Automatic generation of endocardial surface meshes with 1-to-1 correspondence from cine-MR images

NASA Astrophysics Data System (ADS)

Su, Yi; Teo, S.-K.; Lim, C. W.; Zhong, L.; Tan, R. S.

2015-03-01

In this work, we develop an automatic method to generate a set of 4D 1-to-1 corresponding surface meshes of the left ventricle (LV) endocardial surface which are motion registered over the whole cardiac cycle. These 4D meshes have 1- to-1 point correspondence over the entire set, and is suitable for advanced computational processing, such as shape analysis, motion analysis and finite element modelling. The inputs to the method are the set of 3D LV endocardial surface meshes of the different frames/phases of the cardiac cycle. Each of these meshes is reconstructed independently from border-delineated MR images and they have no correspondence in terms of number of vertices/points and mesh connectivity. To generate point correspondence, the first frame of the LV mesh model is used as a template to be matched to the shape of the meshes in the subsequent phases. There are two stages in the mesh correspondence process: (1) a coarse matching phase, and (2) a fine matching phase. In the coarse matching phase, an initial rough matching between the template and the target is achieved using a radial basis function (RBF) morphing process. The feature points on the template and target meshes are automatically identified using a 16-segment nomenclature of the LV. In the fine matching phase, a progressive mesh projection process is used to conform the rough estimate to fit the exact shape of the target. In addition, an optimization-based smoothing process is used to achieve superior mesh quality and continuous point motion.

Accurate Iris Recognition at a Distance Using Stabilized Iris Encoding and Zernike Moments Phase Features.

PubMed

Tan, Chun-Wei; Kumar, Ajay

2014-07-10

Accurate iris recognition from the distantly acquired face or eye images requires development of effective strategies which can account for significant variations in the segmented iris image quality. Such variations can be highly correlated with the consistency of encoded iris features and the knowledge that such fragile bits can be exploited to improve matching accuracy. A non-linear approach to simultaneously account for both local consistency of iris bit and also the overall quality of the weight map is proposed. Our approach therefore more effectively penalizes the fragile bits while simultaneously rewarding more consistent bits. In order to achieve more stable characterization of local iris features, a Zernike moment-based phase encoding of iris features is proposed. Such Zernike moments-based phase features are computed from the partially overlapping regions to more effectively accommodate local pixel region variations in the normalized iris images. A joint strategy is adopted to simultaneously extract and combine both the global and localized iris features. The superiority of the proposed iris matching strategy is ascertained by providing comparison with several state-of-the-art iris matching algorithms on three publicly available databases: UBIRIS.v2, FRGC, CASIA.v4-distance. Our experimental results suggest that proposed strategy can achieve significant improvement in iris matching accuracy over those competing approaches in the literature, i.e., average improvement of 54.3%, 32.7% and 42.6% in equal error rates, respectively for UBIRIS.v2, FRGC, CASIA.v4-distance.

Depth map generation using a single image sensor with phase masks.

PubMed

Jang, Jinbeum; Park, Sangwoo; Jo, Jieun; Paik, Joonki

2016-06-13

Conventional stereo matching systems generate a depth map using two or more digital imaging sensors. It is difficult to use the small camera system because of their high costs and bulky sizes. In order to solve this problem, this paper presents a stereo matching system using a single image sensor with phase masks for the phase difference auto-focusing. A novel pattern of phase mask array is proposed to simultaneously acquire two pairs of stereo images. Furthermore, a noise-invariant depth map is generated from the raw format sensor output. The proposed method consists of four steps to compute the depth map: (i) acquisition of stereo images using the proposed mask array, (ii) variational segmentation using merging criteria to simplify the input image, (iii) disparity map generation using the hierarchical block matching for disparity measurement, and (iv) image matting to fill holes to generate the dense depth map. The proposed system can be used in small digital cameras without additional lenses or sensors.

A theory of phase singularities for image representation and its applications to object tracking and image matching.

PubMed

Qiao, Yu; Wang, Wei; Minematsu, Nobuaki; Liu, Jianzhuang; Takeda, Mitsuo; Tang, Xiaoou

2009-10-01

This paper studies phase singularities (PSs) for image representation. We show that PSs calculated with Laguerre-Gauss filters contain important information and provide a useful tool for image analysis. PSs are invariant to image translation and rotation. We introduce several invariant features to characterize the core structures around PSs and analyze the stability of PSs to noise addition and scale change. We also study the characteristics of PSs in a scale space, which lead to a method to select key scales along phase singularity curves. We demonstrate two applications of PSs: object tracking and image matching. In object tracking, we use the iterative closest point algorithm to determine the correspondences of PSs between two adjacent frames. The use of PSs allows us to precisely determine the motions of tracked objects. In image matching, we combine PSs and scale-invariant feature transform (SIFT) descriptor to deal with the variations between two images and examine the proposed method on a benchmark database. The results indicate that our method can find more correct matching pairs with higher repeatability rates than some well-known methods.

Stereo-Based Region-Growing using String Matching

NASA Technical Reports Server (NTRS)

Mandelbaum, Robert; Mintz, Max

1995-01-01

We present a novel stereo algorithm based on a coarse texture segmentation preprocessing phase. Matching is performed using a string comparison. Matching sub-strings correspond to matching sequences of textures. Inter-scanline clustering of matching sub-strings yields regions of matching texture. The shape of these regions yield information concerning object's height, width and azimuthal position relative to the camera pair. Hence, rather than the standard dense depth map, the output of this algorithm is a segmentation of objects in the scene. Such a format is useful for the integration of stereo with other sensor modalities on a mobile robotic platform. It is also useful for localization; the height and width of a detected object may be used for landmark recognition, while depth and relative azimuthal location determine pose. The algorithm does not rely on the monotonicity of order of image primitives. Occlusions, exposures, and foreshortening effects are not problematic. The algorithm can deal with certain types of transparencies. It is computationally efficient, and very amenable to parallel implementation. Further, the epipolar constraints may be relaxed to some small but significant degree. A version of the algorithm has been implemented and tested on various types of images. It performs best on random dot stereograms, on images with easily filtered backgrounds (as in synthetic images), and on real scenes with uncontrived backgrounds.

Template match using local feature with view invariance

NASA Astrophysics Data System (ADS)

Lu, Cen; Zhou, Gang

2013-10-01

Matching the template image in the target image is the fundamental task in the field of computer vision. Aiming at the deficiency in the traditional image matching methods and inaccurate matching in scene image with rotation, illumination and view changing, a novel matching algorithm using local features are proposed in this paper. The local histograms of the edge pixels (LHoE) are extracted as the invariable feature to resist view and brightness changing. The merits of the LHoE is that the edge points have been little affected with view changing, and the LHoE can resist not only illumination variance but also the polution of noise. For the process of matching are excuded only on the edge points, the computation burden are highly reduced. Additionally, our approach is conceptually simple, easy to implement and do not need the training phase. The view changing can be considered as the combination of rotation, illumination and shear transformation. Experimental results on simulated and real data demonstrated that the proposed approach is superior to NCC(Normalized cross-correlation) and Histogram-based methods with view changing.

New development of the image matching algorithm

NASA Astrophysics Data System (ADS)

Zhang, Xiaoqiang; Feng, Zhao

2018-04-01

To study the image matching algorithm, algorithm four elements are described, i.e., similarity measurement, feature space, search space and search strategy. Four common indexes for evaluating the image matching algorithm are described, i.e., matching accuracy, matching efficiency, robustness and universality. Meanwhile, this paper describes the principle of image matching algorithm based on the gray value, image matching algorithm based on the feature, image matching algorithm based on the frequency domain analysis, image matching algorithm based on the neural network and image matching algorithm based on the semantic recognition, and analyzes their characteristics and latest research achievements. Finally, the development trend of image matching algorithm is discussed. This study is significant for the algorithm improvement, new algorithm design and algorithm selection in practice.

Illumination Invariant Change Detection (iicd): from Earth to Mars

NASA Astrophysics Data System (ADS)

Wan, X.; Liu, J.; Qin, M.; Li, S. Y.

2018-04-01

Multi-temporal Earth Observation and Mars orbital imagery data with frequent repeat coverage provide great capability for planetary surface change detection. When comparing two images taken at different times of day or in different seasons for change detection, the variation of topographic shades and shadows caused by the change of sunlight angle can be so significant that it overwhelms the real object and environmental changes, making automatic detection unreliable. An effective change detection algorithm therefore has to be robust to the illumination variation. This paper presents our research on developing and testing an Illumination Invariant Change Detection (IICD) method based on the robustness of phase correlation (PC) to the variation of solar illumination for image matching. The IICD is based on two key functions: i) initial change detection based on a saliency map derived from pixel-wise dense PC matching and ii) change quantization which combines change type identification, motion estimation and precise appearance change identification. Experiment using multi-temporal Landsat 7 ETM+ satellite images, Rapid eye satellite images and Mars HiRiSE images demonstrate that our frequency based image matching method can reach sub-pixel accuracy and thus the proposed IICD method can effectively detect and precisely segment large scale change such as landslide as well as small object change such as Mars rover, under daily and seasonal sunlight changes.

Shape based segmentation of MRIs of the bones in the knee using phase and intensity information

NASA Astrophysics Data System (ADS)

Fripp, Jurgen; Bourgeat, Pierrick; Crozier, Stuart; Ourselin, Sébastien

2007-03-01

The segmentation of the bones from MR images is useful for performing subsequent segmentation and quantitative measurements of cartilage tissue. In this paper, we present a shape based segmentation scheme for the bones that uses texture features derived from the phase and intensity information in the complex MR image. The phase can provide additional information about the tissue interfaces, but due to the phase unwrapping problem, this information is usually discarded. By using a Gabor filter bank on the complex MR image, texture features (including phase) can be extracted without requiring phase unwrapping. These texture features are then analyzed using a support vector machine classifier to obtain probability tissue matches. The segmentation of the bone is fully automatic and performed using a 3D active shape model based approach driven using gradient and texture information. The 3D active shape model is automatically initialized using a robust affine registration. The approach is validated using a database of 18 FLASH MR images that are manually segmented, with an average segmentation overlap (Dice similarity coefficient) of 0.92 compared to 0.9 obtained using the classifier only.

Symmetric Phase Only Filtering for Improved DPIV Data Processing

NASA Technical Reports Server (NTRS)

Wernet, Mark P.

2006-01-01

The standard approach in Digital Particle Image Velocimetry (DPIV) data processing is to use Fast Fourier Transforms to obtain the cross-correlation of two single exposure subregions, where the location of the cross-correlation peak is representative of the most probable particle displacement across the subregion. This standard DPIV processing technique is analogous to Matched Spatial Filtering, a technique commonly used in optical correlators to perform the crosscorrelation operation. Phase only filtering is a well known variation of Matched Spatial Filtering, which when used to process DPIV image data yields correlation peaks which are narrower and up to an order of magnitude larger than those obtained using traditional DPIV processing. In addition to possessing desirable correlation plane features, phase only filters also provide superior performance in the presence of DC noise in the correlation subregion. When DPIV image subregions contaminated with surface flare light or high background noise levels are processed using phase only filters, the correlation peak pertaining only to the particle displacement is readily detected above any signal stemming from the DC objects. Tedious image masking or background image subtraction are not required. Both theoretical and experimental analyses of the signal-to-noise ratio performance of the filter functions are presented. In addition, a new Symmetric Phase Only Filtering (SPOF) technique, which is a variation on the traditional phase only filtering technique, is described and demonstrated. The SPOF technique exceeds the performance of the traditionally accepted phase only filtering techniques and is easily implemented in standard DPIV FFT based correlation processing with no significant computational performance penalty. An "Automatic" SPOF algorithm is presented which determines when the SPOF is able to provide better signal to noise results than traditional PIV processing. The SPOF based optical correlation processing approach is presented as a new paradigm for more robust cross-correlation processing of low signal-to-noise ratio DPIV image data."

Component-based target recognition inspired by human vision

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Agyepong, Kwabena

2009-05-01

In contrast with machine vision, human can recognize an object from complex background with great flexibility. For example, given the task of finding and circling all cars (no further information) in a picture, you may build a virtual image in mind from the task (or target) description before looking at the picture. Specifically, the virtual car image may be composed of the key components such as driver cabin and wheels. In this paper, we propose a component-based target recognition method by simulating the human recognition process. The component templates (equivalent to the virtual image in mind) of the target (car) are manually decomposed from the target feature image. Meanwhile, the edges of the testing image can be extracted by using a difference of Gaussian (DOG) model that simulates the spatiotemporal response in visual process. A phase correlation matching algorithm is then applied to match the templates with the testing edge image. If all key component templates are matched with the examining object, then this object is recognized as the target. Besides the recognition accuracy, we will also investigate if this method works with part targets (half cars). In our experiments, several natural pictures taken on streets were used to test the proposed method. The preliminary results show that the component-based recognition method is very promising.

Refractive-index-matched hydrogel materials for measuring flow-structure interactions

NASA Astrophysics Data System (ADS)

Byron, Margaret L.; Variano, Evan A.

2013-02-01

In imaging-based studies of flow around solid objects, it is useful to have materials that are refractive-index-matched to the surrounding fluid. However, materials currently in use are usually rigid and matched to liquids that are either expensive or highly viscous. This does not allow for measurements at high Reynolds number, nor accurate modeling of flexible structures. This work explores the use of two hydrogels (agarose and polyacrylamide) as refractive-index-matched models in water. These hydrogels are inexpensive, can be cast into desired shapes, and have flexibility that can be tuned to match biological materials. The use of water as the fluid phase allows this method to be implemented immediately in many experimental facilities and permits investigation of high-Reynolds-number phenomena. We explain fabrication methods and present a summary of the physical and optical properties of both gels, and then show measurements demonstrating the use of hydrogel models in quantitative imaging.

Free-breathing cine DENSE MRI using phase cycling with matchmaking and stimulated-echo image-based navigators.

PubMed

Cai, Xiaoying; Epstein, Frederick H

2018-04-01

This study aimed to develop a self-navigated method for free-breathing spiral cine displacement encoding with stimulated echoes (DENSE), a myocardial strain imaging technique that uses phase-cycling for artifact suppression. The method needed to address 2 consequences of motion for DENSE: striping artifacts from incomplete suppression of the T 1 -relaxation echo and blurring. The method identifies phase-cycled spiral interleaves at matched respiratory phases by minimizing the residual signal due to T 1 relaxation after phase-cycling subtraction. Next, the method reconstructs image-based navigators from matched phase-cycled interleaves that are comprised of the stimulated echo (ste-iNAVs). Ste-iNAVs are used for motion estimation and compensation of k-space data. The method was demonstrated in phantoms and compared to diaphragm-based navigator (dNAV) and conventional iNAV (c-iNAV) methods for the reconstruction of free-breathing volunteer data sets (N = 10). Phantom experiments demonstrated that the proposed method removes striping artifacts and blurring due to motion. Volunteer results showed that respiratory motion measured by ste-iNAVs was better correlated than c-iNAVs to dNAV data (R 2  = 0.82 ± 0.03 vs. 0.70 ± 0.05, P < 0.05). Match-making reconstructions of free-breathing data sets achieved lower residual T 1 -relaxation echo energy (1.04 ± 0.01 vs. 1.18 ± 0.04 for dNAV and 1.18 ± 0.03 for c-iNAV, P < 0.05), higher apparent SNR (11.93 ± 1.05 vs. 10.68 ± 1.06 for dNAV and 10.66 ± 0.99 for c-iNAV, P < 0.05), and better phase quality (0.147 ± 0.012 vs. 0.166 ± 0.017 for dNAV, P = 0.06, and 0.168 ± 0.015 for c-iNAV, P < 0.05) than dNAV and c-iNAV methods. For free-breathing cine DENSE, the proposed method addresses both types of breathing-induced artifacts and provides better quality images than conventional dNAV and iNAV methods. © 2018 International Society for Magnetic Resonance in Medicine.

SU-C-9A-06: The Impact of CT Image Used for Attenuation Correction in 4D-PET

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

Cui, Y; Bowsher, J; Yan, S

2014-06-01

Purpose: To evaluate the appropriateness of using 3D non-gated CT image for attenuation correction (AC) in a 4D-PET (gated PET) imaging protocol used in radiotherapy treatment planning simulation. Methods: The 4D-PET imaging protocol in a Siemens PET/CT simulator (Biograph mCT, Siemens Medical Solutions, Hoffman Estates, IL) was evaluated. CIRS Dynamic Thorax Phantom (CIRS Inc., Norfolk, VA) with a moving glass sphere (8 mL) in the middle of its thorax portion was used in the experiments. The glass was filled with {sup 18}F-FDG and was in a longitudinal motion derived from a real patient breathing pattern. Varian RPM system (Varian Medicalmore » Systems, Palo Alto, CA) was used for respiratory gating. Both phase-gating and amplitude-gating methods were tested. The clinical imaging protocol was modified to use three different CT images for AC in 4D-PET reconstruction: first is to use a single-phase CT image to mimic actual clinical protocol (single-CT-PET); second is to use the average intensity projection CT (AveIP-CT) derived from 4D-CT scanning (AveIP-CT-PET); third is to use 4D-CT image to do the phase-matched AC (phase-matching- PET). Maximum SUV (SUVmax) and volume of the moving target (glass sphere) with threshold of 40% SUVmax were calculated for comparison between 4D-PET images derived with different AC methods. Results: The SUVmax varied 7.3%±6.9% over the breathing cycle in single-CT-PET, compared to 2.5%±2.8% in AveIP-CT-PET and 1.3%±1.2% in phasematching PET. The SUVmax in single-CT-PET differed by up to 15% from those in phase-matching-PET. The target volumes measured from single- CT-PET images also presented variations up to 10% among different phases of 4D PET in both phase-gating and amplitude-gating experiments. Conclusion: Attenuation correction using non-gated CT in 4D-PET imaging is not optimal process for quantitative analysis. Clinical 4D-PET imaging protocols should consider phase-matched 4D-CT image if available to achieve better accuracy.« less

Fine-resolution imaging of solar features using Phase-Diverse Speckle

NASA Technical Reports Server (NTRS)

Paxman, Richard G.

1995-01-01

Phase-diverse speckle (PDS) is a novel imaging technique intended to overcome the degrading effects of atmospheric turbulence on fine-resolution imaging. As its name suggests, PDS is a blend of phase-diversity and speckle-imaging concepts. PDS reconstructions on solar data were validated by simulation, by demonstrating internal consistency of PDS estimates, and by comparing PDS reconstructions with those produced from well accepted speckle-imaging processing. Several sources of error in data collected with the Swedish Vacuum Solar Telescope (SVST) were simulated: CCD noise, quantization error, image misalignment, and defocus error, as well as atmospheric turbulence model error. The simulations demonstrate that fine-resolution information can be reliably recovered out to at least 70% of the diffraction limit without significant introduction of image artifacts. Additional confidence in the SVST restoration is obtained by comparing its spatial power spectrum with previously-published power spectra derived from both space-based images and earth-based images corrected with traditional speckle-imaging techniques; the shape of the spectrum is found to match well the previous measurements. In addition, the imagery is found to be consistent with, but slightly sharper than, imagery reconstructed with accepted speckle-imaging techniques.

Effective low-level processing for interferometric image enhancement

NASA Astrophysics Data System (ADS)

Joo, Wonjong; Cha, Soyoung S.

1995-09-01

The hybrid operation of digital image processing and a knowledge-based AI system has been recognized as a desirable approach of the automated evaluation of noise-ridden interferogram. Early noise/data reduction before phase is extracted is essential for the success of the knowledge- based processing. In this paper, new concepts of effective, interactive low-level processing operators: that is, a background-matched filter and a directional-smoothing filter, are developed and tested with transonic aerodynamic interferograms. The results indicate that these new operators have promising advantages in noise/data reduction over the conventional ones, leading success of the high-level, intelligent phase extraction.

A common-path phase-shift interferometry surface plasmon imaging system

NASA Astrophysics Data System (ADS)

Su, Y.-T.; Chen, Shean-Jen; Yeh, T.-L.

2005-03-01

A biosensing imaging system is proposed based on the integration of surface plasmon resonance (SPR) and common-path phase-shift interferometry (PSI) techniques to measure the two-dimensional spatial phase variation caused by biomolecular interactions upon a sensing chip. The SPR phase imaging system can offer high resolution and high-throughout screening capabilities to analyze microarray biomolecular interaction without the need for additional labeling. With the long-term stability advantage of the common-path PSI technique even with external disturbances such as mechanical vibration, buffer flow noise, and laser unstable issue, the system can match the demand of real-time kinetic study for biomolecular interaction analysis (BIA). The SPR-PSI imaging system has achieved a detection limit of 2×10-7 refraction index change, a long-term phase stability of 2.5x10-4π rms over four hours, and a spatial phase resolution of 10-3 π with a lateral resolution of 100μm.

Fast image matching algorithm based on projection characteristics

NASA Astrophysics Data System (ADS)

Zhou, Lijuan; Yue, Xiaobo; Zhou, Lijun

2011-06-01

Based on analyzing the traditional template matching algorithm, this paper identified the key factors restricting the speed of matching and put forward a brand new fast matching algorithm based on projection. Projecting the grayscale image, this algorithm converts the two-dimensional information of the image into one-dimensional one, and then matches and identifies through one-dimensional correlation, meanwhile, because of normalization has been done, when the image brightness or signal amplitude increasing in proportion, it could also perform correct matching. Experimental results show that the projection characteristics based image registration method proposed in this article could greatly improve the matching speed, which ensuring the matching accuracy as well.

A biometric identification system based on eigenpalm and eigenfinger features.

PubMed

Ribaric, Slobodan; Fratric, Ivan

2005-11-01

This paper presents a multimodal biometric identification system based on the features of the human hand. We describe a new biometric approach to personal identification using eigenfinger and eigenpalm features, with fusion applied at the matching-score level. The identification process can be divided into the following phases: capturing the image; preprocessing; extracting and normalizing the palm and strip-like finger subimages; extracting the eigenpalm and eigenfinger features based on the K-L transform; matching and fusion; and, finally, a decision based on the (k, l)-NN classifier and thresholding. The system was tested on a database of 237 people (1,820 hand images). The experimental results showed the effectiveness of the system in terms of the recognition rate (100 percent), the equal error rate (EER = 0.58 percent), and the total error rate (TER = 0.72 percent).

Logo recognition using alpha-rooted phase correlation in the radon transform domain

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2009-08-01

Alpha-rooted phase correlation (ARPC) is a recently-developed variant of classical phase correlation that includes a Fourier domain image enhancement operation. ARPC combines classical phase correlation with alpha-rooting to provide tunable image enhancement. The alpha-rooting parameters may be adjusted to provide a tradeoff between height and width of the ARPC main lobe. A high narrow main lobe peak provides high matching accuracy for aligned images, but reduced matching performance for misaligned logos. A lower, wider peak trades matching accuracy on aligned logos, for improved matching performance on misaligned imagery. Previously, we developed ARPC and used it in the spatial domain for logo recognition as part of an overall automated document analysis problem. However, spatial domain ARPC performance can be sensitive to logo misalignments, including rotational misalignment. In this paper we use ARPC as a match metric in the radon transform domain for logo recognition. In the radon transform domain, rotational misalignments correspond to translations in the radon transform angle parameter. These translations are captured by ARPC, thereby producing rotation-invariant logo matching. In the paper, we first present an overview of ARPC, and then describe the logo matching algorithm. We present numerical performance results demonstrating matching tolerance to rotational misalignments. We demonstrate robustness of the radon transform domain rotation estimation to noise. We present logo verification and recognition performance results using the proposed approach on a public domain logo database. We compare performance results to performance obtained using spatial domain ARPC, and state-of-the-art SURF features, for logos in salt-and-pepper noise.

