. Conclusion DBT is ideally suited to efficient estimation of both stationary and non-stationary spectral and cross-spectral statistics with minimal susceptibility to spectral leakage. These qualities are broadly desirable in many settings. PMID:26711370

Fast Fourier Transform Spectral Analysis Program

NASA Technical Reports Server (NTRS)

Daniel, J. A., Jr.; Graves, M. L.; Hovey, N. M.

1969-01-01

Fast Fourier Transform Spectral Analysis Program is used in frequency spectrum analysis of postflight, space vehicle telemetered trajectory data. This computer program with a digital algorithm can calculate power spectrum rms amplitudes and cross spectrum of sampled parameters at even time increments.

Detection of latent fingerprints by ultraviolet spectral imaging

NASA Astrophysics Data System (ADS)

Huang, Wei; Xu, Xiaojing; Wang, Guiqiang

2013-12-01

Spectral imaging technology research is becoming more popular in the field of forensic science. Ultraviolet spectral imaging technology is an especial part of the full spectrum of imaging technology. This paper finished the experiment contents of the ultraviolet spectrum imaging method and image acquisition system based on ultraviolet spectral imaging technology. Ultraviolet spectral imaging experiments explores a wide variety of ultraviolet reflectance spectra of the object material curve and its ultraviolet spectrum of imaging modalities, can not only gives a reference for choosing ultraviolet wavelength to show the object surface potential traces of substances, but also gives important data for the ultraviolet spectrum of imaging technology development.

MOVING BEYOND COLOR: THE CASE FOR MULTISPECTRAL IMAGING IN BRIGHTFIELD PATHOLOGY

PubMed Central

Cukierski, William J.; Qi, Xin; Foran, David J.

2009-01-01

A multispectral camera is capable of imaging a histologic slide at narrow bandwidths over the range of the visible spectrum. While several uses for multispectral imaging (MSI) have been demonstrated in pathology [1, 2], there is no unified consensus over when and how MSI might benefit automated analysis [3, 4]. In this work, we use a linear-algebra framework to investigate the relationship between the spectral image and its standard-image counterpart. The multispectral “cube” is treated as an extension of a traditional image in a high-dimensional color space. The concept of metamers is introduced and used to derive regions of the visible spectrum where MSI may provide an advantage. Furthermore, histological stains which are amenable to analysis by MSI are reported. We show the Commission internationale de l’éclairage (CIE) 1931 transformation from spectrum to color is non-neighborhood preserving. Empirical results are demonstrated on multispectral images of peripheral blood smears. PMID:19997528

Hyperspectral infrared nanoimaging of organic samples based on Fourier transform infrared nanospectroscopy

PubMed Central

Amenabar, Iban; Poly, Simon; Goikoetxea, Monika; Nuansing, Wiwat; Lasch, Peter; Hillenbrand, Rainer

2017-01-01

Infrared nanospectroscopy enables novel possibilities for chemical and structural analysis of nanocomposites, biomaterials or optoelectronic devices. Here we introduce hyperspectral infrared nanoimaging based on Fourier transform infrared nanospectroscopy with a tunable bandwidth-limited laser continuum. We describe the technical implementations and present hyperspectral infrared near-field images of about 5,000 pixel, each one covering the spectral range from 1,000 to 1,900 cm−1. To verify the technique and to demonstrate its application potential, we imaged a three-component polymer blend and a melanin granule in a human hair cross-section, and demonstrate that multivariate data analysis can be applied for extracting spatially resolved chemical information. Particularly, we demonstrate that distribution and chemical interaction between the polymer components can be mapped with a spatial resolution of about 30 nm. We foresee wide application potential of hyperspectral infrared nanoimaging for valuable chemical materials characterization and quality control in various fields ranging from materials sciences to biomedicine. PMID:28198384

Hyperspectral infrared nanoimaging of organic samples based on Fourier transform infrared nanospectroscopy

NASA Astrophysics Data System (ADS)

Amenabar, Iban; Poly, Simon; Goikoetxea, Monika; Nuansing, Wiwat; Lasch, Peter; Hillenbrand, Rainer

2017-02-01

Infrared nanospectroscopy enables novel possibilities for chemical and structural analysis of nanocomposites, biomaterials or optoelectronic devices. Here we introduce hyperspectral infrared nanoimaging based on Fourier transform infrared nanospectroscopy with a tunable bandwidth-limited laser continuum. We describe the technical implementations and present hyperspectral infrared near-field images of about 5,000 pixel, each one covering the spectral range from 1,000 to 1,900 cm-1. To verify the technique and to demonstrate its application potential, we imaged a three-component polymer blend and a melanin granule in a human hair cross-section, and demonstrate that multivariate data analysis can be applied for extracting spatially resolved chemical information. Particularly, we demonstrate that distribution and chemical interaction between the polymer components can be mapped with a spatial resolution of about 30 nm. We foresee wide application potential of hyperspectral infrared nanoimaging for valuable chemical materials characterization and quality control in various fields ranging from materials sciences to biomedicine.

Metric Learning for Hyperspectral Image Segmentation

NASA Technical Reports Server (NTRS)

Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

2011-01-01

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Fourier transform infrared spectroscopy imaging of live epithelial cancer cells under non-aqueous media.

PubMed

Soh, JunYi; Chueng, Adeline; Adio, Aminat; Cooper, Alan J; Birch, Brian R; Lwaleed, Bashir A

2013-04-01

Fourier transform infrared (FT-IR) imaging is increasingly being applied to biomedical specimens, but strong IR absorption by water complicates live cell imaging. This study investigates the viability of adherent epithelial cells maintained for short periods under mineral oils in order to facilitate live cell spectroscopy using FT-IR with subsequent imaging. The MGH-U1 urothelial or CaCo2 colorectal cancer cell lines were grown on plastic surfaces or mid-range infrared transparent windows. Medium in established cultures was replaced with paraffin mineral oil, or Fluorolube, for up to 2 h, and viability assessed by supravital staining. Drug handling characteristics were also assessed. Imaging of preparations was attempted by reflectance and transmission using a Varian FT-IR microscope. Cells covered by mineral oil remained viable for 2 h, with recovery into normal medium possible. MTT ((3-(4,5-dimethylthlazol-2-yl)-2,5-diphenyl tetrazolium) conversion to crystalline formazan and differential patterns of drug uptake were maintained. The combination of a calcium fluoride substrate, Fluorolube oil, and transmission optics proved best for spectroscopy. Spectral features were used to obtain images of live cells. The viability of cells overlaid with IR transparent oils was assessed as part of a technique to optimise conditions for FT-IR imaging. Images of untreated cells were obtained using both reflectance and transmission. This represents an effective means of imaging live cells by IR spectroscopy, and also means that imaging is not necessarily a terminal event. It also increases options for producing images based on real-time biochemistry in a range of in vitro experimental and 'optical biopsy' contexts.

Characterization of human oral tissues based on quantitative analysis of optical coherence tomography images

NASA Astrophysics Data System (ADS)

Salehi, Hassan S.; Kosa, Ali; Mahdian, Mina; Moslehpour, Saeid; Alnajjar, Hisham; Tadinada, Aditya

2017-02-01

In this paper, five types of tissues, human enamel, human cortical bone, human trabecular bone, muscular tissue, and fatty tissue were imaged ex vivo using optical coherence tomography (OCT). The specimens were prepared in blocks of 5 x 5 x 3 mm (width x length x height). The OCT imaging system was a swept source OCT system operating at wavelengths ranging between 1250 nm and 1360 nm with an average power of 18 mW and a scan rate of 50 to 100 kHz. The imaging probe was placed on top of a 2 x 2 cm stabilizing device to maintain a standard distance from the samples. Ten image samples from each type of tissue were obtained. To acquire images with minimum inhomogeneity, imaging was performed multiple times at different points. Based on the observed texture differences between OCT images of soft and hard tissues, spatial and spectral features were quantitatively extracted from the OCT images. The Radon transform from angles of 0 deg to 90 deg was computed, averaged over all the angles, normalized to peak at unity, and then fitted with Gaussian function. The mean absolute values of the spatial frequency components of the OCT image were considered as a feature, where 2-D fast Fourier transform (FFT) was done to OCT images. These OCT features can reliably differentiate between a range of hard and soft tissues, and could be extremely valuable in assisting dentists for in vivo evaluation of oral tissues and early detection of pathologic changes in tissues.

Four Forms of the Fourier Transform - for Freshmen, using Matlab

NASA Astrophysics Data System (ADS)

Simons, F. J.; Maloof, A. C.

2016-12-01

In 2015, a Fall "Freshman Seminar" at Princeton University (http://geoweb.princeton.edu/people/simons/FRS-SESC.html) taught students to combine field observations of the natural world with quantitative modeling and interpretation, to answer questions like: "How have Earth and human histories been recorded in the geology of Princeton, the Catskills, France and Spain?" (where we took the students on a data-gathering field trip during Fall Break), and "What experiments and analysis can a first-year (possibly non-future-major) do to query such archives of the past?" In the classroom, through problem sets, and around campus, students gained practical experience collecting geological and geophysical data in a geographic context, and analyzing these data using statistical techniques such as regression, time-series and image analysis, with the programming language Matlab. In this presentation I will detail how we instilled basic Matlab skills for quantitative geoscience data analysis through a 6-week progression of topics and exercises. In the 6 weeks after the Fall Break trip, we strengthened these competencies to make our students fully proficient for further learning, as evidenced by their end-of-term independent research work.The particular case study is focused on introducing power-spectral analysis to Freshmen, in a way that even the least quantitative among them could functionally understand. Not counting (0) "inspection", the four ways by which we have successfully instilled the concept of power-spectral analysis in a hands-on fashion are (1) "correlation", (2) "inversion", (3) "stacking", and formal (4) "Fourier transformation". These four provide the main "mappings". Along the way, of course, we also make sure that the students understand that "power-spectral density estimation" is not the same as "Fourier transformation", nor that every Fourier transform has to be "Fast". Hence, concepts from analysis-of-variance techniques, regression, and hypothesis testing, arise in this context, and will be discussed.

Airborne mapping of chemical plumes in the aftermath of Hurricanes Katrina and Rita

NASA Astrophysics Data System (ADS)

Lewis, Paul E.; Thomas, Mark J.; Kroutil, Robert T.; Combs, Roger; Cummings, Alan S.; Miller, Dave; Curry, Tim; Shen, Sylvia S.

2006-05-01

Infrared airborne spectral measurements were collected over the Gulf Coast area during the aftermath of Hurricanes Katrina and Rita. These measurements allowed surveillance for potentially hazardous chemical vapor releases from industrial facilities caused by storm damage. Data was collected with a mid-longwave infrared multispectral imager and a hyperspectral Fourier transform infrared spectrometer operating in a low altitude aircraft. Signal processing allowed detection and identification of targeted spectral signatures in the presence of interferents, atmospheric contributions, and thermal clutter. Results confirmed the presence of a number of chemical vapors. All detection results were immediately passed along to emergency first responders on the ground. The chemical identification, location, and vapor species concentration information were used by the emergency response ground teams for identification of critical plume releases and subsequent mitigation.

Recent progress of push-broom infrared hyper-spectral imager in SITP

NASA Astrophysics Data System (ADS)

Wang, Yueming; Hu, Weida; Shu, Rong; Li, Chunlai; Yuan, Liyin; Wang, Jianyu

2017-02-01

In the past decades, hyper-spectral imaging technologies were well developed in SITP, CAS. Many innovations for system design and key parts of hyper-spectral imager were finished. First airborne hyper-spectral imager operating from VNIR to TIR in the world was emerged in SITP. It is well known as OMIS(Operational Modular Imaging Spectrometer). Some new technologies were introduced to improve the performance of hyper-spectral imaging system in these years. A high spatial space-borne hyper-spectral imager aboard Tiangong-1 spacecraft was launched on Sep.29, 2011. Thanks for ground motion compensation and high optical efficiency prismatic spectrometer, a large amount of hyper-spectral imagery with high sensitivity and good quality were acquired in the past years. Some important phenomena were observed. To diminish spectral distortion and expand field of view, new type of prismatic imaging spectrometer based curved prism were proposed by SITP. A prototype of hyper-spectral imager based spherical fused silica prism were manufactured, which can operate from 400nm 2500nm. We also made progress in the development of LWIR hyper-spectral imaging technology. Compact and low F number LWIR imaging spectrometer was designed, manufactured and integrated. The spectrometer operated in a cryogenically-cooled vacuum box for background radiation restraint. The system performed well during flight experiment in an airborne platform. Thanks high sensitivity FPA and high performance optics, spatial resolution and spectral resolution and SNR of system are improved enormously. However, more work should be done for high radiometric accuracy in the future.

A Scattered Light Correction to Color Images Taken of Europa by the Galileo Spacecraft: Initial Results

NASA Astrophysics Data System (ADS)

Phillips, C. B.; Valenti, M.

2009-12-01

Jupiter's moon Europa likely possesses an ocean of liquid water beneath its icy surface, but estimates of the thickness of the surface ice shell vary from a few kilometers to tens of kilometers. Color images of Europa reveal the existence of a reddish, non-ice component associated with a variety of geological features. The composition and origin of this material is uncertain, as is its relationship to Europa's various landforms. Published analyses of Galileo Near Infrared Mapping Spectrometer (NIMS) observations indicate the presence of highly hydrated sulfate compounds. This non-ice material may also bear biosignatures or other signs of biotic material. Additional spectral information from the Galileo Solid State Imager (SSI) could further elucidate the nature of the surface deposits, particularly when combined with information from the NIMS. However, little effort has been focused on this approach because proper calibration of the color image data is challenging, requiring both skill and patience to process the data and incorporate the appropriate scattered light correction. We are currently working to properly calibrate the color SSI data. The most important and most difficult issue to address in the analysis of multispectral SSI data entails using thorough calibrations and a correction for scattered light. Early in the Galileo mission, studies of the Galileo SSI data for the moon revealed discrepancies of up to 10% in relative reflectance between images containing scattered light and images corrected for scattered light. Scattered light adds a wavelength-dependent low-intensity brightness factor to pixels across an image. For example, a large bright geological feature located just outside the field of view of an image will scatter extra light onto neighboring pixels within the field of view. Scattered light can be seen as a dim halo surrounding an image that includes a bright limb, and can also come from light scattered inside the camera by dirt, edges, and the interfaces of lenses. Because of the wavelength dependence of this effect, a scattered light correction must be performed on any SSI multispectral dataset before quantitative spectral analysis can be done. The process involves using a point-spread function for each filter that helps determine the amount of scattered light expected for a given pixel based on its location and the model attenuation factor for that pixel. To remove scattered light for a particular image taken through a particular filter, the Fourier transform of the attenuation function, which is the point spread function for that filter, is convolved with the Fourier transform of the image at the same wavelength. The result is then filtered for noise in the frequency domain, and then transformed back to the spatial domain. This results in a version of the original image that would have been taken without the scattered light contribution. We will report on our initial results from this calibration.

Integrating machine learning techniques and high-resolution imagery to generate GIS-ready information for urban water consumption studies

NASA Astrophysics Data System (ADS)

Wolf, Nils; Hof, Angela

2012-10-01

Urban sprawl driven by shifts in tourism development produces new suburban landscapes of water consumption on Mediterranean coasts. Golf courses, ornamental, 'Atlantic' gardens and swimming pools are the most striking artefacts of this transformation, threatening the local water supply systems and exacerbating water scarcity. In the face of climate change, urban landscape irrigation is becoming increasingly important from a resource management point of view. This paper adopts urban remote sensing towards a targeted mapping approach using machine learning techniques and highresolution satellite imagery (WorldView-2) to generate GIS-ready information for urban water consumption studies. Swimming pools, vegetation and - as a subgroup of vegetation - turf grass are extracted as important determinants of water consumption. For image analysis, the complex nature of urban environments suggests spatial-spectral classification, i.e. the complementary use of the spectral signature and spatial descriptors. Multiscale image segmentation provides means to extract the spatial descriptors - namely object feature layers - which can be concatenated at pixel level to the spectral signature. This study assesses the value of object features using different machine learning techniques and amounts of labeled information for learning. The results indicate the benefit of the spatial-spectral approach if combined with appropriate classifiers like tree-based ensembles or support vector machines, which can handle high dimensionality. Finally, a Random Forest classifier was chosen to deliver the classified input data for the estimation of evaporative water loss and net landscape irrigation requirements.

Platform for Postprocessing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Don

2008-01-01

Taking advantage of the similarities that exist among all waveform-based non-destructive evaluation (NDE) methods, a common software platform has been developed containing multiple- signal and image-processing techniques for waveforms and images. The NASA NDE Signal and Image Processing software has been developed using the latest versions of LabVIEW, and its associated Advanced Signal Processing and Vision Toolkits. The software is useable on a PC with Windows XP and Windows Vista. The software has been designed with a commercial grade interface in which two main windows, Waveform Window and Image Window, are displayed if the user chooses a waveform file to display. Within these two main windows, most actions are chosen through logically conceived run-time menus. The Waveform Window has plots for both the raw time-domain waves and their frequency- domain transformations (fast Fourier transform and power spectral density). The Image Window shows the C-scan image formed from information of the time-domain waveform (such as peak amplitude) or its frequency-domain transformation at each scan location. The user also has the ability to open an image, or series of images, or a simple set of X-Y paired data set in text format. Each of the Waveform and Image Windows contains menus from which to perform many user actions. An option exists to use raw waves obtained directly from scan, or waves after deconvolution if system wave response is provided. Two types of deconvolution, time-based subtraction or inverse-filter, can be performed to arrive at a deconvolved wave set. Additionally, the menu on the Waveform Window allows preprocessing of waveforms prior to image formation, scaling and display of waveforms, formation of different types of images (including non-standard types such as velocity), gating of portions of waves prior to image formation, and several other miscellaneous and specialized operations. The menu available on the Image Window allows many further image processing and analysis operations, some of which are found in commercially-available image-processing software programs (such as Adobe Photoshop), and some that are not (removing outliers, Bscan information, region-of-interest analysis, line profiles, and precision feature measurements).

Level 2 processing for the imaging Fourier transform spectrometer GLORIA: derivation and validation of temperature and trace gas volume mixing ratios from calibrated dynamics mode spectra

NASA Astrophysics Data System (ADS)

Ungermann, J.; Blank, J.; Dick, M.; Ebersoldt, A.; Friedl-Vallon, F.; Giez, A.; Guggenmoser, T.; Höpfner, M.; Jurkat, T.; Kaufmann, M.; Kaufmann, S.; Kleinert, A.; Krämer, M.; Latzko, T.; Oelhaf, H.; Olchewski, F.; Preusse, P.; Rolf, C.; Schillings, J.; Suminska-Ebersoldt, O.; Tan, V.; Thomas, N.; Voigt, C.; Zahn, A.; Zöger, M.; Riese, M.

2015-06-01

The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an airborne infrared limb imager combining a two-dimensional infrared detector with a Fourier transform spectrometer. It was operated aboard the new German Gulfstream G550 High Altitude LOng Range (HALO) research aircraft during the Transport And Composition in the upper Troposphere/lowermost Stratosphere (TACTS) and Earth System Model Validation (ESMVAL) campaigns in summer 2012. This paper describes the retrieval of temperature and trace gas (H2O, O3, HNO3) volume mixing ratios from GLORIA dynamics mode spectra that are spectrally sampled every 0.625 cm-1. A total of 26 integrated spectral windows are employed in a joint fit to retrieve seven targets using consecutively a fast and an accurate tabulated radiative transfer model. Typical diagnostic quantities are provided including effects of uncertainties in the calibration and horizontal resolution along the line of sight. Simultaneous in situ observations by the Basic Halo Measurement and Sensor System (BAHAMAS), the Fast In-situ Stratospheric Hygrometer (FISH), an ozone detector named Fairo, and the Atmospheric chemical Ionization Mass Spectrometer (AIMS) allow a validation of retrieved values for three flights in the upper troposphere/lowermost stratosphere region spanning polar and sub-tropical latitudes. A high correlation is achieved between the remote sensing and the in situ trace gas data, and discrepancies can to a large extent be attributed to differences in the probed air masses caused by different sampling characteristics of the instruments. This 1-D processing of GLORIA dynamics mode spectra provides the basis for future tomographic inversions from circular and linear flight paths to better understand selected dynamical processes of the upper troposphere and lowermost stratosphere.

Investigation of relations between skin cancer lesions' images and their fluorescent spectra

NASA Astrophysics Data System (ADS)

Pavlova, P.; Borisova, E.; Avramov, L.; Petkova, El.; Troyanova, P.

2010-03-01

This investigation is based on images obtained from healthy tissue and skin cancer lesions and their fluorescent spectra of cutaneous lesions derived after optical stimulation. Our analyses show that the lesions’ spectra of are different of those, obtained from normal tissue and the differences depend on the type of cancer. We use a comparison between these “healthy” and “unhealthy” spectra to define forms of variations and corresponding diseases. However, the value of the emitted light varies not only between the patients, but also depending on the position of the tested area inside of one lesion. These variations could be result from two reasons: different degree of damaging and different thickness of the suspicious lesion area. Regarded to the visible image of the lesion, it could be connected with the chroma of colour of the tested area and the lesion homogeneity that corresponds to particular disease. For our investigation, images and spectra of three non-melanoma cutanous malignant tumors are investigated, namely—basal cell carcinoma, squamous cell carcinoma, and keratoacanthoma. The images were processed obtaining the chroma by elimination of the background—healthy tissue, and applying it as a basic signal for transformation from RGB to Lab colorimetric model. The chroma of the areas of emission is compared with the relative value of fluorescence spectra. Specific spectral features are used to develop hybrid diagnostic algorithm (including image and spectral features) for differentiation of these three kinds of malignant cutaneous pathologies.

An Improved Variational Method for Hyperspectral Image Pansharpening with the Constraint of Spectral Difference Minimization

NASA Astrophysics Data System (ADS)

Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.

2017-09-01

Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.

Spectral imaging: principles and applications.

PubMed

Garini, Yuval; Young, Ian T; McNamara, George

2006-08-01

Spectral imaging extends the capabilities of biological and clinical studies to simultaneously study multiple features such as organelles and proteins qualitatively and quantitatively. Spectral imaging combines two well-known scientific methodologies, namely spectroscopy and imaging, to provide a new advantageous tool. The need to measure the spectrum at each point of the image requires combining dispersive optics with the more common imaging equipment, and introduces constrains as well. The principles of spectral imaging and a few representative applications are described. Spectral imaging analysis is necessary because the complex data structure cannot be analyzed visually. A few of the algorithms are discussed with emphasis on the usage for different experimental modes (fluorescence and bright field). Finally, spectral imaging, like any method, should be evaluated in light of its advantages to specific applications, a selection of which is described. Spectral imaging is a relatively new technique and its full potential is yet to be exploited. Nevertheless, several applications have already shown its potential. (c) 2006 International Society for Analytical Cytology.

Spectral mapping tools from the earth sciences applied to spectral microscopy data.