A Novel Artificial Bee Colony Algorithm Based on Internal-Feedback Strategy for Image Template Matching

PubMed Central

Gong, Li-Gang

2014-01-01

Image template matching refers to the technique of locating a given reference image over a source image such that they are the most similar. It is a fundamental mission in the field of visual target recognition. In general, there are two critical aspects of a template matching scheme. One is similarity measurement and the other is best-match location search. In this work, we choose the well-known normalized cross correlation model as a similarity criterion. The searching procedure for the best-match location is carried out through an internal-feedback artificial bee colony (IF-ABC) algorithm. IF-ABC algorithm is highlighted by its effort to fight against premature convergence. This purpose is achieved through discarding the conventional roulette selection procedure in the ABC algorithm so as to provide each employed bee an equal chance to be followed by the onlooker bees in the local search phase. Besides that, we also suggest efficiently utilizing the internal convergence states as feedback guidance for searching intensity in the subsequent cycles of iteration. We have investigated four ideal template matching cases as well as four actual cases using different searching algorithms. Our simulation results show that the IF-ABC algorithm is more effective and robust for this template matching mission than the conventional ABC and two state-of-the-art modified ABC algorithms do. PMID:24892107

TU-AB-202-05: GPU-Based 4D Deformable Image Registration Using Adaptive Tetrahedral Mesh Modeling

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

Zhong, Z; Zhuang, L; Gu, X

Purpose: Deformable image registration (DIR) has been employed today as an automated and effective segmentation method to transfer tumor or organ contours from the planning image to daily images, instead of manual segmentation. However, the computational time and accuracy of current DIR approaches are still insufficient for online adaptive radiation therapy (ART), which requires real-time and high-quality image segmentation, especially in a large datasets of 4D-CT images. The objective of this work is to propose a new DIR algorithm, with fast computational speed and high accuracy, by using adaptive feature-based tetrahedral meshing and GPU-based parallelization. Methods: The first step ismore » to generate the adaptive tetrahedral mesh based on the image features of a reference phase of 4D-CT, so that the deformation can be well captured and accurately diffused from the mesh vertices to voxels of the image volume. Subsequently, the deformation vector fields (DVF) and other phases of 4D-CT can be obtained by matching each phase of the target 4D-CT images with the corresponding deformed reference phase. The proposed 4D DIR method is implemented on GPU, resulting in significantly increasing the computational efficiency due to its parallel computing ability. Results: A 4D NCAT digital phantom was used to test the efficiency and accuracy of our method. Both the image and DVF results show that the fine structures and shapes of lung are well preserved, and the tumor position is well captured, i.e., 3D distance error is 1.14 mm. Compared to the previous voxel-based CPU implementation of DIR, such as demons, the proposed method is about 160x faster for registering a 10-phase 4D-CT with a phase dimension of 256×256×150. Conclusion: The proposed 4D DIR method uses feature-based mesh and GPU-based parallelism, which demonstrates the capability to compute both high-quality image and motion results, with significant improvement on the computational speed.« less

Two-level image authentication by two-step phase-shifting interferometry and compressive sensing

NASA Astrophysics Data System (ADS)

Zhang, Xue; Meng, Xiangfeng; Yin, Yongkai; Yang, Xiulun; Wang, Yurong; Li, Xianye; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2018-01-01

A two-level image authentication method is proposed; the method is based on two-step phase-shifting interferometry, double random phase encoding, and compressive sensing (CS) theory, by which the certification image can be encoded into two interferograms. Through discrete wavelet transform (DWT), sparseness processing, Arnold transform, and data compression, two compressed signals can be generated and delivered to two different participants of the authentication system. Only the participant who possesses the first compressed signal attempts to pass the low-level authentication. The application of Orthogonal Match Pursuit CS algorithm reconstruction, inverse Arnold transform, inverse DWT, two-step phase-shifting wavefront reconstruction, and inverse Fresnel transform can result in the output of a remarkable peak in the central location of the nonlinear correlation coefficient distributions of the recovered image and the standard certification image. Then, the other participant, who possesses the second compressed signal, is authorized to carry out the high-level authentication. Therefore, both compressed signals are collected to reconstruct the original meaningful certification image with a high correlation coefficient. Theoretical analysis and numerical simulations verify the feasibility of the proposed method.

Ultrasonic Phased Array Compressive Imaging in Time and Frequency Domain: Simulation, Experimental Verification and Real Application

PubMed Central

Bai, Zhiliang; Chen, Shili; Jia, Lecheng; Zeng, Zhoumo

2018-01-01

Embracing the fact that one can recover certain signals and images from far fewer measurements than traditional methods use, compressive sensing (CS) provides solutions to huge amounts of data collection in phased array-based material characterization. This article describes how a CS framework can be utilized to effectively compress ultrasonic phased array images in time and frequency domains. By projecting the image onto its Discrete Cosine transform domain, a novel scheme was implemented to verify the potentiality of CS for data reduction, as well as to explore its reconstruction accuracy. The results from CIVA simulations indicate that both time and frequency domain CS can accurately reconstruct array images using samples less than the minimum requirements of the Nyquist theorem. For experimental verification of three types of artificial flaws, although a considerable data reduction can be achieved with defects clearly preserved, it is currently impossible to break Nyquist limitation in the time domain. Fortunately, qualified recovery in the frequency domain makes it happen, meaning a real breakthrough for phased array image reconstruction. As a case study, the proposed CS procedure is applied to the inspection of an engine cylinder cavity containing different pit defects and the results show that orthogonal matching pursuit (OMP)-based CS guarantees the performance for real application. PMID:29738452

A review of solid-fluid selection options for optical-based measurements in single-phase liquid, two-phase liquid-liquid and multiphase solid-liquid flows

NASA Astrophysics Data System (ADS)

Wright, Stuart F.; Zadrazil, Ivan; Markides, Christos N.

2017-09-01

Experimental techniques based on optical measurement principles have experienced significant growth in recent decades. They are able to provide detailed information with high-spatiotemporal resolution on important scalar (e.g., temperature, concentration, and phase) and vector (e.g., velocity) fields in single-phase or multiphase flows, as well as interfacial characteristics in the latter, which has been instrumental to step-changes in our fundamental understanding of these flows, and the development and validation of advanced models with ever-improving predictive accuracy and reliability. Relevant techniques rely upon well-established optical methods such as direct photography, laser-induced fluorescence, laser Doppler velocimetry/phase Doppler anemometry, particle image/tracking velocimetry, and variants thereof. The accuracy of the resulting data depends on numerous factors including, importantly, the refractive indices of the solids and liquids used. The best results are obtained when the observational materials have closely matched refractive indices, including test-section walls, liquid phases, and any suspended particles. This paper reviews solid-liquid and solid-liquid-liquid refractive-index-matched systems employed in different fields, e.g., multiphase flows, turbomachinery, bio-fluid flows, with an emphasis on liquid-liquid systems. The refractive indices of various aqueous and organic phases found in the literature span the range 1.330-1.620 and 1.251-1.637, respectively, allowing the identification of appropriate combinations to match selected transparent or translucent plastics/polymers, glasses, or custom materials in single-phase liquid or multiphase liquid-liquid flow systems. In addition, the refractive indices of fluids can be further tuned with the use of additives, which also allows for the matching of important flow similarity parameters such as density and viscosity.

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

Fogg, P; Aland, T; West, M

Purpose: To investigate the effects of external surrogate and tumour motion by observing the reconstructed phases and AveCT in an Amplitude and Time based 4DCT. Methods: Based on patient motion studies, Cos6 and sinusoidal motions were simulated as external surrogate and tumour motions in a motion phantom. The diaphragm and tumour motions may or may not display the same waveform therefore the same and different waveforms were programmed into the phantom, scanned and reconstructed based on Amplitude and Time. The AveCT and phases were investigated with these different scenarios. The AveCT phantom images were also compared with CBCT phantom imagesmore » programmed with the same motions. Results: For the same surrogate and tumour sin motions, the phases (Amplitude and Time) and AveCT indicated similar motions based on the position of the BB at the slice and displayed contrast values respectively. For cos6 motions, due to the varied time the tumour spends at each position, the Amplitude and Time based phases differed. The AveCT images represented the actual tumour motions and the Time and Amplitude based phases were represented by the surrogate with varied times. Conclusion: Different external surrogate and tumour motions may result in different displayed image motions when observing the AveCT and reconstructed phases. During the 4DCT, the surrogate motion is readily available for observation of the amplitude and time of the diaphragm position. Following image reconstruction, the user may need to observe the AveCT in addition to the reconstructed phases to comprehend the time weightings of the tumour motion during the scan. This may also apply to 3D CBCT images where the displayed tumour position in the images is influenced by the long duration of the CBCT. Knowledge of the tumour motion represented by the greyscale of the AveCT may also assist in CBCT treatment beam verification matching.« less

An adaptive clustering algorithm for image matching based on corner feature

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-04-01

The traditional image matching algorithm always can not balance the real-time and accuracy better, to solve the problem, an adaptive clustering algorithm for image matching based on corner feature is proposed in this paper. The method is based on the similarity of the matching pairs of vector pairs, and the adaptive clustering is performed on the matching point pairs. Harris corner detection is carried out first, the feature points of the reference image and the perceived image are extracted, and the feature points of the two images are first matched by Normalized Cross Correlation (NCC) function. Then, using the improved algorithm proposed in this paper, the matching results are clustered to reduce the ineffective operation and improve the matching speed and robustness. Finally, the Random Sample Consensus (RANSAC) algorithm is used to match the matching points after clustering. The experimental results show that the proposed algorithm can effectively eliminate the most wrong matching points while the correct matching points are retained, and improve the accuracy of RANSAC matching, reduce the computation load of whole matching process at the same time.

Memory retrieval of smoking-related images induce greater insula activation as revealed by an fMRI based delayed matching to sample task

PubMed Central

Janes, AC; Ross, RS; Farmer, S; Frederick, BB; Nickerson, L; Lukas, SE; Stern, CE

2013-01-01

Nicotine dependence is a chronic and difficult to treat disorder. While environmental stimuli associated with smoking precipitate craving and relapse, it is unknown whether smoking cues are cognitively processed differently than neutral stimuli. To evaluate working memory differences between smoking-related and neutral stimuli, we conducted a delay-match-to-sample (DMS) task concurrently with functional magnetic resonance imaging (fMRI) in nicotine dependent participants. The DMS task evaluates brain activation during the encoding, maintenance, and retrieval phases of working memory. Smoking images induced significantly more subjective craving, and greater midline cortical activation during encoding in comparison to neutral stimuli that were similar in content yet lacked a smoking component. The insula, which is involved in maintaining nicotine dependence, was active during the successful retrieval of previously viewed smoking vs. neutral images. In contrast, neutral images required more prefrontal cortex-mediated active maintenance during the maintenance period. These findings indicate that distinct brain regions are involved in the different phases of working memory for smoking-related vs. neutral images. Importantly the results implicate the insula in the retrieval of smoking-related stimuli, which is relevant given the insula’s emerging role in addiction. PMID:24261848

Memory retrieval of smoking-related images induce greater insula activation as revealed by an fMRI-based delayed matching to sample task.

PubMed

Janes, Amy C; Ross, Robert S; Farmer, Stacey; Frederick, Blaise B; Nickerson, Lisa D; Lukas, Scott E; Stern, Chantal E

2015-03-01

Nicotine dependence is a chronic and difficult to treat disorder. While environmental stimuli associated with smoking precipitate craving and relapse, it is unknown whether smoking cues are cognitively processed differently than neutral stimuli. To evaluate working memory differences between smoking-related and neutral stimuli, we conducted a delay-match-to-sample (DMS) task concurrently with functional magnetic resonance imaging (fMRI) in nicotine-dependent participants. The DMS task evaluates brain activation during the encoding, maintenance and retrieval phases of working memory. Smoking images induced significantly more subjective craving, and greater midline cortical activation during encoding in comparison to neutral stimuli that were similar in content yet lacked a smoking component. The insula, which is involved in maintaining nicotine dependence, was active during the successful retrieval of previously viewed smoking versus neutral images. In contrast, neutral images required more prefrontal cortex-mediated active maintenance during the maintenance period. These findings indicate that distinct brain regions are involved in the different phases of working memory for smoking-related versus neutral images. Importantly, the results implicate the insula in the retrieval of smoking-related stimuli, which is relevant given the insula's emerging role in addiction. © 2013 Society for the Study of Addiction.

Interferometric inverse synthetic aperture radar imaging for space targets based on wideband direct sampling using two antennas

NASA Astrophysics Data System (ADS)

Tian, Biao; Liu, Yang; Xu, Shiyou; Chen, Zengping

2014-01-01

Interferometric inverse synthetic aperture radar (InISAR) imaging provides complementary information to monostatic inverse synthetic aperture radar (ISAR) imaging. This paper proposes a new InISAR imaging system for space targets based on wideband direct sampling using two antennas. The system is easy to realize in engineering since the motion trajectory of space targets can be known in advance, which is simpler than that of three receivers. In the preprocessing step, high speed movement compensation is carried out by designing an adaptive matched filter containing speed that is obtained from the narrow band information. Then, the coherent processing and keystone transform for ISAR imaging are adopted to reserve the phase history of each antenna. Through appropriate collocation of the system, image registration and phase unwrapping can be avoided. Considering the situation not to be satisfied, the influence of baseline variance is analyzed and compensation method is adopted. The corresponding size can be achieved by interferometric processing of the two complex ISAR images. Experimental results prove the validity of the analysis and the three-dimensional imaging algorithm.

An intergrated image matching algorithm and its application in the production of lunar map based on Chang'E-2 images

NASA Astrophysics Data System (ADS)

Wang, F.; Ren, X.; Liu, J.; Li, C.

2012-12-01

An accurate topographic map is a requisite for nearly every phase of research on lunar surface, as well as an essential tool for spacecraft mission planning and operating. Automatic image matching is a key component in this process that could ensure both quality and efficiency in the production of digital topographic map for the whole lunar coverage. It also provides the basis for lunar photographic surveying block adjustment. Image matching is relatively easy when encountered with good image texture conditions. However, on lunar images with characteristics such as constantly changing lighting conditions, large rotation angle, few or homogeneous texture and low image contrasts, it becomes a difficult and challenging job. Thus, we require a robust algorithm that is capable of dealing with light effect and image deformation to fulfill this task. In order to obtain a comprehensive review of currently dominated feature point extraction operators and test whether they are suitable for lunar images, we applied several operators, such as Harris, Forstner, Moravec, SIFT, to images from Chang'E-2 spacecraft. We found that SITF (Scale Invariant Feature Transform) is a scale invariant interest point detector that can provide robustness against errors caused by image distortions from scale, orientation or illumination condition changes. Meanwhile, its capability in detecting blob-like interest points satisfies the image characteristics of Chang'E-2. However, the uneven distributed and low accurate matching results cannot meet the practical requirements in lunar photogrammetry. In contrast, some high-precision corner detectors, such as Harris, Forstner, Moravec, are limited in their sensitivities to geometric rotation. Therefore, this paper proposed a least square matching algorithm that combines the advantages of both local feature detector and corner detector. We experiment this novel method in several sites. The accuracy assessment shows that the overall matching error is within 0.3 pixel and the matching reliability can reach 98%, which proves its robustness. This method had been successfully applied to over 700 scenes of lunar images that cover the entire moon, in finding corresponding pixels in a pair of images from adjacent tracks and aiding the automatic lunar image mosaicing. The completion of the 7 meter resolution lunar map shows the promise of this least square matching algorithm in applications with a large quantity of images to be processed.

An Improved Image Matching Method Based on Surf Algorithm

NASA Astrophysics Data System (ADS)

Chen, S. J.; Zheng, S. Z.; Xu, Z. G.; Guo, C. C.; Ma, X. L.

2018-04-01

Many state-of-the-art image matching methods, based on the feature matching, have been widely studied in the remote sensing field. These methods of feature matching which get highly operating efficiency, have a disadvantage of low accuracy and robustness. This paper proposes an improved image matching method which based on the SURF algorithm. The proposed method introduces color invariant transformation, information entropy theory and a series of constraint conditions to increase feature points detection and matching accuracy. First, the model of color invariant transformation is introduced for two matching images aiming at obtaining more color information during the matching process and information entropy theory is used to obtain the most information of two matching images. Then SURF algorithm is applied to detect and describe points from the images. Finally, constraint conditions which including Delaunay triangulation construction, similarity function and projective invariant are employed to eliminate the mismatches so as to improve matching precision. The proposed method has been validated on the remote sensing images and the result benefits from its high precision and robustness.

Phase in Optical Image Processing

NASA Astrophysics Data System (ADS)

Naughton, Thomas J.

2010-04-01

The use of phase has a long standing history in optical image processing, with early milestones being in the field of pattern recognition, such as VanderLugt's practical construction technique for matched filters, and (implicitly) Goodman's joint Fourier transform correlator. In recent years, the flexibility afforded by phase-only spatial light modulators and digital holography, for example, has enabled many processing techniques based on the explicit encoding and decoding of phase. One application area concerns efficient numerical computations. Pushing phase measurement to its physical limits, designs employing the physical properties of phase have ranged from the sensible to the wonderful, in some cases making computationally easy problems easier to solve and in other cases addressing mathematics' most challenging computationally hard problems. Another application area is optical image encryption, in which, typically, a phase mask modulates the fractional Fourier transformed coefficients of a perturbed input image, and the phase of the inverse transform is then sensed as the encrypted image. The inherent linearity that makes the system so elegant mitigates against its use as an effective encryption technique, but we show how a combination of optical and digital techniques can restore confidence in that security. We conclude with the concept of digital hologram image processing, and applications of same that are uniquely suited to optical implementation, where the processing, recognition, or encryption step operates on full field information, such as that emanating from a coherently illuminated real-world three-dimensional object.

Multi-template image matching using alpha-rooted biquaternion phase correlation with application to logo recognition

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2011-06-01

Hypercomplex approaches are seeing increased application to signal and image processing problems. The use of multicomponent hypercomplex numbers, such as quaternions, enables the simultaneous co-processing of multiple signal or image components. This joint processing capability can provide improved exploitation of the information contained in the data, thereby leading to improved performance in detection and recognition problems. In this paper, we apply hypercomplex processing techniques to the logo image recognition problem. Specifically, we develop an image matcher by generalizing classical phase correlation to the biquaternion case. We further incorporate biquaternion Fourier domain alpha-rooting enhancement to create Alpha-Rooted Biquaternion Phase Correlation (ARBPC). We present the mathematical properties which justify use of ARBPC as an image matcher. We present numerical performance results of a logo verification problem using real-world logo data, demonstrating the performance improvement obtained using the hypercomplex approach. We compare results of the hypercomplex approach to standard multi-template matching approaches.

A kind of graded sub-pixel motion estimation algorithm combining time-domain characteristics with frequency-domain phase correlation

NASA Astrophysics Data System (ADS)

Xie, Bing; Duan, Zhemin; Chen, Yu

2017-11-01

The mode of navigation based on scene match can assist UAV to achieve autonomous navigation and other missions. However, aerial multi-frame images of the UAV in the complex flight environment easily be affected by the jitter, noise and exposure, which will lead to image blur, deformation and other issues, and result in the decline of detection rate of the interested regional target. Aiming at this problem, we proposed a kind of Graded sub-pixel motion estimation algorithm combining time-domain characteristics with frequency-domain phase correlation. Experimental results prove the validity and accuracy of the proposed algorithm.

MatchGUI: A Graphical MATLAB-Based Tool for Automatic Image Co-Registration

NASA Technical Reports Server (NTRS)

Ansar, Adnan I.

2011-01-01

MatchGUI software, based on MATLAB, automatically matches two images and displays the match result by superimposing one image on the other. A slider bar allows focus to shift between the two images. There are tools for zoom, auto-crop to overlap region, and basic image markup. Given a pair of ortho-rectified images (focused primarily on Mars orbital imagery for now), this software automatically co-registers the imagery so that corresponding image pixels are aligned. MatchGUI requires minimal user input, and performs a registration over scale and inplane rotation fully automatically

Face identification with frequency domain matched filtering in mobile environments

NASA Astrophysics Data System (ADS)

Lee, Dong-Su; Woo, Yong-Hyun; Yeom, Seokwon; Kim, Shin-Hwan

2012-06-01

Face identification at a distance is very challenging since captured images are often degraded by blur and noise. Furthermore, the computational resources and memory are often limited in the mobile environments. Thus, it is very challenging to develop a real-time face identification system on the mobile device. This paper discusses face identification based on frequency domain matched filtering in the mobile environments. Face identification is performed by the linear or phase-only matched filter and sequential verification stages. The candidate window regions are decided by the major peaks of the linear or phase-only matched filtering outputs. The sequential stages comprise a skin-color test and an edge mask filtering test, which verify color and shape information of the candidate regions in order to remove false alarms. All algorithms are built on the mobile device using Android platform. The preliminary results show that face identification of East Asian people can be performed successfully in the mobile environments.

Robust Feature Matching in Terrestrial Image Sequences

NASA Astrophysics Data System (ADS)

Abbas, A.; Ghuffar, S.

2018-04-01

From the last decade, the feature detection, description and matching techniques are most commonly exploited in various photogrammetric and computer vision applications, which includes: 3D reconstruction of scenes, image stitching for panoramic creation, image classification, or object recognition etc. However, in terrestrial imagery of urban scenes contains various issues, which include duplicate and identical structures (i.e. repeated windows and doors) that cause the problem in feature matching phase and ultimately lead to failure of results specially in case of camera pose and scene structure estimation. In this paper, we will address the issue related to ambiguous feature matching in urban environment due to repeating patterns.

MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes

NASA Astrophysics Data System (ADS)

Zhao, Feng; Huang, Qingming; Wang, Hao; Gao, Wen

2010-12-01

Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matching image pairs with scale changes up to a factor of 7. Moreover, MOCC is much faster in comparison with the state-of-the-art matching methods. Experimental results on real images show the robustness and effectiveness of the proposed method.

A Feature-based Approach to Big Data Analysis of Medical Images

PubMed Central

Toews, Matthew; Wachinger, Christian; Estepar, Raul San Jose; Wells, William M.

2015-01-01

This paper proposes an inference method well-suited to large sets of medical images. The method is based upon a framework where distinctive 3D scale-invariant features are indexed efficiently to identify approximate nearest-neighbor (NN) feature matches in O(log N) computational complexity in the number of images N. It thus scales well to large data sets, in contrast to methods based on pair-wise image registration or feature matching requiring O(N) complexity. Our theoretical contribution is a density estimator based on a generative model that generalizes kernel density estimation and K-nearest neighbor (KNN) methods. The estimator can be used for on-the-fly queries, without requiring explicit parametric models or an off-line training phase. The method is validated on a large multi-site data set of 95,000,000 features extracted from 19,000 lung CT scans. Subject-level classification identifies all images of the same subjects across the entire data set despite deformation due to breathing state, including unintentional duplicate scans. State-of-the-art performance is achieved in predicting chronic pulmonary obstructive disorder (COPD) severity across the 5-category GOLD clinical rating, with an accuracy of 89% if both exact and one-off predictions are considered correct. PMID:26221685

A Feature-Based Approach to Big Data Analysis of Medical Images.

PubMed

Toews, Matthew; Wachinger, Christian; Estepar, Raul San Jose; Wells, William M

2015-01-01

This paper proposes an inference method well-suited to large sets of medical images. The method is based upon a framework where distinctive 3D scale-invariant features are indexed efficiently to identify approximate nearest-neighbor (NN) feature matches-in O (log N) computational complexity in the number of images N. It thus scales well to large data sets, in contrast to methods based on pair-wise image registration or feature matching requiring O(N) complexity. Our theoretical contribution is a density estimator based on a generative model that generalizes kernel density estimation and K-nearest neighbor (KNN) methods.. The estimator can be used for on-the-fly queries, without requiring explicit parametric models or an off-line training phase. The method is validated on a large multi-site data set of 95,000,000 features extracted from 19,000 lung CT scans. Subject-level classification identifies all images of the same subjects across the entire data set despite deformation due to breathing state, including unintentional duplicate scans. State-of-the-art performance is achieved in predicting chronic pulmonary obstructive disorder (COPD) severity across the 5-category GOLD clinical rating, with an accuracy of 89% if both exact and one-off predictions are considered correct.

A layered modulation method for pixel matching in online phase measuring profilometry

NASA Astrophysics Data System (ADS)

Li, Hongru; Feng, Guoying; Bourgade, Thomas; Yang, Peng; Zhou, Shouhuan; Asundi, Anand

2016-10-01

An online phase measuring profilometry with new layered modulation method for pixel matching is presented. In this method and in contrast with previous modulation matching methods, the captured images are enhanced by Retinex theory for better modulation distribution, and all different layer modulation masks are fully used to determine the displacement of a rectilinear moving object. High, medium and low modulation masks are obtained by performing binary segmentation with iterative Otsu method. The final shifting pixels are calculated based on centroid concept, and after that the aligned fringe patterns can be extracted from each frame. After performing Stoilov algorithm and a series of subsequent operations, the object profile on a translation stage is reconstructed. All procedures are carried out automatically, without setting specific parameters in advance. Numerical simulations are detailed and experimental results verify the validity and feasibility of the proposed approach.

Artificial intelligence (AI)-based relational matching and multimodal medical image fusion: generalized 3D approaches

NASA Astrophysics Data System (ADS)

Vajdic, Stevan M.; Katz, Henry E.; Downing, Andrew R.; Brooks, Michael J.

1994-09-01

A 3D relational image matching/fusion algorithm is introduced. It is implemented in the domain of medical imaging and is based on Artificial Intelligence paradigms--in particular, knowledge base representation and tree search. The 2D reference and target images are selected from 3D sets and segmented into non-touching and non-overlapping regions, using iterative thresholding and/or knowledge about the anatomical shapes of human organs. Selected image region attributes are calculated. Region matches are obtained using a tree search, and the error is minimized by evaluating a `goodness' of matching function based on similarities of region attributes. Once the matched regions are found and the spline geometric transform is applied to regional centers of gravity, images are ready for fusion and visualization into a single 3D image of higher clarity.

Medical microscopic image matching based on relativity

NASA Astrophysics Data System (ADS)

Xie, Fengying; Zhu, Liangen; Jiang, Zhiguo

2003-12-01

In this paper, an effective medical micro-optical image matching algorithm based on relativity is described. The algorithm includes the following steps: Firstly, selecting a sub-area that has obvious character in one of the two images as standard image; Secondly, finding the right matching position in the other image; Thirdly, applying coordinate transformation to merge the two images together. As a kind of application of image matching in medical micro-optical image, this method overcomes the shortcoming of microscope whose visual field is little and makes it possible to watch a big object or many objects in one view. Simultaneously it implements adaptive selection of standard image, and has a satisfied matching speed and result.

Quantitative 3-d diagnostic ultrasound imaging using a modified transducer array and an automated image tracking technique.

PubMed

Hossack, John A; Sumanaweera, Thilaka S; Napel, Sandy; Ha, Jun S

2002-08-01

An approach for acquiring dimensionally accurate three-dimensional (3-D) ultrasound data from multiple 2-D image planes is presented. This is based on the use of a modified linear-phased array comprising a central imaging array that acquires multiple, essentially parallel, 2-D slices as the transducer is translated over the tissue of interest. Small, perpendicularly oriented, tracking arrays are integrally mounted on each end of the imaging transducer. As the transducer is translated in an elevational direction with respect to the central imaging array, the images obtained by the tracking arrays remain largely coplanar. The motion between successive tracking images is determined using a minimum sum of absolute difference (MSAD) image matching technique with subpixel matching resolution. An initial phantom scanning-based test of a prototype 8 MHz array indicates that linear dimensional accuracy of 4.6% (2 sigma) is achievable. This result compares favorably with those obtained using an assumed average velocity [31.5% (2 sigma) accuracy] and using an approach based on measuring image-to-image decorrelation [8.4% (2 sigma) accuracy]. The prototype array and imaging system were also tested in a clinical environment, and early results suggest that the approach has the potential to enable a low cost, rapid, screening method for detecting carotid artery stenosis. The average time for performing a screening test for carotid stenosis was reduced from an average of 45 minutes using 2-D duplex Doppler to 12 minutes using the new 3-D scanning approach.

Interferometric Imaging Directly with Closure Phases and Closure Amplitudes

NASA Astrophysics Data System (ADS)

Chael, Andrew A.; Johnson, Michael D.; Bouman, Katherine L.; Blackburn, Lindy L.; Akiyama, Kazunori; Narayan, Ramesh

2018-04-01

Interferometric imaging now achieves angular resolutions as fine as ∼10 μas, probing scales that are inaccessible to single telescopes. Traditional synthesis imaging methods require calibrated visibilities; however, interferometric calibration is challenging, especially at high frequencies. Nevertheless, most studies present only a single image of their data after a process of “self-calibration,” an iterative procedure where the initial image and calibration assumptions can significantly influence the final image. We present a method for efficient interferometric imaging directly using only closure amplitudes and closure phases, which are immune to station-based calibration errors. Closure-only imaging provides results that are as noncommittal as possible and allows for reconstructing an image independently from separate amplitude and phase self-calibration. While closure-only imaging eliminates some image information (e.g., the total image flux density and the image centroid), this information can be recovered through a small number of additional constraints. We demonstrate that closure-only imaging can produce high-fidelity results, even for sparse arrays such as the Event Horizon Telescope, and that the resulting images are independent of the level of systematic amplitude error. We apply closure imaging to VLBA and ALMA data and show that it is capable of matching or exceeding the performance of traditional self-calibration and CLEAN for these data sets.

An enhanced multi-view vertical line locus matching algorithm of object space ground primitives based on positioning consistency for aerial and space images

NASA Astrophysics Data System (ADS)

Zhang, Ka; Sheng, Yehua; Wang, Meizhen; Fu, Suxia

2018-05-01

The traditional multi-view vertical line locus (TMVLL) matching method is an object-space-based method that is commonly used to directly acquire spatial 3D coordinates of ground objects in photogrammetry. However, the TMVLL method can only obtain one elevation and lacks an accurate means of validating the matching results. In this paper, we propose an enhanced multi-view vertical line locus (EMVLL) matching algorithm based on positioning consistency for aerial or space images. The algorithm involves three components: confirming candidate pixels of the ground primitive in the base image, multi-view image matching based on the object space constraints for all candidate pixels, and validating the consistency of the object space coordinates with the multi-view matching result. The proposed algorithm was tested using actual aerial images and space images. Experimental results show that the EMVLL method successfully solves the problems associated with the TMVLL method, and has greater reliability, accuracy and computing efficiency.

Adaptive matched filter spatial detection performance on standard imagery from a wideband VHF/UHF SAR

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

Allen, M.R.; Phillips, S.A.; Sofianos, D.J.

1994-12-31

The adaptive matched filter was implemented as a spatial detector for amplitude-only or complex images, and applied to an image formed by standard narrow band means from a wide angle, wideband radar. Direct performance comparisons were made between different implementations and various matched and mismatched cases by using a novel approach to generate ROC curves parametrically. For perfectly matched cases, performance using imaged targets was found to be significantly lower than potential performance of artificial targets whose features differed from the background. Incremental gain due to whitening the background was also found to be small, indicating little background spatial correlation.more » It is conjectured that the relatively featureless behavior in both targets and background is due to the image formation process, since this technique averages together all wide angle, wideband information. For mismatched cases where the signature was unknown, the amplitude detector losses were approximately equal to whatever gain over noncoherent integration that matching provided. However, the complex detector was generally very sensitive to unknown information, especially phase, and produced much larger losses. Whitening under these mismatched conditions produced further losses. Detector choice thus depends primarily on how reproducible target signatures are, especially if phase is used, and the subsequent number of stored signatures necessary to account for various imaging aspect angles.« less

PMN-PT Single-Crystal High-Frequency Kerfless Phased Array

PubMed Central

Chen, Ruimin; Cabrera-Munoz, Nestor E.; Lam, Kwok Ho; Hsu, Hsiu-sheng; Zheng, Fan; Zhou, Qifa; Shung, K. Kirk

2015-01-01

This paper reports the design, fabrication, and characterization of a miniature high-frequency kerfless phased array prepared from a PMN-PT single crystal for forward-looking intravascular or endoscopic imaging applications. After lapping down to around 40 μm, the PMN-PT material was utilized to fabricate 32-element kerfless phased arrays using micromachining techniques. The aperture size of the active area was only 1.0 × 1.0 mm. The measured results showed that the array had a center frequency of 40 MHz, a bandwidth of 34% at −6 dB with a polymer matching layer, and an insertion loss of 20 dB at the center frequency. Phantom images were acquired and compared with simulated images. The results suggest that the feasibility of developing a phased array mounted at the tip of a forward-looking intravascular catheter or endoscope. The fabricated array exhibits much higher sensitivity than PZT ceramic-based arrays and demonstrates that PMN-PT is well suited for this application. PMID:24859667

Leakage radiation interference microscopy.

PubMed

Descrovi, Emiliano; Barakat, Elsie; Angelini, Angelo; Munzert, Peter; De Leo, Natascia; Boarino, Luca; Giorgis, Fabrizio; Herzig, Hans Peter

2013-09-01

We present a proof of principle for a new imaging technique combining leakage radiation microscopy with high-resolution interference microscopy. By using oil immersion optics it is demonstrated that amplitude and phase can be retrieved from optical fields, which are evanescent in air. This technique is illustratively applied for mapping a surface mode propagating onto a planar dielectric multilayer on a thin glass substrate. The surface mode propagation constant estimated after Fourier transformation of the measured complex field is well matched with an independent measurement based on back focal plane imaging.

Overcoming turbulence-induced space-variant blur by using phase-diverse speckle.

PubMed

Thelen, Brian J; Paxman, Richard G; Carrara, David A; Seldin, John H

2009-01-01

Space-variant blur occurs when imaging through volume turbulence over sufficiently large fields of view. Space-variant effects are particularly severe in horizontal-path imaging, slant-path (air-to-ground or ground-to-air) geometries, and ground-based imaging of low-elevation satellites or astronomical objects. In these geometries, the isoplanatic angle can be comparable to or even smaller than the diffraction-limited resolution angle. We report on a postdetection correction method that seeks to correct for the effects of space-variant aberrations, with the goal of reconstructing near-diffraction-limited imagery. Our approach has been to generalize the method of phase-diverse speckle (PDS) by using a physically motivated distributed-phase-screen model. Simulation results are presented that demonstrate the reconstruction of near-diffraction-limited imagery under both matched and mismatched model assumptions. In addition, we present evidence that PDS could be used as a beaconless wavefront sensor in a multiconjugate adaptive optics system when imaging extended scenes.

Automatic Matching of Large Scale Images and Terrestrial LIDAR Based on App Synergy of Mobile Phone

NASA Astrophysics Data System (ADS)

Xia, G.; Hu, C.

2018-04-01

The digitalization of Cultural Heritage based on ground laser scanning technology has been widely applied. High-precision scanning and high-resolution photography of cultural relics are the main methods of data acquisition. The reconstruction with the complete point cloud and high-resolution image requires the matching of image and point cloud, the acquisition of the homonym feature points, the data registration, etc. However, the one-to-one correspondence between image and corresponding point cloud depends on inefficient manual search. The effective classify and management of a large number of image and the matching of large image and corresponding point cloud will be the focus of the research. In this paper, we propose automatic matching of large scale images and terrestrial LiDAR based on APP synergy of mobile phone. Firstly, we develop an APP based on Android, take pictures and record related information of classification. Secondly, all the images are automatically grouped with the recorded information. Thirdly, the matching algorithm is used to match the global and local image. According to the one-to-one correspondence between the global image and the point cloud reflection intensity image, the automatic matching of the image and its corresponding laser radar point cloud is realized. Finally, the mapping relationship between global image, local image and intensity image is established according to homonym feature point. So we can establish the data structure of the global image, the local image in the global image, the local image corresponding point cloud, and carry on the visualization management and query of image.

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.

3D deformable organ model based liver motion tracking in ultrasound videos

NASA Astrophysics Data System (ADS)

Kim, Jung-Bae; Hwang, Youngkyoo; Oh, Young-Taek; Bang, Won-Chul; Lee, Heesae; Kim, James D. K.; Kim, Chang Yeong

2013-03-01

This paper presents a novel method of using 2D ultrasound (US) cine images during image-guided therapy to accurately track the 3D position of a tumor even when the organ of interest is in motion due to patient respiration. Tracking is possible thanks to a 3D deformable organ model we have developed. The method consists of three processes in succession. The first process is organ modeling where we generate a personalized 3D organ model from high quality 3D CT or MR data sets captured during three different respiratory phases. The model includes the organ surface, vessel and tumor, which can all deform and move in accord with patient respiration. The second process is registration of the organ model to 3D US images. From 133 respiratory phase candidates generated from the deformable organ model, we resolve the candidate that best matches the 3D US images according to vessel centerline and surface. As a result, we can determine the position of the US probe. The final process is real-time tracking using 2D US cine images captured by the US probe. We determine the respiratory phase by tracking the diaphragm on the image. The 3D model is then deformed according to respiration phase and is fitted to the image by considering the positions of the vessels. The tumor's 3D positions are then inferred based on respiration phase. Testing our method on real patient data, we have found the accuracy of 3D position is within 3.79mm and processing time is 5.4ms during tracking.

Robust feature estimation by non-rigid hierarchical image registration and its application in disparity measurement

NASA Astrophysics Data System (ADS)

Badshah, Amir; Choudhry, Aadil Jaleel; Ullah, Shan

2017-03-01

Industries are moving towards automation in order to increase productivity and ensure quality. Variety of electronic and electromagnetic systems are being employed to assist human operator in fast and accurate quality inspection of products. Majority of these systems are equipped with cameras and rely on diverse image processing algorithms. Information is lost in 2D image, therefore acquiring accurate 3D data from 2D images is an open issue. FAST, SURF and SIFT are well-known spatial domain techniques for features extraction and henceforth image registration to find correspondence between images. The efficiency of these methods is measured in terms of the number of perfect matches found. A novel fast and robust technique for stereo-image processing is proposed. It is based on non-rigid registration using modified normalized phase correlation. The proposed method registers two images in hierarchical fashion using quad-tree structure. The registration process works through global to local level resulting in robust matches even in presence of blur and noise. The computed matches can further be utilized to determine disparity and depth for industrial product inspection. The same can be used in driver assistance systems. The preliminary tests on Middlebury dataset produced satisfactory results. The execution time for a 413 x 370 stereo-pair is 500ms approximately on a low cost DSP.

A FPGA-based architecture for real-time image matching

NASA Astrophysics Data System (ADS)

Wang, Jianhui; Zhong, Sheng; Xu, Wenhui; Zhang, Weijun; Cao, Zhiguo

2013-10-01

Image matching is a fundamental task in computer vision. It is used to establish correspondence between two images taken at different viewpoint or different time from the same scene. However, its large computational complexity has been a challenge to most embedded systems. This paper proposes a single FPGA-based image matching system, which consists of SIFT feature detection, BRIEF descriptor extraction and BRIEF matching. It optimizes the FPGA architecture for the SIFT feature detection to reduce the FPGA resources utilization. Moreover, we implement BRIEF description and matching on FPGA also. The proposed system can implement image matching at 30fps (frame per second) for 1280x720 images. Its processing speed can meet the demand of most real-life computer vision applications.

An accurate algorithm to match imperfectly matched images for lung tumor detection without markers

PubMed Central

Rozario, Timothy; Bereg, Sergey; Yan, Yulong; Chiu, Tsuicheng; Liu, Honghuan; Kearney, Vasant; Jiang, Lan

2015-01-01

In order to locate lung tumors on kV projection images without internal markers, digitally reconstructed radiographs (DRRs) are created and compared with projection images. However, lung tumors always move due to respiration and their locations change on projection images while they are static on DRRs. In addition, global image intensity discrepancies exist between DRRs and projections due to their different image orientations, scattering, and noises. This adversely affects comparison accuracy. A simple but efficient comparison algorithm is reported to match imperfectly matched projection images and DRRs. The kV projection images were matched with different DRRs in two steps. Preprocessing was performed in advance to generate two sets of DRRs. The tumors were removed from the planning 3D CT for a single phase of planning 4D CT images using planning contours of tumors. DRRs of background and DRRs of tumors were generated separately for every projection angle. The first step was to match projection images with DRRs of background signals. This method divided global images into a matrix of small tiles and similarities were evaluated by calculating normalized cross‐correlation (NCC) between corresponding tiles on projections and DRRs. The tile configuration (tile locations) was automatically optimized to keep the tumor within a single projection tile that had a bad matching with the corresponding DRR tile. A pixel‐based linear transformation was determined by linear interpolations of tile transformation results obtained during tile matching. The background DRRs were transformed to the projection image level and subtracted from it. The resulting subtracted image now contained only the tumor. The second step was to register DRRs of tumors to the subtracted image to locate the tumor. This method was successfully applied to kV fluoro images (about 1000 images) acquired on a Vero (BrainLAB) for dynamic tumor tracking on phantom studies. Radiation opaque markers were implanted and used as ground truth for tumor positions. Although other organs and bony structures introduced strong signals superimposed on tumors at some angles, this method accurately located tumors on every projection over 12 gantry angles. The maximum error was less than 2.2 mm, while the total average error was less than 0.9 mm. This algorithm was capable of detecting tumors without markers, despite strong background signals. PACS numbers: 87.57.cj, 87.57.cp87.57.nj, 87.57.np, 87.57.Q‐, 87.59.bf, 87.63.lm

Determining similarity in histological images using graph-theoretic description and matching methods for content-based image retrieval in medical diagnostics.

PubMed

Sharma, Harshita; Alekseychuk, Alexander; Leskovsky, Peter; Hellwich, Olaf; Anand, R S; Zerbe, Norman; Hufnagl, Peter

2012-10-04

Computer-based analysis of digitalized histological images has been gaining increasing attention, due to their extensive use in research and routine practice. The article aims to contribute towards the description and retrieval of histological images by employing a structural method using graphs. Due to their expressive ability, graphs are considered as a powerful and versatile representation formalism and have obtained a growing consideration especially by the image processing and computer vision community. The article describes a novel method for determining similarity between histological images through graph-theoretic description and matching, for the purpose of content-based retrieval. A higher order (region-based) graph-based representation of breast biopsy images has been attained and a tree-search based inexact graph matching technique has been employed that facilitates the automatic retrieval of images structurally similar to a given image from large databases. The results obtained and evaluation performed demonstrate the effectiveness and superiority of graph-based image retrieval over a common histogram-based technique. The employed graph matching complexity has been reduced compared to the state-of-the-art optimal inexact matching methods by applying a pre-requisite criterion for matching of nodes and a sophisticated design of the estimation function, especially the prognosis function. The proposed method is suitable for the retrieval of similar histological images, as suggested by the experimental and evaluation results obtained in the study. It is intended for the use in Content Based Image Retrieval (CBIR)-requiring applications in the areas of medical diagnostics and research, and can also be generalized for retrieval of different types of complex images. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1224798882787923.

Determining similarity in histological images using graph-theoretic description and matching methods for content-based image retrieval in medical diagnostics

PubMed Central

2012-01-01

Background Computer-based analysis of digitalized histological images has been gaining increasing attention, due to their extensive use in research and routine practice. The article aims to contribute towards the description and retrieval of histological images by employing a structural method using graphs. Due to their expressive ability, graphs are considered as a powerful and versatile representation formalism and have obtained a growing consideration especially by the image processing and computer vision community. Methods The article describes a novel method for determining similarity between histological images through graph-theoretic description and matching, for the purpose of content-based retrieval. A higher order (region-based) graph-based representation of breast biopsy images has been attained and a tree-search based inexact graph matching technique has been employed that facilitates the automatic retrieval of images structurally similar to a given image from large databases. Results The results obtained and evaluation performed demonstrate the effectiveness and superiority of graph-based image retrieval over a common histogram-based technique. The employed graph matching complexity has been reduced compared to the state-of-the-art optimal inexact matching methods by applying a pre-requisite criterion for matching of nodes and a sophisticated design of the estimation function, especially the prognosis function. Conclusion The proposed method is suitable for the retrieval of similar histological images, as suggested by the experimental and evaluation results obtained in the study. It is intended for the use in Content Based Image Retrieval (CBIR)-requiring applications in the areas of medical diagnostics and research, and can also be generalized for retrieval of different types of complex images. Virtual Slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1224798882787923. PMID:23035717

Assessment of phase based dose modulation for improved dose efficiency in cardiac CT on an anthropomorphic motion phantom

NASA Astrophysics Data System (ADS)

Budde, Adam; Nilsen, Roy; Nett, Brian

2014-03-01

State of the art automatic exposure control modulates the tube current across view angle and Z based on patient anatomy for use in axial full scan reconstructions. Cardiac CT, however, uses a fundamentally different image reconstruction that applies a temporal weighting to reduce motion artifacts. This paper describes a phase based mA modulation that goes beyond axial and ECG modulation; it uses knowledge of the temporal view weighting applied within the reconstruction algorithm to improve dose efficiency in cardiac CT scanning. Using physical phantoms and synthetic noise emulation, we measure how knowledge of sinogram temporal weighting and the prescribed cardiac phase can be used to improve dose efficiency. First, we validated that a synthetic CT noise emulation method produced realistic image noise. Next, we used the CT noise emulation method to simulate mA modulation on scans of a physical anthropomorphic phantom where a motion profile corresponding to a heart rate of 60 beats per minute was used. The CT noise emulation method matched noise to lower dose scans across the image within 1.5% relative error. Using this noise emulation method to simulate modulating the mA while keeping the total dose constant, the image variance was reduced by an average of 11.9% on a scan with 50 msec padding, demonstrating improved dose efficiency. Radiation dose reduction in cardiac CT can be achieved while maintaining the same level of image noise through phase based dose modulation that incorporates knowledge of the cardiac reconstruction algorithm.