PubMed

Harris, A Thomas

2006-08-01

Spectral imaging, originating from the field of earth remote sensing, is a powerful tool that is being increasingly used in a wide variety of applications for material identification. Several workers have used techniques like linear spectral unmixing (LSU) to discriminate materials in images derived from spectral microscopy. However, many spectral analysis algorithms rely on assumptions that are often violated in microscopy applications. This study explores algorithms originally developed as improvements on early earth imaging techniques that can be easily translated for use with spectral microscopy. To best demonstrate the application of earth remote sensing spectral analysis tools to spectral microscopy data, earth imaging software was used to analyze data acquired with a Leica confocal microscope with mechanical spectral scanning. For this study, spectral training signatures (often referred to as endmembers) were selected with the ENVI (ITT Visual Information Solutions, Boulder, CO) "spectral hourglass" processing flow, a series of tools that use the spectrally over-determined nature of hyperspectral data to find the most spectrally pure (or spectrally unique) pixels within the data set. This set of endmember signatures was then used in the full range of mapping algorithms available in ENVI to determine locations, and in some cases subpixel abundances of endmembers. Mapping and abundance images showed a broad agreement between the spectral analysis algorithms, supported through visual assessment of output classification images and through statistical analysis of the distribution of pixels within each endmember class. The powerful spectral analysis algorithms available in COTS software, the result of decades of research in earth imaging, are easily translated to new sources of spectral data. Although the scale between earth imagery and spectral microscopy is radically different, the problem is the same: mapping material locations and abundances based on unique spectral signatures. (c) 2006 International Society for Analytical Cytology.

Research on the principle and experimentation of optical compressive spectral imaging

NASA Astrophysics Data System (ADS)

Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Ji, Yiqun; Shen, Weimin

2013-12-01

The optical compressive spectral imaging method is a novel spectral imaging technique that draws in the inspiration of compressed sensing, which takes on the advantages such as reducing acquisition data amount, realizing snapshot imaging, increasing signal to noise ratio and so on. Considering the influence of the sampling quality on the ultimate imaging quality, researchers match the sampling interval with the modulation interval in former reported imaging system, while the depressed sampling rate leads to the loss on the original spectral resolution. To overcome that technical defect, the demand for the matching between the sampling interval and the modulation interval is disposed of and the spectral channel number of the designed experimental device increases more than threefold comparing to that of the previous method. Imaging experiment is carried out by use of the experiment installation and the spectral data cube of the shooting target is reconstructed with the acquired compressed image by use of the two-step iterative shrinkage/thresholding algorithms. The experimental result indicates that the spectral channel number increases effectively and the reconstructed data stays high-fidelity. The images and spectral curves are able to accurately reflect the spatial and spectral character of the target.

Fast Imaging Detector Readout Circuits with In-Pixel ADCs for Fourier Transform Imaging Spectrometers

NASA Technical Reports Server (NTRS)

Rider, D.; Blavier, J-F.; Cunningham, T.; Hancock, B.; Key, R.; Pannell, Z.; Sander, S.; Seshadri, S.; Sun, C.; Wrigley, C.

2011-01-01

Focal plane arrays (FPAs) with high frame rates and many pixels benefit several upcoming Earth science missions including GEO-CAPE, GACM, and ACE by enabling broader spatial coverage and higher spectral resolution. FPAs for the PanFTS, a high spatial resolution Fourier transform spectrometer and a candidate instrument for the GEO-CAPE mission are the focus of the developments reported here, but this FPA technology has the potential to enable a variety of future measurements and instruments. The ESTO ACT Program funded the developed of a fast readout integrated circuit (ROIC) based on an innovative in-pixel analog-to-digital converter (ADC). The 128 X 128 pixel ROIC features 60 ?m pixels, a 14-bit ADC in each pixel and operates at a continuous frame rate of 14 kHz consuming only 1.1 W of power. The ROIC outputs digitized data completely eliminating the bulky, power consuming signal chains needed by conventional FPAs. The 128 X 128 pixel ROIC has been fabricated in CMOS and tested at the Jet Propulsion Laboratory. The current version is designed to be hybridized with PIN photodiode arrays via indium bump bonding for light detection in the visible and ultraviolet spectral regions. However, the ROIC design incorporates a small photodiode in each cell to permit detailed characterization of the ROICperformance without the need for hybridization. We will describe the essential features of the ROIC design and present results of ROIC performance measurements.

"Relative CIR": an image enhancement and visualization technique

USGS Publications Warehouse

Fleming, Michael D.

1993-01-01

Many techniques exist to spectrally and spatially enhance digital multispectral scanner data. One technique enhances an image while keeping the colors as they would appear in a color-infrared (CIR) image. This "relative CIR" technique generates an image that is both spectrally and spatially enhanced, while displaying a maximum range of colors. The technique enables an interpreter to visualize either spectral or land cover classes by their relative CIR characteristics. A relative CIR image is generated by developed spectral statistics for each class in the classifications and then, using a nonparametric approach for spectral enhancement, the means of the classes for each band are ranked. A 3 by 3 pixel smoothing filter is applied to the classification for spatial enhancement and the classes are mapped to the representative rank for each band. Practical applications of the technique include displaying an image classification product as a CIR image that was not derived directly from a spectral image, visualizing how a land cover classification would look as a CIR image, and displaying a spectral classification or intermediate product that will be used to label spectral classes.

Slit Function Measurement of An Imaging Spectrograph Using Fourier Transform Techniques

NASA Technical Reports Server (NTRS)

Park, Hongwoo; Swimyard, Bruce; Jakobsen, Peter; Moseley, Harvey; Greenhouse, Matthew

2004-01-01

Knowledge of a spectrograph slit function is necessary to interpret the unresolved lines in an observed spectrum. A theoretical slit function can be calculated from the sizes of the entrance slit, the detector aperture when it functions as an exit slit, the dispersion characteristic of the disperser, and the point spread function of the spectrograph. A measured slit function is preferred to the theoretical one for the correct interpretation of the spectral data. In a scanning spectrometer with a single exit slit, the slit function is easily measured. In a fixed grating/or disperser spectrograph, illuminating the entrance slit with a near monochromatic light from a pre-monochrmator or a tunable laser and varying the wavelength of the incident light can measure the slit function. Even though the latter technique had been used successfully for the slit function measurements, it had been very laborious and it would be prohibitive to an imaging spectrograph or a multi-object spectrograph that has a large field of view. We explore an alternative technique that is manageable for the measurements. In the proposed technique, the imaging spectrograph is used as a detector of a Fourier transform spectrometer. This method can be applied not only to an IR spectrograph but also has a potential to a visible/UV spectrograph including a wedge filter spectrograph. This technique will require a blackbody source of known temperature and a bolometer to characterize the interferometer part of the Fourier Transform spectrometer. This pa?er will describe the alternative slit function measurement technique using a Fourier transform spectrometer.

Remote sensing of soil organic matter of farmland with hyperspectral image

NASA Astrophysics Data System (ADS)

Gu, Xiaohe; Wang, Lei; Yang, Guijun; Zhang, Liyan

2017-10-01

Monitoring soil organic matter (SOM) of cultivated land quantitively and mastering its spatial change are helpful for fertility adjustment and sustainable development of agriculture. The study aimed to analyze the response between SOM and reflectivity of hyperspectral image with different pixel size and develop the optimal model of estimating SOM with imaging spectral technology. The wavelet transform method was used to analyze the correlation between the hyperspectral reflectivity and SOM. Then the optimal pixel size and sensitive wavelet feature scale were screened to develop the inversion model of SOM. Result showed that wavelet transform of soil hyperspectrum was help to improve the correlation between the wavelet features and SOM. In the visible wavelength range, the susceptible wavelet features of SOM mainly concentrated 460 603 nm. As the wavelength increased, the wavelet scale corresponding correlation coefficient increased maximum and then gradually decreased. In the near infrared wavelength range, the susceptible wavelet features of SOM mainly concentrated 762 882 nm. As the wavelength increased, the wavelet scale gradually decreased. The study developed multivariate model of continuous wavelet transforms by the method of stepwise linear regression (SLR). The CWT-SLR models reached higher accuracies than those of univariate models. With the resampling scale increasing, the accuracies of CWT-SLR models gradually increased, while the determination coefficients (R2) fluctuated from 0.52 to 0.59. The R2 of 5*5 scale reached highest (0.5954), while the RMSE reached lowest (2.41 g/kg). It indicated that multivariate model based on continuous wavelet transform had better ability for estimating SOM than univariate model.

The Stellar Imager (SI) Project: Resolving Stellar Surfaces, Interiors, and Magnetic Activity

NASA Technical Reports Server (NTRS)

Carpenter, Kenneth G.; Schrijver, K.; Karovska, M.

2007-01-01

The Stellar Imager (SI) is a UV/Optical. Space-Based Interferometer designed to enable 0.1 milli-arcsec (mas) spectral imaging of stellar surfaces and, via asteroseismology, stellar interiors and of the Universe in general. The ultra-sharp images of SI will revolutionize our view of many dynamic astrophysical processes by transforming point sources into extended sources, and snapshots into evolving views. The science of SI focuses on the role of magnetism in the Universe, particularly on magnetic activity on the surfaces of stars like the Sun. Its prime goal is to enable long-term forecasting of solar activity and the space weather that it drives. SI will also revolutionize our understanding of the formation of planetary systems, of the habitability and climatology of distant planets, and of many magneto-hydrodynamically controlled processes in the Universe. In this paper we discuss the science goals, technology needs, and baseline design of the SI mission.

Colors of the Sublunar

PubMed Central

van Doorn, Andrea

2017-01-01

Generic red, green, and blue images can be regarded as data sources of coarse (three bins) local spectra, typical data volumes are 104 to 107 spectra. Image data bases often yield hundreds or thousands of images, yielding data sources of 109 to 1010 spectra. There is usually no calibration, and there often are various nonlinear image transformations involved. However, we argue that sheer numbers make up for such ambiguity. We propose a model of spectral data mining that applies to the sublunar realm, spectra due to the scattering of daylight by objects from the generic terrestrial environment. The model involves colorimetry and ecological physics. Whereas the colorimetry is readily dealt with, one needs to handle the ecological physics with heuristic methods. The results suggest evolutionary causes of the human visual system. We also suggest effective methods to generate red, green, and blue color gamuts for various terrains. PMID:28989697

Review of spectral imaging technology in biomedical engineering: achievements and challenges.

PubMed

Li, Qingli; He, Xiaofu; Wang, Yiting; Liu, Hongying; Xu, Dongrong; Guo, Fangmin

2013-10-01

Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.

Integrated Spectral Low Noise Image Sensor with Nanowire Polarization Filters for Low Contrast Imaging

DTIC Science & Technology

2015-11-05

AFRL-AFOSR-VA-TR-2015-0359 Integrated Spectral Low Noise Image Sensor with Nanowire Polarization Filters for Low Contrast Imaging Viktor Gruev...To) 02/15/2011 - 08/15/2015 4. TITLE AND SUBTITLE Integrated Spectral Low Noise Image Sensor with Nanowire Polarization Filters for Low Contrast...investigate alternative spectral imaging architectures based on my previous experience in this research area. I will develop nanowire polarization

Localization of polyhydroxybutyrate in sugarcane using Fourier-transform infrared microspectroscopy and multivariate imaging

DOE PAGES

Lupoi, Jason S.; Smith-Moritz, Andreia; Singh, Seema; ...

2015-07-10

Background: Slow-degrading, fossil fuel-derived plastics can have deleterious effects on the environment, especially marine ecosystems. The production of bio-based, biodegradable plastics from or in plants can assist in supplanting those manufactured using fossil fuels. Polyhydroxybutyrate (PHB) is one such biodegradable polyester that has been evaluated as a possible candidate for relinquishing the use of environmentally harmful plastics. Results: PHB, possessing similar properties to polyesters produced from non-renewable sources, has been previously engineered in sugarcane, thereby creating a high-value co-product in addition to the high biomass yield. This manuscript illustrates the coupling of a Fourier-transform infrared microspectrometer, equipped with a focalmore » plane array (FPA) detector, with multivariate imaging to successfully identify and localize PHB aggregates. Principal component analysis imaging facilitated the mining of the abundant quantity of spectral data acquired using the FPA for distinct PHB vibrational modes. PHB was measured in the chloroplasts of mesophyll and bundle sheath cells, acquiescent with previously evaluated plant samples. Conclusion: This study demonstrates the power of IR microspectroscopy to rapidly image plant sections to provide a snapshot of the chemical composition of the cell. While PHB was localized in sugarcane, this method is readily transferable to other value-added co-products in different plants.« less

Localization of polyhydroxybutyrate in sugarcane using Fourier-transform infrared microspectroscopy and multivariate imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lupoi, Jason S.; Smith-Moritz, Andreia; Singh, Seema

Background: Slow-degrading, fossil fuel-derived plastics can have deleterious effects on the environment, especially marine ecosystems. The production of bio-based, biodegradable plastics from or in plants can assist in supplanting those manufactured using fossil fuels. Polyhydroxybutyrate (PHB) is one such biodegradable polyester that has been evaluated as a possible candidate for relinquishing the use of environmentally harmful plastics. Results: PHB, possessing similar properties to polyesters produced from non-renewable sources, has been previously engineered in sugarcane, thereby creating a high-value co-product in addition to the high biomass yield. This manuscript illustrates the coupling of a Fourier-transform infrared microspectrometer, equipped with a focalmore » plane array (FPA) detector, with multivariate imaging to successfully identify and localize PHB aggregates. Principal component analysis imaging facilitated the mining of the abundant quantity of spectral data acquired using the FPA for distinct PHB vibrational modes. PHB was measured in the chloroplasts of mesophyll and bundle sheath cells, acquiescent with previously evaluated plant samples. Conclusion: This study demonstrates the power of IR microspectroscopy to rapidly image plant sections to provide a snapshot of the chemical composition of the cell. While PHB was localized in sugarcane, this method is readily transferable to other value-added co-products in different plants.« less

Classification algorithm of ovarian tissue based on co-registered ultrasound and photoacoustic tomography

NASA Astrophysics Data System (ADS)

Li, Hai; Kumavor, Patrick D.; Alqasemi, Umar; Zhu, Quing

2014-03-01

Human ovarian tissue features extracted from photoacoustic spectra data, beam envelopes and co-registered ultrasound and photoacoustic images are used to characterize cancerous vs. normal processes using a support vector machine (SVM) classifier. The centers of suspicious tumor areas are estimated from the Gaussian fitting of the mean Radon transforms of the photoacoustic image along 0 and 90 degrees. Normalized power spectra are calculated using the Fourier transform of the photoacoustic beamformed data across these suspicious areas, where the spectral slope and 0-MHz intercepts are extracted. Image statistics, envelope histogram fitting and maximum output of 6 composite filters of cancerous or normal patterns along with other previously used features are calculated to compose a total of 17 features. These features are extracted from 169 datasets of 19 ex vivo ovaries. Half of the cancerous and normal datasets are randomly chosen to train a SVM classifier with polynomial kernel and the remainder is used for testing. With 50 times data resampling, the SVM classifier, for the training group, gives 100% sensitivity and 100% specificity. For the testing group, it gives 89.68+/- 6.37% sensitivity and 93.16+/- 3.70% specificity. These results are superior to those obtained earlier by our group using features extracted from photoacoustic raw data or image statistics only.

Image Stability Requirements For a Geostationary Imaging Fourier Transform Spectrometer (GIFTS)

NASA Technical Reports Server (NTRS)

Bingham, G. E.; Cantwell, G.; Robinson, R. C.; Revercomb, H. E.; Smith, W. L.

2001-01-01

A Geostationary Imaging Fourier Transform Spectrometer (GIFTS) has been selected for the NASA New Millennium Program (NMP) Earth Observing-3 (EO-3) mission. Our paper will discuss one of the key GIFTS measurement requirements, Field of View (FOV) stability, and its impact on required system performance. The GIFTS NMP mission is designed to demonstrate new and emerging sensor and data processing technologies with the goal of making revolutionary improvements in meteorological observational capability and forecasting accuracy. The GIFTS payload is a versatile imaging FTS with programmable spectral resolution and spatial scene selection that allows radiometric accuracy and atmospheric sounding precision to be traded in near real time for area coverage. The GIFTS sensor combines high sensitivity with a massively parallel spatial data collection scheme to allow high spatial resolution measurement of the Earth's atmosphere and rapid broad area coverage. An objective of the GIFTS mission is to demonstrate the advantages of high spatial resolution (4 km ground sample distance - gsd) on temperature and water vapor retrieval by allowing sampling in broken cloud regions. This small gsd, combined with the relatively long scan time required (approximately 10 s) to collect high resolution spectra from geostationary (GEO) orbit, may require extremely good pointing control. This paper discusses the analysis of this requirement.

Comparison of Background Parenchymal Enhancement at Contrast-enhanced Spectral Mammography and Breast MR Imaging.

PubMed

Sogani, Julie; Morris, Elizabeth A; Kaplan, Jennifer B; D'Alessio, Donna; Goldman, Debra; Moskowitz, Chaya S; Jochelson, Maxine S

2017-01-01

Purpose To assess the extent of background parenchymal enhancement (BPE) at contrast material-enhanced (CE) spectral mammography and breast magnetic resonance (MR) imaging, to evaluate interreader agreement in BPE assessment, and to examine the relationships between clinical factors and BPE. Materials and Methods This was a retrospective, institutional review board-approved, HIPAA-compliant study. Two hundred seventy-eight women from 25 to 76 years of age with increased breast cancer risk who underwent CE spectral mammography and MR imaging for screening or staging from 2010 through 2014 were included. Three readers independently rated BPE on CE spectral mammographic and MR images with the ordinal scale: minimal, mild, moderate, or marked. To assess pairwise agreement between BPE levels on CE spectral mammographic and MR images and among readers, weighted κ coefficients with quadratic weights were calculated. For overall agreement, mean κ values and bootstrapped 95% confidence intervals were calculated. The univariate and multivariate associations between BPE and clinical factors were examined by using generalized estimating equations separately for CE spectral mammography and MR imaging. Results Most women had minimal or mild BPE at both CE spectral mammography (68%-76%) and MR imaging (69%-76%). Between CE spectral mammography and MR imaging, the intrareader agreement ranged from moderate to substantial (κ = 0.55-0.67). Overall agreement on BPE levels between CE spectral mammography and MR imaging and among readers was substantial (κ = 0.66; 95% confidence interval: 0.61, 0.70). With both modalities, BPE demonstrated significant association with menopausal status, prior breast radiation therapy, hormonal treatment, breast density on CE spectral mammographic images, and amount of fibroglandular tissue on MR images (P < .001 for all). Conclusion There was substantial agreement between readers for BPE detected on CE spectral mammographic and MR images. © RSNA, 2016.

Feasibility study of a novel miniaturized spectral imaging system architecture in UAV surveillance

NASA Astrophysics Data System (ADS)

Liu, Shuyang; Zhou, Tao; Jia, Xiaodong; Cui, Hushan; Huang, Chengjun

2016-01-01

The spectral imaging technology is able to analysis the spectral and spatial geometric character of the target at the same time. To break through the limitation brought by the size, weight and cost of the traditional spectral imaging instrument, a miniaturized novel spectral imaging based on CMOS processing has been introduced in the market. This technology has enabled the possibility of applying spectral imaging in the UAV platform. In this paper, the relevant technology and the related possible applications have been presented to implement a quick, flexible and more detailed remote sensing system.

Spectral Properties and Dynamics of Gold Nanorods Revealed by EMCCD Based Spectral-Phasor Method

PubMed Central

Chen, Hongtao; Digman, Michelle A.

2015-01-01

Gold nanorods (NRs) with tunable plasmon-resonant absorption in the near-infrared region have considerable advantages over organic fluorophores as imaging agents. However, the luminescence spectral properties of NRs have not been fully explored at the single particle level in bulk due to lack of proper analytic tools. Here we present a global spectral phasor analysis method which allows investigations of NRs' spectra at single particle level with their statistic behavior and spatial information during imaging. The wide phasor distribution obtained by the spectral phasor analysis indicates spectra of NRs are different from particle to particle. NRs with different spectra can be identified graphically in corresponding spatial images with high spectral resolution. Furthermore, spectral behaviors of NRs under different imaging conditions, e.g. different excitation powers and wavelengths, were carefully examined by our laser-scanning multiphoton microscope with spectral imaging capability. Our results prove that the spectral phasor method is an easy and efficient tool in hyper-spectral imaging analysis to unravel subtle changes of the emission spectrum. Moreover, we applied this method to study the spectral dynamics of NRs during direct optical trapping and by optothermal trapping. Interestingly, spectral shifts were observed in both trapping phenomena. PMID:25684346

Detection and classification of salmonella serotypes using spectral signatures collected by fourier transform infrared (FT-IR) spectroscopy

USDA-ARS?s Scientific Manuscript database

Spectral signatures of Salmonella serotypes namely Salmonella Typhimurium, Salmonella Enteritidis, Salmonella Infantis, Salmonella Heidelberg and Salmonella Kentucky were collected using Fourier transform infrared spectroscopy (FT-IR). About 5-10 µL of Salmonella suspensions with concentrations of 1...

Nonsubsampled rotated complex wavelet transform (NSRCxWT) for medical image fusion related to clinical aspects in neurocysticercosis.

PubMed

Chavan, Satishkumar S; Mahajan, Abhishek; Talbar, Sanjay N; Desai, Subhash; Thakur, Meenakshi; D'cruz, Anil

2017-02-01

Neurocysticercosis (NCC) is a parasite infection caused by the tapeworm Taenia solium in its larvae stage which affects the central nervous system of the human body (a definite host). It results in the formation of multiple lesions in the brain at different locations during its various stages. During diagnosis of such symptomatic patients, these lesions can be better visualized using a feature based fusion of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). This paper presents a novel approach to Multimodality Medical Image Fusion (MMIF) used for the analysis of the lesions for the diagnostic purpose and post treatment review of NCC. The MMIF presented here is a technique of combining CT and MRI data of the same patient into a new slice using a Nonsubsampled Rotated Complex Wavelet Transform (NSRCxWT). The forward NSRCxWT is applied on both the source modalities separately to extract the complementary and the edge related features. These features are then combined to form a composite spectral plane using average and maximum value selection fusion rules. The inverse transformation on this composite plane results into a new, visually better, and enriched fused image. The proposed technique is tested on the pilot study data sets of patients infected with NCC. The quality of these fused images is measured using objective and subjective evaluation metrics. Objective evaluation is performed by estimating the fusion parameters like entropy, fusion factor, image quality index, edge quality measure, mean structural similarity index measure, etc. The fused images are also evaluated for their visual quality using subjective analysis with the help of three expert radiologists. The experimental results on 43 image data sets of 17 patients are promising and superior when compared with the state of the art wavelet based fusion algorithms. The proposed algorithm can be a part of computer-aided detection and diagnosis (CADD) system which assists the radiologists in clinical practices. Copyright © 2016 Elsevier Ltd. All rights reserved.