Image encryption based on fractal-structured phase mask in fractional Fourier transform domain

NASA Astrophysics Data System (ADS)

Zhao, Meng-Dan; Gao, Xu-Zhen; Pan, Yue; Zhang, Guan-Lin; Tu, Chenghou; Li, Yongnan; Wang, Hui-Tian

2018-04-01

We present an optical encryption approach based on the combination of fractal Fresnel lens (FFL) and fractional Fourier transform (FrFT). Our encryption approach is in fact a four-fold encryption scheme, including the random phase encoding produced by the Gerchberg–Saxton algorithm, a FFL, and two FrFTs. A FFL is composed of a Sierpinski carpet fractal plate and a Fresnel zone plate. In our encryption approach, the security is enhanced due to the more expandable key spaces and the use of FFL overcomes the alignment problem of the optical axis in optical system. Only using the perfectly matched parameters of the FFL and the FrFT, the plaintext can be recovered well. We present an image encryption algorithm that from the ciphertext we can get two original images by the FrFT with two different phase distribution keys, obtained by performing 100 iterations between the two plaintext and ciphertext, respectively. We test the sensitivity of our approach to various parameters such as the wavelength of light, the focal length of FFL, and the fractional orders of FrFT. Our approach can resist various attacks.

Implementation of sobel method to detect the seed rubber plant leaves

NASA Astrophysics Data System (ADS)

Suyanto; Munte, J.

2018-03-01

This research was conducted to develop a system that can identify and recognize the type of rubber tree based on the pattern of leaves of the plant. The steps research are started with the identification of the image data acquisition, image processing, image edge detection and identification method template matching. Edge detection is using Sobel edge detection. Pattern recognition would detect image as input and compared with other images in a database called templates. Experiments carried out in one phase, identification of the leaf edge, using a rubber plant leaf image 14 are superior and 5 for each type of test images (clones) of the plant. From the experimental results obtained by the recognition rate of 91.79%.

WE-H-207A-02: Attenuation Correction in 4D-PET Using a Single-Phase Attenuation Map

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

Kalantari, F; Wang, J

2016-06-15

Purpose: 4D-PET imaging has been proposed as a potential solution to the respiratory motion effect in thoracic region. CT-based attenuation correction (AC) is an essential step toward quantitative imaging for PET. However, due to the temporal difference of 4D-PET and a single breath-hold CT, motion artifacts are observed in the attenuation-corrected PET images that can lead to error in tumor shape and uptake. We introduce a practical method for aligning single-phase CT to all other 4D-PET phases using a penalized non-rigid demons registration. Methods: Individual 4D-PET frames were reconstructed without AC. Non-rigid Demons registration was used to derive deformation vectormore » fields (DVFs) between the PET matched with CT phase and other 4D-PET images. While attenuated PET images provide enough useful data for organ borders such as lung and liver, tumors are not distinguishable from background due to loss of contrast. To preserve tumor shape in different phases, from CT image an ROI covering tumor was excluded from non-rigid transformation. Mean DVF of the central region of the tumor was assigned to all voxels in the ROI. This process mimics a rigid transformation of tumor along with a non-rigid transformation of other organs. 4D XCAT phantom with spherical tumors in lung with diameters ranging from 10 to 40 mm was used to evaluate the algorithm. Results: Motion related induced artifacts in attenuation-corrected 4D-PET images were significantly reduced. For tumors smaller than 20 mm, non-rigid transformation was capable to provide quantitative results. However, for larger tumors, where tumor self-attenuation is considerable, our combined method yields superior results. Conclusion: We introduced a practical method for deforming a single CT to match all 4D-PET images for accurate AC. Although 4D-PET data include insignificant anatomical information, we showed that they are still useful to estimate DVFs for aligning attenuation map and accurate AC.« less

Image matching for digital close-range stereo photogrammetry based on constraints of Delaunay triangulated network and epipolar-line

NASA Astrophysics Data System (ADS)

Zhang, K.; Sheng, Y. H.; Li, Y. Q.; Han, B.; Liang, Ch.; Sha, W.

2006-10-01

In the field of digital photogrammetry and computer vision, the determination of conjugate points in a stereo image pair, referred to as "image matching," is the critical step to realize automatic surveying and recognition. Traditional matching methods encounter some problems in the digital close-range stereo photogrammetry, because the change of gray-scale or texture is not obvious in the close-range stereo images. The main shortcoming of traditional matching methods is that geometric information of matching points is not fully used, which will lead to wrong matching results in regions with poor texture. To fully use the geometry and gray-scale information, a new stereo image matching algorithm is proposed in this paper considering the characteristics of digital close-range photogrammetry. Compared with the traditional matching method, the new algorithm has three improvements on image matching. Firstly, shape factor, fuzzy maths and gray-scale projection are introduced into the design of synthetical matching measure. Secondly, the topology connecting relations of matching points in Delaunay triangulated network and epipolar-line are used to decide matching order and narrow the searching scope of conjugate point of the matching point. Lastly, the theory of parameter adjustment with constraint is introduced into least square image matching to carry out subpixel level matching under epipolar-line constraint. The new algorithm is applied to actual stereo images of a building taken by digital close-range photogrammetric system. The experimental result shows that the algorithm has a higher matching speed and matching accuracy than pyramid image matching algorithm based on gray-scale correlation.

MIMO channel estimation and evaluation for airborne traffic surveillance in cellular networks

NASA Astrophysics Data System (ADS)

Vahidi, Vahid; Saberinia, Ebrahim

2018-01-01

A channel estimation (CE) procedure based on compressed sensing is proposed to estimate the multiple-input multiple-output sparse channel for traffic data transmission from drones to ground stations. The proposed procedure consists of an offline phase and a real-time phase. In the offline phase, a pilot arrangement method, which considers the interblock and block mutual coherence simultaneously, is proposed. The real-time phase contains three steps. At the first step, it obtains the priori estimate of the channel by block orthogonal matching pursuit; afterward, it utilizes that estimated channel to calculate the linear minimum mean square error of the received pilots. Finally, the block compressive sampling matching pursuit utilizes the enhanced received pilots to estimate the channel more accurately. The performance of the CE procedure is evaluated by simulating the transmission of traffic data through the communication channel and evaluating its fidelity for car detection after demodulation. Simulation results indicate that the proposed CE technique enhances the performance of the car detection in a traffic image considerably.

Global rotational motion and displacement estimation of digital image stabilization based on the oblique vectors matching algorithm

NASA Astrophysics Data System (ADS)

Yu, Fei; Hui, Mei; Zhao, Yue-jin

2009-08-01

The image block matching algorithm based on motion vectors of correlative pixels in oblique direction is presented for digital image stabilization. The digital image stabilization is a new generation of image stabilization technique which can obtains the information of relative motion among frames of dynamic image sequences by the method of digital image processing. In this method the matching parameters are calculated from the vectors projected in the oblique direction. The matching parameters based on the vectors contain the information of vectors in transverse and vertical direction in the image blocks at the same time. So the better matching information can be obtained after making correlative operation in the oblique direction. And an iterative weighted least square method is used to eliminate the error of block matching. The weights are related with the pixels' rotational angle. The center of rotation and the global emotion estimation of the shaking image can be obtained by the weighted least square from the estimation of each block chosen evenly from the image. Then, the shaking image can be stabilized with the center of rotation and the global emotion estimation. Also, the algorithm can run at real time by the method of simulated annealing in searching method of block matching. An image processing system based on DSP was used to exam this algorithm. The core processor in the DSP system is TMS320C6416 of TI, and the CCD camera with definition of 720×576 pixels was chosen as the input video signal. Experimental results show that the algorithm can be performed at the real time processing system and have an accurate matching precision.

Nonlocal Means Denoising of Self-Gated and k-Space Sorted 4-Dimensional Magnetic Resonance Imaging Using Block-Matching and 3-Dimensional Filtering: Implications for Pancreatic Tumor Registration and Segmentation

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

Jin, Jun; McKenzie, Elizabeth; Fan, Zhaoyang

Purpose: To denoise self-gated k-space sorted 4-dimensional magnetic resonance imaging (SG-KS-4D-MRI) by applying a nonlocal means denoising filter, block-matching and 3-dimensional filtering (BM3D), to test its impact on the accuracy of 4D image deformable registration and automated tumor segmentation for pancreatic cancer patients. Methods and Materials: Nine patients with pancreatic cancer and abdominal SG-KS-4D-MRI were included in the study. Block-matching and 3D filtering was adapted to search in the axial slices/frames adjacent to the reference image patch in the spatial and temporal domains. The patches with high similarity to the reference patch were used to collectively denoise the 4D-MRI image. Themore » pancreas tumor was manually contoured on the first end-of-exhalation phase for both the raw and the denoised 4D-MRI. B-spline deformable registration was applied to the subsequent phases for contour propagation. The consistency of tumor volume defined by the standard deviation of gross tumor volumes from 10 breathing phases (σ-GTV), tumor motion trajectories in 3 cardinal motion planes, 4D-MRI imaging noise, and image contrast-to-noise ratio were compared between the raw and denoised groups. Results: Block-matching and 3D filtering visually and quantitatively reduced image noise by 52% and improved image contrast-to-noise ratio by 56%, without compromising soft tissue edge definitions. Automatic tumor segmentation is statistically more consistent on the denoised 4D-MRI (σ-GTV = 0.6 cm{sup 3}) than on the raw 4D-MRI (σ-GTV = 0.8 cm{sup 3}). Tumor end-of-exhalation location is also more reproducible on the denoised 4D-MRI than on the raw 4D-MRI in all 3 cardinal motion planes. Conclusions: Block-matching and 3D filtering can significantly reduce random image noise while maintaining structural features in the SG-KS-4D-MRI datasets. In this study of pancreatic tumor segmentation, automatic segmentation of GTV in the registered image sets is shown to be more consistent on the denoised 4D-MRI than on the raw 4D-MRI.« less

Fuzzy Matching Based on Gray-scale Difference for Quantum Images

NASA Astrophysics Data System (ADS)

Luo, GaoFeng; Zhou, Ri-Gui; Liu, XingAo; Hu, WenWen; Luo, Jia

2018-05-01

Quantum image processing has recently emerged as an essential problem in practical tasks, e.g. real-time image matching. Previous studies have shown that the superposition and entanglement of quantum can greatly improve the efficiency of complex image processing. In this paper, a fuzzy quantum image matching scheme based on gray-scale difference is proposed to find out the target region in a reference image, which is very similar to the template image. Firstly, we employ the proposed enhanced quantum representation (NEQR) to store digital images. Then some certain quantum operations are used to evaluate the gray-scale difference between two quantum images by thresholding. If all of the obtained gray-scale differences are not greater than the threshold value, it indicates a successful fuzzy matching of quantum images. Theoretical analysis and experiments show that the proposed scheme performs fuzzy matching at a low cost and also enables exponentially significant speedup via quantum parallel computation.

Constraint-based stereo matching

NASA Technical Reports Server (NTRS)

Kuan, D. T.

1987-01-01

The major difficulty in stereo vision is the correspondence problem that requires matching features in two stereo images. Researchers describe a constraint-based stereo matching technique using local geometric constraints among edge segments to limit the search space and to resolve matching ambiguity. Edge segments are used as image features for stereo matching. Epipolar constraint and individual edge properties are used to determine possible initial matches between edge segments in a stereo image pair. Local edge geometric attributes such as continuity, junction structure, and edge neighborhood relations are used as constraints to guide the stereo matching process. The result is a locally consistent set of edge segment correspondences between stereo images. These locally consistent matches are used to generate higher-level hypotheses on extended edge segments and junctions to form more global contexts to achieve global consistency.

A diffusion-matched principal component analysis (DM-PCA) based two-channel denoising procedure for high-resolution diffusion-weighted MRI

PubMed Central

Chang, Hing-Chiu; Bilgin, Ali; Bernstein, Adam; Trouard, Theodore P.

2018-01-01

Over the past several years, significant efforts have been made to improve the spatial resolution of diffusion-weighted imaging (DWI), aiming at better detecting subtle lesions and more reliably resolving white-matter fiber tracts. A major concern with high-resolution DWI is the limited signal-to-noise ratio (SNR), which may significantly offset the advantages of high spatial resolution. Although the SNR of DWI data can be improved by denoising in post-processing, existing denoising procedures may potentially reduce the anatomic resolvability of high-resolution imaging data. Additionally, non-Gaussian noise induced signal bias in low-SNR DWI data may not always be corrected with existing denoising approaches. Here we report an improved denoising procedure, termed diffusion-matched principal component analysis (DM-PCA), which comprises 1) identifying a group of (not necessarily neighboring) voxels that demonstrate very similar magnitude signal variation patterns along the diffusion dimension, 2) correcting low-frequency phase variations in complex-valued DWI data, 3) performing PCA along the diffusion dimension for real- and imaginary-components (in two separate channels) of phase-corrected DWI voxels with matched diffusion properties, 4) suppressing the noisy PCA components in real- and imaginary-components, separately, of phase-corrected DWI data, and 5) combining real- and imaginary-components of denoised DWI data. Our data show that the new two-channel (i.e., for real- and imaginary-components) DM-PCA denoising procedure performs reliably without noticeably compromising anatomic resolvability. Non-Gaussian noise induced signal bias could also be reduced with the new denoising method. The DM-PCA based denoising procedure should prove highly valuable for high-resolution DWI studies in research and clinical uses. PMID:29694400

Effective increase in beam emittance by phase-space expansion using asymmetric Bragg diffraction.

PubMed

Chu, Chia-Hung; Tang, Mau-Tsu; Chang, Shih-Lin

2015-08-24

We propose an innovative method to extend the utilization of the phase space downstream of a synchrotron light source for X-ray transmission microscopy. Based on the dynamical theory of X-ray diffraction, asymmetrically cut perfect crystals are applied to reshape the position-angle-wavelength space of the light source, by which the usable phase space of the source can be magnified by over one hundred times, thereby "phase-space-matching" the source with the objective lens of the microscope. The method's validity is confirmed using SHADOW code simulations, and aberration through an optical lens such as a Fresnel zone plate is examined via matrix optics for nano-resolution X-ray images.

Probabilistic model for quick detection of dissimilar binary images

NASA Astrophysics Data System (ADS)

Mustafa, Adnan A. Y.

2015-09-01

We present a quick method to detect dissimilar binary images. The method is based on a "probabilistic matching model" for image matching. The matching model is used to predict the probability of occurrence of distinct-dissimilar image pairs (completely different images) when matching one image to another. Based on this model, distinct-dissimilar images can be detected by matching only a few points between two images with high confidence, namely 11 points for a 99.9% successful detection rate. For image pairs that are dissimilar but not distinct-dissimilar, more points need to be mapped. The number of points required to attain a certain successful detection rate or confidence depends on the amount of similarity between the compared images. As this similarity increases, more points are required. For example, images that differ by 1% can be detected by mapping fewer than 70 points on average. More importantly, the model is image size invariant; so, images of any sizes will produce high confidence levels with a limited number of matched points. As a result, this method does not suffer from the image size handicap that impedes current methods. We report on extensive tests conducted on real images of different sizes.

Interferometric imaging of the 2011-2013 Campi Flegrei unrest

NASA Astrophysics Data System (ADS)

De Siena, Luca; Nakahara, Hisashi; Zaccarelli, Lucia; Sammarco, Carmelo; La Rocca, Mario; Bianco, Francesca

2017-04-01

After its 1983-84 seismic and deformation crisis, seismologists have recorded very low and clustered seismicity at Campi Flegrei caldera (Italy). Hence, noise interferometry imaging has become the only option to image the present volcano logical state of the volcano. Three-component noise data recorded before, during, and after Campi Flegrei last deformation and geochemical unrest (2011-2013) have thus been processed with up-to-date interferometric imaging workflow based on MSNoise. Noise anisotropy, which strongly affects measurements throughout the caldera at all frequencies, has been accounted for by self-correlation measurements and smoothed by phase weighted stacking and phase-match filtering. The final group-velocity maps show strong low-velocity anomalies at the location of the last Campi Flegrei eruption (1538 A.D.). The main low-velocity anomalies contour Solfatara volcano and follow geomorphological cross-faulting. The comparison with geophysical imaging results obtained during the last seismic unrest at the caldera suggest strong changes in the physical properties of the volcano, particularly in the area of major hydrogeological hazard.

Fan fault diagnosis based on symmetrized dot pattern analysis and image matching

NASA Astrophysics Data System (ADS)

Xu, Xiaogang; Liu, Haixiao; Zhu, Hao; Wang, Songling

2016-07-01

To detect the mechanical failure of fans, a new diagnostic method based on the symmetrized dot pattern (SDP) analysis and image matching is proposed. Vibration signals of 13 kinds of running states are acquired on a centrifugal fan test bed and reconstructed by the SDP technique. The SDP pattern templates of each running state are established. An image matching method is performed to diagnose the fault. In order to improve the diagnostic accuracy, the single template, multiple templates and clustering fault templates are used to perform the image matching.

Robust feature matching via support-line voting and affine-invariant ratios

NASA Astrophysics Data System (ADS)

Li, Jiayuan; Hu, Qingwu; Ai, Mingyao; Zhong, Ruofei

2017-10-01

Robust image matching is crucial for many applications of remote sensing and photogrammetry, such as image fusion, image registration, and change detection. In this paper, we propose a robust feature matching method based on support-line voting and affine-invariant ratios. We first use popular feature matching algorithms, such as SIFT, to obtain a set of initial matches. A support-line descriptor based on multiple adaptive binning gradient histograms is subsequently applied in the support-line voting stage to filter outliers. In addition, we use affine-invariant ratios computed by a two-line structure to refine the matching results and estimate the local affine transformation. The local affine model is more robust to distortions caused by elevation differences than the global affine transformation, especially for high-resolution remote sensing images and UAV images. Thus, the proposed method is suitable for both rigid and non-rigid image matching problems. Finally, we extract as many high-precision correspondences as possible based on the local affine extension and build a grid-wise affine model for remote sensing image registration. We compare the proposed method with six state-of-the-art algorithms on several data sets and show that our method significantly outperforms the other methods. The proposed method achieves 94.46% average precision on 15 challenging remote sensing image pairs, while the second-best method, RANSAC, only achieves 70.3%. In addition, the number of detected correct matches of the proposed method is approximately four times the number of initial SIFT matches.

Noise distribution and denoising of current density images

PubMed Central

Beheshti, Mohammadali; Foomany, Farbod H.; Magtibay, Karl; Jaffray, David A.; Krishnan, Sridhar; Nanthakumar, Kumaraswamy; Umapathy, Karthikeyan

2015-01-01

Abstract. Current density imaging (CDI) is a magnetic resonance (MR) imaging technique that could be used to study current pathways inside the tissue. The current distribution is measured indirectly as phase changes. The inherent noise in the MR imaging technique degrades the accuracy of phase measurements leading to imprecise current variations. The outcome can be affected significantly, especially at a low signal-to-noise ratio (SNR). We have shown the residual noise distribution of the phase to be Gaussian-like and the noise in CDI images approximated as a Gaussian. This finding matches experimental results. We further investigated this finding by performing comparative analysis with denoising techniques, using two CDI datasets with two different currents (20 and 45 mA). We found that the block-matching and three-dimensional (BM3D) technique outperforms other techniques when applied on current density (J). The minimum gain in noise power by BM3D applied to J compared with the next best technique in the analysis was found to be around 2 dB per pixel. We characterize the noise profile in CDI images and provide insights on the performance of different denoising techniques when applied at two different stages of current density reconstruction. PMID:26158100

SKL algorithm based fabric image matching and retrieval

NASA Astrophysics Data System (ADS)

Cao, Yichen; Zhang, Xueqin; Ma, Guojian; Sun, Rongqing; Dong, Deping

2017-07-01

Intelligent computer image processing technology provides convenience and possibility for designers to carry out designs. Shape analysis can be achieved by extracting SURF feature. However, high dimension of SURF feature causes to lower matching speed. To solve this problem, this paper proposed a fast fabric image matching algorithm based on SURF K-means and LSH algorithm. By constructing the bag of visual words on K-Means algorithm, and forming feature histogram of each image, the dimension of SURF feature is reduced at the first step. Then with the help of LSH algorithm, the features are encoded and the dimension is further reduced. In addition, the indexes of each image and each class of image are created, and the number of matching images is decreased by LSH hash bucket. Experiments on fabric image database show that this algorithm can speed up the matching and retrieval process, the result can satisfy the requirement of dress designers with accuracy and speed.

Real-time volumetric image reconstruction and 3D tumor localization based on a single x-ray projection image for lung cancer radiotherapy.

PubMed

Li, Ruijiang; Jia, Xun; Lewis, John H; Gu, Xuejun; Folkerts, Michael; Men, Chunhua; Jiang, Steve B

2010-06-01

To develop an algorithm for real-time volumetric image reconstruction and 3D tumor localization based on a single x-ray projection image for lung cancer radiotherapy. Given a set of volumetric images of a patient at N breathing phases as the training data, deformable image registration was performed between a reference phase and the other N-1 phases, resulting in N-1 deformation vector fields (DVFs). These DVFs can be represented efficiently by a few eigenvectors and coefficients obtained from principal component analysis (PCA). By varying the PCA coefficients, new DVFs can be generated, which, when applied on the reference image, lead to new volumetric images. A volumetric image can then be reconstructed from a single projection image by optimizing the PCA coefficients such that its computed projection matches the measured one. The 3D location of the tumor can be derived by applying the inverted DVF on its position in the reference image. The algorithm was implemented on graphics processing units (GPUs) to achieve real-time efficiency. The training data were generated using a realistic and dynamic mathematical phantom with ten breathing phases. The testing data were 360 cone beam projections corresponding to one gantry rotation, simulated using the same phantom with a 50% increase in breathing amplitude. The average relative image intensity error of the reconstructed volumetric images is 6.9% +/- 2.4%. The average 3D tumor localization error is 0.8 +/- 0.5 mm. On an NVIDIA Tesla C1060 GPU card, the average computation time for reconstructing a volumetric image from each projection is 0.24 s (range: 0.17 and 0.35 s). The authors have shown the feasibility of reconstructing volumetric images and localizing tumor positions in 3D in near real-time from a single x-ray image.

Rapid matching of stereo vision based on fringe projection profilometry

NASA Astrophysics Data System (ADS)

Zhang, Ruihua; Xiao, Yi; Cao, Jian; Guo, Hongwei

2016-09-01

As the most important core part of stereo vision, there are still many problems to solve in stereo matching technology. For smooth surfaces on which feature points are not easy to extract, this paper adds a projector into stereo vision measurement system based on fringe projection techniques, according to the corresponding point phases which extracted from the left and right camera images are the same, to realize rapid matching of stereo vision. And the mathematical model of measurement system is established and the three-dimensional (3D) surface of the measured object is reconstructed. This measurement method can not only broaden application fields of optical 3D measurement technology, and enrich knowledge achievements in the field of optical 3D measurement, but also provide potential possibility for the commercialized measurement system in practical projects, which has very important scientific research significance and economic value.

An improved feature extraction algorithm based on KAZE for multi-spectral image

NASA Astrophysics Data System (ADS)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

Phase matching considerations in second harmonic generation from tissues: Effects on emission directionality, conversion efficiency and observed morphology

NASA Astrophysics Data System (ADS)

LaComb, Ronald; Nadiarnykh, Oleg; Townsend, Sallie S.; Campagnola, Paul J.

2008-04-01

We present a heuristic treatment which relates SHG image intensities, signal directionality, and observed morphology to the physical structure of collagen and cellulose fibrillar tissues. The SHG creation model is based upon relaxed phase matching conditions which account for dispersion, randomness, and axial momentum contributions from the media, and includes a mathematical treatment which relates SHG conversion efficiency to fibril diameter and packing through the inclusion of potential intensity amplification resultant from quasi-phase matching (QPM). A direct consequence of this theory is that SHG in biological tissues is not strictly a coherent process, and that the forward directed SHG has a longer coherence length than the backward component, Through this treatment, we show that the emission directionality and also conversion efficiency do not arise solely from the fibril size but also depend on packing density and order of the inter-fibril structure. We demonstrate these principles in comparing the SHG response in normal and Osteogenesis Imperfecta (OI) skin. We show that the observed directionality and decreased relative intensity in the diseased state is consistent with phase matching conditions arising from the decreased fibril size and more random assembly. We further use this theory to explain the differences in morphology seen in forward and backward collected SHG in fibrillar tissues (e.g., collagenous and cellulosic). Specifically, we attribute segmented appearance to destructive interference between small fibrils separated by less than the coherence length. We suggest the approach based on relaxed phasematching conditions is general in predicting the SHG response in tissues and may be broadly applicable in interpreting the SHG contrast for diagnostic applications.

An Integrated Ransac and Graph Based Mismatch Elimination Approach for Wide-Baseline Image Matching

NASA Astrophysics Data System (ADS)

Hasheminasab, M.; Ebadi, H.; Sedaghat, A.

2015-12-01

In this paper we propose an integrated approach in order to increase the precision of feature point matching. Many different algorithms have been developed as to optimizing the short-baseline image matching while because of illumination differences and viewpoints changes, wide-baseline image matching is so difficult to handle. Fortunately, the recent developments in the automatic extraction of local invariant features make wide-baseline image matching possible. The matching algorithms which are based on local feature similarity principle, using feature descriptor as to establish correspondence between feature point sets. To date, the most remarkable descriptor is the scale-invariant feature transform (SIFT) descriptor , which is invariant to image rotation and scale, and it remains robust across a substantial range of affine distortion, presence of noise, and changes in illumination. The epipolar constraint based on RANSAC (random sample consensus) method is a conventional model for mismatch elimination, particularly in computer vision. Because only the distance from the epipolar line is considered, there are a few false matches in the selected matching results based on epipolar geometry and RANSAC. Aguilariu et al. proposed Graph Transformation Matching (GTM) algorithm to remove outliers which has some difficulties when the mismatched points surrounded by the same local neighbor structure. In this study to overcome these limitations, which mentioned above, a new three step matching scheme is presented where the SIFT algorithm is used to obtain initial corresponding point sets. In the second step, in order to reduce the outliers, RANSAC algorithm is applied. Finally, to remove the remained mismatches, based on the adjacent K-NN graph, the GTM is implemented. Four different close range image datasets with changes in viewpoint are utilized to evaluate the performance of the proposed method and the experimental results indicate its robustness and capability.

A blur-invariant local feature for motion blurred image matching

NASA Astrophysics Data System (ADS)

Tong, Qiang; Aoki, Terumasa

2017-07-01

Image matching between a blurred (caused by camera motion, out of focus, etc.) image and a non-blurred image is a critical task for many image/video applications. However, most of the existing local feature schemes fail to achieve this work. This paper presents a blur-invariant descriptor and a novel local feature scheme including the descriptor and the interest point detector based on moment symmetry - the authors' previous work. The descriptor is based on a new concept - center peak moment-like element (CPME) which is robust to blur and boundary effect. Then by constructing CPMEs, the descriptor is also distinctive and suitable for image matching. Experimental results show our scheme outperforms state of the art methods for blurred image matching

Dense real-time stereo matching using memory efficient semi-global-matching variant based on FPGAs

NASA Astrophysics Data System (ADS)

Buder, Maximilian

2012-06-01

This paper presents a stereo image matching system that takes advantage of a global image matching method. The system is designed to provide depth information for mobile robotic applications. Typical tasks of the proposed system are to assist in obstacle avoidance, SLAM and path planning. Mobile robots pose strong requirements about size, energy consumption, reliability and output quality of the image matching subsystem. Current available systems either rely on active sensors or on local stereo image matching algorithms. The first are only suitable in controlled environments while the second suffer from low quality depth-maps. Top ranking quality results are only achieved by an iterative approach using global image matching and color segmentation techniques which are computationally demanding and therefore difficult to be executed in realtime. Attempts were made to still reach realtime performance with global methods by simplifying the routines. The depth maps are at the end almost comparable to local methods. An equally named semi-global algorithm was proposed earlier that shows both very good image matching results and relatively simple operations. A memory efficient variant of the Semi-Global-Matching algorithm is reviewed and adopted for an implementation based on reconfigurable hardware. The implementation is suitable for realtime execution in the field of robotics. It will be shown that the modified version of the efficient Semi-Global-Matching method is delivering equivalent result compared to the original algorithm based on the Middlebury dataset. The system has proven to be capable of processing VGA sized images with a disparity resolution of 64 pixel at 33 frames per second based on low cost to mid-range hardware. In case the focus is shifted to a higher image resolution, 1024×1024-sized stereo frames may be processed with the same hardware at 10 fps. The disparity resolution settings stay unchanged. A mobile system that covers preprocessing, matching and interfacing operations is also presented.

Non-phase-matched enhancement of second-harmonic generation in multilayer nonlinear structures with internal reflections.

PubMed

Centini, Marco; D'Aguanno, Giuseppe; Sciscione, Letizia; Sibilia, Concita; Bertolotti, Mario; Scalora, Michael; Bloemer, Mark J

2004-08-15

Traditional notions of second-harmonic generation rely on phase matching or quasi phase matching to achieve good conversion efficiencies. We present an entirely new concept for efficient second-harmonic generation that is based on the interference of counterpropagating waves in multilayer structures. Conversion efficiencies are an order of magnitude larger than with phase-matched second-harmonic generation in similar multilayer structures.

Content-based image retrieval by matching hierarchical attributed region adjacency graphs

NASA Astrophysics Data System (ADS)

Fischer, Benedikt; Thies, Christian J.; Guld, Mark O.; Lehmann, Thomas M.

2004-05-01

Content-based image retrieval requires a formal description of visual information. In medical applications, all relevant biological objects have to be represented by this description. Although color as the primary feature has proven successful in publicly available retrieval systems of general purpose, this description is not applicable to most medical images. Additionally, it has been shown that global features characterizing the whole image do not lead to acceptable results in the medical context or that they are only suitable for specific applications. For a general purpose content-based comparison of medical images, local, i.e. regional features that are collected on multiple scales must be used. A hierarchical attributed region adjacency graph (HARAG) provides such a representation and transfers image comparison to graph matching. However, building a HARAG from an image requires a restriction in size to be computationally feasible while at the same time all visually plausible information must be preserved. For this purpose, mechanisms for the reduction of the graph size are presented. Even with a reduced graph, the problem of graph matching remains NP-complete. In this paper, the Similarity Flooding approach and Hopfield-style neural networks are adapted from the graph matching community to the needs of HARAG comparison. Based on synthetic image material build from simple geometric objects, all visually similar regions were matched accordingly showing the framework's general applicability to content-based image retrieval of medical images.

Photogrammetric Point Clouds Generation in Urban Areas from Integrated Image Matching and Segmentation

NASA Astrophysics Data System (ADS)

Ye, L.; Wu, B.

2017-09-01

High-resolution imagery is an attractive option for surveying and mapping applications due to the advantages of high quality imaging, short revisit time, and lower cost. Automated reliable and dense image matching is essential for photogrammetric 3D data derivation. Such matching, in urban areas, however, is extremely difficult, owing to the complexity of urban textures and severe occlusion problems on the images caused by tall buildings. Aimed at exploiting high-resolution imagery for 3D urban modelling applications, this paper presents an integrated image matching and segmentation approach for reliable dense matching of high-resolution imagery in urban areas. The approach is based on the framework of our existing self-adaptive triangulation constrained image matching (SATM), but incorporates three novel aspects to tackle the image matching difficulties in urban areas: 1) occlusion filtering based on image segmentation, 2) segment-adaptive similarity correlation to reduce the similarity ambiguity, 3) improved dense matching propagation to provide more reliable matches in urban areas. Experimental analyses were conducted using aerial images of Vaihingen, Germany and high-resolution satellite images in Hong Kong. The photogrammetric point clouds were generated, from which digital surface models (DSMs) were derived. They were compared with the corresponding airborne laser scanning data and the DSMs generated from the Semi-Global matching (SGM) method. The experimental results show that the proposed approach is able to produce dense and reliable matches comparable to SGM in flat areas, while for densely built-up areas, the proposed method performs better than SGM. The proposed method offers an alternative solution for 3D surface reconstruction in urban areas.

Using an Improved SIFT Algorithm and Fuzzy Closed-Loop Control Strategy for Object Recognition in Cluttered Scenes

PubMed Central

Nie, Haitao; Long, Kehui; Ma, Jun; Yue, Dan; Liu, Jinguo

2015-01-01

Partial occlusions, large pose variations, and extreme ambient illumination conditions generally cause the performance degradation of object recognition systems. Therefore, this paper presents a novel approach for fast and robust object recognition in cluttered scenes based on an improved scale invariant feature transform (SIFT) algorithm and a fuzzy closed-loop control method. First, a fast SIFT algorithm is proposed by classifying SIFT features into several clusters based on several attributes computed from the sub-orientation histogram (SOH), in the feature matching phase only features that share nearly the same corresponding attributes are compared. Second, a feature matching step is performed following a prioritized order based on the scale factor, which is calculated between the object image and the target object image, guaranteeing robust feature matching. Finally, a fuzzy closed-loop control strategy is applied to increase the accuracy of the object recognition and is essential for autonomous object manipulation process. Compared to the original SIFT algorithm for object recognition, the result of the proposed method shows that the number of SIFT features extracted from an object has a significant increase, and the computing speed of the object recognition processes increases by more than 40%. The experimental results confirmed that the proposed method performs effectively and accurately in cluttered scenes. PMID:25714094

SU-F-I-11: Software Development for 4D-CBCT Research of Real-Time-Image Gated Spot Scanning Proton Therapy

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

Fujii, T; Fujii, Y; Shimizu, S

Purpose: To acquire correct information for inside the body in patient positioning of Real-time-image Gated spot scanning Proton Therapy (RGPT), utilization of tomographic image at exhale phase of patient respiration obtained from 4-dimensional Cone beam CT (4D-CBCT) has been desired. We developed software named “Image Analysis Platform” for 4D-CBCT researches which has technique to segment projection-images based on 3D marker position in the body. The 3D marker position can be obtained by using two axes CBCT system at Hokkaido University Hospital Proton Therapy Center. Performance verification of the software was implemented. Methods: The software calculates 3D marker position retrospectively bymore » using matching positions on pair projection-images obtained by two axes fluoroscopy mode of CBCT system. Log data of 3D marker tracking are outputted after the tracking. By linking the Log data and gantry-angle file of projection-image, all projection-images are equally segmented to spatial five-phases according to marker 3D position of SI direction and saved to specified phase folder. Segmented projection-images are used for CBCT reconstruction of each phase. As performance verification of the software, test of segmented projection-images was implemented for sample CT phantom (Catphan) image acquired by two axes fluoroscopy mode of CBCT. Dummy marker was added on the images. Motion of the marker was modeled to move in 3D space. Motion type of marker is sin4 wave function has amplitude 10.0 mm/5.0 mm/0 mm, cycle 4 s/4 s/0 s for SI/AP/RL direction. Results: The marker was tracked within 0.58 mm accuracy in 3D for all images, and it was confirmed that all projection-images were segmented and saved to each phase folder correctly. Conclusion: We developed software for 4D-CBCT research which can segment projection-image based on 3D marker position. It will be helpful to create high quality of 4D-CBCT reconstruction image for RGPT.« less

Efficient image projection by Fourier electroholography.

PubMed

Makowski, Michał; Ducin, Izabela; Kakarenko, Karol; Kolodziejczyk, Andrzej; Siemion, Agnieszka; Siemion, Andrzej; Suszek, Jaroslaw; Sypek, Maciej; Wojnowski, Dariusz

2011-08-15

An improved efficient projection of color images is presented. It uses a phase spatial light modulator with three iteratively optimized Fourier holograms displayed simultaneously--each for one primary color. This spatial division instead of time division provides stable images. A pixelated structure of the modulator and fluctuations of liquid crystal molecules cause a zeroth-order peak, eliminated by additional wavelength-dependent phase factors shifting it before the image plane, where it is blocked with a matched filter. Speckles are suppressed by time integration of variable speckle patterns generated by additional randomizations of an initial phase and minor changes of the signal. © 2011 Optical Society of America

Robust image matching via ORB feature and VFC for mismatch removal

NASA Astrophysics Data System (ADS)

Ma, Tao; Fu, Wenxing; Fang, Bin; Hu, Fangyu; Quan, Siwen; Ma, Jie

2018-03-01

Image matching is at the base of many image processing and computer vision problems, such as object recognition or structure from motion. Current methods rely on good feature descriptors and mismatch removal strategies for detection and matching. In this paper, we proposed a robust image match approach based on ORB feature and VFC for mismatch removal. ORB (Oriented FAST and Rotated BRIEF) is an outstanding feature, it has the same performance as SIFT with lower cost. VFC (Vector Field Consensus) is a state-of-the-art mismatch removing method. The experiment results demonstrate that our method is efficient and robust.

A Featured-Based Strategy for Stereovision Matching in Sensors with Fish-Eye Lenses for Forest Environments

PubMed Central

Herrera, Pedro Javier; Pajares, Gonzalo; Guijarro, Maria; Ruz, José J.; Cruz, Jesús M.; Montes, Fernando

2009-01-01

This paper describes a novel feature-based stereovision matching process based on a pair of omnidirectional images in forest stands acquired with a stereovision sensor equipped with fish-eye lenses. The stereo analysis problem consists of the following steps: image acquisition, camera modelling, feature extraction, image matching and depth determination. Once the depths of significant points on the trees are obtained, the growing stock volume can be estimated by considering the geometrical camera modelling, which is the final goal. The key steps are feature extraction and image matching. This paper is devoted solely to these two steps. At a first stage a segmentation process extracts the trunks, which are the regions used as features, where each feature is identified through a set of attributes of properties useful for matching. In the second step the features are matched based on the application of the following four well known matching constraints, epipolar, similarity, ordering and uniqueness. The combination of the segmentation and matching processes for this specific kind of sensors make the main contribution of the paper. The method is tested with satisfactory results and compared against the human expert criterion. PMID:22303134

WE-AB-303-01: FEATURED PRESENTATION: A Dual-Detector Phase-Matched Digital Tomosynthesis (DTS) Imaging Scheme Using Aggregated KV and MV Projections for Intra-Treatment Lung Tumor Tracking

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

Zhang, Y; Yin, F; Mao, R

2015-06-15

Purpose: To develop a dual-detector phase-matched DTS technique for continuous and fast intra-treatment lung tumor localization. Methods: Tumor localization accuracy of limited-angle DTS imaging is affected by low inter-slice resolution. The dual-detector DTS technique aims to overcome this limitation through combining orthogonally acquired beam’s eye view MV projections and kV projections for intra-treatment DTS reconstruction and localization. To aggregate the kV and MV projections for reconstruction, the MV projections were linearly converted to synthesize corresponding kV projections. To further address the lung motion induced localization errors, this technique uses respiratory phase-matching to match the motion information between on-board DTS andmore » reference DTS to offset the adverse effects of motion blurriness in tumor localization.A study was performed using the CIRS008A lung phantom to simulate different on-board target variation scenarios for localization. The intra-treatment kV and MV acquisition was achieved through the Varian TrueBeam Developer Mode. Four methods were compared for their localization accuracy: 1. the proposed dual-detector phase-matched DTS technique; 2. the single-detector phase-matched DTS technique; 3. the dual-detector 3D-DTS technique without phase-matching; and 4. the single-detector 3D-DTS technique without phase-matching. Results: For scan angles of 2.5°, 5°, 10°, 20° and 30°, the dual-detector phase-matched DTS technique localized the tumor with average(±standard deviations) errors of 0.4±0.3 mm, 0.5±0.3 mm, 0.6±0.2 mm, 0.9±0.4 mm and 1.0±0.3 mm, respectively. The corresponding values of single-detector phase-matched DTS technique were 4.0±2.5 mm, 2.7±1.1 mm, 1.7±1.2 mm, 2.2±0.9 mm and 1.5±0.8 mm, respectively. The values of dual-detector 3D-DTS technique were 6.2±1.7 mm, 6.3±1.2 mm, 5.3±1.3 mm, 2.0±2.2 mm and 1.5±0.5 mm, respectively. And the values of single-detector 3D-DTS technique were 9.7±8.9 mm, 9.8±8.8 mm, 10.0±9.7 mm, 3.9±2.7 mm and 2.2±1.3 mm, respectively. Conclusion: The dual-detector phase-matched DTS technique substantially improves the tumor localization accuracy, which can be applied to real-time intra-treatment lung tumor localization. The research was funded by the National Institutes of Health Grant No. R01-CA184173 and a grant from Varian Medical Systems.« less

Hard x-ray phase contrastmicroscopy - techniques and applications

NASA Astrophysics Data System (ADS)

Holzner, Christian

In 1918, Einstein provided the first description of the nature of the refractive index for X-rays, showing that phase contrast effects are significant. A century later, most x-ray microscopy and nearly all medical imaging remains based on absorption contrast, even though phase contrast offers orders of magnitude improvements in contrast and reduced radiation exposure at multi-keV x-ray energies. The work presented is concerned with developing practical and quantitative methods of phase contrast for x-ray microscopy. A theoretical framework for imaging in phase contrast is put forward; this is used to obtain quantitative images in a scanning microscope using a segmented detector, and to correct for artifacts in a commercial phase contrast x-ray nano-tomography system. The principle of reciprocity between scanning and full-field microscopes is then used to arrive at a novel solution: Zernike contrast in a scanning microscope. These approaches are compared on a theoretical and experimental basis in direct connection with applications using multi-keV x-ray microscopes at the Advanced Photon Source at Argonne National Laboratory. Phase contrast provides the best means to image mass and ultrastructure of light elements that mainly constitute biological matter, while stimulated x-ray fluorescence provides high sensitivity for studies of the distribution of heavier trace elements, such as metals. These approaches are combined in a complementary way to yield quantitative maps of elemental concentration from 2D images, with elements placed in their ultrastructural context. The combination of x-ray fluorescence and phase contrast poses an ideal match for routine, high resolution tomographic imaging of biological samples in the future. The presented techniques and demonstration experiments will help pave the way for this development.

Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory.

PubMed

Zhou, Rui; Sun, Jinping; Hu, Yuxin; Qi, Yaolong

2018-01-31

Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.

Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory

PubMed Central

Zhou, Rui; Hu, Yuxin; Qi, Yaolong

2018-01-01

Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm. PMID:29385059

Object-based connectedness facilitates matching.

PubMed

Koning, Arno; van Lier, Rob

2003-10-01

In two matching tasks, participants had to match two images of object pairs. Image-based (IB) connectedness refers to connectedness between the objects in an image. Object-based (OB) connectedness refers to connectedness between the interpreted objects. In Experiment 1, a monocular depth cue (shadow) was used to distinguish different relation types between object pairs. Three relation types were created: IB/OB-connected objects, IB/OB-disconnected objects, and IB-connected/OB-disconnected objects. It was found that IB/OB-connected objects were matched faster than IB/OB-disconnected objects. Objects that were IB-connected/OB-disconnected were matched equally to IB/OB-disconnected objects. In Experiment 2, stereoscopic presentation was used. With relation types comparable to those in Experiment 1, it was again found that OB connectedness determined speed of matching, rather than IB connectedness. We conclude that matching of projections of three-dimensional objects depends more on OB connectedness than on IB connectedness.

2-D Myocardial Deformation Imaging Based on RF-Based Nonrigid Image Registration.

PubMed

Chakraborty, Bidisha; Liu, Zhi; Heyde, Brecht; Luo, Jianwen; D'hooge, Jan

2018-06-01

Myocardial deformation imaging is a well-established echocardiographic technique for the assessment of myocardial function. Although some solutions make use of speckle tracking of the reconstructed B-mode images, others apply block matching (BM) on the underlying radio frequency (RF) data in order to increase sensitivity to small interframe motion and deformation. However, for both approaches, lateral motion estimation remains a challenge due to the relatively poor lateral resolution of the ultrasound image in combination with the lack of phase information in this direction. Hereto, nonrigid image registration (NRIR) of B-mode images has previously been proposed as an attractive solution. However, hereby, the advantages of RF-based tracking were lost. The aim of this paper was, therefore, to develop an NRIR motion estimator adapted to RF data sets. The accuracy of this estimator was quantified using synthetic data and was contrasted against a state-of-the-art BM solution. The results show that RF-based NRIR outperforms BM in terms of tracking accuracy, particularly, as hypothesized, in the lateral direction. Finally, this RF-based NRIR algorithm was applied clinically, illustrating its ability to estimate both in-plane velocity components in vivo.

Monoplane 3D-2D registration of cerebral angiograms based on multi-objective stratified optimization

NASA Astrophysics Data System (ADS)

Aksoy, T.; Špiclin, Ž.; Pernuš, F.; Unal, G.

2017-12-01

Registration of 3D pre-interventional to 2D intra-interventional medical images has an increasingly important role in surgical planning, navigation and treatment, because it enables the physician to co-locate depth information given by pre-interventional 3D images with the live information in intra-interventional 2D images such as x-ray. Most tasks during image-guided interventions are carried out under a monoplane x-ray, which is a highly ill-posed problem for state-of-the-art 3D to 2D registration methods. To address the problem of rigid 3D-2D monoplane registration we propose a novel multi-objective stratified parameter optimization, wherein a small set of high-magnitude intensity gradients are matched between the 3D and 2D images. The stratified parameter optimization matches rotation templates to depth templates, first sampled from projected 3D gradients and second from the 2D image gradients, so as to recover 3D rigid-body rotations and out-of-plane translation. The objective for matching was the gradient magnitude correlation coefficient, which is invariant to in-plane translation. The in-plane translations are then found by locating the maximum of the gradient phase correlation between the best matching pair of rotation and depth templates. On twenty pairs of 3D and 2D images of ten patients undergoing cerebral endovascular image-guided intervention the 3D to monoplane 2D registration experiments were setup with a rather high range of initial mean target registration error from 0 to 100 mm. The proposed method effectively reduced the registration error to below 2 mm, which was further refined by a fast iterative method and resulted in a high final registration accuracy (0.40 mm) and high success rate (> 96%). Taking into account a fast execution time below 10 s, the observed performance of the proposed method shows a high potential for application into clinical image-guidance systems.

Spherical grating based x-ray Talbot interferometry.