Miniature Compressive Ultra-spectral Imaging System Utilizing a Single Liquid Crystal Phase Retarder

NASA Astrophysics Data System (ADS)

August, Isaac; Oiknine, Yaniv; Abuleil, Marwan; Abdulhalim, Ibrahim; Stern, Adrian

2016-03-01

Spectroscopic imaging has been proved to be an effective tool for many applications in a variety of fields, such as biology, medicine, agriculture, remote sensing and industrial process inspection. However, due to the demand for high spectral and spatial resolution it became extremely challenging to design and implement such systems in a miniaturized and cost effective manner. Using a Compressive Sensing (CS) setup based on a single variable Liquid Crystal (LC) retarder and a sensor array, we present an innovative Miniature Ultra-Spectral Imaging (MUSI) system. The LC retarder acts as a compact wide band spectral modulator. Within the framework of CS, a sequence of spectrally modulated images is used to recover ultra-spectral image cubes. Using the presented compressive MUSI system, we demonstrate the reconstruction of gigapixel spatio-spectral image cubes from spectral scanning shots numbering an order of magnitude less than would be required using conventional systems.

Spectral imaging of neurosurgical target tissues through operation microscope

NASA Astrophysics Data System (ADS)

Antikainen, Jukka; von Und Zu Fraunberg, Mikael; Orava, Joni; Jaaskelainen, Juha E.; Hauta-Kasari, Markku

2011-11-01

It has been noticed that spectral information can be used for analyzing and separating different biological tissues. However, most of the studies for spectral image acquisitions are mainly done in vitro. Usually the main restrictions for in vivo measurements are the size or the weight of the spectral camera. If the camera weights too much, the surgery microscope cannot be stabilized. If the size of the camera is too big, it will disturb the surgeon or even risk the safety of the patient. The main goal of this study was to develop an independent spectral imaging device which can be used for collecting spectral information from the neurosurgeries without any previously described restrictions. Size of the imaging system is small enough not to disturb the surgeon during the surgery. The developed spectral imaging system is used for collecting a spectral database which can be used for the future imaging systems.

Miniature Compressive Ultra-spectral Imaging System Utilizing a Single Liquid Crystal Phase Retarder.

PubMed

August, Isaac; Oiknine, Yaniv; AbuLeil, Marwan; Abdulhalim, Ibrahim; Stern, Adrian

2016-03-23

Spectroscopic imaging has been proved to be an effective tool for many applications in a variety of fields, such as biology, medicine, agriculture, remote sensing and industrial process inspection. However, due to the demand for high spectral and spatial resolution it became extremely challenging to design and implement such systems in a miniaturized and cost effective manner. Using a Compressive Sensing (CS) setup based on a single variable Liquid Crystal (LC) retarder and a sensor array, we present an innovative Miniature Ultra-Spectral Imaging (MUSI) system. The LC retarder acts as a compact wide band spectral modulator. Within the framework of CS, a sequence of spectrally modulated images is used to recover ultra-spectral image cubes. Using the presented compressive MUSI system, we demonstrate the reconstruction of gigapixel spatio-spectral image cubes from spectral scanning shots numbering an order of magnitude less than would be required using conventional systems.

Miniaturized imaging spectrometer based on Fabry-Perot MOEMS filters and HgCdTe infrared focal plane arrays

NASA Astrophysics Data System (ADS)

Velicu, S.; Buurma, C.; Bergeson, J. D.; Kim, Tae Sung; Kubby, J.; Gupta, N.

2014-05-01

Imaging spectrometry can be utilized in the midwave infrared (MWIR) and long wave infrared (LWIR) bands to detect, identify and map complex chemical agents based on their rotational and vibrational emission spectra. Hyperspectral datasets are typically obtained using grating or Fourier transform spectrometers to separate the incoming light into spectral bands. At present, these spectrometers are large, cumbersome, slow and expensive, and their resolution is limited by bulky mechanical components such as mirrors and gratings. As such, low-cost, miniaturized imaging spectrometers are of great interest. Microfabrication of micro-electro-mechanicalsystems (MEMS)-based components opens the door for producing low-cost, reliable optical systems. We present here our work on developing a miniaturized IR imaging spectrometer by coupling a mercury cadmium telluride (HgCdTe)-based infrared focal plane array (FPA) with a MEMS-based Fabry-Perot filter (FPF). The two membranes are fabricated from silicon-oninsulator (SOI) wafers using bulk micromachining technology. The fixed membrane is a standard silicon membrane, fabricated using back etching processes. The movable membrane is implemented as an X-beam structure to improve mechanical stability. The geometries of the distributed Bragg reflector (DBR)-based tunable FPFs are modeled to achieve the desired spectral resolution and wavelength range. Additionally, acceptable fabrication tolerances are determined by modeling the spectral performance of the FPFs as a function of DBR surface roughness and membrane curvature. These fabrication non-idealities are then mitigated by developing an optimized DBR process flow yielding high-performance FPF cavities. Zinc Sulfide (ZnS) and Germanium (Ge) are chosen as the low and the high index materials, respectively, and are deposited using an electron beam process. Simulations are presented showing the impact of these changes and non-idealities in both a device and systems level.

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

Efficient hyperspectral image segmentation using geometric active contour formulation

NASA Astrophysics Data System (ADS)

Albalooshi, Fatema A.; Sidike, Paheding; Asari, Vijayan K.

2014-10-01

In this paper, we present a new formulation of geometric active contours that embeds the local hyperspectral image information for an accurate object region and boundary extraction. We exploit self-organizing map (SOM) unsupervised neural network to train our model. The segmentation process is achieved by the construction of a level set cost functional, in which, the dynamic variable is the best matching unit (BMU) coming from SOM map. In addition, we use Gaussian filtering to discipline the deviation of the level set functional from a signed distance function and this actually helps to get rid of the re-initialization step that is computationally expensive. By using the properties of the collective computational ability and energy convergence capability of the active control models (ACM) energy functional, our method optimizes the geometric ACM energy functional with lower computational time and smoother level set function. The proposed algorithm starts with feature extraction from raw hyperspectral images. In this step, the principal component analysis (PCA) transformation is employed, and this actually helps in reducing dimensionality and selecting best sets of the significant spectral bands. Then the modified geometric level set functional based ACM is applied on the optimal number of spectral bands determined by the PCA. By introducing local significant spectral band information, our proposed method is capable to force the level set functional to be close to a signed distance function, and therefore considerably remove the need of the expensive re-initialization procedure. To verify the effectiveness of the proposed technique, we use real-life hyperspectral images and test our algorithm in varying textural regions. This framework can be easily adapted to different applications for object segmentation in aerial hyperspectral imagery.

AOTF hyperspectral microscopic imaging for foodborne pathogenic bacteria detection

NASA Astrophysics Data System (ADS)

Park, Bosoon; Lee, Sangdae; Yoon, Seung-Chul; Sundaram, Jaya; Windham, William R.; Hinton, Arthur, Jr.; Lawrence, Kurt C.

2011-06-01

Hyperspectral microscope imaging (HMI) method which provides both spatial and spectral information can be effective for foodborne pathogen detection. The AOTF-based hyperspectral microscope imaging method can be used to characterize spectral properties of biofilm formed by Salmonella enteritidis as well as Escherichia coli. The intensity of spectral imagery and the pattern of spectral distribution varied with system parameters (integration time and gain) of HMI system. The preliminary results demonstrated determination of optimum parameter values of HMI system and the integration time must be no more than 250 ms for quality image acquisition from biofilm formed by S. enteritidis. Among the contiguous spectral imagery between 450 and 800 nm, the intensity of spectral images at 498, 522, 550 and 594 nm were distinctive for biofilm; whereas, the intensity of spectral images at 546 nm was distinctive for E. coli. For more accurate comparison of intensity from spectral images, a calibration protocol, using neutral density filters and multiple exposures, need to be developed to standardize image acquisition. For the identification or classification of unknown food pathogen samples, ground truth regions-of-interest pixels need to be selected for "spectrally pure fingerprints" for the Salmonella and E. coli species.

Interferometric and nonlinear-optical spectral-imaging techniques for outer space and live cells

NASA Astrophysics Data System (ADS)

Itoh, Kazuyoshi

2015-12-01

Multidimensional signals such as the spectral images allow us to have deeper insights into the natures of objects. In this paper the spectral imaging techniques that are based on optical interferometry and nonlinear optics are presented. The interferometric imaging technique is based on the unified theory of Van Cittert-Zernike and Wiener-Khintchine theorems and allows us to retrieve a spectral image of an object in the far zone from the 3D spatial coherence function. The retrieval principle is explained using a very simple object. The promising applications to space interferometers for astronomy that are currently in progress will also be briefly touched on. An interesting extension of interferometric spectral imaging is a 3D and spectral imaging technique that records 4D information of objects where the 3D and spectral information is retrieved from the cross-spectral density function of optical field. The 3D imaging is realized via the numerical inverse propagation of the cross-spectral density. A few techniques suggested recently are introduced. The nonlinear optical technique that utilizes stimulated Raman scattering (SRS) for spectral imaging of biomedical targets is presented lastly. The strong signals of SRS permit us to get vibrational information of molecules in the live cell or tissue in real time. The vibrational information of unstained or unlabeled molecules is crucial especially for medical applications. The 3D information due to the optical nonlinearity is also the attractive feature of SRS spectral microscopy.

Generalization of the Lyot filter and its application to snapshot spectral imaging.

PubMed

Gorman, Alistair; Fletcher-Holmes, David William; Harvey, Andrew Robert

2010-03-15

A snapshot multi-spectral imaging technique is described which employs multiple cascaded birefringent interferometers to simultaneously spectrally filter and demultiplex multiple spectral images onto a single detector array. Spectral images are recorded directly without the need for inversion and without rejection of light and so the technique offers the potential for high signal-to-noise ratio. An example of an eight-band multi-spectral movie sequence is presented; we believe this is the first such demonstration of a technique able to record multi-spectral movie sequences without the need for computer reconstruction.

Improving color constancy by discounting the variation of camera spectral sensitivity

NASA Astrophysics Data System (ADS)

Gao, Shao-Bing; Zhang, Ming; Li, Chao-Yi; Li, Yong-Jie

2017-08-01

It is an ill-posed problem to recover the true scene colors from a color biased image by discounting the effects of scene illuminant and camera spectral sensitivity (CSS) at the same time. Most color constancy (CC) models have been designed to first estimate the illuminant color, which is then removed from the color biased image to obtain an image taken under white light, without the explicit consideration of CSS effect on CC. This paper first studies the CSS effect on illuminant estimation arising in the inter-dataset-based CC (inter-CC), i.e., training a CC model on one dataset and then testing on another dataset captured by a distinct CSS. We show the clear degradation of existing CC models for inter-CC application. Then a simple way is proposed to overcome such degradation by first learning quickly a transform matrix between the two distinct CSSs (CSS-1 and CSS-2). The learned matrix is then used to convert the data (including the illuminant ground truth and the color biased images) rendered under CSS-1 into CSS-2, and then train and apply the CC model on the color biased images under CSS-2, without the need of burdensome acquiring of training set under CSS-2. Extensive experiments on synthetic and real images show that our method can clearly improve the inter-CC performance for traditional CC algorithms. We suggest that by taking the CSS effect into account, it is more likely to obtain the truly color constant images invariant to the changes of both illuminant and camera sensors.

Wavelength calibration of an imaging spectrometer based on Savart interferometer

NASA Astrophysics Data System (ADS)

Li, Qiwei; Zhang, Chunmin; Yan, Tingyu; Quan, Naicheng; Wei, Yutong; Tong, Cuncun

2017-09-01

The basic principle of Fourier-transform imaging spectrometer (FTIS) based on Savart interferometer is outlined. The un-identical distribution of the optical path difference which leads to the wavelength drift of each row of the interferogram is analyzed. Two typical methods for wavelength calibration of the presented system are described. The first method unifies different spectral intervals and maximum spectral frequencies of each row by a reference monochromatic light with known wavelength, and the dispersion compensation of Savart interferometer is also involved. The second approach is based on the least square fitting which builds the functional relation between recovered wavelength, row number and calibrated wavelength by concise equations. The effectiveness of the two methods is experimentally demonstrated with monochromatic lights and mixed light source across the detecting band of the system, and the results indicate that the first method has higher precision and the mean root-mean-square error of the recovered wavelengths is significantly reduced from 19.896 nm to 1.353 nm, while the second method is more convenient to implement and also has good precision of 2.709 nm.

Atmospheric limb sounding with imaging FTS

NASA Astrophysics Data System (ADS)

Friedl-Vallon, Felix; Riese, Martin; Preusse, Peter; Oelhaf, Hermann; Fischer, Herbert

Imaging Fourier transform spectrometers in the thermal infrared are a promising new class of sensors for atmospheric science. The availability of fast and sensitive large focal plane arrays with appropriate spectral coverage in the infrared region allows the conception and construction of innovative sensors for Nadir and Limb geometry. Instruments in Nadir geometry have already reached prototype status (e.g. Geostationary Imaging Fourier Transform Spectrometer / U. Wisconsin and NASA) or are in Phase A study (infrared sounding mission on Meteosat third generation / ESA and EUMETSAT). The first application of the new technical possibilities to atmospheric limb sounding from space, the Imaging Michelson Interferometer for Passive Atmospheric Sounding (IMIPAS), is currently studied by industry in the context of preparatory work for the next set of ESA earth explorers. The scientific focus of the instrument is on the processes controlling the composition of the mid/upper troposphere and lower stratosphere. The instrument concept of IMIPAS has been conceived at the research centres Karlsruhe and J¨lich. The development of a precursor instrument (GLORIA-AB) at these research institutions u started already in 2005. The instrument will be able to fly on board of various airborne platforms. First scientific missions are planned for the second half of the year 2009 on board the new German research aircraft HALO. This airborne sensor serves its own scientific purpose, but it also provides a test bed to learn about this new instrument class and its peculiarities and to learn to exploit and interpret the wealth of information provided by a limb imaging IR Fourier transform spectrometer. The presentation will discuss design considerations and challenges for GLORIA-AB and put them in the context of the planned satellite application. It will describe the solutions found, present first laboratory figures of merit for the prototype instrument and outline the new scientific possibilities.

Characterizing the marsh dieback spectral response at the plant and canopy level with hyperspectral and temporal remote sensing data

USGS Publications Warehouse

Ramsey, E.; Rangoonwala, A.

2008-01-01

We describe newly developed remote sensing tools to map the localized occurrences and regional distribution of the marsh dieback in coastal Louisiana (Fig. 1). As a final goal of our research and development, we identified what spectral features accompanied the onset of dieback and could be directly linked to the optical signal measured at the satellite. In order to accomplish our research goal, we carried out two interlinked objectives. First, we determined the spectral features within the hyperspectral spectra of the impacted plant that could be linked to the spectral return. This was accomplished by measuring the differences in leaf optical properties of impacted and non impacted marsh plants in such a way that the measured differences could be linked to the dieback onset and progression. The spectral analyses were constrained to selected wavelengths (bands of reflectance data) historically associated with changes in leaf composition and structure caused by changes in the plant biophysical environment. Second, we determined what changes in the canopy reflectance (canopy signal sensed at the satellite) could be linked to dieback onset and progression. Third, we transformed a suite of six Landsat Thematic Mapper images collected before, during, and in the final stages of dieback to maps of dieback occurrences. ??2008 IEEE.

Optimization of compressive 4D-spatio-spectral snapshot imaging

NASA Astrophysics Data System (ADS)

Zhao, Xia; Feng, Weiyi; Lin, Lihua; Su, Wu; Xu, Guoqing

2017-10-01

In this paper, a modified 3D computational reconstruction method in the compressive 4D-spectro-volumetric snapshot imaging system is proposed for better sensing spectral information of 3D objects. In the design of the imaging system, a microlens array (MLA) is used to obtain a set of multi-view elemental images (EIs) of the 3D scenes. Then, these elemental images with one dimensional spectral information and different perspectives are captured by the coded aperture snapshot spectral imager (CASSI) which can sense the spectral data cube onto a compressive 2D measurement image. Finally, the depth images of 3D objects at arbitrary depths, like a focal stack, are computed by inversely mapping the elemental images according to geometrical optics. With the spectral estimation algorithm, the spectral information of 3D objects is also reconstructed. Using a shifted translation matrix, the contrast of the reconstruction result is further enhanced. Numerical simulation results verify the performance of the proposed method. The system can obtain both 3D spatial information and spectral data on 3D objects using only one single snapshot, which is valuable in the agricultural harvesting robots and other 3D dynamic scenes.

[Research of dual-photoelastic-modulator-based beat frequency modulation and Fourier-Bessel transform imaging spectrometer].

PubMed

Wang, Zhi-Bin; Zhang, Rui; Wang, Yao-Li; Huang, Yan-Fei; Chen, You-Hua; Wang, Li-Fu; Yang, Qiang

2014-02-01

As the existing photoelastic-modulator(PEM) modulating frequency in the tens of kHz to hundreds of kHz between, leading to frequency of modulated interference signal is higher, so ordinary array detector cannot effectively caprure interference signal..A new beat frequency modulation method based on dual-photoelastic-modulator (Dual-PEM) and Fourier-Bessel transform is proposed as an key component of dual-photoelastic-modulator-based imaging spectrometer (Dual-PEM-IS) combined with charge coupled device (CCD). The dual-PEM are operated as an electro-optic circular retardance modulator, Operating the PEMs at slightly different resonant frequencies w1 and w2 respectively, generates a differential signal at a much lower heterodyne frequency that modulates the incident light. This method not only retains the advantages of the existing PEM, but also the frequency of modulated photocurrent decreased by 2-3 orders of magnitude (10-500 Hz) and can be detected by common array detector, and the incident light spectra can be obtained by Fourier-Bessel transform of low frequency component in the modulated signal. The method makes the PEM has the dual capability of imaging and spectral measurement. The basic principle is introduced, the basic equations is derived, and the feasibility is verified through the corresponding numerical simulation and experiment. This method has' potential applications in imaging spectrometer technology, and analysis of the effect of deviation of the optical path difference. This work provides the necessary theoretical basis for remote sensing of new Dual-PEM-IS and for engineering implementation of spectra inversion.

Automated cloud screening of AVHRR imagery using split-and-merge clustering

NASA Technical Reports Server (NTRS)

Gallaudet, Timothy C.; Simpson, James J.

1991-01-01

Previous methods to segment clouds from ocean in AVHRR imagery have shown varying degrees of success, with nighttime approaches being the most limited. An improved method of automatic image segmentation, the principal component transformation split-and-merge clustering (PCTSMC) algorithm, is presented and applied to cloud screening of both nighttime and daytime AVHRR data. The method combines spectral differencing, the principal component transformation, and split-and-merge clustering to sample objectively the natural classes in the data. This segmentation method is then augmented by supervised classification techniques to screen clouds from the imagery. Comparisons with other nighttime methods demonstrate its improved capability in this application. The sensitivity of the method to clustering parameters is presented; the results show that the method is insensitive to the split-and-merge thresholds.

Parallel-multiplexed excitation light-sheet microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Xu, Dongli; Zhou, Weibin; Peng, Leilei

2017-02-01

Laser scanning light-sheet imaging allows fast 3D image of live samples with minimal bleach and photo-toxicity. Existing light-sheet techniques have very limited capability in multi-label imaging. Hyper-spectral imaging is needed to unmix commonly used fluorescent proteins with large spectral overlaps. However, the challenge is how to perform hyper-spectral imaging without sacrificing the image speed, so that dynamic and complex events can be captured live. We report wavelength-encoded structured illumination light sheet imaging (λ-SIM light-sheet), a novel light-sheet technique that is capable of parallel multiplexing in multiple excitation-emission spectral channels. λ-SIM light-sheet captures images of all possible excitation-emission channels in true parallel. It does not require compromising the imaging speed and is capable of distinguish labels by both excitation and emission spectral properties, which facilitates unmixing fluorescent labels with overlapping spectral peaks and will allow more labels being used together. We build a hyper-spectral light-sheet microscope that combined λ-SIM with an extended field of view through Bessel beam illumination. The system has a 250-micron-wide field of view and confocal level resolution. The microscope, equipped with multiple laser lines and an unlimited number of spectral channels, can potentially image up to 6 commonly used fluorescent proteins from blue to red. Results from in vivo imaging of live zebrafish embryos expressing various genetic markers and sensors will be shown. Hyper-spectral images from λ-SIM light-sheet will allow multiplexed and dynamic functional imaging in live tissue and animals.

Optimal Band Ratio Analysis of WORLDVIEW-3 Imagery for Bathymetry of Shallow Rivers (case Study: Sarca River, Italy)

NASA Astrophysics Data System (ADS)

Niroumand-Jadidi, M.; Vitti, A.

2016-06-01

The Optimal Band Ratio Analysis (OBRA) could be considered as an efficient technique for bathymetry from optical imagery due to its robustness on substrate variability. This point receives more attention for very shallow rivers where different substrate types can contribute remarkably into total at-sensor radiance. The OBRA examines the total possible pairs of spectral bands in order to identify the optimal two-band ratio that its log transformation yields a strong linear relation with field measured water depths. This paper aims at investigating the effectiveness of additional spectral bands of newly launched WorldView-3 (WV-3) imagery in the visible and NIR spectrum through OBRA for retrieving water depths in shallow rivers. In this regard, the OBRA is performed on a WV-3 image as well as a GeoEye image of a small Alpine river in Italy. In-situ depths are gathered in two river reaches using a precise GPS device. In each testing scenario, 50% of the field data is used for calibration of the model and the remained as independent check points for accuracy assessment. In general, the effect of changes in water depth is highly pronounced in longer wavelengths (i.e. NIR) due to high and rapid absorption of light in this spectrum as long as it is not saturated. As the studied river is shallow, NIR portion of the spectrum has not been reduced so much not to reach the riverbed; making use of the observed radiance over this spectral range as denominator has shown a strong correlation through OBRA. More specifically, tightly focused channels of red-edge, NIR-1 and NIR-2 provide a wealth of choices for OBRA rather than a single NIR band of conventional 4-band images (e.g. GeoEye). This advantage of WV-3 images is outstanding as well for choosing the optimal numerator of the ratio model. Coastal-blue and yellow bands of WV-3 are identified as proper numerators while only green band of the GeoEye image contributed to a reliable correlation of image derived values and field measured depths. According to the results, the additional and narrow spectral bands of WV-3 image lead to an average determination coefficient of 67% in two river segments, which is 10% higher than that of obtained from the 4-band GeoEye image. In addition, RMSEs of depth estimations are calculated as 4 cm and 6 cm respectively for WV-3 and GeoEye images, considering the optimal band ratio.

Accommodating multiple illumination sources in an imaging colorimetry environment

NASA Astrophysics Data System (ADS)

Tobin, Kenneth W., Jr.; Goddard, James S., Jr.; Hunt, Martin A.; Hylton, Kathy W.; Karnowski, Thomas P.; Simpson, Marc L.; Richards, Roger K.; Treece, Dale A.

2000-03-01

Researchers at the Oak Ridge National Laboratory have been developing a method for measuring color quality in textile products using a tri-stimulus color camera system. Initial results of the Imaging Tristimulus Colorimeter (ITC) were reported during 1999. These results showed that the projection onto convex sets (POCS) approach to color estimation could be applied to complex printed patterns on textile products with high accuracy and repeatability. Image-based color sensors used for on-line measurement are not colorimetric by nature and require a non-linear transformation of the component colors based on the spectral properties of the incident illumination, imaging sensor, and the actual textile color. Our earlier work reports these results for a broad-band, smoothly varying D65 standard illuminant. To move the measurement to the on-line environment with continuously manufactured textile webs, the illumination source becomes problematic. The spectral content of these light sources varies substantially from the D65 standard illuminant and can greatly impact the measurement performance of the POCS system. Although absolute color measurements are difficult to make under different illumination, referential measurements to monitor color drift provide a useful indication of product quality. Modifications to the ITC system have been implemented to enable the study of different light sources. These results and the subsequent analysis of relative color measurements will be reported for textile products.