PubMed

Cong, Wenxiang; Xi, Yan; Wang, Ge

2015-11-01

Grating interferometry is a state-of-the-art x-ray imaging approach, which can acquire information on x-ray attenuation, phase shift, and small-angle scattering simultaneously. Phase-contrast imaging and dark-field imaging are very sensitive to microstructural variation and offers superior contrast resolution for biological soft tissues. However, a common x-ray tube is a point-like source. As a result, the popular planar grating imaging configuration seriously restricts the flux of photons and decreases the visibility of signals, yielding a limited field of view. The purpose of this study is to extend the planar x-ray grating imaging theory and methods to a spherical grating scheme for a wider range of preclinical and clinical applications. A spherical grating matches the wave front of a point x-ray source very well, allowing the perpendicular incidence of x-rays on the grating to achieve a higher visibility over a larger field of view than the planer grating counterpart. A theoretical analysis of the Talbot effect for spherical grating imaging is proposed to establish a basic foundation for x-ray spherical gratings interferometry. An efficient method of spherical grating imaging is also presented to extract attenuation, differential phase, and dark-field images in the x-ray spherical grating interferometer. Talbot self-imaging with spherical gratings is analyzed based on the Rayleigh-Sommerfeld diffraction formula, featuring a periodic angular distribution in a polar coordinate system. The Talbot distance is derived to reveal the Talbot self-imaging pattern. Numerical simulation results show the self-imaging phenomenon of a spherical grating interferometer, which is in agreement with the theoretical prediction. X-ray Talbot interferometry with spherical gratings has a significant practical promise. Relative to planar grating imaging, spherical grating based x-ray Talbot interferometry has a larger field of view and improves both signal visibility and dose utilization for pre-clinical and clinical applications.

Spherical grating based x-ray Talbot interferometry

PubMed Central

Cong, Wenxiang; Xi, Yan; Wang, Ge

2015-01-01

Purpose: Grating interferometry is a state-of-the-art x-ray imaging approach, which can acquire information on x-ray attenuation, phase shift, and small-angle scattering simultaneously. Phase-contrast imaging and dark-field imaging are very sensitive to microstructural variation and offers superior contrast resolution for biological soft tissues. However, a common x-ray tube is a point-like source. As a result, the popular planar grating imaging configuration seriously restricts the flux of photons and decreases the visibility of signals, yielding a limited field of view. The purpose of this study is to extend the planar x-ray grating imaging theory and methods to a spherical grating scheme for a wider range of preclinical and clinical applications. Methods: A spherical grating matches the wave front of a point x-ray source very well, allowing the perpendicular incidence of x-rays on the grating to achieve a higher visibility over a larger field of view than the planer grating counterpart. A theoretical analysis of the Talbot effect for spherical grating imaging is proposed to establish a basic foundation for x-ray spherical gratings interferometry. An efficient method of spherical grating imaging is also presented to extract attenuation, differential phase, and dark-field images in the x-ray spherical grating interferometer. Results: Talbot self-imaging with spherical gratings is analyzed based on the Rayleigh–Sommerfeld diffraction formula, featuring a periodic angular distribution in a polar coordinate system. The Talbot distance is derived to reveal the Talbot self-imaging pattern. Numerical simulation results show the self-imaging phenomenon of a spherical grating interferometer, which is in agreement with the theoretical prediction. Conclusions: X-ray Talbot interferometry with spherical gratings has a significant practical promise. Relative to planar grating imaging, spherical grating based x-ray Talbot interferometry has a larger field of view and improves both signal visibility and dose utilization for pre-clinical and clinical applications. PMID:26520741

Spherical grating based x-ray Talbot interferometry

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

Cong, Wenxiang, E-mail: congw@rpi.edu, E-mail: xiy2@rpi.edu, E-mail: wangg6@rpi.edu; Xi, Yan, E-mail: congw@rpi.edu, E-mail: xiy2@rpi.edu, E-mail: wangg6@rpi.edu; Wang, Ge, E-mail: congw@rpi.edu, E-mail: xiy2@rpi.edu, E-mail: wangg6@rpi.edu

2015-11-15

Purpose: Grating interferometry is a state-of-the-art x-ray imaging approach, which can acquire information on x-ray attenuation, phase shift, and small-angle scattering simultaneously. Phase-contrast imaging and dark-field imaging are very sensitive to microstructural variation and offers superior contrast resolution for biological soft tissues. However, a common x-ray tube is a point-like source. As a result, the popular planar grating imaging configuration seriously restricts the flux of photons and decreases the visibility of signals, yielding a limited field of view. The purpose of this study is to extend the planar x-ray grating imaging theory and methods to a spherical grating scheme formore » a wider range of preclinical and clinical applications. Methods: A spherical grating matches the wave front of a point x-ray source very well, allowing the perpendicular incidence of x-rays on the grating to achieve a higher visibility over a larger field of view than the planer grating counterpart. A theoretical analysis of the Talbot effect for spherical grating imaging is proposed to establish a basic foundation for x-ray spherical gratings interferometry. An efficient method of spherical grating imaging is also presented to extract attenuation, differential phase, and dark-field images in the x-ray spherical grating interferometer. Results: Talbot self-imaging with spherical gratings is analyzed based on the Rayleigh–Sommerfeld diffraction formula, featuring a periodic angular distribution in a polar coordinate system. The Talbot distance is derived to reveal the Talbot self-imaging pattern. Numerical simulation results show the self-imaging phenomenon of a spherical grating interferometer, which is in agreement with the theoretical prediction. Conclusions: X-ray Talbot interferometry with spherical gratings has a significant practical promise. Relative to planar grating imaging, spherical grating based x-ray Talbot interferometry has a larger field of view and improves both signal visibility and dose utilization for pre-clinical and clinical applications.« less

A fast image matching algorithm based on key points

NASA Astrophysics Data System (ADS)

Wang, Huilin; Wang, Ying; An, Ru; Yan, Peng

2014-05-01

Image matching is a very important technique in image processing. It has been widely used for object recognition and tracking, image retrieval, three-dimensional vision, change detection, aircraft position estimation, and multi-image registration. Based on the requirements of matching algorithm for craft navigation, such as speed, accuracy and adaptability, a fast key point image matching method is investigated and developed. The main research tasks includes: (1) Developing an improved celerity key point detection approach using self-adapting threshold of Features from Accelerated Segment Test (FAST). A method of calculating self-adapting threshold was introduced for images with different contrast. Hessian matrix was adopted to eliminate insecure edge points in order to obtain key points with higher stability. This approach in detecting key points has characteristics of small amount of computation, high positioning accuracy and strong anti-noise ability; (2) PCA-SIFT is utilized to describe key point. 128 dimensional vector are formed based on the SIFT method for the key points extracted. A low dimensional feature space was established by eigenvectors of all the key points, and each eigenvector was projected onto the feature space to form a low dimensional eigenvector. These key points were re-described by dimension-reduced eigenvectors. After reducing the dimension by the PCA, the descriptor was reduced to 20 dimensions from the original 128. This method can reduce dimensions of searching approximately near neighbors thereby increasing overall speed; (3) Distance ratio between the nearest neighbour and second nearest neighbour searching is regarded as the measurement criterion for initial matching points from which the original point pairs matched are obtained. Based on the analysis of the common methods (e.g. RANSAC (random sample consensus) and Hough transform cluster) used for elimination false matching point pairs, a heuristic local geometric restriction strategy is adopted to discard false matched point pairs further; and (4) Affine transformation model is introduced to correct coordinate difference between real-time image and reference image. This resulted in the matching of the two images. SPOT5 Remote sensing images captured at different date and airborne images captured with different flight attitude were used to test the performance of the method from matching accuracy, operation time and ability to overcome rotation. Results show the effectiveness of the approach.

Content based image retrieval for matching images of improvised explosive devices in which snake initialization is viewed as an inverse problem

NASA Astrophysics Data System (ADS)

Acton, Scott T.; Gilliam, Andrew D.; Li, Bing; Rossi, Adam

2008-02-01

Improvised explosive devices (IEDs) are common and lethal instruments of terrorism, and linking a terrorist entity to a specific device remains a difficult task. In the effort to identify persons associated with a given IED, we have implemented a specialized content based image retrieval system to search and classify IED imagery. The system makes two contributions to the art. First, we introduce a shape-based matching technique exploiting shape, color, and texture (wavelet) information, based on novel vector field convolution active contours and a novel active contour initialization method which treats coarse segmentation as an inverse problem. Second, we introduce a unique graph theoretic approach to match annotated printed circuit board images for which no schematic or connectivity information is available. The shape-based image retrieval method, in conjunction with the graph theoretic tool, provides an efficacious system for matching IED images. For circuit imagery, the basic retrieval mechanism has a precision of 82.1% and the graph based method has a precision of 98.1%. As of the fall of 2007, the working system has processed over 400,000 case images.

Adaptive elastic segmentation of brain MRI via shape-model-guided evolutionary programming.

PubMed

Pitiot, Alain; Toga, Arthur W; Thompson, Paul M

2002-08-01

This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequent quantitative analysis. We propose a new hybrid strategy that combines a general elastic template matching approach and an evolutionary heuristic. The evolutionary algorithm uses prior statistical information about the shape of the target structure to control the behavior of a number of deformable templates. Each template, modeled in the form of a B-spline, is warped in a potential field which is itself dynamically adapted. Such a hybrid scheme proves to be promising: by maintaining a population of templates, we cover a large domain of the solution space under the global guidance of the evolutionary heuristic, and thoroughly explore interesting areas. We address key issues of automated image segmentation systems. The potential fields are initially designed based on the spatial features of the edges in the input image, and are subjected to spatially adaptive diffusion to guarantee the deformation of the template. This also improves its global consistency and convergence speed. The deformation algorithm can modify the internal structure of the templates to allow a better match. We investigate in detail the preprocessing phase that the images undergo before they can be used more effectively in the iterative elastic matching procedure: a texture classifier, trained via linear discriminant analysis of a learning set, is used to enhance the contrast of the target structure with respect to surrounding tissues. We show how these techniques interact within a statistically driven evolutionary scheme to achieve a better tradeoff between template flexibility and sensitivity to noise and outliers. We focus on understanding the features of template matching that are most beneficial in terms of the achieved match. Examples from simulated and real image data are discussed, with considerations of algorithmic efficiency.

Using the phase-space imager to analyze partially coherent imaging systems: bright-field, phase contrast, differential interference contrast, differential phase contrast, and spiral phase contrast

NASA Astrophysics Data System (ADS)

Mehta, Shalin B.; Sheppard, Colin J. R.

2010-05-01

Various methods that use large illumination aperture (i.e. partially coherent illumination) have been developed for making transparent (i.e. phase) specimens visible. These methods were developed to provide qualitative contrast rather than quantitative measurement-coherent illumination has been relied upon for quantitative phase analysis. Partially coherent illumination has some important advantages over coherent illumination and can be used for measurement of the specimen's phase distribution. However, quantitative analysis and image computation in partially coherent systems have not been explored fully due to the lack of a general, physically insightful and computationally efficient model of image formation. We have developed a phase-space model that satisfies these requirements. In this paper, we employ this model (called the phase-space imager) to elucidate five different partially coherent systems mentioned in the title. We compute images of an optical fiber under these systems and verify some of them with experimental images. These results and simulated images of a general phase profile are used to compare the contrast and the resolution of the imaging systems. We show that, for quantitative phase imaging of a thin specimen with matched illumination, differential phase contrast offers linear transfer of specimen information to the image. We also show that the edge enhancement properties of spiral phase contrast are compromised significantly as the coherence of illumination is reduced. The results demonstrate that the phase-space imager model provides a useful framework for analysis, calibration, and design of partially coherent imaging methods.

Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-01-01

To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

Segmenting human from photo images based on a coarse-to-fine scheme.

PubMed

Lu, Huchuan; Fang, Guoliang; Shao, Xinqing; Li, Xuelong

2012-06-01

Human segmentation in photo images is a challenging and important problem that finds numerous applications ranging from album making and photo classification to image retrieval. Previous works on human segmentation usually demand a time-consuming training phase for complex shape-matching processes. In this paper, we propose a straightforward framework to automatically recover human bodies from color photos. Employing a coarse-to-fine strategy, we first detect a coarse torso (CT) using the multicue CT detection algorithm and then extract the accurate region of the upper body. Then, an iterative multiple oblique histogram algorithm is presented to accurately recover the lower body based on human kinematics. The performance of our algorithm is evaluated on our own data set (contains 197 images with human body region ground truth data), VOC 2006, and the 2010 data set. Experimental results demonstrate the merits of the proposed method in segmenting a person with various poses.

a New Paradigm for Matching - and Aerial Images

NASA Astrophysics Data System (ADS)

Koch, T.; Zhuo, X.; Reinartz, P.; Fraundorfer, F.

2016-06-01

This paper investigates the performance of SIFT-based image matching regarding large differences in image scaling and rotation, as this is usually the case when trying to match images captured from UAVs and airplanes. This task represents an essential step for image registration and 3d-reconstruction applications. Various real world examples presented in this paper show that SIFT, as well as A-SIFT perform poorly or even fail in this matching scenario. Even if the scale difference in the images is known and eliminated beforehand, the matching performance suffers from too few feature point detections, ambiguous feature point orientations and rejection of many correct matches when applying the ratio-test afterwards. Therefore, a new feature matching method is provided that overcomes these problems and offers thousands of matches by a novel feature point detection strategy, applying a one-to-many matching scheme and substitute the ratio-test by adding geometric constraints to achieve geometric correct matches at repetitive image regions. This method is designed for matching almost nadir-directed images with low scene depth, as this is typical in UAV and aerial image matching scenarios. We tested the proposed method on different real world image pairs. While standard SIFT failed for most of the datasets, plenty of geometrical correct matches could be found using our approach. Comparing the estimated fundamental matrices and homographies with ground-truth solutions, mean errors of few pixels can be achieved.

Acousto-optic tunable filter chromatic aberration analysis and reduction with auto-focus system

NASA Astrophysics Data System (ADS)

Wang, Yaoli; Chen, Yuanyuan

2018-07-01

An acousto-optic tunable filter (AOTF) displays optical band broadening and sidelobes as a result of the coupling between the acoustic wave and optical waves of different wavelengths. These features were analysed by wave-vector phase matching between the optical and acoustic waves. A crossed-line test board was imaged by an AOTF multi-spectral imaging system, showing image blurring in the direction of diffraction and image sharpness in the orthogonal direction produced by the greater bandwidth and sidelobes in the former direction. Applying the secondary-imaging principle and considering the wavelength-dependent refractive index, focal length varies over the broad wavelength range. An automatic focusing method is therefore proposed for use in AOTF multi-spectral imaging systems. A new method for image-sharpness evaluation, based on improved Structure Similarity Index Measurement (SSIM), is also proposed, based on the characteristics of the AOTF imaging system. Compared with the traditional gradient operator, as same as it, the new evaluation function realized the evaluation between different image quality, thus could achieve the automatic focusing for different multispectral images.

Matching Aerial Images to 3D Building Models Using Context-Based Geometric Hashing

PubMed Central

Jung, Jaewook; Sohn, Gunho; Bang, Kiin; Wichmann, Andreas; Armenakis, Costas; Kada, Martin

2016-01-01

A city is a dynamic entity, which environment is continuously changing over time. Accordingly, its virtual city models also need to be regularly updated to support accurate model-based decisions for various applications, including urban planning, emergency response and autonomous navigation. A concept of continuous city modeling is to progressively reconstruct city models by accommodating their changes recognized in spatio-temporal domain, while preserving unchanged structures. A first critical step for continuous city modeling is to coherently register remotely sensed data taken at different epochs with existing building models. This paper presents a new model-to-image registration method using a context-based geometric hashing (CGH) method to align a single image with existing 3D building models. This model-to-image registration process consists of three steps: (1) feature extraction; (2) similarity measure; and matching, and (3) estimating exterior orientation parameters (EOPs) of a single image. For feature extraction, we propose two types of matching cues: edged corner features representing the saliency of building corner points with associated edges, and contextual relations among the edged corner features within an individual roof. A set of matched corners are found with given proximity measure through geometric hashing, and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on collinearity equations. The result shows that acceptable accuracy of EOPs of a single image can be achievable using the proposed registration approach as an alternative to a labor-intensive manual registration process. PMID:27338410

The 3-D image recognition based on fuzzy neural network technology

NASA Technical Reports Server (NTRS)

Hirota, Kaoru; Yamauchi, Kenichi; Murakami, Jun; Tanaka, Kei

1993-01-01

Three dimensional stereoscopic image recognition system based on fuzzy-neural network technology was developed. The system consists of three parts; preprocessing part, feature extraction part, and matching part. Two CCD color camera image are fed to the preprocessing part, where several operations including RGB-HSV transformation are done. A multi-layer perception is used for the line detection in the feature extraction part. Then fuzzy matching technique is introduced in the matching part. The system is realized on SUN spark station and special image input hardware system. An experimental result on bottle images is also presented.

Improvement of the Accuracy of InSAR Image Co-Registration Based On Tie Points - A Review.

PubMed

Zou, Weibao; Li, Yan; Li, Zhilin; Ding, Xiaoli

2009-01-01

Interferometric Synthetic Aperture Radar (InSAR) is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR) images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs) and the measurement of ground surface deformations. However, many critical factors affect the quality of InSAR data and limit its applications. One of the factors is InSAR data processing, which consists of image co-registration, interferogram generation, phase unwrapping and geocoding. The co-registration of InSAR images is the first step and dramatically influences the accuracy of InSAR products. In this paper, the principle and processing procedures of InSAR techniques are reviewed. One of important factors, tie points, to be considered in the improvement of the accuracy of InSAR image co-registration are emphatically reviewed, such as interval of tie points, extraction of feature points, window size for tie point matching and the measurement for the quality of an interferogram.

Improvement of the Accuracy of InSAR Image Co-Registration Based On Tie Points – A Review

PubMed Central

Zou, Weibao; Li, Yan; Li, Zhilin; Ding, Xiaoli

2009-01-01

Interferometric Synthetic Aperture Radar (InSAR) is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR) images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs) and the measurement of ground surface deformations. However, many critical factors affect the quality of InSAR data and limit its applications. One of the factors is InSAR data processing, which consists of image co-registration, interferogram generation, phase unwrapping and geocoding. The co-registration of InSAR images is the first step and dramatically influences the accuracy of InSAR products. In this paper, the principle and processing procedures of InSAR techniques are reviewed. One of important factors, tie points, to be considered in the improvement of the accuracy of InSAR image co-registration are emphatically reviewed, such as interval of tie points, extraction of feature points, window size for tie point matching and the measurement for the quality of an interferogram. PMID:22399966

Coherent hybrid electromagnetic field imaging

DOEpatents

Cooke, Bradly J [Jemez Springs, NM; Guenther, David C [Los Alamos, NM

2008-08-26

An apparatus and corresponding method for coherent hybrid electromagnetic field imaging of a target, where an energy source is used to generate a propagating electromagnetic beam, an electromagnetic beam splitting means to split the beam into two or more coherently matched beams of about equal amplitude, and where the spatial and temporal self-coherence between each two or more coherently matched beams is preserved. Two or more differential modulation means are employed to modulate each two or more coherently matched beams with a time-varying polarization, frequency, phase, and amplitude signal. An electromagnetic beam combining means is used to coherently combine said two or more coherently matched beams into a coherent electromagnetic beam. One or more electromagnetic beam controlling means are used for collimating, guiding, or focusing the coherent electromagnetic beam. One or more apertures are used for transmitting and receiving the coherent electromagnetic beam to and from the target. A receiver is used that is capable of square-law detection of the coherent electromagnetic beam. A waveform generator is used that is capable of generation and control of time-varying polarization, frequency, phase, or amplitude modulation waveforms and sequences. A means of synchronizing time varying waveform is used between the energy source and the receiver. Finally, a means of displaying the images created by the interaction of the coherent electromagnetic beam with target is employed.

Unsupervised image matching based on manifold alignment.

PubMed

Pei, Yuru; Huang, Fengchun; Shi, Fuhao; Zha, Hongbin

2012-08-01

This paper challenges the issue of automatic matching between two image sets with similar intrinsic structures and different appearances, especially when there is no prior correspondence. An unsupervised manifold alignment framework is proposed to establish correspondence between data sets by a mapping function in the mutual embedding space. We introduce a local similarity metric based on parameterized distance curves to represent the connection of one point with the rest of the manifold. A small set of valid feature pairs can be found without manual interactions by matching the distance curve of one manifold with the curve cluster of the other manifold. To avoid potential confusions in image matching, we propose an extended affine transformation to solve the nonrigid alignment in the embedding space. The comparatively tight alignments and the structure preservation can be obtained simultaneously. The point pairs with the minimum distance after alignment are viewed as the matchings. We apply manifold alignment to image set matching problems. The correspondence between image sets of different poses, illuminations, and identities can be established effectively by our approach.

Feature extraction and descriptor calculation methods for automatic georeferencing of Philippines' first microsatellite imagery

NASA Astrophysics Data System (ADS)

Tupas, M. E. A.; Dasallas, J. A.; Jiao, B. J. D.; Magallon, B. J. P.; Sempio, J. N. H.; Ramos, M. K. F.; Aranas, R. K. D.; Tamondong, A. M.

2017-10-01

The FAST-SIFT corner detector and descriptor extractor combination was used to automatically georeference DIWATA-1 Spaceborne Multispectral Imager images. Features from the Fast Accelerated Segment Test (FAST) algorithm detects corners or keypoints in an image, and these robustly detected keypoints have well-defined positions. Descriptors were computed using Scale-Invariant Feature Transform (SIFT) extractor. FAST-SIFT method effectively SMI same-subscene images detected by the NIR sensor. The method was also tested in stitching NIR images with varying subscene swept by the camera. The slave images were matched to the master image. The keypoints served as the ground control points. Random sample consensus was used to eliminate fall-out matches and ensure accuracy of the feature points from which the transformation parameters were derived. Keypoints are matched based on their descriptor vector. Nearest-neighbor matching is employed based on a metric distance between the descriptors. The metrics include Euclidean and city block, among others. Rough matching outputs not only the correct matches but also the faulty matches. A previous work in automatic georeferencing incorporates a geometric restriction. In this work, we applied a simplified version of the learning method. RANSAC was used to eliminate fall-out matches and ensure accuracy of the feature points. This method identifies if a point fits the transformation function and returns inlier matches. The transformation matrix was solved by Affine, Projective, and Polynomial models. The accuracy of the automatic georeferencing method were determined by calculating the RMSE of interest points, selected randomly, between the master image and transformed slave image.

Content Based Image Matching for Planetary Science

NASA Astrophysics Data System (ADS)

Deans, M. C.; Meyer, C.

2006-12-01

Planetary missions generate large volumes of data. With the MER rovers still functioning on Mars, PDS contains over 7200 released images from the Microscopic Imagers alone. These data products are only searchable by keys such as the Sol, spacecraft clock, or rover motion counter index, with little connection to the semantic content of the images. We have developed a method for matching images based on the visual textures in images. For every image in a database, a series of filters compute the image response to localized frequencies and orientations. Filter responses are turned into a low dimensional descriptor vector, generating a 37 dimensional fingerprint. For images such as the MER MI, this represents a compression ratio of 99.9965% (the fingerprint is approximately 0.0035% the size of the original image). At query time, fingerprints are quickly matched to find images with similar appearance. Image databases containing several thousand images are preprocessed offline in a matter of hours. Image matches from the database are found in a matter of seconds. We have demonstrated this image matching technique using three sources of data. The first database consists of 7200 images from the MER Microscopic Imager. The second database consists of 3500 images from the Narrow Angle Mars Orbital Camera (MOC-NA), which were cropped into 1024×1024 sub-images for consistency. The third database consists of 7500 scanned archival photos from the Apollo Metric Camera. Example query results from all three data sources are shown. We have also carried out user tests to evaluate matching performance by hand labeling results. User tests verify approximately 20% false positive rate for the top 14 results for MOC NA and MER MI data. This means typically 10 to 12 results out of 14 match the query image sufficiently. This represents a powerful search tool for databases of thousands of images where the a priori match probability for an image might be less than 1%. Qualitatively, correct matches can also be confirmed by verifying MI images taken in the same z-stack, or MOC image tiles taken from the same image strip. False negatives are difficult to quantify as it would mean finding matches in the database of thousands of images that the algorithm did not detect.

Automatic structural matching of 3D image data

NASA Astrophysics Data System (ADS)

Ponomarev, Svjatoslav; Lutsiv, Vadim; Malyshev, Igor

2015-10-01

A new image matching technique is described. It is implemented as an object-independent hierarchical structural juxtaposition algorithm based on an alphabet of simple object-independent contour structural elements. The structural matching applied implements an optimized method of walking through a truncated tree of all possible juxtapositions of two sets of structural elements. The algorithm was initially developed for dealing with 2D images such as the aerospace photographs, and it turned out to be sufficiently robust and reliable for matching successfully the pictures of natural landscapes taken in differing seasons from differing aspect angles by differing sensors (the visible optical, IR, and SAR pictures, as well as the depth maps and geographical vector-type maps). At present (in the reported version), the algorithm is enhanced based on additional use of information on third spatial coordinates of observed points of object surfaces. Thus, it is now capable of matching the images of 3D scenes in the tasks of automatic navigation of extremely low flying unmanned vehicles or autonomous terrestrial robots. The basic principles of 3D structural description and matching of images are described, and the examples of image matching are presented.

Automatic diagnosis of malaria based on complete circle-ellipse fitting search algorithm.

PubMed

Sheikhhosseini, M; Rabbani, H; Zekri, M; Talebi, A

2013-12-01

Diagnosis of malaria parasitemia from blood smears is a subjective and time-consuming task for pathologists. The automatic diagnostic process will reduce the diagnostic time. Also, it can be worked as a second opinion for pathologists and may be useful in malaria screening. This study presents an automatic method for malaria diagnosis from thin blood smears. According to this fact that malaria life cycle is started by forming a ring around the parasite nucleus, the proposed approach is mainly based on curve fitting to detect parasite ring in the blood smear. The method is composed of six main phases: stain object extraction step, which extracts candidate objects that may be infected by malaria parasites. This phase includes stained pixel extraction step based on intensity and colour, and stained object segmentation by defining stained circle matching. Second step is preprocessing phase which makes use of nonlinear diffusion filtering. The process continues with detection of parasite nucleus from resulted image of previous step according to image intensity. Fourth step introduces a complete search process in which the circle search step identifies the direction and initial points for direct least-square ellipse fitting algorithm. Furthermore in the ellipse searching process, although parasite shape is completed undesired regions with high error value are removed and ellipse parameters are modified. Features are extracted from the parasite candidate region instead of whole candidate object in the fifth step. By employing this special feature extraction way, which is provided by special searching process, the necessity of employing clump splitting methods is removed. Also, defining stained circle matching process in the first step speeds up the whole procedure. Finally, a series of decision rules are applied on the extracted features to decide on the positivity or negativity of malaria parasite presence. The algorithm is applied on 26 digital images which are provided from thin blood smear films. The images are contained 1274 objects which may be infected by parasite or healthy. Applying the automatic identification of malaria on provided database showed a sensitivity of 82.28% and specificity of 98.02%. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Selective suppression of high-order harmonics within phase-matched spectral regions.

PubMed

Lerner, Gavriel; Diskin, Tzvi; Neufeld, Ofer; Kfir, Ofer; Cohen, Oren

2017-04-01

Phase matching in high-harmonic generation leads to enhancement of multiple harmonics. It is sometimes desired to control the spectral structure within the phase-matched spectral region. We propose a scheme for selective suppression of high-order harmonics within the phase-matched spectral region while weakly influencing the other harmonics. The method is based on addition of phase-mismatched segments within a phase-matched medium. We demonstrate the method numerically in two examples. First, we show that one phase-mismatched segment can significantly suppress harmonic orders 9, 15, and 21. Second, we show that two phase-mismatched segments can efficiently suppress circularly polarized harmonics with one helicity over the other when driven by a bi-circular field. The new method may be useful for various applications, including the generation of highly helical bright attosecond pulses.

Evaluation of Deep Learning Based Stereo Matching Methods: from Ground to Aerial Images

NASA Astrophysics Data System (ADS)

Liu, J.; Ji, S.; Zhang, C.; Qin, Z.

2018-05-01

Dense stereo matching has been extensively studied in photogrammetry and computer vision. In this paper we evaluate the application of deep learning based stereo methods, which were raised from 2016 and rapidly spread, on aerial stereos other than ground images that are commonly used in computer vision community. Two popular methods are evaluated. One learns matching cost with a convolutional neural network (known as MC-CNN); the other produces a disparity map in an end-to-end manner by utilizing both geometry and context (known as GC-net). First, we evaluate the performance of the deep learning based methods for aerial stereo images by a direct model reuse. The models pre-trained on KITTI 2012, KITTI 2015 and Driving datasets separately, are directly applied to three aerial datasets. We also give the results of direct training on target aerial datasets. Second, the deep learning based methods are compared to the classic stereo matching method, Semi-Global Matching(SGM), and a photogrammetric software, SURE, on the same aerial datasets. Third, transfer learning strategy is introduced to aerial image matching based on the assumption of a few target samples available for model fine tuning. It experimentally proved that the conventional methods and the deep learning based methods performed similarly, and the latter had greater potential to be explored.

Histogram Curve Matching Approaches for Object-based Image Classification of Land Cover and Land Use

PubMed Central

Toure, Sory I.; Stow, Douglas A.; Weeks, John R.; Kumar, Sunil

2013-01-01

The classification of image-objects is usually done using parametric statistical measures of central tendency and/or dispersion (e.g., mean or standard deviation). The objectives of this study were to analyze digital number histograms of image objects and evaluate classifications measures exploiting characteristic signatures of such histograms. Two histograms matching classifiers were evaluated and compared to the standard nearest neighbor to mean classifier. An ADS40 airborne multispectral image of San Diego, California was used for assessing the utility of curve matching classifiers in a geographic object-based image analysis (GEOBIA) approach. The classifications were performed with data sets having 0.5 m, 2.5 m, and 5 m spatial resolutions. Results show that histograms are reliable features for characterizing classes. Also, both histogram matching classifiers consistently performed better than the one based on the standard nearest neighbor to mean rule. The highest classification accuracies were produced with images having 2.5 m spatial resolution. PMID:24403648

Feature Matching of Historical Images Based on Geometry of Quadrilaterals

NASA Astrophysics Data System (ADS)

Maiwald, F.; Schneider, D.; Henze, F.; Münster, S.; Niebling, F.

2018-05-01

This contribution shows an approach to match historical images from the photo library of the Saxon State and University Library Dresden (SLUB) in the context of a historical three-dimensional city model of Dresden. In comparison to recent images, historical photography provides diverse factors which make an automatical image analysis (feature detection, feature matching and relative orientation of images) difficult. Due to e.g. film grain, dust particles or the digitalization process, historical images are often covered by noise interfering with the image signal needed for a robust feature matching. The presented approach uses quadrilaterals in image space as these are commonly available in man-made structures and façade images (windows, stones, claddings). It is explained how to generally detect quadrilaterals in images. Consequently, the properties of the quadrilaterals as well as the relationship to neighbouring quadrilaterals are used for the description and matching of feature points. The results show that most of the matches are robust and correct but still small in numbers.

Study of image matching algorithm and sub-pixel fitting algorithm in target tracking

NASA Astrophysics Data System (ADS)

Yang, Ming-dong; Jia, Jianjun; Qiang, Jia; Wang, Jian-yu

2015-03-01

Image correlation matching is a tracking method that searched a region most approximate to the target template based on the correlation measure between two images. Because there is no need to segment the image, and the computation of this method is little. Image correlation matching is a basic method of target tracking. This paper mainly studies the image matching algorithm of gray scale image, which precision is at sub-pixel level. The matching algorithm used in this paper is SAD (Sum of Absolute Difference) method. This method excels in real-time systems because of its low computation complexity. The SAD method is introduced firstly and the most frequently used sub-pixel fitting algorithms are introduced at the meantime. These fitting algorithms can't be used in real-time systems because they are too complex. However, target tracking often requires high real-time performance, we put forward a fitting algorithm named paraboloidal fitting algorithm based on the consideration above, this algorithm is simple and realized easily in real-time system. The result of this algorithm is compared with that of surface fitting algorithm through image matching simulation. By comparison, the precision difference between these two algorithms is little, it's less than 0.01pixel. In order to research the influence of target rotation on precision of image matching, the experiment of camera rotation was carried on. The detector used in the camera is a CMOS detector. It is fixed to an arc pendulum table, take pictures when the camera rotated different angles. Choose a subarea in the original picture as the template, and search the best matching spot using image matching algorithm mentioned above. The result shows that the matching error is bigger when the target rotation angle is larger. It's an approximate linear relation. Finally, the influence of noise on matching precision was researched. Gaussian noise and pepper and salt noise were added in the image respectively, and the image was processed by mean filter and median filter, then image matching was processed. The result show that when the noise is little, mean filter and median filter can achieve a good result. But when the noise density of salt and pepper noise is bigger than 0.4, or the variance of Gaussian noise is bigger than 0.0015, the result of image matching will be wrong.

High-speed Fourier ptychographic microscopy based on programmable annular illuminations.

PubMed

Sun, Jiasong; Zuo, Chao; Zhang, Jialin; Fan, Yao; Chen, Qian

2018-05-16

High-throughput quantitative phase imaging (QPI) is essential to cellular phenotypes characterization as it allows high-content cell analysis and avoids adverse effects of staining reagents on cellular viability and cell signaling. Among different approaches, Fourier ptychographic microscopy (FPM) is probably the most promising technique to realize high-throughput QPI by synthesizing a wide-field, high-resolution complex image from multiple angle-variably illuminated, low-resolution images. However, the large dataset requirement in conventional FPM significantly limits its imaging speed, resulting in low temporal throughput. Moreover, the underlying theoretical mechanism as well as optimum illumination scheme for high-accuracy phase imaging in FPM remains unclear. Herein, we report a high-speed FPM technique based on programmable annular illuminations (AIFPM). The optical-transfer-function (OTF) analysis of FPM reveals that the low-frequency phase information can only be correctly recovered if the LEDs are precisely located at the edge of the objective numerical aperture (NA) in the frequency space. By using only 4 low-resolution images corresponding to 4 tilted illuminations matching a 10×, 0.4 NA objective, we present the high-speed imaging results of in vitro Hela cells mitosis and apoptosis at a frame rate of 25 Hz with a full-pitch resolution of 655 nm at a wavelength of 525 nm (effective NA = 0.8) across a wide field-of-view (FOV) of 1.77 mm 2 , corresponding to a space-bandwidth-time product of 411 megapixels per second. Our work reveals an important capability of FPM towards high-speed high-throughput imaging of in vitro live cells, achieving video-rate QPI performance across a wide range of scales, both spatial and temporal.

Photogrammetric Processing of Planetary Linear Pushbroom Images Based on Approximate Orthophotos

NASA Astrophysics Data System (ADS)

Geng, X.; Xu, Q.; Xing, S.; Hou, Y. F.; Lan, C. Z.; Zhang, J. J.

2018-04-01

It is still a great challenging task to efficiently produce planetary mapping products from orbital remote sensing images. There are many disadvantages in photogrammetric processing of planetary stereo images, such as lacking ground control information and informative features. Among which, image matching is the most difficult job in planetary photogrammetry. This paper designs a photogrammetric processing framework for planetary remote sensing images based on approximate orthophotos. Both tie points extraction for bundle adjustment and dense image matching for generating digital terrain model (DTM) are performed on approximate orthophotos. Since most of planetary remote sensing images are acquired by linear scanner cameras, we mainly deal with linear pushbroom images. In order to improve the computational efficiency of orthophotos generation and coordinates transformation, a fast back-projection algorithm of linear pushbroom images is introduced. Moreover, an iteratively refined DTM and orthophotos scheme was adopted in the DTM generation process, which is helpful to reduce search space of image matching and improve matching accuracy of conjugate points. With the advantages of approximate orthophotos, the matching results of planetary remote sensing images can be greatly improved. We tested the proposed approach with Mars Express (MEX) High Resolution Stereo Camera (HRSC) and Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) images. The preliminary experimental results demonstrate the feasibility of the proposed approach.

Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

PubMed Central

Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia

2016-01-01

An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996

Illumination invariant feature point matching for high-resolution planetary remote sensing images

NASA Astrophysics Data System (ADS)

Wu, Bo; Zeng, Hai; Hu, Han

2018-03-01

Despite its success with regular close-range and remote-sensing images, the scale-invariant feature transform (SIFT) algorithm is essentially not invariant to illumination differences due to the use of gradients for feature description. In planetary remote sensing imagery, which normally lacks sufficient textural information, salient regions are generally triggered by the shadow effects of keypoints, reducing the matching performance of classical SIFT. Based on the observation of dual peaks in a histogram of the dominant orientations of SIFT keypoints, this paper proposes an illumination-invariant SIFT matching method for high-resolution planetary remote sensing images. First, as the peaks in the orientation histogram are generally aligned closely with the sub-solar azimuth angle at the time of image collection, an adaptive suppression Gaussian function is tuned to level the histogram and thereby alleviate the differences in illumination caused by a changing solar angle. Next, the suppression function is incorporated into the original SIFT procedure for obtaining feature descriptors, which are used for initial image matching. Finally, as the distribution of feature descriptors changes after anisotropic suppression, and the ratio check used for matching and outlier removal in classical SIFT may produce inferior results, this paper proposes an improved matching procedure based on cross-checking and template image matching. The experimental results for several high-resolution remote sensing images from both the Moon and Mars, with illumination differences of 20°-180°, reveal that the proposed method retrieves about 40%-60% more matches than the classical SIFT method. The proposed method is of significance for matching or co-registration of planetary remote sensing images for their synergistic use in various applications. It also has the potential to be useful for flyby and rover images by integrating with the affine invariant feature detectors.

Kingfisher: a system for remote sensing image database management

NASA Astrophysics Data System (ADS)

Bruzzo, Michele; Giordano, Ferdinando; Dellepiane, Silvana G.

2003-04-01

At present retrieval methods in remote sensing image database are mainly based on spatial-temporal information. The increasing amount of images to be collected by the ground station of earth observing systems emphasizes the need for database management with intelligent data retrieval capabilities. The purpose of the proposed method is to realize a new content based retrieval system for remote sensing images database with an innovative search tool based on image similarity. This methodology is quite innovative for this application, at present many systems exist for photographic images, as for example QBIC and IKONA, but they are not able to extract and describe properly remote image content. The target database is set by an archive of images originated from an X-SAR sensor (spaceborne mission, 1994). The best content descriptors, mainly texture parameters, guarantees high retrieval performances and can be extracted without losses independently of image resolution. The latter property allows DBMS (Database Management System) to process low amount of information, as in the case of quick-look images, improving time performance and memory access without reducing retrieval accuracy. The matching technique has been designed to enable image management (database population and retrieval) independently of dimensions (width and height). Local and global content descriptors are compared, during retrieval phase, with the query image and results seem to be very encouraging.

Buildings Change Detection Based on Shape Matching for Multi-Resolution Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Abdessetar, M.; Zhong, Y.

2017-09-01

Buildings change detection has the ability to quantify the temporal effect, on urban area, for urban evolution study or damage assessment in disaster cases. In this context, changes analysis might involve the utilization of the available satellite images with different resolutions for quick responses. In this paper, to avoid using traditional method with image resampling outcomes and salt-pepper effect, building change detection based on shape matching is proposed for multi-resolution remote sensing images. Since the object's shape can be extracted from remote sensing imagery and the shapes of corresponding objects in multi-scale images are similar, it is practical for detecting buildings changes in multi-scale imagery using shape analysis. Therefore, the proposed methodology can deal with different pixel size for identifying new and demolished buildings in urban area using geometric properties of objects of interest. After rectifying the desired multi-dates and multi-resolutions images, by image to image registration with optimal RMS value, objects based image classification is performed to extract buildings shape from the images. Next, Centroid-Coincident Matching is conducted, on the extracted building shapes, based on the Euclidean distance measurement between shapes centroid (from shape T0 to shape T1 and vice versa), in order to define corresponding building objects. Then, New and Demolished buildings are identified based on the obtained distances those are greater than RMS value (No match in the same location).

Multi-phase imaging of intermittency at steady state using differential imaging method by X-ray micro-tomography

NASA Astrophysics Data System (ADS)

Gao, Y.; Lin, Q.; Bijeljic, B.; Blunt, M. J.

2017-12-01

To observe intermittency in consolidated rock, we image a steady state flow of brine and decane in Bentheimer sandstone. We devise an experimental method based on X-ray differential imaging method to examine how changes in flow rate impact the pore-scale distribution of fluids during co-injection flow under dynamic flow conditions at steady state. This helps us elucidate the diverse flow regimes (connected, intermittent break-up, or continual break-up of the non-wetting phase pathways) for two capillary numbers. Also, relative permeability curves under both capillary and viscous limited conditions could be measured. We have performed imbibition sample floods using oil-brine and measured steady state relative permeability on a sandstone rock core in order to fully characterize the flow behaviour at low and high Ca. Two sets of experiments at high and low flow rates are provided to explore the time-evolution of the non-wetting phase clusters distribution under different flow conditions. The high flow rate is 0.5 mL/min, whose corresponding capillary number is 7.7×10-6. The low flow rate is 0.02 mL/min, whose capillary number is 3.1×10-7. A procedure based on using high-salinity brine as the contrast phase and applying differential imaging between the dry scan and that of the sample saturation with a 30 wt% Potassium iodide (KI) doped brine help to make sure there is no non-wetting phase in micro-pores. Then the intermittent phase in multiphase flow image at high Ca can be quantified by obtaining the differential image between the 30 wt% KI brine image and the scans that taken at each fixed fractional flow. By using the grey scale histogram distribution of the raw images at each condition, the oil proportion in the intermittent phase can be calculated. The pressure drops at each fractional flow at low and high Ca can be measured by high-precision pressure differential sensors and utilized to calculate to the relative permeability at pore scale. The relative permeability data and fw-Sw relationship obtained by our experiment at pore scale are compared with the data collected from experiments which were conducted at core scale, and they match well.

A Parallel Point Matching Algorithm for Landmark Based Image Registration Using Multicore Platform

PubMed Central

Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L.; Foran, David J.

2013-01-01

Point matching is crucial for many computer vision applications. Establishing the correspondence between a large number of data points is a computationally intensive process. Some point matching related applications, such as medical image registration, require real time or near real time performance if applied to critical clinical applications like image assisted surgery. In this paper, we report a new multicore platform based parallel algorithm for fast point matching in the context of landmark based medical image registration. We introduced a non-regular data partition algorithm which utilizes the K-means clustering algorithm to group the landmarks based on the number of available processing cores, which optimize the memory usage and data transfer. We have tested our method using the IBM Cell Broadband Engine (Cell/B.E.) platform. The results demonstrated a significant speed up over its sequential implementation. The proposed data partition and parallelization algorithm, though tested only on one multicore platform, is generic by its design. Therefore the parallel algorithm can be extended to other computing platforms, as well as other point matching related applications. PMID:24308014

SU-E-J-140: Availability of Using Diaphragm Matching in Stereotactic Body Radiotherapy (SBRT) at the Time in Breath-Holding SBRT for Liver Cancer

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

Kawahara, D; Tsuda, S.; Section of Radiation Therapy, Department of Clinical Support, Hiroshima University Hospital Health

2014-06-01

Purpose: IGRT based on the bone matching may produce a larger target positioning error in terms of the reproducibility of the expiration breath hold. Therefore, the feasibility of the 3D image matching between planning CT image and pretreatment CBCT image based on the diaphragm matching was investigated. Methods: In fifteen-nine liver SBRT cases, Lipiodol, uptake after TACE was outlined as the marker of the tumor. The relative coordinate of the isocenter obtained by the contrast matching was defined as the reference coordinate. The target positioning difference between diaphragm matching and bone matching were evaluated by the relative coordinate of themore » isocenter from the reference coordinate obtained by each matching technique. In addition, we evaluated PTV margins by van Herk setup margin formula. Results: The target positioning error by the diaphragm matching and the bone matching was 1.31±0.83 and 3.10±2.80 mm in the cranial-caudal(C-C) direction, 1.04±0.95 and 1.62±1.02 mm in the anterior-posterior(A-P) direction, 0.93±1.19 and 1.12±0.94 mm in the left-right(L-R) direction, respectively. The positioning error by the diaphragm matching was significantly smaller than the bone matching in the C-C direction (p<0.05). The setup margin of diaphragm matching and bone matching that we had calculated based on van Herk margin formula was 4.5mm and 6.2mm(C-C), and 3.6mm and 6.3mm(A-P), and 2.6mm and 4.5mm(L-R), respectively. Conclusion: IGRT based on a diaphragm matching could be one alternative image matching technique for the positioning of the patients with liver tumor.« less

A 3D terrain reconstruction method of stereo vision based quadruped robot navigation system

NASA Astrophysics Data System (ADS)

Ge, Zhuo; Zhu, Ying; Liang, Guanhao

2017-01-01

To provide 3D environment information for the quadruped robot autonomous navigation system during walking through rough terrain, based on the stereo vision, a novel 3D terrain reconstruction method is presented. In order to solve the problem that images collected by stereo sensors have large regions with similar grayscale and the problem that image matching is poor at real-time performance, watershed algorithm and fuzzy c-means clustering algorithm are combined for contour extraction. Aiming at the problem of error matching, duel constraint with region matching and pixel matching is established for matching optimization. Using the stereo matching edge pixel pairs, the 3D coordinate algorithm is estimated according to the binocular stereo vision imaging model. Experimental results show that the proposed method can yield high stereo matching ratio and reconstruct 3D scene quickly and efficiently.

PSK Shift Timing Information Detection Using Image Processing and a Matched Filter

DTIC Science & Technology

2009-09-01

phase shifts are enhanced.  Develop, design, and test the resulting phase shift identification scheme. xx  Develop, design, and test an optional...and the resulting phase shift identification algorithm is investigated for SNR levels in the range -2dB to 12 dB. Detection performances are derived...test the resulting phase shift identification scheme.  Develop, design, and test an optional analysis window overlapping technique to improve phase

Report of improved performance in Talbot–Lau phase-contrast computed tomography

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

Weber, Thomas, E-mail: thomas.weber@fau.de; Pelzer, Georg; Rieger, Jens

Purpose: Many expectations have been raised since the use of conventional x-ray tubes on grating-based x-ray phase-contrast imaging. Despite a reported increase in contrast-to-noise ratio (CNR) in many publications, there is doubt on whether phase-contrast computed tomography (CT) is advantageous in clinical CT scanners in vivo. The aim of this paper is to contribute to this discussion by analyzing the performance of a phase-contrast CT laboratory setup. Methods: A phase-contrast CT performance analysis was done. Projection images of a phantom were recorded, and image slices were reconstructed using standard filtered back projection methods. The resulting image slices were analyzed bymore » determining the CNRs in the attenuation and phase image. These results were compared to analytically calculated expectations according to the already published phase-contrast CT performance analysis by Raupach and Flohr [Med. Phys. 39, 4761–4774 (2012)]. There, a severe mistake was found leading to wrong predictions of the performance of phase-contrast CT. The error was corrected and with the new formulae, the experimentally obtained results matched the analytical calculations. Results: The squared ratios of the phase-contrast CNR and the attenuation CNR obtained in the authors’ experiment are five- to ten-fold higher than predicted by Raupach and Flohr [Med. Phys. 39, 4761–4774 (2012)]. The effective lateral spatial coherence length deduced outnumbers the already optimistic assumption of Raupach and Flohr [Med. Phys. 39, 4761–4774 (2012)] by a factor of 3. Conclusions: The authors’ results indicate that the assumptions made in former performance analyses are pessimistic. The break-even point, when phase-contrast CT outperforms attenuation CT, is within reach even with realistic, nonperfect gratings. Further improvements to state-of-the-art clinical CT scanners, like increasing the spatial resolution, could change the balance in favor of phase-contrast computed tomography even more. This could be done by, e.g., quantum-counting pixel detectors with four-fold smaller pixel pitches.« less

Image matching as a data source for forest inventory - Comparison of Semi-Global Matching and Next-Generation Automatic Terrain Extraction algorithms in a typical managed boreal forest environment

NASA Astrophysics Data System (ADS)

Kukkonen, M.; Maltamo, M.; Packalen, P.