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

NASA Astrophysics Data System (ADS)

Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose

2018-06-01

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

A database for spectral image quality

NASA Astrophysics Data System (ADS)

Le Moan, Steven; George, Sony; Pedersen, Marius; Blahová, Jana; Hardeberg, Jon Yngve

2015-01-01

We introduce a new image database dedicated to multi-/hyperspectral image quality assessment. A total of nine scenes representing pseudo-at surfaces of different materials (textile, wood, skin. . . ) were captured by means of a 160 band hyperspectral system with a spectral range between 410 and 1000nm. Five spectral distortions were designed, applied to the spectral images and subsequently compared in a psychometric experiment, in order to provide a basis for applications such as the evaluation of spectral image difference measures. The database can be downloaded freely from http://www.colourlab.no/cid.

Trace gas detection in hyperspectral imagery using the wavelet packet subspace

NASA Astrophysics Data System (ADS)

Salvador, Mark A. Z.

This dissertation describes research into a new remote sensing method to detect trace gases in hyperspectral and ultra-spectral data. This new method is based on the wavelet packet transform. It attempts to improve both the computational tractability and the detection of trace gases in airborne and spaceborne spectral imagery. Atmospheric trace gas research supports various Earth science disciplines to include climatology, vulcanology, pollution monitoring, natural disasters, and intelligence and military applications. Hyperspectral and ultra-spectral data significantly increases the data glut of existing Earth science data sets. Spaceborne spectral data in particular significantly increases spectral resolution while performing daily global collections of the earth. Application of the wavelet packet transform to the spectral space of hyperspectral and ultra-spectral imagery data potentially improves remote sensing detection algorithms. It also facilities the parallelization of these methods for high performance computing. This research seeks two science goals, (1) developing a new spectral imagery detection algorithm, and (2) facilitating the parallelization of trace gas detection in spectral imagery data.

Results of ACTIM: an EDA study on spectral laser imaging

NASA Astrophysics Data System (ADS)

Hamoir, Dominique; Hespel, Laurent; Déliot, Philippe; Boucher, Yannick; Steinvall, Ove; Ahlberg, Jörgen; Larsson, Hakan; Letalick, Dietmar; Lutzmann, Peter; Repasi, Endre; Ritt, Gunnar

2011-11-01

The European Defence Agency (EDA) launched the Active Imaging (ACTIM) study to investigate the potential of active imaging, especially that of spectral laser imaging. The work included a literature survey, the identification of promising military applications, system analyses, a roadmap and recommendations. Passive multi- and hyper-spectral imaging allows discriminating between materials. But the measured radiance in the sensor is difficult to relate to spectral reflectance due to the dependence on e.g. solar angle, clouds, shadows... In turn, active spectral imaging offers a complete control of the illumination, thus eliminating these effects. In addition it allows observing details at long ranges, seeing through degraded atmospheric conditions, penetrating obscurants (foliage, camouflage...) or retrieving polarization information. When 3D, it is suited to producing numerical terrain models and to performing geometry-based identification. Hence fusing the knowledge of ladar and passive spectral imaging will result in new capabilities. We have identified three main application areas for active imaging, and for spectral active imaging in particular: (1) long range observation for identification, (2) mid-range mapping for reconnaissance, (3) shorter range perception for threat detection. We present the system analyses that have been performed for confirming the interests, limitations and requirements of spectral active imaging in these three prioritized applications.

Hyperspectral Imaging Sensors and the Marine Coastal Zone

NASA Technical Reports Server (NTRS)

Richardson, Laurie L.

2000-01-01

Hyperspectral imaging sensors greatly expand the potential of remote sensing to assess, map, and monitor marine coastal zones. Each pixel in a hyperspectral image contains an entire spectrum of information. As a result, hyperspectral image data can be processed in two very different ways: by image classification techniques, to produce mapped outputs of features in the image on a regional scale; and by use of spectral analysis of the spectral data embedded within each pixel of the image. The latter is particularly useful in marine coastal zones because of the spectral complexity of suspended as well as benthic features found in these environments. Spectral-based analysis of hyperspectral (AVIRIS) imagery was carried out to investigate a marine coastal zone of South Florida, USA. Florida Bay is a phytoplankton-rich estuary characterized by taxonomically distinct phytoplankton assemblages and extensive seagrass beds. End-member spectra were extracted from AVIRIS image data corresponding to ground-truth sample stations and well-known field sites. Spectral libraries were constructed from the AVIRIS end-member spectra and used to classify images using the Spectral Angle Mapper (SAM) algorithm, a spectral-based approach that compares the spectrum, in each pixel of an image with each spectrum in a spectral library. Using this approach different phytoplankton assemblages containing diatoms, cyanobacteria, and green microalgae, as well as benthic community (seagrasses), were mapped.

Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

NASA Astrophysics Data System (ADS)

Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.

2015-08-01

A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as <0.66, 0.66-1.06, 1.06-1.62, and >1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.

The Global Aerosol System As Viewed By MODIS Today

NASA Technical Reports Server (NTRS)

Remer, Lorraine

2008-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) aerosol algorithms have been working steadily since early 2000 to transform the MODIS-measured spectral solar reflectance from the Earth's surface and atmosphere into a variety of aerosol products. In this lecture I will proceed through a survey of these products, answering the following questions as I proceed. What are the products? How do they compare with ground truth? How do we use these products to describe the global aerosol system? Are aerosols increasing or decreasing? How do aerosols affect climate and clouds?

Detection and mapping of volcanic rock assemblages and associated hydrothermal alteration with Thermal Infrared Multiband Scanner (TIMS) data Comstock Lode Mining District, Virginia City, Nevada

NASA Technical Reports Server (NTRS)

Taranik, James V.; Hutsinpiller, Amy; Borengasser, Marcus

1986-01-01

Thermal Infrared Multispectral Scanner (TIMS) data were acquired over the Virginia City area on September 12, 1984. The data were acquired at approximately 1130 hours local time (1723 IRIG). The TIMS data were analyzed using both photointerpretation and digital processing techniques. Karhuen-Loeve transformations were utilized to display variations in radiant spectral emittance. The TIMS image data were compared with color infrared metric camera photography, LANDSAT Thematic Mapper (TM) data, and key areas were photographed in the field.

Ratiometric spectral imaging for fast tumor detection and chemotherapy monitoring in vivo

PubMed Central

Hwang, Jae Youn; Gross, Zeev; Gray, Harry B.; Medina-Kauwe, Lali K.; Farkas, Daniel L.

2011-01-01

We report a novel in vivo spectral imaging approach to cancer detection and chemotherapy assessment. We describe and characterize a ratiometric spectral imaging and analysis method and evaluate its performance for tumor detection and delineation by quantitatively monitoring the specific accumulation of targeted gallium corrole (HerGa) into HER2-positive (HER2 +) breast tumors. HerGa temporal accumulation in nude mice bearing HER2 + breast tumors was monitored comparatively by a. this new ratiometric imaging and analysis method; b. established (reflectance and fluorescence) spectral imaging; c. more commonly used fluorescence intensity imaging. We also tested the feasibility of HerGa imaging in vivo using the ratiometric spectral imaging method for tumor detection and delineation. Our results show that the new method not only provides better quantitative information than typical spectral imaging, but also better specificity than standard fluorescence intensity imaging, thus allowing enhanced in vivo outlining of tumors and dynamic, quantitative monitoring of targeted chemotherapy agent accumulation into them. PMID:21721808

Resolution Enhancement of Hyperion Hyperspectral Data using Ikonos Multispectral Data

DTIC Science & Technology

2007-09-01

spatial - resolution hyperspectral image to produce a sharpened product. The result is a product that has the spectral properties of the ...multispectral sensors. In this work, we examine the benefits of combining data from high- spatial - resolution , low- spectral - resolution spectral imaging...sensors with data obtained from high- spectral - resolution , low- spatial - resolution spectral imaging sensors.

Low thermal emissivity surfaces using AgNW thin films

NASA Astrophysics Data System (ADS)

Pantoja, Elisa; Bhatt, Rajendra; Liu, Anping; Gupta, Mool C.

2017-12-01

The properties of silver nanowire (AgNW) films in the optical and infrared spectral regime offer an interesting opportunity for a broad range of applications that require low-emissivity coatings. This work reports a method to reduce the thermal emissivity of substrates by the formation of low-emissivity AgNW coating films from solution. The spectral emissivity was characterized by thermal imaging with an FLIR camera, followed by Fourier transform infrared spectroscopy. In a combined experimental and simulation study, we provide fundamental data of the transmittance, reflectance, haze, and emissivity of AgNW thin films. Emissivity values were finely tuned by modifying the concentration of the metal nanowires in the films. The simulation models based on the transfer matrix method developed for the AgNW thin films provided optical values that show a good agreement with the measurements.

Influence of spectral resolution, spectral range and signal-to-noise ratio of Fourier transform infra-red spectra on identification of high explosive substances

NASA Astrophysics Data System (ADS)

Banas, Krzysztof; Banas, Agnieszka M.; Heussler, Sascha P.; Breese, Mark B. H.

2018-01-01

In the contemporary spectroscopy there is a trend to record spectra with the highest possible spectral resolution. This is clearly justified if the spectral features in the spectrum are very narrow (for example infra-red spectra of gas samples). However there is a plethora of samples (in the liquid and especially in the solid form) where there is a natural spectral peak broadening due to collisions and proximity predominately. Additionally there is a number of portable devices (spectrometers) with inherently restricted spectral resolution, spectral range or both, which are extremely useful in some field applications (archaeology, agriculture, food industry, cultural heritage, forensic science). In this paper the investigation of the influence of spectral resolution, spectral range and signal-to-noise ratio on the identification of high explosive substances by applying multivariate statistical methods on the Fourier transform infra-red spectral data sets is studied. All mathematical procedures on spectral data for dimension reduction, clustering and validation were implemented within R open source environment.

Spectral imaging toolbox: segmentation, hyperstack reconstruction, and batch processing of spectral images for the determination of cell and model membrane lipid order.

PubMed

Aron, Miles; Browning, Richard; Carugo, Dario; Sezgin, Erdinc; Bernardino de la Serna, Jorge; Eggeling, Christian; Stride, Eleanor

2017-05-12

Spectral imaging with polarity-sensitive fluorescent probes enables the quantification of cell and model membrane physical properties, including local hydration, fluidity, and lateral lipid packing, usually characterized by the generalized polarization (GP) parameter. With the development of commercial microscopes equipped with spectral detectors, spectral imaging has become a convenient and powerful technique for measuring GP and other membrane properties. The existing tools for spectral image processing, however, are insufficient for processing the large data sets afforded by this technological advancement, and are unsuitable for processing images acquired with rapidly internalized fluorescent probes. Here we present a MATLAB spectral imaging toolbox with the aim of overcoming these limitations. In addition to common operations, such as the calculation of distributions of GP values, generation of pseudo-colored GP maps, and spectral analysis, a key highlight of this tool is reliable membrane segmentation for probes that are rapidly internalized. Furthermore, handling for hyperstacks, 3D reconstruction and batch processing facilitates analysis of data sets generated by time series, z-stack, and area scan microscope operations. Finally, the object size distribution is determined, which can provide insight into the mechanisms underlying changes in membrane properties and is desirable for e.g. studies involving model membranes and surfactant coated particles. Analysis is demonstrated for cell membranes, cell-derived vesicles, model membranes, and microbubbles with environmentally-sensitive probes Laurdan, carboxyl-modified Laurdan (C-Laurdan), Di-4-ANEPPDHQ, and Di-4-AN(F)EPPTEA (FE), for quantification of the local lateral density of lipids or lipid packing. The Spectral Imaging Toolbox is a powerful tool for the segmentation and processing of large spectral imaging datasets with a reliable method for membrane segmentation and no ability in programming required. The Spectral Imaging Toolbox can be downloaded from https://uk.mathworks.com/matlabcentral/fileexchange/62617-spectral-imaging-toolbox .

Semiconductor Laser Multi-Spectral Sensing and Imaging

PubMed Central

Le, Han Q.; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers. PMID:22315555

Semiconductor laser multi-spectral sensing and imaging.

PubMed

Le, Han Q; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

Spectrally-encoded color imaging

PubMed Central

Kang, DongKyun; Yelin, Dvir; Bouma, Brett E.; Tearney, Guillermo J.

2010-01-01

Spectrally-encoded endoscopy (SEE) is a technique for ultraminiature endoscopy that encodes each spatial location on the sample with a different wavelength. One limitation of previous incarnations of SEE is that it inherently creates monochromatic images, since the spectral bandwidth is expended in the spatial encoding process. Here we present a spectrally-encoded imaging system that has color imaging capability. The new imaging system utilizes three distinct red, green, and blue spectral bands that are configured to illuminate the grating at different incident angles. By careful selection of the incident angles, the three spectral bands can be made to overlap on the sample. To demonstrate the method, a bench-top system was built, comprising a 2400-lpmm grating illuminated by three 525-μm-diameter beams with three different spectral bands. Each spectral band had a bandwidth of 75 nm, producing 189 resolvable points. A resolution target, color phantoms, and excised swine small intestine were imaged to validate the system's performance. The color SEE system showed qualitatively and quantitatively similar color imaging performance to that of a conventional digital camera. PMID:19688002

Linear and Nonlinear Molecular Spectroscopy with Laser Frequency Combs

NASA Astrophysics Data System (ADS)

Picque, Nathalie

2013-06-01

The regular pulse train of a mode-locked femtosecond laser can give rise to a comb spectrum of millions of laser modes with a spacing precisely equal to the pulse repetition frequency. Laser frequency combs were conceived a decade ago as tools for the precision spectroscopy of atomic hydrogen. They are now becoming enabling tools for an increasing number of applications, including molecular spectroscopy. Recent experiments of multi-heterodyne frequency comb Fourier transform spectroscopy (also called dual-comb spectroscopy) have demonstrated that the precisely spaced spectral lines of a laser frequency comb can be harnessed for new techniques of linear absorption spectroscopy. The first proof-of-principle experiments have demonstrated a very exciting potential of dual-comb spectroscopy without moving parts for ultra-rapid and ultra-sensitive recording of complex broad spectral bandwidth molecular spectra. Compared to conventional Michelson-based Fourier transform spectroscopy, recording times could be shortened from seconds to microseconds, with intriguing prospects for spectroscopy of short lived transient species. The resolution improves proportionally to the measurement time. Therefore longer recordings allow high resolution spectroscopy of molecules with extreme precision, since the absolute frequency of each laser comb line can be known with the accuracy of an atomic clock. Moreover, since laser frequency combs involve intense ultrashort laser pulses, nonlinear interactions can be harnessed. Broad spectral bandwidth ultra-rapid nonlinear molecular spectroscopy and imaging with two laser frequency combs is demonstrated with coherent Raman effects and two-photon excitation. Real-time multiplex accessing of hyperspectral images may dramatically expand the range of applications of nonlinear microscopy. B. Bernhardt et al., Nature Photonics 4, 55-57 (2010); A. Schliesser et al. Nature Photonics 6, 440-449 (2012); T. Ideguchi et al. arXiv:1201.4177 (2012) T. Ideguchi et al., Optics letters 37, 4498-4500 (2012); T. Ideguchi et al. arXiv:1302.2414 (2013)

Imaging Fourier transform spectroscopy of the boundary layer plume from laser irradiated polymers and carbon materials

NASA Astrophysics Data System (ADS)

Acosta, Roberto I.

The high-energy laser (HEL) lethality community needs for enhanced laser weapons systems requires a better understanding of a wide variety of emerging threats. In order to reduce the dimensionality of laser-materials interaction it is necessary to develop novel predictive capabilities of these events. The objective is to better understand the fundamentals of laser lethality testing by developing empirical models from hyperspectral imagery, enabling a robust library of experiments for vulnerability assessments. Emissive plumes from laser irradiated fiberglass reinforced polymers (FRP), poly(methyl methacrylate) (PMMA) and porous graphite targets were investigated primarily using a mid-wave infrared (MWIR) imaging Fourier transform spectrometer (FTS). Polymer and graphite targets were irradiated with a continuous wave (cw) fiber lasers. Data was acquired with a spectral resolution of 2 cm-1 and spatial resolution as high as 0.52 mm2 per pixel. Strong emission from H2O, CO, CO2 and hydrocarbons were observed in the MWIR between 1900-4000 cm-1. A single-layer radiative transfer model was developed to estimate spatial maps of temperature and column densities of CO and CO2 from the hyperspectral imagery of the boundary layer plume. The spectral model was used to compute the absorption cross sections of CO and CO2, using spectral line parameters from the high temperature extension of the HITRAN. Also, spatial maps of gas-phase temperature and methyl methacrylate (MMA) concentration were developed from laser irradiated carbon black-pigmented PMMA at irradiances of 4-22 W/cm2. Global kinetics interplay between heterogeneous and homogeneous combustion kinetics are shown from experimental observations at high spatial resolutions. Overall the boundary layer profile at steady-state is consistent with CO being mainly produced at the surface by heterogeneous reactions followed by a rapid homogeneous combustion in the boundary layer towards buoyancy.

Areas of activity in biofilms through the biospeckle and the spectral domain

NASA Astrophysics Data System (ADS)

Marques, J. K.; Braga, R. A.; Pereira, J.

2010-09-01

The dynamic laser speckle or biospeckle laser has been used to analyze the activity of biological and non-biological material by means of various statistical techniques and image processing. However, a challenge to adopt this technique is the ability to identify, in the same material, an area of low activity immersed in an environment of a higher activity. This work was carried out to evaluate the spectral approach associated to biospeckle laser technique as an alternative to identify distinct activities areas in the same material. Biofilm samples, which present well known protocols to be prepared, and a simpler structure than vegetal and animal tissues, were prepared with potato starch and corn starch with areas of different levels of moisture and were analyzed using the biospeckle laser associated with the wavelets transform in order to evaluate the data in the spectral domain. The effect of a black or white background below the samples was also tested. The image analysis was conducted using Generalized Difference and Fujii techniques before and after the implementation of the wavelets transform producing the filtration of the data. The results allowed the visualization of different activities areas in different frequency bands. The areas of activity were presented clearer than the traditional procedures without filtering. A new way to present the results of the biospeckle and the frequency domain information was proposed to enhance the visualization of a whole picture. It was also noted that the greatest contrast between areas of different activity were promoted by materials of different compositions. In some experimental configurations there were possible to tag the relationship between the frequency and depth of the active or inactive material. The influence of the color, black or white, of the background was also noticed in the results, but with white background better in some configurations and with the black better in others.

Technical Note: Quantitative accuracy evaluation for spectral images from a detector-based spectral CT scanner using an iodine phantom.

PubMed

Duan, Xinhui; Arbique, Gary; Guild, Jeffrey; Xi, Yin; Anderson, Jon

2018-05-01

The purpose of this study was to evaluate the quantitative accuracy of spectral images from a detector-based spectral CT scanner using a phantom with iodine-loaded inserts. A 40-cm long-body phantom with seven iodine inserts (2-20 mg/ml of iodine) was used in the study. The inserts could be placed at 5.5 or 10.5 cm from the phantom axis. The phantom was scanned five times for each insert configuration using 120 kVp tube voltage. A set of iodine, virtual noncontrast, effective atomic number, and virtual monoenergetic spectral CT images were generated and measurements were made for all the iodine rods. Measured values were compared with reference values calculated from the chemical composition information provided by the phantom manufacturer. Radiation dose from the spectral CT was compared to a conventional CT using a CTDI (32 cm) phantom. Good agreement between measurements and reference values was achieved for all types of spectral images. The differences ranged from -0.46 to 0.1 mg/ml for iodine concentration, -9.95 to 6.41 HU for virtual noncontrast images, 0.12 to 0.35 for effective Z images, and -17.7 to 55.7 HU for virtual monoenergetic images. For a similar CTDIvol, image noise from the conventional CT was 10% lower than the spectral CT. The detector-based spectral CT can achieve accurate spectral measurements on iodine concentration, virtual non-contrast images, effective atomic numbers, and virtual monoenergetic images. © 2018 American Association of Physicists in Medicine.

Recent Advances in Techniques for Hyperspectral Image Processing

NASA Technical Reports Server (NTRS)

Plaza, Antonio; Benediktsson, Jon Atli; Boardman, Joseph W.; Brazile, Jason; Bruzzone, Lorenzo; Camps-Valls, Gustavo; Chanussot, Jocelyn; Fauvel, Mathieu; Gamba, Paolo; Gualtieri, Anthony;

Real-Time Noise Removal for Line-Scanning Hyperspectral Devices Using a Minimum Noise Fraction-Based Approach

PubMed Central

Bjorgan, Asgeir; Randeberg, Lise Lyngsnes

2015-01-01

Processing line-by-line and in real-time can be convenient for some applications of line-scanning hyperspectral imaging technology. Some types of processing, like inverse modeling and spectral analysis, can be sensitive to noise. The MNF (minimum noise fraction) transform provides suitable denoising performance, but requires full image availability for the estimation of image and noise statistics. In this work, a modified algorithm is proposed. Incrementally-updated statistics enables the algorithm to denoise the image line-by-line. The denoising performance has been compared to conventional MNF and found to be equal. With a satisfying denoising performance and real-time implementation, the developed algorithm can denoise line-scanned hyperspectral images in real-time. The elimination of waiting time before denoised data are available is an important step towards real-time visualization of processed hyperspectral data. The source code can be found at http://www.github.com/ntnu-bioopt/mnf. This includes an implementation of conventional MNF denoising. PMID:25654717

Parallel Computing for the Computed-Tomography Imaging Spectrometer

NASA Technical Reports Server (NTRS)

Lee, Seungwon

2008-01-01

This software computes the tomographic reconstruction of spatial-spectral data from raw detector images of the Computed-Tomography Imaging Spectrometer (CTIS), which enables transient-level, multi-spectral imaging by capturing spatial and spectral information in a single snapshot.

Wavelet analysis for wind fields estimation.

PubMed

Leite, Gladeston C; Ushizima, Daniela M; Medeiros, Fátima N S; de Lima, Gilson G

2010-01-01

Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B(3) spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms(-1). Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms.

Comparison of Background Parenchymal Enhancement at Contrast-enhanced Spectral Mammography and Breast MR Imaging

PubMed Central

Morris, Elizabeth A.; Kaplan, Jennifer B.; D’Alessio, Donna; Goldman, Debra; Moskowitz, Chaya S.

2017-01-01

Purpose To assess the extent of background parenchymal enhancement (BPE) at contrast material–enhanced (CE) spectral mammography and breast magnetic resonance (MR) imaging, to evaluate interreader agreement in BPE assessment, and to examine the relationships between clinical factors and BPE. Materials and Methods This was a retrospective, institutional review board–approved, HIPAA-compliant study. Two hundred seventy-eight women from 25 to 76 years of age with increased breast cancer risk who underwent CE spectral mammography and MR imaging for screening or staging from 2010 through 2014 were included. Three readers independently rated BPE on CE spectral mammographic and MR images with the ordinal scale: minimal, mild, moderate, or marked. To assess pairwise agreement between BPE levels on CE spectral mammographic and MR images and among readers, weighted κ coefficients with quadratic weights were calculated. For overall agreement, mean κ values and bootstrapped 95% confidence intervals were calculated. The univariate and multivariate associations between BPE and clinical factors were examined by using generalized estimating equations separately for CE spectral mammography and MR imaging. Results Most women had minimal or mild BPE at both CE spectral mammography (68%–76%) and MR imaging (69%–76%). Between CE spectral mammography and MR imaging, the intrareader agreement ranged from moderate to substantial (κ = 0.55–0.67). Overall agreement on BPE levels between CE spectral mammography and MR imaging and among readers was substantial (κ = 0.66; 95% confidence interval: 0.61, 0.70). With both modalities, BPE demonstrated significant association with menopausal status, prior breast radiation therapy, hormonal treatment, breast density on CE spectral mammographic images, and amount of fibroglandular tissue on MR images (P < .001 for all). Conclusion There was substantial agreement between readers for BPE detected on CE spectral mammographic and MR images. © RSNA, 2016 PMID:27379544

Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals

NASA Technical Reports Server (NTRS)

Thompson, David R.; Mandrake, Lukas; Green, Robert O.

2013-01-01

Mapping localized spectral features in large images demands sensitive and robust detection algorithms. Two aspects of large images that can harm matched-filter detection performance are addressed simultaneously. First, multimodal backgrounds may thwart the typical Gaussian model. Second, outlier features can trigger false detections from large projections onto the target vector. Two state-of-the-art approaches are combined that independently address outlier false positives and multimodal backgrounds. The background clustering models multimodal backgrounds, and the mixture tuned matched filter (MT-MF) addresses outliers. Combining the two methods captures significant additional performance benefits. The resulting mixture tuned clutter matched filter (MT-CMF) shows effective performance on simulated and airborne datasets. The classical MNF transform was applied, followed by k-means clustering. Then, each cluster s mean, covariance, and the corresponding eigenvalues were estimated. This yields a cluster-specific matched filter estimate as well as a cluster- specific feasibility score to flag outlier false positives. The technology described is a proof of concept that may be employed in future target detection and mapping applications for remote imaging spectrometers. It is of most direct relevance to JPL proposals for airborne and orbital hyperspectral instruments. Applications include subpixel target detection in hyperspectral scenes for military surveillance. Earth science applications include mineralogical mapping, species discrimination for ecosystem health monitoring, and land use classification.

Toward Fourier interferometry fluorescence excitation/emission imaging of malignant cells combined with photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Kohen, Elli; Hirschberg, Joseph G.; Berry, John P.; Ozkutuk, Nuri; Ornek, Ceren; Monti, Marco; Leblanc, Roger M.; Schachtschabel, Dietrich O.; Haroon, Sumaira

2003-10-01

Dual excitation fluorescence imaging has been used as a first step towards multi-wavelength excitation/emission fluorescence spectral imaging. Target cells are transformed keratinocytes, and other osteosarcoma, human breast and color cancer cells. Mitochondrial membrane potential probes, e.g. TMRM (tetramethylrhodamine methyl ester), Mitotracker Green (Molecular Probes, Inc., Eugene OR,USA; a recently synthesized mitochondrial oxygen probe, [PRE,P1"- pyrene butyl)-2-rhodamine ester] allow dual excitation in the UV plus in teh blue-green spectral regions. Also, using the natural endogenous probe NAD(P)H, preliminary results indicate mitochondrial responses to metabolic challenges (e.g. glucose addition), plus changes in mitochonrial distribution and morphology. In terms of application to biomedicine (for diagnostiscs, prognostsics and drug trials) three parameters have been selected in addition to the natural probe NAD(P)H, i.e. vital fluorescence probing of mitochondria, lysosomes and Golgi apparatus. It is hoped that such a multiparameter approach will allow malignant cell characterization and grading. A new area being introduced is the use of similar methodology for biotechnical applications such as the study of the hydrogen-producing alga Chlamydomonas Reinhardtii, and possible agricultural applications, such as Saccharomyces yeast for oenology. Complementation by Photoacoustic Microscopy is also contemplated, to study the internal conversion component which follows the excitation by photons.

Comparison of temporal and spectral scattering methods using acoustically large breast models derived from magnetic resonance images.

PubMed

Hesford, Andrew J; Tillett, Jason C; Astheimer, Jeffrey P; Waag, Robert C

2014-08-01

Accurate and efficient modeling of ultrasound propagation through realistic tissue models is important to many aspects of clinical ultrasound imaging. Simplified problems with known solutions are often used to study and validate numerical methods. Greater confidence in a time-domain k-space method and a frequency-domain fast multipole method is established in this paper by analyzing results for realistic models of the human breast. Models of breast tissue were produced by segmenting magnetic resonance images of ex vivo specimens into seven distinct tissue types. After confirming with histologic analysis by pathologists that the model structures mimicked in vivo breast, the tissue types were mapped to variations in sound speed and acoustic absorption. Calculations of acoustic scattering by the resulting model were performed on massively parallel supercomputer clusters using parallel implementations of the k-space method and the fast multipole method. The efficient use of these resources was confirmed by parallel efficiency and scalability studies using large-scale, realistic tissue models. Comparisons between the temporal and spectral results were performed in representative planes by Fourier transforming the temporal results. An RMS field error less than 3% throughout the model volume confirms the accuracy of the methods for modeling ultrasound propagation through human breast.

A fluctuation-induced plasma transport diagnostic based upon fast-Fourier transform spectral analysis

NASA Technical Reports Server (NTRS)

Powers, E. J.; Kim, Y. C.; Hong, J. Y.; Roth, J. R.; Krawczonek, W. M.

1978-01-01

A diagnostic, based on fast Fourier-transform spectral analysis techniques, that provides experimental insight into the relationship between the experimentally observable spectral characteristics of the fluctuations and the fluctuation-induced plasma transport is described. The model upon which the diagnostic technique is based and its experimental implementation is discussed. Some characteristic results obtained during the course of an experimental study of fluctuation-induced transport in the electric field dominated NASA Lewis bumpy torus plasma are presented.

Laboratory spectroscopy of meteorite samples at UV-vis-NIR wavelengths: Analysis and discrimination by principal components analysis

NASA Astrophysics Data System (ADS)

Penttilä, Antti; Martikainen, Julia; Gritsevich, Maria; Muinonen, Karri

2018-02-01

Meteorite samples are measured with the University of Helsinki integrating-sphere UV-vis-NIR spectrometer. The resulting spectra of 30 meteorites are compared with selected spectra from the NASA Planetary Data System meteorite spectra database. The spectral measurements are transformed with the principal component analysis, and it is shown that different meteorite types can be distinguished from the transformed data. The motivation is to improve the link between asteroid spectral observations and meteorite spectral measurements.

Logarithmic compression methods for spectral data

DOEpatents

Dunham, Mark E.

2003-01-01

A method is provided for logarithmic compression, transmission, and expansion of spectral data. A log Gabor transformation is made of incoming time series data to output spectral phase and logarithmic magnitude values. The output phase and logarithmic magnitude values are compressed by selecting only magnitude values above a selected threshold and corresponding phase values to transmit compressed phase and logarithmic magnitude values. A reverse log Gabor transformation is then performed on the transmitted phase and logarithmic magnitude values to output transmitted time series data to a user.

Analysis of spectrally resolved autofluorescence images by support vector machines

NASA Astrophysics Data System (ADS)

Mateasik, A.; Chorvat, D.; Chorvatova, A.

2013-02-01

Spectral analysis of the autofluorescence images of isolated cardiac cells was performed to evaluate and to classify the metabolic state of the cells in respect to the responses to metabolic modulators. The classification was done using machine learning approach based on support vector machine with the set of the automatically calculated features from recorded spectral profile of spectral autofluorescence images. This classification method was compared with the classical approach where the individual spectral components contributing to cell autofluorescence were estimated by spectral analysis, namely by blind source separation using non-negative matrix factorization. Comparison of both methods showed that machine learning can effectively classify the spectrally resolved autofluorescence images without the need of detailed knowledge about the sources of autofluorescence and their spectral properties.

Newly Diagnosed Breast Cancer: Comparison of Contrast-enhanced Spectral Mammography and Breast MR Imaging in the Evaluation of Extent of Disease.

PubMed

Lee-Felker, Stephanie A; Tekchandani, Leena; Thomas, Mariam; Gupta, Esha; Andrews-Tang, Denise; Roth, Antoinette; Sayre, James; Rahbar, Guita

2017-11-01

Purpose To compare the diagnostic performances of contrast material-enhanced spectral mammography and breast magnetic resonance (MR) imaging in the detection of index and secondary cancers in women with newly diagnosed breast cancer by using histologic or imaging follow-up as the standard of reference. Materials and Methods This institutional review board-approved, HIPAA-compliant, retrospective study included 52 women who underwent breast MR imaging and contrast-enhanced spectral mammography for newly diagnosed unilateral breast cancer between March 2014 and October 2015. Of those 52 patients, 46 were referred for contrast-enhanced spectral mammography and targeted ultrasonography because they had additional suspicious lesions at MR imaging. In six of the 52 patients, breast cancer had been diagnosed at an outside institution. These patients were referred for contrast-enhanced spectral mammography and targeted US as part of diagnostic imaging. Images from contrast-enhanced spectral mammography were analyzed by two fellowship-trained breast imagers with 2.5 years of experience with contrast-enhanced spectral mammography. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated for both imaging modalities and compared by using the Bennett statistic. Results Fifty-two women with 120 breast lesions were included for analysis (mean age, 50 years; range, 29-73 years). Contrast-enhanced spectral mammography had similar sensitivity to MR imaging (94% [66 of 70 lesions] vs 99% [69 of 70 lesions]), a significantly higher PPV than MR imaging (93% [66 of 71 lesions] vs 60% [69 of 115 lesions]), and fewer false-positive findings than MR imaging (five vs 45) (P < .001 for all results). In addition, contrast-enhanced spectral mammography depicted 11 of the 11 secondary cancers (100%) and MR imaging depicted 10 (91%). Conclusion Contrast-enhanced spectral mammography is potentially as sensitive as MR imaging in the evaluation of extent of disease in newly diagnosed breast cancer, with a higher PPV. © RSNA, 2017.

Push-broom imaging spectrometer based on planar lightwave circuit MZI array

NASA Astrophysics Data System (ADS)

Yang, Minyue; Li, Mingyu; He, Jian-Jun

2017-05-01

We propose a large aperture static imaging spectrometer (LASIS) based on planar lightwave circuit (PLC) MZI array. The imaging spectrometer works in the push-broom mode with the spectrum performed by interferometry. While the satellite/aircraft is orbiting, the same source, seen from the satellite/aircraft, moves across the aperture and enters different MZIs, while adjacent sources enter adjacent MZIs at the same time. The on-chip spectrometer consists of 256 input mode converters, followed by 256 MZIs with linearly increasing optical path delays and a detector array. Multiple chips are stick together to form the 2D image surface and receive light from the imaging lens. Two MZI arrays are proposed, one works in wavelength ranging from 500nm to 900nm with SiON(refractive index 1.6) waveguides and another ranging from 1100nm to 1700nm with SOI platform. To meet the requirements of imaging spectrometer applications, we choose large cross-section ridge waveguide to achieve polarization insensitive, maintain single mode propagation in broad spectrum and increase production tolerance. The SiON on-chip spectrometer has a spectral resolution of 80cm-1 with a footprint of 17×15mm2 and the SOI based on-chip spectrometer has a resolution of 38cm-1 with a size of 22×19mm2. The spectral and space resolution of the imaging spectrometer can be further improved by simply adding more MZIs. The on-chip waveguide MZI array based Fourier transform imaging spectrometer can provide a highly compact solution for remote sensing on unmanned aerial vehicles or satellites with advantages of small size, light weight, no moving parts and large input aperture.

Spectral imaging as a potential tool for optical sentinel lymph node biopsies

NASA Astrophysics Data System (ADS)

O'Sullivan, Jack D.; Hoy, Paul R.; Rutt, Harvey N.

2011-07-01

Sentinel Lymph Node Biopsy (SLNB) is an increasingly standard procedure to help oncologists accurately stage cancers. It is performed as an alternative to full axillary lymph node dissection in breast cancer patients, reducing the risk of longterm health problems associated with lymph node removal. Intraoperative analysis is currently performed using touchprint cytology, which can introduce significant delay into the procedure. Spectral imaging is forming a multi-plane image where reflected intensities from a number of spectral bands are recorded at each pixel in the spatial plane. We investigate the possibility of using spectral imaging to assess sentinel lymph nodes of breast cancer patients with a view to eventually developing an optical technique that could significantly reduce the time required to perform this procedure. We investigate previously reported spectra of normal and metastatic tissue in the visible and near infrared region, using them as the basis of dummy spectral images. We analyse these images using the spectral angle map (SAM), a tool routinely used in other fields where spectral imaging is prevalent. We simulate random noise in these images in order to determine whether the SAM can discriminate between normal and metastatic pixels as the quality of the images deteriorates. We show that even in cases where noise levels are up to 20% of the maximum signal, the spectral angle map can distinguish healthy pixels from metastatic. We believe that this makes spectral imaging a good candidate for further study in the development of an optical SLNB.

Fourier Transform Spectrometer System

NASA Technical Reports Server (NTRS)

Campbell, Joel F. (Inventor)

2014-01-01

A Fourier transform spectrometer (FTS) data acquisition system includes an FTS spectrometer that receives a spectral signal and a laser signal. The system further includes a wideband detector, which is in communication with the FTS spectrometer and receives the spectral signal and laser signal from the FTS spectrometer. The wideband detector produces a composite signal comprising the laser signal and the spectral signal. The system further comprises a converter in communication with the wideband detector to receive and digitize the composite signal. The system further includes a signal processing unit that receives the composite signal from the converter. The signal processing unit further filters the laser signal and the spectral signal from the composite signal and demodulates the laser signal, to produce velocity corrected spectral data.

A technique for phase correction in Fourier transform spectroscopy

NASA Astrophysics Data System (ADS)

Artsang, P.; Pongchalee, P.; Palawong, K.; Buisset, C.; Meemon, P.

2018-03-01

Fourier transform spectroscopy (FTS) is a type of spectroscopy that can be used to analyze components in the sample. The basic setup that is commonly used in this technique is "Michelson interferometer". The interference signal obtained from interferometer can be Fourier transformed into the spectral pattern of the illuminating light source. To experimentally study the concept of the Fourier transform spectroscopy, the project started by setup the Michelson interferometer in the laboratory. The implemented system used a broadband light source in near infrared region (0.81-0.89 μm) and controlled the movable mirror by using computer controlled motorized translation stage. In the early study, there is no sample the interference path. Therefore, the theoretical spectral results after the Fourier transformation of the captured interferogram must be the spectral shape of the light source. One main challenge of the FTS is to retrieve the correct phase information of the inferferogram that relates with the correct spectral shape of the light source. One main source of the phase distortion in FTS that we observed from our system is the non-linear movement of the movable reference mirror of the Michelson interferometer. Therefore, to improve the result, we coupled a monochromatic light source to the implemented interferometer. We simultaneously measured the interferograms of the monochromatic and broadband light sources. The interferogram of the monochromatic light source was used to correct the phase of the interferogram of the broadband light source. The result shows significant improvement in the computed spectral shape.

Spectral-Element Seismic Wave Propagation Codes for both Forward Modeling in Complex Media and Adjoint Tomography

NASA Astrophysics Data System (ADS)

Smith, J. A.; Peter, D. B.; Tromp, J.; Komatitsch, D.; Lefebvre, M. P.

2015-12-01

We present both SPECFEM3D_Cartesian and SPECFEM3D_GLOBE open-source codes, representing high-performance numerical wave solvers simulating seismic wave propagation for local-, regional-, and global-scale application. These codes are suitable for both forward propagation in complex media and tomographic imaging. Both solvers compute highly accurate seismic wave fields using the continuous Galerkin spectral-element method on unstructured meshes. Lateral variations in compressional- and shear-wave speeds, density, as well as 3D attenuation Q models, topography and fluid-solid coupling are all readily included in both codes. For global simulations, effects due to rotation, ellipticity, the oceans, 3D crustal models, and self-gravitation are additionally included. Both packages provide forward and adjoint functionality suitable for adjoint tomography on high-performance computing architectures. We highlight the most recent release of the global version which includes improved performance, simultaneous MPI runs, OpenCL and CUDA support via an automatic source-to-source transformation library (BOAST), parallel I/O readers and writers for databases using ADIOS and seismograms using the recently developed Adaptable Seismic Data Format (ASDF) with built-in provenance. This makes our spectral-element solvers current state-of-the-art, open-source community codes for high-performance seismic wave propagation on arbitrarily complex 3D models. Together with these solvers, we provide full-waveform inversion tools to image the Earth's interior at unprecedented resolution.

3D coaxial out-of-plane metallic antennas for filtering and multi-spectral imaging in the infrared range.

PubMed

Jacassi, Andrea; Bozzola, Angelo; Zilio, Pierfrancesco; Tantussi, Francesco; De Angelis, Francesco

2016-06-27

We fabricated and investigated a new configuration of 3D coaxial metallic antennas working in the infrared which combines the strong lateral light scattering of vertical plasmonic structures with the selective spectral transmission of 2D arrays of coaxial apertures. The coaxial structures are fabricated with a top-down method based on a template of hollow 3D antennas. Each antenna has a multilayer radial structure consisting of dielectric and metallic materials not achievable in a 2D configuration. A planar metallic layer is inserted normally to the antennas. The outer dielectric shell of the antenna defines a nanometric gap between the horizontal plane and the vertical walls. Thanks to this aperture, light can tunnel to the other side of the plane, and be transmitted to the far field in a set of resonances. These are investigated with finite-elements electromagnetic calculations and with Fourier-transform infrared spectroscopy measurements. The spectral position of the resonances can be tuned by changing the lattice period and/or the antenna length. Thanks to the strong scattering provided by the 3D geometry, the transmission peaks possess a high signal-to-noise ratio even when the illuminated area is less than 2 × 2 times the operation wavelength. This opens new possibilities for multispectral imaging in the IR with wavelength-scale spatial resolution.

The software and algorithms for hyperspectral data processing

NASA Astrophysics Data System (ADS)

Shyrayeva, Anhelina; Martinov, Anton; Ivanov, Victor; Katkovsky, Leonid

2017-04-01

Hyperspectral remote sensing technique is widely used for collecting and processing -information about the Earth's surface objects. Hyperspectral data are combined to form a three-dimensional (x, y, λ) data cube. Department of Aerospace Research of the Institute of Applied Physical Problems of the Belarusian State University presents a general model of the software for hyperspectral image data analysis and processing. The software runs in Windows XP/7/8/8.1/10 environment on any personal computer. This complex has been has been written in C++ language using QT framework and OpenGL for graphical data visualization. The software has flexible structure that consists of a set of independent plugins. Each plugin was compiled as Qt Plugin and represents Windows Dynamic library (dll). Plugins can be categorized in terms of data reading types, data visualization (3D, 2D, 1D) and data processing The software has various in-built functions for statistical and mathematical analysis, signal processing functions like direct smoothing function for moving average, Savitzky-Golay smoothing technique, RGB correction, histogram transformation, and atmospheric correction. The software provides two author's engineering techniques for the solution of atmospheric correction problem: iteration method of refinement of spectral albedo's parameters using Libradtran and analytical least square method. The main advantages of these methods are high rate of processing (several minutes for 1 GB data) and low relative error in albedo retrieval (less than 15%). Also, the software supports work with spectral libraries, region of interest (ROI) selection, spectral analysis such as cluster-type image classification and automatic hypercube spectrum comparison by similarity criterion with similar ones from spectral libraries, and vice versa. The software deals with different kinds of spectral information in order to identify and distinguish spectrally unique materials. Also, the following advantages should be noted: fast and low memory hypercube manipulation features, user-friendly interface, modularity, and expandability.

Automated high-throughput assessment of prostate biopsy tissue using infrared spectroscopic chemical imaging

NASA Astrophysics Data System (ADS)

Bassan, Paul; Sachdeva, Ashwin; Shanks, Jonathan H.; Brown, Mick D.; Clarke, Noel W.; Gardner, Peter

2014-03-01

Fourier transform infrared (FT-IR) chemical imaging has been demonstrated as a promising technique to complement histopathological assessment of biomedical tissue samples. Current histopathology practice involves preparing thin tissue sections and staining them using hematoxylin and eosin (H&E) after which a histopathologist manually assess the tissue architecture under a visible microscope. Studies have shown that there is disagreement between operators viewing the same tissue suggesting that a complementary technique for verification could improve the robustness of the evaluation, and improve patient care. FT-IR chemical imaging allows the spatial distribution of chemistry to be rapidly imaged at a high (diffraction-limited) spatial resolution where each pixel represents an area of 5.5 × 5.5 μm2 and contains a full infrared spectrum providing a chemical fingerprint which studies have shown contains the diagnostic potential to discriminate between different cell-types, and even the benign or malignant state of prostatic epithelial cells. We report a label-free (i.e. no chemical de-waxing, or staining) method of imaging large pieces of prostate tissue (typically 1 cm × 2 cm) in tens of minutes (at a rate of 0.704 × 0.704 mm2 every 14.5 s) yielding images containing millions of spectra. Due to refractive index matching between sample and surrounding paraffin, minimal signal processing is required to recover spectra with their natural profile as opposed to harsh baseline correction methods, paving the way for future quantitative analysis of biochemical signatures. The quality of the spectral information is demonstrated by building and testing an automated cell-type classifier based upon spectral features.

Dynamics of modulated beams in spectral domain

DOE PAGES

Yampolsky, Nikolai A.

2017-07-16

General formalism for describing dynamics of modulated beams along linear beamlines is developed. We describe modulated beams with spectral distribution function which represents Fourier transform of the conventional beam distribution function in the 6-dimensional phase space. The introduced spectral distribution function is localized in some region of the spectral domain for nearly monochromatic modulations. It can be characterized with a small number of typical parameters such as the lowest order moments of the spectral distribution. We study evolution of the modulated beams in linear beamlines and find that characteristic spectral parameters transform linearly. The developed approach significantly simplifies analysis ofmore » various schemes proposed for seeding X-ray free electron lasers. We use this approach to study several recently proposed schemes and find the bandwidth of the output bunching in each case.« less

Parallel ICA and its hardware implementation in hyperspectral image analysis

NASA Astrophysics Data System (ADS)

Du, Hongtao; Qi, Hairong; Peterson, Gregory D.

2004-04-01

Advances in hyperspectral images have dramatically boosted remote sensing applications by providing abundant information using hundreds of contiguous spectral bands. However, the high volume of information also results in excessive computation burden. Since most materials have specific characteristics only at certain bands, a lot of these information is redundant. This property of hyperspectral images has motivated many researchers to study various dimensionality reduction algorithms, including Projection Pursuit (PP), Principal Component Analysis (PCA), wavelet transform, and Independent Component Analysis (ICA), where ICA is one of the most popular techniques. It searches for a linear or nonlinear transformation which minimizes the statistical dependence between spectral bands. Through this process, ICA can eliminate superfluous but retain practical information given only the observations of hyperspectral images. One hurdle of applying ICA in hyperspectral image (HSI) analysis, however, is its long computation time, especially for high volume hyperspectral data sets. Even the most efficient method, FastICA, is a very time-consuming process. In this paper, we present a parallel ICA (pICA) algorithm derived from FastICA. During the unmixing process, pICA divides the estimation of weight matrix into sub-processes which can be conducted in parallel on multiple processors. The decorrelation process is decomposed into the internal decorrelation and the external decorrelation, which perform weight vector decorrelations within individual processors and between cooperative processors, respectively. In order to further improve the performance of pICA, we seek hardware solutions in the implementation of pICA. Until now, there are very few hardware designs for ICA-related processes due to the complicated and iterant computation. This paper discusses capacity limitation of FPGA implementations for pICA in HSI analysis. A synthesis of Application-Specific Integrated Circuit (ASIC) is designed for pICA-based dimensionality reduction in HSI analysis. The pICA design is implemented using standard-height cells and aimed at TSMC 0.18 micron process. During the synthesis procedure, three ICA-related reconfigurable components are developed for the reuse and retargeting purpose. Preliminary results show that the standard-height cell based ASIC synthesis provide an effective solution for pICA and ICA-related processes in HSI analysis.

[Rapid Identification of Epicarpium Citri Grandis via Infrared Spectroscopy and Fluorescence Spectrum Imaging Technology Combined with Neural Network].

PubMed

Pan, Sha-sha; Huang, Fu-rong; Xiao, Chi; Xian, Rui-yi; Ma, Zhi-guo

2015-10-01

To explore rapid reliable methods for detection of Epicarpium citri grandis (ECG), the experiment using Fourier Transform Attenuated Total Reflection Infrared Spectroscopy (FTIR/ATR) and Fluorescence Spectrum Imaging Technology combined with Multilayer Perceptron (MLP) Neural Network pattern recognition, for the identification of ECG, and the two methods are compared. Infrared spectra and fluorescence spectral images of 118 samples, 81 ECG and 37 other kinds of ECG, are collected. According to the differences in tspectrum, the spectra data in the 550-1 800 cm(-1) wavenumber range and 400-720 nm wavelength are regarded as the study objects of discriminant analysis. Then principal component analysis (PCA) is applied to reduce the dimension of spectroscopic data of ECG and MLP Neural Network is used in combination to classify them. During the experiment were compared the effects of different methods of data preprocessing on the model: multiplicative scatter correction (MSC), standard normal variable correction (SNV), first-order derivative(FD), second-order derivative(SD) and Savitzky-Golay (SG). The results showed that: after the infrared spectra data via the Savitzky-Golay (SG) pretreatment through the MLP Neural Network with the hidden layer function as sigmoid, we can get the best discrimination of ECG, the correct percent of training set and testing set are both 100%. Using fluorescence spectral imaging technology, corrected by the multiple scattering (MSC) results in the pretreatment is the most ideal. After data preprocessing, the three layers of the MLP Neural Network of the hidden layer function as sigmoid function can get 100% correct percent of training set and 96.7% correct percent of testing set. It was shown that the FTIR/ATR and fluorescent spectral imaging technology combined with MLP Neural Network can be used for the identification study of ECG and has the advantages of rapid, reliable effect.

Design of a modified endoscope illuminator for spectral imaging of colorectal tissues

NASA Astrophysics Data System (ADS)

Browning, Craig M.; Mayes, Samuel; Rich, Thomas C.; Leavesley, Silas J.

2017-02-01

The gold standard for locating colonic polyps is a white light endoscope in a colonoscopy, however, polyps smaller than 5 mm can be easily missed. Modified procedures such as narrow band imaging have shown only marginal increases in detection rates. Spectral imaging is a potential solution to improve the sensitivity and specificity of colonoscopies by providing the ability to distinguish molecular fluorescence differences in tissues. The goal of this work is to implement a spectral endoscopic light source to acquire spectral image data of colorectal tissues. A beta-version endoscope light source was developed, by retrofitting a white light endoscope light source (Olympus, CLK-4) with 16 narrow band LEDs. This redesigned, beta-prototype uses high-power LEDs with a minimum output of 500 mW to provide sufficient spectral output (0.5 mW) through the endoscope. A mounting apparatus was designed to provide sufficient heat dissipation. Here, we report recent results of our tests to characterize the intensity output through the light source and endoscope to determine the flat spectral output for imaging and intensity losses through the endoscope. We also report preliminary spectral imaging data from transverse pig colon that demonstrates the ability to result in working practical spectral data. Preliminary results of this revised prototype spectral endoscope system demonstrate that there is sufficient power to allow the imaging process to continue and potentially determine spectral differences in cancerous and normal tissue from imaging ex vivo pairs. Future work will focus on building a spectral library for the colorectal region and refining the user interface the system for in vivo use.

Ortho-Rectification of Narrow Band Multi-Spectral Imagery Assisted by Dslr RGB Imagery Acquired by a Fixed-Wing Uas

NASA Astrophysics Data System (ADS)

Rau, J.-Y.; Jhan, J.-P.; Huang, C.-Y.

2015-08-01

Miniature Multiple Camera Array (MiniMCA-12) is a frame-based multilens/multispectral sensor composed of 12 lenses with narrow band filters. Due to its small size and light weight, it is suitable to mount on an Unmanned Aerial System (UAS) for acquiring high spectral, spatial and temporal resolution imagery used in various remote sensing applications. However, due to its wavelength range is only 10 nm that results in low image resolution and signal-to-noise ratio which are not suitable for image matching and digital surface model (DSM) generation. In the meantime, the spectral correlation among all 12 bands of MiniMCA images are low, it is difficult to perform tie-point matching and aerial triangulation at the same time. In this study, we thus propose the use of a DSLR camera to assist automatic aerial triangulation of MiniMCA-12 imagery and to produce higher spatial resolution DSM for MiniMCA12 ortho-image generation. Depending on the maximum payload weight of the used UAS, these two kinds of sensors could be collected at the same time or individually. In this study, we adopt a fixed-wing UAS to carry a Canon EOS 5D Mark2 DSLR camera and a MiniMCA-12 multi-spectral camera. For the purpose to perform automatic aerial triangulation between a DSLR camera and the MiniMCA-12, we choose one master band from MiniMCA-12 whose spectral range has overlap with the DSLR camera. However, all lenses of MiniMCA-12 have different perspective centers and viewing angles, the original 12 channels have significant band misregistration effect. Thus, the first issue encountered is to reduce the band misregistration effect. Due to all 12 MiniMCA lenses being frame-based, their spatial offsets are smaller than 15 cm and all images are almost 98% overlapped, we thus propose a modified projective transformation (MPT) method together with two systematic error correction procedures to register all 12 bands of imagery on the same image space. It means that those 12 bands of images acquired at the same exposure time will have same interior orientation parameters (IOPs) and exterior orientation parameters (EOPs) after band-to-band registration (BBR). Thus, in the aerial triangulation stage, the master band of MiniMCA-12 was treated as a reference channel to link with DSLR RGB images. It means, all reference images from the master band of MiniMCA-12 and all RGB images were triangulated at the same time with same coordinate system of ground control points (GCP). Due to the spatial resolution of RGB images is higher than the MiniMCA-12, the GCP can be marked on the RGB images only even they cannot be recognized on the MiniMCA images. Furthermore, a one meter gridded digital surface model (DSM) is created by the RGB images and applied to the MiniMCA imagery for ortho-rectification. Quantitative error analyses show that the proposed BBR scheme can achieve 0.33 pixels of average misregistration residuals length and the co-registration errors among 12 MiniMCA ortho-images and between MiniMCA and Canon RGB ortho-images are all less than 0.6 pixels. The experimental results demonstrate that the proposed method is robust, reliable and accurate for future remote sensing applications.

The extended Fourier transform for 2D spectral estimation.

PubMed

Armstrong, G S; Mandelshtam, V A

2001-11-01

We present a linear algebraic method, named the eXtended Fourier Transform (XFT), for spectral estimation from truncated time signals. The method is a hybrid of the discrete Fourier transform (DFT) and the regularized resolvent transform (RRT) (J. Chen et al., J. Magn. Reson. 147, 129-137 (2000)). Namely, it estimates the remainder of a finite DFT by RRT. The RRT estimation corresponds to solution of an ill-conditioned problem, which requires regularization. The regularization depends on a parameter, q, that essentially controls the resolution. By varying q from 0 to infinity one can "tune" the spectrum between a high-resolution spectral estimate and the finite DFT. The optimal value of q is chosen according to how well the data fits the form of a sum of complex sinusoids and, in particular, the signal-to-noise ratio. Both 1D and 2D XFT are presented with applications to experimental NMR signals. Copyright 2001 Academic Press.

Hyperspectral Image Analysis for Skin Tumor Detection

NASA Astrophysics Data System (ADS)

Kong, Seong G.; Park, Lae-Jeong

This chapter presents hyperspectral imaging of fluorescence for nonin-vasive detection of tumorous tissue on mouse skin. Hyperspectral imaging sensors collect two-dimensional (2D) image data of an object in a number of narrow, adjacent spectral bands. This high-resolution measurement of spectral information reveals a continuous emission spectrum for each image pixel useful for skin tumor detection. The hyperspectral image data used in this study are fluorescence intensities of a mouse sample consisting of 21 spectral bands in the visible spectrum of wavelengths ranging from 440 to 640 nm. Fluorescence signals are measured using a laser excitation source with the center wavelength of 337 nm. An acousto-optic tunable filter is used to capture individual spectral band images at a 10-nm resolution. All spectral band images are spatially registered with the reference band image at 490 nm to obtain exact pixel correspondences by compensating the offsets caused during the image capture procedure. The support vector machines with polynomial kernel functions provide decision boundaries with a maximum separation margin to classify malignant tumor and normal tissue from the observed fluorescence spectral signatures for skin tumor detection.

Analytical design of a hyper-spectral imaging spectrometer utilizing a convex grating

NASA Astrophysics Data System (ADS)

Kim, Seo H.; Kong, Hong J.; Ku, Hana; Lee, Jun H.

2012-09-01

This paper describes about the new design method for hyper-spectral Imaging spectrometers utilizing convex grating. Hyper-spectral imaging systems are power tools in the field of remote sensing. HSI systems collect at least 100 spectral bands of 10~20 nm width. Because the spectral signature is different and induced unique for each material, it should be possible to discriminate between one material and another based on difference in spectral signature of material. I mathematically analyzed parameters for the intellectual initial design. Main concept of this is the derivative of "ring of minimum aberration without vignetting". This work is a kind of analytical design of an Offner imaging spectrometer. Also, several experiment methods will be contrived to evaluate the performance of imaging spectrometer.

Investigation of Parallax Issues for Multi-Lens Multispectral Camera Band Co-Registration

NASA Astrophysics Data System (ADS)

Jhan, J. P.; Rau, J. Y.; Haala, N.; Cramer, M.

2017-08-01

The multi-lens multispectral cameras (MSCs), such as Micasense Rededge and Parrot Sequoia, can record multispectral information by each separated lenses. With their lightweight and small size, which making they are more suitable for mounting on an Unmanned Aerial System (UAS) to collect high spatial images for vegetation investigation. However, due to the multi-sensor geometry of multi-lens structure induces significant band misregistration effects in original image, performing band co-registration is necessary in order to obtain accurate spectral information. A robust and adaptive band-to-band image transform (RABBIT) is proposed to perform band co-registration of multi-lens MSCs. First is to obtain the camera rig information from camera system calibration, and utilizes the calibrated results for performing image transformation and lens distortion correction. Since the calibration uncertainty leads to different amount of systematic errors, the last step is to optimize the results in order to acquire a better co-registration accuracy. Due to the potential issues of parallax that will cause significant band misregistration effects when images are closer to the targets, four datasets thus acquired from Rededge and Sequoia were applied to evaluate the performance of RABBIT, including aerial and close-range imagery. From the results of aerial images, it shows that RABBIT can achieve sub-pixel accuracy level that is suitable for the band co-registration purpose of any multi-lens MSC. In addition, the results of close-range images also has same performance, if we focus on the band co-registration on specific target for 3D modelling, or when the target has equal distance to the camera.

Efficient material decomposition method for dual-energy X-ray cargo inspection system

NASA Astrophysics Data System (ADS)

Lee, Donghyeon; Lee, Jiseoc; Min, Jonghwan; Lee, Byungcheol; Lee, Byeongno; Oh, Kyungmin; Kim, Jaehyun; Cho, Seungryong

2018-03-01

Dual-energy X-ray inspection systems are widely used today for it provides X-ray attenuation contrast of the imaged object and also its material information. Material decomposition capability allows a higher detection sensitivity of potential targets including purposely loaded impurities in agricultural product inspections and threats in security scans for example. Dual-energy X-ray transmission data can be transformed into two basis material thickness data, and its transformation accuracy heavily relies on a calibration of material decomposition process. The calibration process in general can be laborious and time consuming. Moreover, a conventional calibration method is often challenged by the nonuniform spectral characteristics of the X-ray beam in the entire field-of-view (FOV). In this work, we developed an efficient material decomposition calibration process for a linear accelerator (LINAC) based high-energy X-ray cargo inspection system. We also proposed a multi-spot calibration method to improve the decomposition performance throughout the entire FOV. Experimental validation of the proposed method has been demonstrated by use of a cargo inspection system that supports 6 MV and 9 MV dual-energy imaging.

Fat suppression in magnetic resonance imaging of the head and neck region: is the two-point DIXON technique superior to spectral fat suppression?

PubMed

Wendl, Christina M; Eiglsperger, Johannes; Dendl, Lena-Marie; Brodoefel, Harald; Schebesch, Karl-Michael; Stroszczynski, Christian; Fellner, Claudia

2018-05-01

The aim of our study was to systematically compare two-point Dixon fat suppression (FS) and spectral FS techniques in contrast enhanced imaging of the head and neck region. Three independent readers analysed coronal T 1 weighted images recorded after contrast medium injection with Dixon and spectral FS techniques with regard to FS homogeneity, motion artefacts, lesion contrast, image sharpness and overall image quality. 85 patients were prospectively enrolled in the study. Images generated with Dixon-FS technique were of higher overall image quality and had a more homogenous FS over the whole field of view compared with the standard spectral fat-suppressed images (p < 0.001). Concerning motion artefacts, flow artefacts, lesion contrast and image sharpness no statistically significant difference was observed. The Dixon-FS technique is superior to the spectral technique due to improved homogeneity of FS and overall image quality while maintaining lesion contrast. Advances in knowledge: T 1 with Dixon FS technique offers, compared to spectral FS, significantly improved FS homogeneity and over all image quality in imaging of the head and neck region.

Research on hyperspectral dynamic scene and image sequence simulation

NASA Astrophysics Data System (ADS)

Sun, Dandan; Gao, Jiaobo; Sun, Kefeng; Hu, Yu; Li, Yu; Xie, Junhu; Zhang, Lei

2016-10-01

This paper presents a simulation method of hyper-spectral dynamic scene and image sequence for hyper-spectral equipment evaluation and target detection algorithm. Because of high spectral resolution, strong band continuity, anti-interference and other advantages, in recent years, hyper-spectral imaging technology has been rapidly developed and is widely used in many areas such as optoelectronic target detection, military defense and remote sensing systems. Digital imaging simulation, as a crucial part of hardware in loop simulation, can be applied to testing and evaluation hyper-spectral imaging equipment with lower development cost and shorter development period. Meanwhile, visual simulation can produce a lot of original image data under various conditions for hyper-spectral image feature extraction and classification algorithm. Based on radiation physic model and material characteristic parameters this paper proposes a generation method of digital scene. By building multiple sensor models under different bands and different bandwidths, hyper-spectral scenes in visible, MWIR, LWIR band, with spectral resolution 0.01μm, 0.05μm and 0.1μm have been simulated in this paper. The final dynamic scenes have high real-time and realistic, with frequency up to 100 HZ. By means of saving all the scene gray data in the same viewpoint image sequence is obtained. The analysis results show whether in the infrared band or the visible band, the grayscale variations of simulated hyper-spectral images are consistent with the theoretical analysis results.

In-vivo assessment of microvascular functional dynamics by combination of cmOCT and wavelet transform

NASA Astrophysics Data System (ADS)

Smirni, Salvatore; MacDonald, Michael P.; Robertson, Catherine P.; McNamara, Paul M.; O'Gorman, Sean; Leahy, Martin J.; Khan, Faisel

2018-02-01

The cutaneous microcirculation represents an index of the health status of the cardiovascular system. Conventional methods to evaluate skin microvascular function are based on measuring blood flow by laser Doppler in combination with reactive tests such as post-occlusive reactive hyperaemia (PORH). Moreover, the spectral analysis of blood flow signals by continuous wavelet transform (CWT) reveals nonlinear oscillations reflecting the functionality of microvascular biological factors, e.g. endothelial cells (ECs). Correlation mapping optical coherence tomography (cmOCT) has been previously described as an efficient methodology for the morphological visualisation of cutaneous micro-vessels. Here, we show that cmOCT flow maps can also provide information on the functional components of the microcirculation. A spectral domain optical coherence tomography (SD-OCT) imaging system was used to acquire 90 sequential 3D OCT volumes from the forearm of a volunteer, while challenging the micro-vessels with a PORH test. The volumes were sampled in a temporal window of 25 minutes, and were processed by cmOCT to obtain flow maps at different tissue depths. The images clearly show changes of flow in response to the applied stimulus. Furthermore, a blood flow signal was reconstructed from cmOCT maps intensities to investigate the microvascular nonlinear dynamics by CWT. The analysis revealed oscillations changing in response to PORH, associated with the activity of ECs and the sympathetic innervation. The results demonstrate that cmOCT may be potentially used as diagnostic tool for the assessment of microvascular function, with the advantage of also providing spatial resolution and structural information compared to the traditional laser Doppler techniques.

Image enhancement by spectral-error correction for dual-energy computed tomography.

PubMed

Park, Kyung-Kook; Oh, Chang-Hyun; Akay, Metin

2011-01-01

Dual-energy CT (DECT) was reintroduced recently to use the additional spectral information of X-ray attenuation and aims for accurate density measurement and material differentiation. However, the spectral information lies in the difference between low and high energy images or measurements, so that it is difficult to acquire accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, an image enhancement technique for DECT is proposed, based on the fact that the attenuation of a higher density material decreases more rapidly as X-ray energy increases. We define as spectral error the case when a pixel pair of low and high energy images deviates far from the expected attenuation trend. After analyzing the spectral-error sources of DECT images, we propose a DECT image enhancement method, which consists of three steps: water-reference offset correction, spectral-error correction, and anti-correlated noise reduction. It is the main idea of this work that makes spectral errors distributed like random noise over the true attenuation and suppressed by the well-known anti-correlated noise reduction. The proposed method suppressed noise of liver lesions and improved contrast between liver lesions and liver parenchyma in DECT contrast-enhanced abdominal images and their two-material decomposition.

Spectral K-edge subtraction imaging

NASA Astrophysics Data System (ADS)

Zhu, Y.; Samadi, N.; Martinson, M.; Bassey, B.; Wei, Z.; Belev, G.; Chapman, D.

2014-05-01

We describe a spectral x-ray transmission method to provide images of independent material components of an object using a synchrotron x-ray source. The imaging system and process is similar to K-edge subtraction (KES) imaging where two imaging energies are prepared above and below the K-absorption edge of a contrast element and a quantifiable image of the contrast element and a water equivalent image are obtained. The spectral method, termed ‘spectral-KES’ employs a continuous spectrum encompassing an absorption edge of an element within the object. The spectrum is prepared by a bent Laue monochromator with good focal and energy dispersive properties. The monochromator focuses the spectral beam at the object location, which then diverges onto an area detector such that one dimension in the detector is an energy axis. A least-squares method is used to interpret the transmitted spectral data with fits to either measured and/or calculated absorption of the contrast and matrix material-water. The spectral-KES system is very simple to implement and is comprised of a bent Laue monochromator, a stage for sample manipulation for projection and computed tomography imaging, and a pixelated area detector. The imaging system and examples of its applications to biological imaging are presented. The system is particularly well suited for a synchrotron bend magnet beamline with white beam access.

Spectral characterization of near-infrared acousto-optic tunable filter (AOTF) hyperspectral imaging systems using standard calibration materials.

PubMed

Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2011-04-01

In this study, we propose and evaluate a method for spectral characterization of acousto-optic tunable filter (AOTF) hyperspectral imaging systems in the near-infrared (NIR) spectral region from 900 nm to 1700 nm. The proposed spectral characterization method is based on the SRM-2035 standard reference material, exhibiting distinct spectral features, which enables robust non-rigid matching of the acquired and reference spectra. The matching is performed by simultaneously optimizing the parameters of the AOTF tuning curve, spectral resolution, baseline, and multiplicative effects. In this way, the tuning curve (frequency-wavelength characteristics) and the corresponding spectral resolution of the AOTF hyperspectral imaging system can be characterized simultaneously. Also, the method enables simple spectral characterization of the entire imaging plane of hyperspectral imaging systems. The results indicate that the method is accurate and efficient and can easily be integrated with systems operating in diffuse reflection or transmission modes. Therefore, the proposed method is suitable for characterization, calibration, or validation of AOTF hyperspectral imaging systems. © 2011 Society for Applied Spectroscopy

Statistical analysis of 16-year phase velocity distribution of mesospheric and ionospheric waves in airglow images: Comparison between Rikubetsu and Shigaraki, Japan

NASA Astrophysics Data System (ADS)

Tsuchiya, S.; Shiokawa, K.; Fujinami, H.; Otsuka, Y.; Nakamura, T.; Yamamoto, M.

2017-12-01

A new spectral analysis technique has been developed to obtain power spectra in the horizontal phase velocity by using the 3-D Fast Fourier Transform [Matsuda et al., JGR, 2014]. Takeo et al. (JGR, 2017) studied spectral parameters of atmospheric gravity waves (AGWs) in the mesopause region and medium-scale traveling ionospheric disturbances (MSTIDs) in the thermosphere over 16 years by using airglow images at wavelengths of 557.7 nm (emission altitudes: 90-100 km) and 630.0 nm (200-300 km) obtained at Shigaraki (34.8N, 136.1E), Japan. In this study, we have applied the same spectral analysis technique to the 557.7 nm and 630.0-nm airglow images obtained at Rikubetsu (43.5N, 143.8E), Japan, for 16 years from 1999 to 2014. We compared spectral features of AGWs and MSTIDs over 16 years observed at Shigaraki and Rikubetsu, which are separated by 1,174 km. The propagation direction of mesospheric AGWs seen in 557.7-nm airglow images is northeastward in summer and southwestward in winter at both Shigaraki and Rikubetsu, probably due to wind filtering of these waves by the mesospheric jet. In winter, the propagation direction of AGWs gradually shifted from southwestward to northwestward as time progresses from evening to morning at both stations. We suggest that this local-time shift of propagation direction can also be explained by the wind filtering effect. The propagation direction of AGWs changed from southwestward to northeastward at Rikubetsu on the day of the reversal of eastward zonal wind at 60N and 10 hPa (about 35 km in altitude) by the stratospheric sudden warming (SSW), while such a SSW-associated change was not identified at Shigaraki, indicating that the effect of SSW wind reversal reached only to the Rikubetsu latitudes. For MSTIDs, there is a negative correlation between yearly variation of powers spectral density and F10.7 flux and propagation direction is southwestward in all season at both Shigaraki and Rikubetsu. This negative correlation can be explained by considering the linear growth rate of the Perkins instability which is a cause of the nighttime MSTIDs.

CytoSpectre: a tool for spectral analysis of oriented structures on cellular and subcellular levels.

PubMed

Kartasalo, Kimmo; Pölönen, Risto-Pekka; Ojala, Marisa; Rasku, Jyrki; Lekkala, Jukka; Aalto-Setälä, Katriina; Kallio, Pasi

2015-10-26

Orientation and the degree of isotropy are important in many biological systems such as the sarcomeres of cardiomyocytes and other fibrillar structures of the cytoskeleton. Image based analysis of such structures is often limited to qualitative evaluation by human experts, hampering the throughput, repeatability and reliability of the analyses. Software tools are not readily available for this purpose and the existing methods typically rely at least partly on manual operation. We developed CytoSpectre, an automated tool based on spectral analysis, allowing the quantification of orientation and also size distributions of structures in microscopy images. CytoSpectre utilizes the Fourier transform to estimate the power spectrum of an image and based on the spectrum, computes parameter values describing, among others, the mean orientation, isotropy and size of target structures. The analysis can be further tuned to focus on targets of particular size at cellular or subcellular scales. The software can be operated via a graphical user interface without any programming expertise. We analyzed the performance of CytoSpectre by extensive simulations using artificial images, by benchmarking against FibrilTool and by comparisons with manual measurements performed for real images by a panel of human experts. The software was found to be tolerant against noise and blurring and superior to FibrilTool when analyzing realistic targets with degraded image quality. The analysis of real images indicated general good agreement between computational and manual results while also revealing notable expert-to-expert variation. Moreover, the experiment showed that CytoSpectre can handle images obtained of different cell types using different microscopy techniques. Finally, we studied the effect of mechanical stretching on cardiomyocytes to demonstrate the software in an actual experiment and observed changes in cellular orientation in response to stretching. CytoSpectre, a versatile, easy-to-use software tool for spectral analysis of microscopy images was developed. The tool is compatible with most 2D images and can be used to analyze targets at different scales. We expect the tool to be useful in diverse applications dealing with structures whose orientation and size distributions are of interest. While designed for the biological field, the software could also be useful in non-biological applications.

Lossless compression algorithm for multispectral imagers

NASA Astrophysics Data System (ADS)

Gladkova, Irina; Grossberg, Michael; Gottipati, Srikanth

2008-08-01

Multispectral imaging is becoming an increasingly important tool for monitoring the earth and its environment from space borne and airborne platforms. Multispectral imaging data consists of visible and IR measurements from a scene across space and spectrum. Growing data rates resulting from faster scanning and finer spatial and spectral resolution makes compression an increasingly critical tool to reduce data volume for transmission and archiving. Research for NOAA NESDIS has been directed to finding for the characteristics of satellite atmospheric Earth science Imager sensor data what level of Lossless compression ratio can be obtained as well as appropriate types of mathematics and approaches that can lead to approaching this data's entropy level. Conventional lossless do not achieve the theoretical limits for lossless compression on imager data as estimated from the Shannon entropy. In a previous paper, the authors introduce a lossless compression algorithm developed for MODIS as a proxy for future NOAA-NESDIS satellite based Earth science multispectral imagers such as GOES-R. The algorithm is based on capturing spectral correlations using spectral prediction, and spatial correlations with a linear transform encoder. In decompression, the algorithm uses a statistically computed look up table to iteratively predict each channel from a channel decompressed in the previous iteration. In this paper we present a new approach which fundamentally differs from our prior work. In this new approach, instead of having a single predictor for each pair of bands we introduce a piecewise spatially varying predictor which significantly improves the compression results. Our new algorithm also now optimizes the sequence of channels we use for prediction. Our results are evaluated by comparison with a state of the art wavelet based image compression scheme, Jpeg2000. We present results on the 14 channel subset of the MODIS imager, which serves as a proxy for the GOES-R imager. We will also show results of the algorithm for on NOAA AVHRR data and data from SEVIRI. The algorithm is designed to be adapted to the wide range of multispectral imagers and should facilitate distribution of data throughout globally. This compression research is managed by Roger Heymann, PE of OSD NOAA NESDIS Engineering, in collaboration with the NOAA NESDIS STAR Research Office through Mitch Goldberg, Tim Schmit, Walter Wolf.

Characterization of a compact 6-band multifunctional camera based on patterned spectral filters in the focal plane

NASA Astrophysics Data System (ADS)

Torkildsen, H. E.; Hovland, H.; Opsahl, T.; Haavardsholm, T. V.; Nicolas, S.; Skauli, T.

2014-06-01

In some applications of multi- or hyperspectral imaging, it is important to have a compact sensor. The most compact spectral imaging sensors are based on spectral filtering in the focal plane. For hyperspectral imaging, it has been proposed to use a "linearly variable" bandpass filter in the focal plane, combined with scanning of the field of view. As the image of a given object in the scene moves across the field of view, it is observed through parts of the filter with varying center wavelength, and a complete spectrum can be assembled. However if the radiance received from the object varies with viewing angle, or with time, then the reconstructed spectrum will be distorted. We describe a camera design where this hyperspectral functionality is traded for multispectral imaging with better spectral integrity. Spectral distortion is minimized by using a patterned filter with 6 bands arranged close together, so that a scene object is seen by each spectral band in rapid succession and with minimal change in viewing angle. The set of 6 bands is repeated 4 times so that the spectral data can be checked for internal consistency. Still the total extent of the filter in the scan direction is small. Therefore the remainder of the image sensor can be used for conventional imaging with potential for using motion tracking and 3D reconstruction to support the spectral imaging function. We show detailed characterization of the point spread function of the camera, demonstrating the importance of such characterization as a basis for image reconstruction. A simplified image reconstruction based on feature-based image coregistration is shown to yield reasonable results. Elimination of spectral artifacts due to scene motion is demonstrated.

A novel and compact spectral imaging system based on two curved prisms

NASA Astrophysics Data System (ADS)

Nie, Yunfeng; Bin, Xiangli; Zhou, Jinsong; Li, Yang

2013-09-01

As a novel detection approach which simultaneously acquires two-dimensional visual picture and one-dimensional spectral information, spectral imaging offers promising applications on biomedical imaging, conservation and identification of artworks, surveillance of food safety, and so forth. A novel moderate-resolution spectral imaging system consisting of merely two optical elements is illustrated in this paper. It can realize the function of a relay imaging system as well as a 10nm spectral resolution spectroscopy. Compared to conventional prismatic imaging spectrometers, this design is compact and concise with only two special curved prisms by utilizing two reflective surfaces. In contrast to spectral imagers based on diffractive grating, the usage of compound-prism possesses characteristics of higher energy utilization and wider free spectral range. The seidel aberration theory and dispersive principle of this special prism are analyzed at first. According to the results, the optical system of this design is simulated, and the performance evaluation including spot diagram, MTF and distortion, is presented. In the end, considering the difficulty and particularity of manufacture and alignment, an available method for fabrication and measurement is proposed.

3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).

Characterization of a digital camera as an absolute tristimulus colorimeter

NASA Astrophysics Data System (ADS)

Martinez-Verdu, Francisco; Pujol, Jaume; Vilaseca, Meritxell; Capilla, Pascual

2003-01-01

An algorithm is proposed for the spectral and colorimetric characterization of digital still cameras (DSC) which allows to use them as tele-colorimeters with CIE-XYZ color output, in cd/m2. The spectral characterization consists of the calculation of the color-matching functions from the previously measured spectral sensitivities. The colorimetric characterization consists of transforming the RGB digital data into absolute tristimulus values CIE-XYZ (in cd/m2) under variable and unknown spectroradiometric conditions. Thus, at the first stage, a gray balance has been applied over the RGB digital data to convert them into RGB relative colorimetric values. At a second stage, an algorithm of luminance adaptation vs. lens aperture has been inserted in the basic colorimetric profile. Capturing the ColorChecker chart under different light sources, the DSC color analysis accuracy indexes, both in a raw state and with the corrections from a linear model of color correction, have been evaluated using the Pointer'86 color reproduction index with the unrelated Hunt'91 color appearance model. The results indicate that our digital image capture device, in raw performance, lightens and desaturates the colors.

Neuro-classification of multi-type Landsat Thematic Mapper data

NASA Technical Reports Server (NTRS)

Zhuang, Xin; Engel, Bernard A.; Fernandez, R. N.; Johannsen, Chris J.

1991-01-01

Neural networks have been successful in image classification and have shown potential for classifying remotely sensed data. This paper presents classifications of multitype Landsat Thematic Mapper (TM) data using neural networks. The Landsat TM Image for March 23, 1987 with accompanying ground observation data for a study area In Miami County, Indiana, U.S.A. was utilized to assess recognition of crop residues. Principal components and spectral ratio transformations were performed on the TM data. In addition, a layer of the geographic information system (GIS) for the study site was incorporated to generate GIS-enhanced TM data. This paper discusses (1) the performance of neuro-classification on each type of data, (2) how neural networks recognized each type of data as a new image and (3) comparisons of the results for each type of data obtained using neural networks, maximum likelihood, and minimum distance classifiers.

A scale-invariant change detection method for land use/cover change research

NASA Astrophysics Data System (ADS)

Xing, Jin; Sieber, Renee; Caelli, Terrence

2018-07-01

Land Use/Cover Change (LUCC) detection relies increasingly on comparing remote sensing images with different spatial and spectral scales. Based on scale-invariant image analysis algorithms in computer vision, we propose a scale-invariant LUCC detection method to identify changes from scale heterogeneous images. This method is composed of an entropy-based spatial decomposition, two scale-invariant feature extraction methods, Maximally Stable Extremal Region (MSER) and Scale-Invariant Feature Transformation (SIFT) algorithms, a spatial regression voting method to integrate MSER and SIFT results, a Markov Random Field-based smoothing method, and a support vector machine classification method to assign LUCC labels. We test the scale invariance of our new method with a LUCC case study in Montreal, Canada, 2005-2012. We found that the scale-invariant LUCC detection method provides similar accuracy compared with the resampling-based approach but this method avoids the LUCC distortion incurred by resampling.

Hyperspectral retinal imaging with a spectrally tunable light source

NASA Astrophysics Data System (ADS)

Francis, Robert P.; Zuzak, Karel J.; Ufret-Vincenty, Rafael

2011-03-01

Hyperspectral retinal imaging can measure oxygenation and identify areas of ischemia in human patients, but the devices used by current researchers are inflexible in spatial and spectral resolution. We have developed a flexible research prototype consisting of a DLP®-based spectrally tunable light source coupled to a fundus camera to quickly explore the effects of spatial resolution, spectral resolution, and spectral range on hyperspectral imaging of the retina. The goal of this prototype is to (1) identify spectral and spatial regions of interest for early diagnosis of diseases such as glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy (DR); and (2) define required specifications for commercial products. In this paper, we describe the challenges and advantages of using a spectrally tunable light source for hyperspectral retinal imaging, present clinical results of initial imaging sessions, and describe how this research can be leveraged into specifying a commercial product.

Camouflage target detection via hyperspectral imaging plus information divergence measurement

NASA Astrophysics Data System (ADS)

Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Ji, Yiqun; Shen, Weimin

2016-01-01

Target detection is one of most important applications in remote sensing. Nowadays accurate camouflage target distinction is often resorted to spectral imaging technique due to its high-resolution spectral/spatial information acquisition ability as well as plenty of data processing methods. In this paper, hyper-spectral imaging technique together with spectral information divergence measure method is used to solve camouflage target detection problem. A self-developed visual-band hyper-spectral imaging device is adopted to collect data cubes of certain experimental scene before spectral information divergences are worked out so as to discriminate target camouflage and anomaly. Full-band information divergences are measured to evaluate target detection effect visually and quantitatively. Information divergence measurement is proved to be a low-cost and effective tool for target detection task and can be further developed to other target detection applications beyond spectral imaging technique.

An algorithm for chlorophyll using first difference transformations of AVIRIS reflectance spectra

NASA Technical Reports Server (NTRS)

Novo, Evlyn; Gastil, Mary; Melack, John

1995-01-01

Experimental results have shown the existence of a strong relationship between chlorophyll alpha concentration and remote sensing reflectance measured at lake level with a high resolution spectroradiometer. The objective of our study was to investigate the relationship between surface chlorophyll alpha concentration at Mono Lake and water reflectance retrieved from Airborne Visible - Infrared Imaging Spectrometer (AVIRIS) data obtained in october 7, 1992. AVIRIS data were atmospherically corrected as described by Green et al. A description of the lake-level sampling is found in Melack and Gastil. The relationship between chlorophyll concentration and both the single band reflectance and the first difference transformation of the reflectance spectra for the first 40 AVIRIS spectral bands (400 nm to 740 nm) was examined. The relationship was then used to produce a map of the surface chlorophyll distribution.

Influence of the cubic spectral phase of high-power laser pulses on their self-phase modulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ginzburg, V N; Kochetkov, A A; Yakovlev, I V

2016-02-28

Spectral broadening of high-power transform-limited laser pulses under self-phase modulation in a medium with cubic nonlinearity is widely used to reduce pulse duration and to increase its power. It is shown that the cubic spectral phase of the initial pulse leads to a qualitatively different broadening of its spectrum: the spectrum has narrow peaks and broadening decreases. However, the use of chirped mirrors allows such pulses to be as effectively compressed as transform-limited pulses. (nonlinear optical phenomena)

Comparative studies on cervical and colonic malignancies using FTIR microspectroscopy

NASA Astrophysics Data System (ADS)

Mordechai, Shaul; Mark, Shlomo; Podshyvalov, A.; Kantarovich, Keren; Bernshtain, Y.; Salman, Ahmad; Erukhimovitch, Vitaly; Guterman, Hugo; Goldstein, Jed; Argov, Shmuel; Jagannathan, R.

2003-07-01

IR spectroscopy provides a new diagnostic tool due to its sensitivity to molecular composition and structure in cells, which accompany transformation from healthy to diseased state. The IR spectrum of a sample is, therefore, a biochemical fingerprint. It has been found that the most significant changes occur in the mid-IR spectral range 3-25 mm. Encouraging results have been reported in the literature on various types of cancers, such as human breast, lung, colon, cervical, and leukemia using FT-IR microspectroscopy. Much progress has also been made by several groups on IR spectral maps and IR imaging with good agreement between the data and the histopathological information. In an attempt to characterize healthy and diseased tissues, infrared microspectroscopy of cervical and colon human tissues was studied using an infrared microscopy. The comparative qualitative and quantitative changes detected using FTIR microspectroscopy are discussed.

Task-oriented comparison of power spectral density estimation methods for quantifying acoustic attenuation in diagnostic ultrasound using a reference phantom method.

PubMed

Rosado-Mendez, Ivan M; Nam, Kibo; Hall, Timothy J; Zagzebski, James A

2013-07-01

Reported here is a phantom-based comparison of methods for determining the power spectral density (PSD) of ultrasound backscattered signals. Those power spectral density values are then used to estimate parameters describing α(f), the frequency dependence of the acoustic attenuation coefficient. Phantoms were scanned with a clinical system equipped with a research interface to obtain radiofrequency echo data. Attenuation, modeled as a power law α(f)= α0 f (β), was estimated using a reference phantom method. The power spectral density was estimated using the short-time Fourier transform (STFT), Welch's periodogram, and Thomson's multitaper technique, and performance was analyzed when limiting the size of the parameter-estimation region. Errors were quantified by the bias and standard deviation of the α0 and β estimates, and by the overall power-law fit error (FE). For parameter estimation regions larger than ~34 pulse lengths (~1 cm for this experiment), an overall power-law FE of 4% was achieved with all spectral estimation methods. With smaller parameter estimation regions as in parametric image formation, the bias and standard deviation of the α0 and β estimates depended on the size of the parameter estimation region. Here, the multitaper method reduced the standard deviation of the α0 and β estimates compared with those using the other techniques. The results provide guidance for choosing methods for estimating the power spectral density in quantitative ultrasound methods.

[Research on Spectral Polarization Imaging System Based on Static Modulation].

PubMed

Zhao, Hai-bo; Li, Huan; Lin, Xu-ling; Wang, Zheng

2015-04-01

The main disadvantages of traditional spectral polarization imaging system are: complex structure, with moving parts, low throughput. A novel method of spectral polarization imaging system is discussed, which is based on static polarization intensity modulation combined with Savart polariscope interference imaging. The imaging system can obtain real-time information of spectral and four Stokes polarization messages. Compared with the conventional methods, the advantages of the imaging system are compactness, low mass and no moving parts, no electrical control, no slit and big throughput. The system structure and the basic theory are introduced. The experimental system is established in the laboratory. The experimental system consists of reimaging optics, polarization intensity module, interference imaging module, and CCD data collecting and processing module. The spectral range is visible and near-infrared (480-950 nm). The white board and the plane toy are imaged by using the experimental system. The ability of obtaining spectral polarization imaging information is verified. The calibration system of static polarization modulation is set up. The statistical error of polarization degree detection is less than 5%. The validity and feasibility of the basic principle is proved by the experimental result. The spectral polarization data captured by the system can be applied to object identification, object classification and remote sensing detection.

Study on multispectral imaging detection and recognition

NASA Astrophysics Data System (ADS)

Jun, Wang; Na, Ding; Gao, Jiaobo; Yu, Hu; Jun, Wu; Li, Junna; Zheng, Yawei; Fei, Gao; Sun, Kefeng

2009-07-01

Multispectral imaging detecting technology use target radiation character in spectral spatial distribution and relation between spectral and image to detect target and remote sensing measure. Its speciality is multi channel, narrow bandwidth, large amount of information, high accuracy. The ability of detecting target in environment of clutter, camouflage, concealment and beguilement is improved. At present, spectral imaging technology in the range of multispectral and hyperspectral develop greatly. The multispectral imaging equipment of unmanned aerial vehicle can be used in mine detection, information, surveillance and reconnaissance. Spectral imaging spectrometer operating in MWIR and LWIR has already been applied in the field of remote sensing and military in the advanced country. The paper presents the technology of multispectral imaging. It can enhance the reflectance, scatter and radiation character of the artificial targets among nature background. The targets among complex background and camouflage/stealth targets can be effectively identified. The experiment results and the data of spectral imaging is obtained.

Nonlinear Fusion of Multispectral Citrus Fruit Image Data with Information Contents.

PubMed

Li, Peilin; Lee, Sang-Heon; Hsu, Hung-Yao; Park, Jae-Sam

2017-01-13

The main issue of vison-based automatic harvesting manipulators is the difficulty in the correct fruit identification in the images under natural lighting conditions. Mostly, the solution has been based on a linear combination of color components in the multispectral images. However, the results have not reached a satisfactory level. To overcome this issue, this paper proposes a robust nonlinear fusion method to augment the original color image with the synchronized near infrared image. The two images are fused with Daubechies wavelet transform (DWT) in a multiscale decomposition approach. With DWT, the background noises are reduced and the necessary image features are enhanced by fusing the color contrast of the color components and the homogeneity of the near infrared (NIR) component. The resulting fused color image is classified with a C-means algorithm for reconstruction. The performance of the proposed approach is evaluated with the statistical F measure in comparison to some existing methods using linear combinations of color components. The results show that the fusion of information in different spectral components has the advantage of enhancing the image quality, therefore improving the classification accuracy in citrus fruit identification in natural lighting conditions.

Nonlinear Fusion of Multispectral Citrus Fruit Image Data with Information Contents

PubMed Central

Li, Peilin; Lee, Sang-Heon; Hsu, Hung-Yao; Park, Jae-Sam

2017-01-01

The main issue of vison-based automatic harvesting manipulators is the difficulty in the correct fruit identification in the images under natural lighting conditions. Mostly, the solution has been based on a linear combination of color components in the multispectral images. However, the results have not reached a satisfactory level. To overcome this issue, this paper proposes a robust nonlinear fusion method to augment the original color image with the synchronized near infrared image. The two images are fused with Daubechies wavelet transform (DWT) in a multiscale decomposition approach. With DWT, the background noises are reduced and the necessary image features are enhanced by fusing the color contrast of the color components and the homogeneity of the near infrared (NIR) component. The resulting fused color image is classified with a C-means algorithm for reconstruction. The performance of the proposed approach is evaluated with the statistical F measure in comparison to some existing methods using linear combinations of color components. The results show that the fusion of information in different spectral components has the advantage of enhancing the image quality, therefore improving the classification accuracy in citrus fruit identification in natural lighting conditions. PMID:28098797

Snapshot hyperspectral retinal imaging using compact spectral resolving detector array.

PubMed

Li, Hao; Liu, Wenzhong; Dong, Biqin; Kaluzny, Joel V; Fawzi, Amani A; Zhang, Hao F

2017-06-01

Hyperspectral retinal imaging captures the light spectrum from each imaging pixel. It provides spectrally encoded retinal physiological and morphological information, which could potentially benefit diagnosis and therapeutic monitoring of retinal diseases. The key challenges in hyperspectral retinal imaging are how to achieve snapshot imaging to avoid motions between the images from multiple spectral bands, and how to design a compact snapshot imager suitable for clinical use. Here, we developed a compact, snapshot hyperspectral fundus camera for rodents using a novel spectral resolving detector array (SRDA), on which a thin-film Fabry-Perot cavity filter was monolithically fabricated on each imaging pixel. We achieved hyperspectral retinal imaging with 16 wavelength bands (460 to 630 nm) at 20 fps. We also demonstrated false-color vessel contrast enhancement and retinal oxygen saturation (sO 2 ) measurement through spectral analysis. This work could potentially bring hyperspectral retinal imaging from bench to bedside. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fresnel zone plate light field spectral imaging simulation

NASA Astrophysics Data System (ADS)

Hallada, Francis D.; Franz, Anthony L.; Hawks, Michael R.

2017-05-01

Through numerical simulation, we have demonstrated a novel snapshot spectral imaging concept using binary diffractive optics. Binary diffractive optics, such as Fresnel zone plates (FZP) or photon sieves, can be used as the single optical element in a spectral imager that conducts both imaging and dispersion. In previous demonstrations of spectral imaging with diffractive optics, the detector array was physically translated along the optic axis to measure different image formation planes. In this new concept the wavelength-dependent images are constructed synthetically, by using integral photography concepts commonly applied to light field (plenoptic) cameras. Light field cameras use computational digital refocusing methods after exposure to make images at different object distances. Our concept refocuses to make images at different wavelengths instead of different object distances. The simulations in this study demonstrate this concept for an imager designed with a FZP. Monochromatic light from planar sources is propagated through the system to a measurement plane using wave optics in the Fresnel approximation. Simple images, placed at optical infinity, are illuminated by monochromatic sources and then digitally refocused to show different spectral bins. We show the formation of distinct images from different objects, illuminated by monochromatic sources in the VIS/NIR spectrum. Additionally, this concept could easily be applied to imaging in the MWIR and LWIR ranges. In conclusion, this new type of imager offers a rugged and simple optical design for snapshot spectral imaging and warrants further development.

Fluorescent marker-based and marker-free discrimination between healthy and cancerous human tissues using hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

2015-06-01

Two problems are addressed in this paper (i) the fluorescent marker-based and the (ii) marker-free discrimination between healthy and cancerous human tissues. For both applications the performance of hyper-spectral methods are quantified. Fluorescent marker-based tissue classification uses a number of fluorescent markers to dye specific parts of a human cell. The challenge is that the emission spectra of the fluorescent dyes overlap considerably. They are, furthermore disturbed by the inherent auto-fluorescence of human tissue. This results in ambiguities and decreased image contrast causing difficulties for the treatment decision. The higher spectral resolution introduced by tunable-filter-based spectral imaging in combination with spectral unmixing techniques results in an improvement of the image contrast and therefore more reliable information for the physician to choose the treatment decision. Marker-free tissue classification is based solely on the subtle spectral features of human tissue without the use of artificial markers. The challenge in this case is that the spectral differences between healthy and cancerous tissues are subtle and embedded in intra- and inter-patient variations of these features. The contributions of this paper are (i) the evaluation of hyper-spectral imaging in combination with spectral unmixing techniques for fluorescence marker-based tissue classification, (ii) the evaluation of spectral imaging for marker-free intra surgery tissue classification. Within this paper, we consider real hyper-spectral fluorescence and endoscopy data sets to emphasize the practical capability of the proposed methods. It is shown that the combination of spectral imaging with multivariate statistical methods can improve the sensitivity and specificity of the detection and the staging of cancerous tissues compared to standard procedures.

Detecting early stage pressure ulcer on dark skin using multispectral imager

NASA Astrophysics Data System (ADS)

Kong, Linghua; Sprigle, Stephen; Yi, Dingrong; Wang, Chao; Wang, Fengtao; Liu, Fuhan; Wang, Jiwu; Zhao, Futing

2009-10-01

This paper introduces a novel idea, innovative technology in building multi spectral imaging based device. The benefit from them is people can have low cost, handheld and standing alone device which makes acquire multi spectral images real time with just a snapshot. The paper for the first time publishes some images got from such prototyped miniaturized multi spectral imager.

A semi-Lagrangian advection scheme for radioactive tracers in a regional spectral model

NASA Astrophysics Data System (ADS)

Chang, E.-C.; Yoshimura, K.

2015-06-01

In this study, the non-iteration dimensional-split semi-Lagrangian (NDSL) advection scheme is applied to the National Centers for Environmental Prediction (NCEP) regional spectral model (RSM) to alleviate the Gibbs phenomenon. The Gibbs phenomenon is a problem wherein negative values of positive-definite quantities (e.g., moisture and tracers) are generated by the spectral space transformation in a spectral model system. To solve this problem, the spectral prognostic specific humidity and radioactive tracer advection scheme is replaced by the NDSL advection scheme, which considers advection of tracers in a grid system without spectral space transformations. A regional version of the NDSL is developed in this study and is applied to the RSM. Idealized experiments show that the regional version of the NDSL is successful. The model runs for an actual case study suggest that the NDSL can successfully advect radioactive tracers (iodine-131 and cesium-137) without noise from the Gibbs phenomenon. The NDSL can also remove negative specific humidity values produced in spectral calculations without losing detailed features.

Programmable Remapper with Single Flow Architecture

NASA Technical Reports Server (NTRS)

Fisher, Timothy E. (Inventor)

1993-01-01

An apparatus for image processing comprising a camera for receiving an original visual image and transforming the original visual image into an analog image, a first converter for transforming the analog image of the camera to a digital image, a processor having a single flow architecture for receiving the digital image and producing, with a single algorithm, an output image, a second converter for transforming the digital image of the processor to an analog image, and a viewer for receiving the analog image, transforming the analog image into a transformed visual image for observing the transformations applied to the original visual image. The processor comprises one or more subprocessors for the parallel reception of a digital image for producing an output matrix of the transformed visual image. More particularly, the processor comprises a plurality of subprocessors for receiving in parallel and transforming the digital image for producing a matrix of the transformed visual image, and an output interface means for receiving the respective portions of the transformed visual image from the respective subprocessor for producing an output matrix of the transformed visual image.

Hyper-spectral image segmentation using spectral clustering with covariance descriptors

NASA Astrophysics Data System (ADS)

Kursun, Olcay; Karabiber, Fethullah; Koc, Cemalettin; Bal, Abdullah

2009-02-01

Image segmentation is an important and difficult computer vision problem. Hyper-spectral images pose even more difficulty due to their high-dimensionality. Spectral clustering (SC) is a recently popular clustering/segmentation algorithm. In general, SC lifts the data to a high dimensional space, also known as the kernel trick, then derive eigenvectors in this new space, and finally using these new dimensions partition the data into clusters. We demonstrate that SC works efficiently when combined with covariance descriptors that can be used to assess pixelwise similarities rather than in the high-dimensional Euclidean space. We present the formulations and some preliminary results of the proposed hybrid image segmentation method for hyper-spectral images.

Development of a digital-micromirror-device-based multishot snapshot spectral imaging system.

PubMed

Wu, Yuehao; Mirza, Iftekhar O; Arce, Gonzalo R; Prather, Dennis W

2011-07-15

We report on the development of a digital-micromirror-device (DMD)-based multishot snapshot spectral imaging (DMD-SSI) system as an alternative to current piezostage-based multishot coded aperture snapshot spectral imager (CASSI) systems. In this system, a DMD is used to implement compressive sensing (CS) measurement patterns for reconstructing the spatial/spectral information of an imaging scene. Based on the CS measurement results, we demonstrated the concurrent reconstruction of 24 spectral images. The DMD-SSI system is versatile in nature as it can be used to implement independent CS measurement patterns in addition to spatially shifted patterns that piezostage-based systems can offer. © 2011 Optical Society of America

Evaluation of the effects of the seasonal variation of solar elevation angle and azimuth on the processes of digital filtering and thematic classification of relief units

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Novo, E. M. L. M.

1983-01-01

The effects of the seasonal variation of illumination over digital processing of LANDSAT images are evaluated. Two sets of LANDSAT data referring to the orbit 150 and row 28 were selected with illumination parameters varying from 43 deg to 64 deg for azimuth and from 30 deg to 36 deg for solar elevation respectively. IMAGE-100 system permitted the digital processing of LANDSAT data. Original images were transformed by means of digital filtering so as to enhance their spatial features. The resulting images were used to obtain an unsupervised classification of relief units. Topographic variables (declivity, altitude, relief range and slope length) were used to identify the true relief units existing on the ground. The LANDSAT over pass data show that digital processing is highly affected by illumination geometry, and there is no correspondence between relief units as defined by spectral features and those resulting from topographic features.

A Robust Image Watermarking in the Joint Time-Frequency Domain

NASA Astrophysics Data System (ADS)

Öztürk, Mahmut; Akan, Aydın; Çekiç, Yalçın

2010-12-01

With the rapid development of computers and internet applications, copyright protection of multimedia data has become an important problem. Watermarking techniques are proposed as a solution to copyright protection of digital media files. In this paper, a new, robust, and high-capacity watermarking method that is based on spatiofrequency (SF) representation is presented. We use the discrete evolutionary transform (DET) calculated by the Gabor expansion to represent an image in the joint SF domain. The watermark is embedded onto selected coefficients in the joint SF domain. Hence, by combining the advantages of spatial and spectral domain watermarking methods, a robust, invisible, secure, and high-capacity watermarking method is presented. A correlation-based detector is also proposed to detect and extract any possible watermarks on an image. The proposed watermarking method was tested on some commonly used test images under different signal processing attacks like additive noise, Wiener and Median filtering, JPEG compression, rotation, and cropping. Simulation results show that our method is robust against all of the attacks.

Evaluating visibility of age spot and freckle based on simulated spectral reflectance distribution and facial color image

NASA Astrophysics Data System (ADS)

Hirose, Misa; Toyota, Saori; Tsumura, Norimichi

2018-02-01

In this research, we evaluate the visibility of age spot and freckle with changing the blood volume based on simulated spectral reflectance distribution and the actual facial color images, and compare these results. First, we generate three types of spatial distribution of age spot and freckle in patch-like images based on the simulated spectral reflectance. The spectral reflectance is simulated using Monte Carlo simulation of light transport in multi-layered tissue. Next, we reconstruct the facial color image with changing the blood volume. We acquire the concentration distribution of melanin, hemoglobin and shading components by applying the independent component analysis on a facial color image. We reproduce images using the obtained melanin and shading concentration and the changed hemoglobin concentration. Finally, we evaluate the visibility of pigmentations using simulated spectral reflectance distribution and facial color images. In the result of simulated spectral reflectance distribution, we found that the visibility became lower as the blood volume increases. However, we can see that a specific blood volume reduces the visibility of the actual pigmentations from the result of the facial color images.

A proposed mechanism for rapid adaptation to spectrally distorted speech.

PubMed

Azadpour, Mahan; Balaban, Evan

2015-07-01

The mechanisms underlying perceptual adaptation to severely spectrally-distorted speech were studied by training participants to comprehend spectrally-rotated speech, which is obtained by inverting the speech spectrum. Spectral-rotation produces severe distortion confined to the spectral domain while preserving temporal trajectories. During five 1-hour training sessions, pairs of participants attempted to extract spoken messages from the spectrally-rotated speech of their training partner. Data on training-induced changes in comprehension of spectrally-rotated sentences and identification/discrimination of spectrally-rotated phonemes were used to evaluate the plausibility of three different classes of underlying perceptual mechanisms: (1) phonemic remapping (the formation of new phonemic categories that specifically incorporate spectrally-rotated acoustic information); (2) experience-dependent generation of a perceptual "inverse-transform" that compensates for spectral-rotation; and (3) changes in cue weighting (the identification of sets of acoustic cues least affected by spectral-rotation, followed by a rapid shift in perceptual emphasis to favour those cues, combined with the recruitment of the same type of "perceptual filling-in" mechanisms used to disambiguate speech-in-noise). Results exclusively support the third mechanism, which is the only one predicting that learning would specifically target temporally-dynamic cues that were transmitting phonetic information most stably in spite of spectral-distortion. No support was found for phonemic remapping or for inverse-transform generation.

CALIBRATION AND VALIDATION OF CONFOCAL SPECTRAL IMAGING SYSTEMS

EPA Science Inventory

Confocal spectral imaging (CSI) microscope systems now on the market can perform spectral characterization of biological specimens containing fluorescent proteins, labels or dyes. Some CSI have been found to present inconsistent spectral characterizations within a particular syst...

Smile effect detection for dispersive hypersepctral imager based on the doped reflectance panel

NASA Astrophysics Data System (ADS)

Zhou, Jiankang; Liu, Xiaoli; Ji, Yiqun; Chen, Yuheng; Shen, Weimin

2012-11-01

Hyperspectral imager is now widely used in many regions, such as resource development, environmental monitoring and so on. The reliability of spectral data is based on the instrument calibration. The smile, wavelengths at the center pixels of imaging spectrometer detector array are different from the marginal pixels, is a main factor in the spectral calibration because it can deteriorate the spectral data accuracy. When the spectral resolution is high, little smile can result in obvious signal deviation near weak atmospheric absorption peak. The traditional method of detecting smile is monochromator wavelength scanning which is time consuming and complex and can not be used in the field or at the flying platform. We present a new smile detection method based on the holmium oxide panel which has the rich of absorbed spectral features. The higher spectral resolution spectrometer and the under-test imaging spectrometer acquired the optical signal from the Spectralon panel and the holmium oxide panel respectively. The wavelength absorption peak positions of column pixels are determined by curve fitting method which includes spectral response function sequence model and spectral resampling. The iteration strategy and Pearson coefficient together are used to confirm the correlation between the measured and modeled spectral curve. The present smile detection method is posed on our designed imaging spectrometer and the result shows that it can satisfy precise smile detection requirement of high spectral resolution imaging spectrometer.

ACTIM: an EDA initiated study on spectral active imaging

NASA Astrophysics Data System (ADS)

Steinvall, O.; Renhorn, I.; Ahlberg, J.; Larsson, H.; Letalick, D.; Repasi, E.; Lutzmann, P.; Anstett, G.; Hamoir, D.; Hespel, L.; Boucher, Y.

2010-10-01

This paper will describe ongoing work from an EDA initiated study on Active Imaging with emphasis of using multi or broadband spectral lasers and receivers. Present laser based imaging and mapping systems are mostly based on a fixed frequency lasers. On the other hand great progress has recently occurred in passive multi- and hyperspectral imaging with applications ranging from environmental monitoring and geology to mapping, military surveillance, and reconnaissance. Data bases on spectral signatures allow the possibility to discriminate between different materials in the scene. Present multi- and hyperspectral sensors mainly operate in the visible and short wavelength region (0.4-2.5 μm) and rely on the solar radiation giving shortcoming due to shadows, clouds, illumination angles and lack of night operation. Active spectral imaging however will largely overcome these difficulties by a complete control of the illumination. Active illumination enables spectral night and low-light operation beside a robust way of obtaining polarization and high resolution 2D/3D information. Recent development of broadband lasers and advanced imaging 3D focal plane arrays has led to new opportunities for advanced spectral and polarization imaging with high range resolution. Fusing the knowledge of ladar and passive spectral imaging will result in new capabilities in the field of EO-sensing to be shown in the study. We will present an overview of technology, systems and applications for active spectral imaging and propose future activities in connection with some prioritized applications.

Wavelet Analysis for Wind Fields Estimation

PubMed Central

Leite, Gladeston C.; Ushizima, Daniela M.; Medeiros, Fátima N. S.; de Lima, Gilson G.

2010-01-01

Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B3 spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms−1. Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms. PMID:22219699

Micro-attenuated total reflection spectral imaging in archaeology: application to Maya paint and plaster wall decorations.

PubMed

Goodall, Rosemary A; Hall, Jay; Sharer, Robert J; Traxler, Loa; Rintoul, Llew; Fredericks, Peter M

2008-01-01

Fourier transform infrared (FT-IR) attenuated total reflection (ATR) imaging has been successfully used to identify individual mineral components of ancient Maya paint. The high spatial resolution of a micro FT-IR-ATR system in combination with a focal plane array detector has allowed individual particles in the paint to be resolved and identified from their spectra. This system has been used in combination with micro-Raman spectroscopy to characterize the paint, which was found to be a mixture of hematite and silicate particles with minor amounts of calcite, carbon, and magnetite particles in a sub-micrometer hematite and calcite matrix. The underlying stucco was also investigated and found to be a combination of calcite with fine carbon particles, making a dark sub-ground for the paint.

Spectral characteristics and meridional variations of energy transformations during the first and second special observation periods of FGGE

NASA Technical Reports Server (NTRS)

Kung, E. C.; Tanaka, H.

1984-01-01

The global features and meridional spectral energy transformation variations of the first and second special observation periods of the First Global GARP Experiment (FGGE) are investigated, together with the latitudinal distribution of the kinetic energy balance. Specific seasonal characteristics are shown by the spectral distributions of the global transformations between (1) zonal mean and eddy components of the available potential energy, (2) the zonal mean and eddy components of the kinetic energy, and (3) the available potential energy and the kinetic energy. Maximum kinetic energy production is found to occur at subtropical latitudes, with a secondary maximum at higher middle latitudes. Between these two regions, there is another region characterized by the adiabatic destruction of kinetic energy above the lower troposphere.

[Study on Differential Optical Absorption Spectroscopy Data Processing Based on Chirp-Z Transformation].

PubMed

Zheng, Hai-ming; Li, Guang-jie; Wu, Hao

2015-06-01

Differential optical absorption spectroscopy (DOAS) is a commonly used atmospheric pollution monitoring method. Denoising of monitoring spectral data will improve the inversion accuracy. Fourier transform filtering method is effectively capable of filtering out the noise in the spectral data. But the algorithm itself can introduce errors. In this paper, a chirp-z transform method is put forward. By means of the local thinning of Fourier transform spectrum, it can retain the denoising effect of Fourier transform and compensate the error of the algorithm, which will further improve the inversion accuracy. The paper study on the concentration retrieving of SO2 and NO2. The results show that simple division causes bigger error and is not very stable. Chirp-z transform is proved to be more accurate than Fourier transform. Results of the frequency spectrum analysis show that Fourier transform cannot solve the distortion and weakening problems of characteristic absorption spectrum. Chirp-z transform shows ability in fine refactoring of specific frequency spectrum.

A new simultaneous compression and encryption method for images suitable to recognize form by optical correlation

NASA Astrophysics Data System (ADS)

Alfalou, Ayman; Elbouz, Marwa; Jridi, Maher; Loussert, Alain

2009-09-01

In some recognition form applications (which require multiple images: facial identification or sign-language), many images should be transmitted or stored. This requires the use of communication systems with a good security level (encryption) and an acceptable transmission rate (compression rate). In the literature, several encryption and compression techniques can be found. In order to use optical correlation, encryption and compression techniques cannot be deployed independently and in a cascade manner. Otherwise, our system will suffer from two major problems. In fact, we cannot simply use these techniques in a cascade manner without considering the impact of one technique over another. Secondly, a standard compression can affect the correlation decision, because the correlation is sensitive to the loss of information. To solve both problems, we developed a new technique to simultaneously compress & encrypt multiple images using a BPOF optimized filter. The main idea of our approach consists in multiplexing the spectrums of different transformed images by a Discrete Cosine Transform (DCT). To this end, the spectral plane should be divided into several areas and each of them corresponds to the spectrum of one image. On the other hand, Encryption is achieved using the multiplexing, a specific rotation functions, biometric encryption keys and random phase keys. A random phase key is widely used in optical encryption approaches. Finally, many simulations have been conducted. Obtained results corroborate the good performance of our approach. We should also mention that the recording of the multiplexed and encrypted spectra is optimized using an adapted quantification technique to improve the overall compression rate.

Technology for detecting spectral radiance by a snapshot multi-imaging spectroradiometer

NASA Astrophysics Data System (ADS)

Zuber, Ralf; Stührmann, Ansgar; Gugg-Helminger, Anton; Seckmeyer, Gunther

2017-12-01

Technologies to determine spectral sky radiance distributions have evolved in recent years and have enabled new applications in remote sensing, for sky radiance measurements, in biological/diagnostic applications and luminance measurements. Most classical spectral imaging radiance technologies are based on mechanical and/or spectral scans. However, these methods require scanning time in which the spectral radiance distribution might change. To overcome this limitation, different so-called snapshot spectral imaging technologies have been developed that enable spectral and spatial non-scanning measurements. We present a new setup based on a facet mirror that is already used in imaging slicing spectrometers. By duplicating the input image instead of slicing it and using a specially designed entrance slit, we are able to select nearly 200 (14 × 14) channels within the field of view (FOV) for detecting spectral radiance in different directions. In addition, a megapixel image of the FOV is captured by an additional RGB camera. This image can be mapped onto the snapshot spectral image. In this paper, the mechanical setup, technical design considerations and first measurement results of a prototype are presented. For a proof of concept, the device is radiometrically calibrated and a 10 mm × 10 mm test pattern measured within a spectral range of 380 nm-800 nm with an optical bandwidth of 10 nm (full width at half maximum or FWHM). To show its potential in the UV spectral region, zenith sky radiance measurements in the UV of a clear sky were performed. Hence, the prototype was equipped with an entrance optic with a FOV of 0.5° and modified to obtain a radiometrically calibrated spectral range of 280 nm-470 nm with a FWHM of 3 nm. The measurement results have been compared to modeled data processed by UVSPEC, which showed deviations of less than 30%. This is far from being ideal, but an acceptable result with respect to available state-of-the-art intercomparisons.

Mineral mapping in the Maherabad area, eastern Iran, using the HyMap remote sensing data

NASA Astrophysics Data System (ADS)

Molan, Yusuf Eshqi; Refahi, Davood; Tarashti, Ali Hoseinmardi

2014-04-01

This study applies matched filtering on the HyMap airborne hyperspectral data to obtain the distribution map of alteration minerals in the Maherabad area and uses virtual verification to verify the results. This paper also introduces "moving threshold" which tries to find an appropriate threshold value to convert gray scale images, produced by mapping methods, to target and background pixels. The Maherabad area, located in the eastern part of the Lut block, is a Cu-Au porphyry system in which quartz-sericite-pyrite, argillic and propylitic alteration are most common. Minimum noise fraction transform coupled with a pixel purity index was applied on the HyMap images to extract the endmembers of the alteration minerals, including kaolinite, montmorillonite, sericite (muscovite/illite), calcite, chlorite, epidote, and goethite. Since there was no access to any portable spectrometer and/or lab spectral measurements for the verification of the remote sensing imagery results, virtual verification achieved using the USGS spectral library and showed an agreement of 83.19%. The comparison between the results of the matched filtering and X-ray diffraction (XRD) analyses also showed an agreement of 56.13%.

Radiometric and spectral calibrations of the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) using principle component analysis

NASA Astrophysics Data System (ADS)

Tian, Jialin; Smith, William L.; Gazarik, Michael J.

2008-10-01

The ultimate remote sensing benefits of the high resolution Infrared radiance spectrometers will be realized with their geostationary satellite implementation in the form of imaging spectrometers. This will enable dynamic features of the atmosphere's thermodynamic fields and pollutant and greenhouse gas constituents to be observed for revolutionary improvements in weather forecasts and more accurate air quality and climate predictions. As an important step toward realizing this application objective, the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) was successfully developed under the NASA New Millennium Program, 2000-2006. The GIFTS-EDU instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw GIFTS interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. The radiometric calibration is achieved using internal blackbody calibration references at ambient (260 K) and hot (286 K) temperatures. The absolute radiometric performance of the instrument is affected by several factors including the FPA off-axis effect, detector/readout electronics induced nonlinearity distortions, and fore-optics offsets. The GIFTS-EDU, being the very first imaging spectrometer to use ultra-high speed electronics to readout its large area format focal plane array detectors, operating at wavelengths as large as 15 microns, possessed non-linearity's not easily removable in the initial calibration process. In this paper, we introduce a refined calibration technique that utilizes Principle Component (PC) analysis to compensate for instrument distortions and artifacts remaining after the initial radiometric calibration process, thus, further enhance the absolute calibration accuracy. This method is applied to data collected during an atmospheric measurement experiment with the GIFTS, together with simultaneous observations by the accurately calibrated AERI (Atmospheric Emitted Radiance Interferometer), both simultaneously zenith viewing the sky through the same external scene mirror at ten-minute intervals throughout a cloudless day at Logan Utah on September 13, 2006. The PC vectors of the calibrated radiance spectra are defined from the AERI observations and regression matrices relating the initial GIFTS radiance PC scores to the AERI radiance PC scores are calculated using the least squares inverse method. A new set of accurately calibrated GIFTS radiances are produced using the first four PC scores in the regression model. Temperature and moisture profiles retrieved from the PC-calibrated GIFTS radiances are verified against radiosonde measurements collected throughout the GIFTS sky measurement period.