2017-08-01

Image matching is emerging as a compelling alternative to airborne laser scanning (ALS) as a data source for forest inventory and management. There is currently an open discussion in the forest inventory community about whether, and to what extent, the new method can be applied to practical inventory campaigns. This paper aims to contribute to this discussion by comparing two different image matching algorithms (Semi-Global Matching [SGM] and Next-Generation Automatic Terrain Extraction [NGATE]) and ALS in a typical managed boreal forest environment in southern Finland. Spectral features from unrectified aerial images were included in the modeling and the potential of image matching in areas without a high resolution digital terrain model (DTM) was also explored. Plot level predictions for total volume, stem number, basal area, height of basal area median tree and diameter of basal area median tree were modeled using an area-based approach. Plot level dominant tree species were predicted using a random forest algorithm, also using an area-based approach. The statistical difference between the error rates from different datasets was evaluated using a bootstrap method. Results showed that ALS outperformed image matching with every forest attribute, even when a high resolution DTM was used for height normalization and spectral information from images was included. Dominant tree species classification with image matching achieved accuracy levels similar to ALS regardless of the resolution of the DTM when spectral metrics were used. Neither of the image matching algorithms consistently outperformed the other, but there were noticeably different error rates depending on the parameter configuration, spectral band, resolution of DTM, or response variable. This study showed that image matching provides reasonable point cloud data for forest inventory purposes, especially when a high resolution DTM is available and information from the understory is redundant.

Automatic digital surface model (DSM) generation from aerial imagery data

NASA Astrophysics Data System (ADS)

Zhou, Nan; Cao, Shixiang; He, Hongyan; Xing, Kun; Yue, Chunyu

2018-04-01

Aerial sensors are widely used to acquire imagery for photogrammetric and remote sensing application. In general, the images have large overlapped region, which provide a lot of redundant geometry and radiation information for matching. This paper presents a POS supported dense matching procedure for automatic DSM generation from aerial imagery data. The method uses a coarse-to-fine hierarchical strategy with an effective combination of several image matching algorithms: image radiation pre-processing, image pyramid generation, feature point extraction and grid point generation, multi-image geometrically constraint cross-correlation (MIG3C), global relaxation optimization, multi-image geometrically constrained least squares matching (MIGCLSM), TIN generation and point cloud filtering. The image radiation pre-processing is used in order to reduce the effects of the inherent radiometric problems and optimize the images. The presented approach essentially consists of 3 components: feature point extraction and matching procedure, grid point matching procedure and relational matching procedure. The MIGCLSM method is used to achieve potentially sub-pixel accuracy matches and identify some inaccurate and possibly false matches. The feasibility of the method has been tested on different aerial scale images with different landcover types. The accuracy evaluation is based on the comparison between the automatic extracted DSMs derived from the precise exterior orientation parameters (EOPs) and the POS.

Real-time line matching from stereo images using a nonparametric transform of spatial relations and texture information

NASA Astrophysics Data System (ADS)

Park, Jonghee; Yoon, Kuk-Jin

2015-02-01

We propose a real-time line matching method for stereo systems. To achieve real-time performance while retaining a high level of matching precision, we first propose a nonparametric transform to represent the spatial relations between neighboring lines and nearby textures as a binary stream. Since the length of a line can vary across images, the matching costs between lines are computed within an overlap area (OA) based on the binary stream. The OA is determined for each line pair by employing the properties of a rectified image pair. Finally, the line correspondence is determined using a winner-takes-all method with a left-right consistency check. To reduce the computational time requirements further, we filter out unreliable matching candidates in advance based on their rectification properties. The performance of the proposed method was compared with state-of-the-art methods in terms of the computational time, matching precision, and recall. The proposed method required 47 ms to match lines from an image pair in the KITTI dataset with an average precision of 95%. We also verified the proposed method under image blur, illumination variation, and viewpoint changes.

Speckle-reducing scale-invariant feature transform match for synthetic aperture radar image registration

NASA Astrophysics Data System (ADS)

Wang, Xianmin; Li, Bo; Xu, Qizhi

2016-07-01

The anisotropic scale space (ASS) is often used to enhance the performance of a scale-invariant feature transform (SIFT) algorithm in the registration of synthetic aperture radar (SAR) images. The existing ASS-based methods usually suffer from unstable keypoints and false matches, since the anisotropic diffusion filtering has limitations in reducing the speckle noise from SAR images while building the ASS image representation. We proposed a speckle reducing SIFT match method to obtain stable keypoints and acquire precise matches for the SAR image registration. First, the keypoints are detected in a speckle reducing anisotropic scale space constructed by the speckle reducing anisotropic diffusion, so that speckle noise is greatly reduced and prominent structures of the images are preserved, consequently the stable keypoints can be derived. Next, the probabilistic relaxation labeling approach is employed to establish the matches of the keypoints then the correct match rate of the keypoints is significantly increased. Experiments conducted on simulated speckled images and real SAR images demonstrate the effectiveness of the proposed method.

Optical implementation of the synthetic discriminant function

NASA Astrophysics Data System (ADS)

Butler, S.; Riggins, J.

1984-10-01

Much attention is focused on the use of coherent optical pattern recognition (OPR) using matched spatial filters for robotics and intelligent systems. The OPR problem consists of three aspects -- information input, information processing, and information output. This paper discusses the information processing aspect which consists of choosing a filter to provide robust correlation with high efficiency. The filter should ideally be invariant to image shift, rotation and scale, provide a reasonable signal-to-noise (S/N) ratio and allow high throughput efficiency. The physical implementation of a spatial matched filter involves many choices. These include the use of conventional holograms or computer-generated holograms (CGH) and utilizing absorption or phase materials. Conventional holograms inherently modify the reference image by non-uniform emphasis of spatial frequencies. Proper use of film nonlinearity provides improved filter performance by emphasizing frequency ranges crucial to target discrimination. In the case of a CGH, the emphasis of the reference magnitude and phase can be controlled independently of the continuous tone or binary writing processes. This paper describes computer simulation and optical implementation of a geometrical shape and a Synthetic Discriminant Function (SDF) matched filter. The authors chose the binary Allebach-Keegan (AK) CGH algorithm to produce actual filters. The performances of these filters were measured to verify the simulation results. This paper provides a brief summary of the matched filter theory, the SDF, CGH algorithms, Phase-Only-Filtering, simulation procedures, and results.

Application of phase matching autofocus in airborne long-range oblique photography camera

NASA Astrophysics Data System (ADS)

Petrushevsky, Vladimir; Guberman, Asaf

2014-06-01

The Condor2 long-range oblique photography (LOROP) camera is mounted in an aerodynamically shaped pod carried by a fast jet aircraft. Large aperture, dual-band (EO/MWIR) camera is equipped with TDI focal plane arrays and provides high-resolution imagery of extended areas at long stand-off ranges, at day and night. Front Ritchey-Chretien optics is made of highly stable materials. However, the camera temperature varies considerably in flight conditions. Moreover, a composite-material structure of the reflective objective undergoes gradual dehumidification in dry nitrogen atmosphere inside the pod, causing some small decrease of the structure length. The temperature and humidity effects change a distance between the mirrors by just a few microns. The distance change is small but nevertheless it alters the camera's infinity focus setpoint significantly, especially in the EO band. To realize the optics' resolution potential, the optimal focus shall be constantly maintained. In-flight best focus calibration and temperature-based open-loop focus control give mostly satisfactory performance. To get even better focusing precision, a closed-loop phase-matching autofocus method was developed for the camera. The method makes use of an existing beamsharer prism FPA arrangement where aperture partition exists inherently in an area of overlap between the adjacent detectors. The defocus is proportional to an image phase shift in the area of overlap. Low-pass filtering of raw defocus estimate reduces random errors related to variable scene content. Closed-loop control converges robustly to precise focus position. The algorithm uses the temperature- and range-based focus prediction as an initial guess for the closed-loop phase-matching control. The autofocus algorithm achieves excellent results and works robustly in various conditions of scene illumination and contrast.

An Evolutionary Algorithm for Fast Intensity Based Image Matching Between Optical and SAR Satellite Imagery

NASA Astrophysics Data System (ADS)

Fischer, Peter; Schuegraf, Philipp; Merkle, Nina; Storch, Tobias

2018-04-01

This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR) optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search) and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

A Coarse-to-Fine Geometric Scale-Invariant Feature Transform for Large Size High Resolution Satellite Image Registration

PubMed Central

Chang, Xueli; Du, Siliang; Li, Yingying; Fang, Shenghui

2018-01-01

Large size high resolution (HR) satellite image matching is a challenging task due to local distortion, repetitive structures, intensity changes and low efficiency. In this paper, a novel matching approach is proposed for the large size HR satellite image registration, which is based on coarse-to-fine strategy and geometric scale-invariant feature transform (SIFT). In the coarse matching step, a robust matching method scale restrict (SR) SIFT is implemented at low resolution level. The matching results provide geometric constraints which are then used to guide block division and geometric SIFT in the fine matching step. The block matching method can overcome the memory problem. In geometric SIFT, with area constraints, it is beneficial for validating the candidate matches and decreasing searching complexity. To further improve the matching efficiency, the proposed matching method is parallelized using OpenMP. Finally, the sensing image is rectified to the coordinate of reference image via Triangulated Irregular Network (TIN) transformation. Experiments are designed to test the performance of the proposed matching method. The experimental results show that the proposed method can decrease the matching time and increase the number of matching points while maintaining high registration accuracy. PMID:29702589

A novel image registration approach via combining local features and geometric invariants

PubMed Central

Lu, Yan; Gao, Kun; Zhang, Tinghua; Xu, Tingfa

2018-01-01

Image registration is widely used in many fields, but the adaptability of the existing methods is limited. This work proposes a novel image registration method with high precision for various complex applications. In this framework, the registration problem is divided into two stages. First, we detect and describe scale-invariant feature points using modified computer vision-oriented fast and rotated brief (ORB) algorithm, and a simple method to increase the performance of feature points matching is proposed. Second, we develop a new local constraint of rough selection according to the feature distances. Evidence shows that the existing matching techniques based on image features are insufficient for the images with sparse image details. Then, we propose a novel matching algorithm via geometric constraints, and establish local feature descriptions based on geometric invariances for the selected feature points. Subsequently, a new price function is constructed to evaluate the similarities between points and obtain exact matching pairs. Finally, we employ the progressive sample consensus method to remove wrong matches and calculate the space transform parameters. Experimental results on various complex image datasets verify that the proposed method is more robust and significantly reduces the rate of false matches while retaining more high-quality feature points. PMID:29293595

Brain medical image diagnosis based on corners with importance-values.

PubMed

Gao, Linlin; Pan, Haiwei; Li, Qing; Xie, Xiaoqin; Zhang, Zhiqiang; Han, Jinming; Zhai, Xiao

2017-11-21

Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. However, existing corner detection studies do not consider the domain information of brain. This leads to many useless corners and the loss of significant information. Regarding corner matching, the uncertainty and structure of brain are not employed in existing methods. Moreover, most corner matching studies are used for 3D image registration. They are inapplicable for 2D brain image diagnosis because of the different mechanisms. To address these problems, we propose a novel corner-based brain medical image classification method. Specifically, we automatically extract multilayer texture images (MTIs) which embody diagnostic information from neurologists. Moreover, we present a corner matching method utilizing the uncertainty and structure of brain medical images and a bipartite graph model. Finally, we propose a similarity calculation method for diagnosis. Brain CT and MRI image sets are utilized to evaluate the proposed method. First, classifiers are trained in N-fold cross-validation analysis to produce the best θ and K. Then independent brain image sets are tested to evaluate the classifiers. Moreover, the classifiers are also compared with advanced brain image classification studies. For the brain CT image set, the proposed classifier outperforms the comparison methods by at least 8% on accuracy and 2.4% on F1-score. Regarding the brain MRI image set, the proposed classifier is superior to the comparison methods by more than 7.3% on accuracy and 4.9% on F1-score. Results also demonstrate that the proposed method is robust to different intensity ranges of brain medical image. In this study, we develop a robust corner-based brain medical image classifier. Specifically, we propose a corner detection method utilizing the diagnostic information from neurologists and a corner matching method based on the uncertainty and structure of brain medical images. Additionally, we present a similarity calculation method for brain image classification. Experimental results on two brain image sets show the proposed corner-based brain medical image classifier outperforms the state-of-the-art studies.

FAST TRACK COMMUNICATION Far-field x-ray phase contrast imaging has no detailed information on the object

NASA Astrophysics Data System (ADS)

Kohn, V. G.; Argunova, T. S.; Je, J. H.

2010-11-01

We show that x-ray phase contrast images of some objects with a small cross-section diameter d satisfy a condition for a far-field approximation d Lt r1 where r1 = (λz)1/2, λ is the x-ray wavelength, z is the distance from the object to the detector. In this case the size of the image does not match the size of the object contrary to the edge detection technique. Moreover, the structure of the central fringes of the image is universal, i.e. it is independent of the object cross-section structure. Therefore, these images have no detailed information on the object.

a Band Selection Method for High Precision Registration of Hyperspectral Image

NASA Astrophysics Data System (ADS)

Yang, H.; Li, X.

2018-04-01

During the registration of hyperspectral images and high spatial resolution images, too much bands in a hyperspectral image make it difficult to select bands with good registration performance. Terrible bands are possible to reduce matching speed and accuracy. To solve this problem, an algorithm based on Cram'er-Rao lower bound theory is proposed to select good matching bands in this paper. The algorithm applies the Cram'er-Rao lower bound theory to the study of registration accuracy, and selects good matching bands by CRLB parameters. Experiments show that the algorithm in this paper can choose good matching bands and provide better data for the registration of hyperspectral image and high spatial resolution image.

Infrared super-resolution imaging based on compressed sensing

NASA Astrophysics Data System (ADS)

Sui, Xiubao; Chen, Qian; Gu, Guohua; Shen, Xuewei

2014-03-01

The theoretical basis of traditional infrared super-resolution imaging method is Nyquist sampling theorem. The reconstruction premise is that the relative positions of the infrared objects in the low-resolution image sequences should keep fixed and the image restoration means is the inverse operation of ill-posed issues without fixed rules. The super-resolution reconstruction ability of the infrared image, algorithm's application area and stability of reconstruction algorithm are limited. To this end, we proposed super-resolution reconstruction method based on compressed sensing in this paper. In the method, we selected Toeplitz matrix as the measurement matrix and realized it by phase mask method. We researched complementary matching pursuit algorithm and selected it as the recovery algorithm. In order to adapt to the moving target and decrease imaging time, we take use of area infrared focal plane array to acquire multiple measurements at one time. Theoretically, the method breaks though Nyquist sampling theorem and can greatly improve the spatial resolution of the infrared image. The last image contrast and experiment data indicate that our method is effective in improving resolution of infrared images and is superior than some traditional super-resolution imaging method. The compressed sensing super-resolution method is expected to have a wide application prospect.

Quantification of organ motion based on an adaptive image-based scale invariant feature method

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

Paganelli, Chiara; Peroni, Marta; Baroni, Guido

2013-11-15

Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application ofmore » contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT, providing a motion description comparable to expert manual identification, as confirmed by DIR.Conclusions: The application of the method to a 4D lung CT patient dataset demonstrated adaptive-SIFT potential as an automatic tool to detect landmarks for DIR regularization and internal motion quantification. Future works should include the optimization of the computational cost and the application of the method to other anatomical sites and image modalities.« less

A Robust False Matching Points Detection Method for Remote Sensing Image Registration

NASA Astrophysics Data System (ADS)

Shan, X. J.; Tang, P.

2015-04-01

Given the influences of illumination, imaging angle, and geometric distortion, among others, false matching points still occur in all image registration algorithms. Therefore, false matching points detection is an important step in remote sensing image registration. Random Sample Consensus (RANSAC) is typically used to detect false matching points. However, RANSAC method cannot detect all false matching points in some remote sensing images. Therefore, a robust false matching points detection method based on Knearest- neighbour (K-NN) graph (KGD) is proposed in this method to obtain robust and high accuracy result. The KGD method starts with the construction of the K-NN graph in one image. K-NN graph can be first generated for each matching points and its K nearest matching points. Local transformation model for each matching point is then obtained by using its K nearest matching points. The error of each matching point is computed by using its transformation model. Last, L matching points with largest error are identified false matching points and removed. This process is iterative until all errors are smaller than the given threshold. In addition, KGD method can be used in combination with other methods, such as RANSAC. Several remote sensing images with different resolutions and terrains are used in the experiment. We evaluate the performance of KGD method, RANSAC + KGD method, RANSAC, and Graph Transformation Matching (GTM). The experimental results demonstrate the superior performance of the KGD and RANSAC + KGD methods.

Landmark matching based retinal image alignment by enforcing sparsity in correspondence matrix.

PubMed

Zheng, Yuanjie; Daniel, Ebenezer; Hunter, Allan A; Xiao, Rui; Gao, Jianbin; Li, Hongsheng; Maguire, Maureen G; Brainard, David H; Gee, James C

2014-08-01

Retinal image alignment is fundamental to many applications in diagnosis of eye diseases. In this paper, we address the problem of landmark matching based retinal image alignment. We propose a novel landmark matching formulation by enforcing sparsity in the correspondence matrix and offer its solutions based on linear programming. The proposed formulation not only enables a joint estimation of the landmark correspondences and a predefined transformation model but also combines the benefits of the softassign strategy (Chui and Rangarajan, 2003) and the combinatorial optimization of linear programming. We also introduced a set of reinforced self-similarities descriptors which can better characterize local photometric and geometric properties of the retinal image. Theoretical analysis and experimental results with both fundus color images and angiogram images show the superior performances of our algorithms to several state-of-the-art techniques. Copyright © 2013 Elsevier B.V. All rights reserved.

A fuzzy structural matching scheme for space robotics vision

NASA Technical Reports Server (NTRS)

Naka, Masao; Yamamoto, Hiromichi; Homma, Khozo; Iwata, Yoshitaka

1994-01-01

In this paper, we propose a new fuzzy structural matching scheme for space stereo vision which is based on the fuzzy properties of regions of images and effectively reduces the computational burden in the following low level matching process. Three dimensional distance images of a space truss structural model are estimated using this scheme from stereo images sensed by Charge Coupled Device (CCD) TV cameras.

A framework for medical image retrieval using machine learning and statistical similarity matching techniques with relevance feedback.

PubMed

Rahman, Md Mahmudur; Bhattacharya, Prabir; Desai, Bipin C

2007-01-01

A content-based image retrieval (CBIR) framework for diverse collection of medical images of different imaging modalities, anatomic regions with different orientations and biological systems is proposed. Organization of images in such a database (DB) is well defined with predefined semantic categories; hence, it can be useful for category-specific searching. The proposed framework consists of machine learning methods for image prefiltering, similarity matching using statistical distance measures, and a relevance feedback (RF) scheme. To narrow down the semantic gap and increase the retrieval efficiency, we investigate both supervised and unsupervised learning techniques to associate low-level global image features (e.g., color, texture, and edge) in the projected PCA-based eigenspace with their high-level semantic and visual categories. Specially, we explore the use of a probabilistic multiclass support vector machine (SVM) and fuzzy c-mean (FCM) clustering for categorization and prefiltering of images to reduce the search space. A category-specific statistical similarity matching is proposed in a finer level on the prefiltered images. To incorporate a better perception subjectivity, an RF mechanism is also added to update the query parameters dynamically and adjust the proposed matching functions. Experiments are based on a ground-truth DB consisting of 5000 diverse medical images of 20 predefined categories. Analysis of results based on cross-validation (CV) accuracy and precision-recall for image categorization and retrieval is reported. It demonstrates the improvement, effectiveness, and efficiency achieved by the proposed framework.

Automatic orientation and 3D modelling from markerless rock art imagery

NASA Astrophysics Data System (ADS)

Lerma, J. L.; Navarro, S.; Cabrelles, M.; Seguí, A. E.; Hernández, D.

2013-02-01

This paper investigates the use of two detectors and descriptors on image pyramids for automatic image orientation and generation of 3D models. The detectors and descriptors replace manual measurements and are used to detect, extract and match features across multiple imagery. The Scale-Invariant Feature Transform (SIFT) and the Speeded Up Robust Features (SURF) will be assessed based on speed, number of features, matched features, and precision in image and object space depending on the adopted hierarchical matching scheme. The influence of applying in addition Area Based Matching (ABM) with normalised cross-correlation (NCC) and least squares matching (LSM) is also investigated. The pipeline makes use of photogrammetric and computer vision algorithms aiming minimum interaction and maximum accuracy from a calibrated camera. Both the exterior orientation parameters and the 3D coordinates in object space are sequentially estimated combining relative orientation, single space resection and bundle adjustment. The fully automatic image-based pipeline presented herein to automate the image orientation step of a sequence of terrestrial markerless imagery is compared with manual bundle block adjustment and terrestrial laser scanning (TLS) which serves as ground truth. The benefits of applying ABM after FBM will be assessed both in image and object space for the 3D modelling of a complex rock art shelter.

Motion tracking in MR-guided liver therapy by using navigator echoes and projection profile matching.

PubMed

Tokuda, Junichi; Morikawa, Shigehiro; Dohi, Takeyoshi; Hata, Nobuhiko

2004-01-01

Image registration in magnetic resonance (MR) image-guided liver therapy enhances surgical guidance by fusing preoperative multimodality images with intraoperative images, or by fusing intramodality images to correlate serial intraoperative images to monitor the effect of therapy. The objective of this paper is to describe the application of navigator echo and projection profile matching to fast two-dimensional image registration for MR-guided liver therapy. We obtain navigator echoes along the read-out and phase-encoding directions by using modified gradient echo imaging. This registration is made possible by masking out the liver profile from the image and performing profile matching with cross-correlation or mutual information as similarity measures. The set of experiments include a phantom study with a 2.0-T experimental MR scanner, and a volunteer and a clinical study with a 0.5-T open-configuration MR scanner, and these evaluate the accuracy and effectiveness of this method for liver therapy. Both the phantom and volunteer study indicate that this method can perform registration in 34 ms with root-mean-square error of 1.6 mm when the given misalignment of a liver is 30 mm. The clinical studies demonstrate that the method can track liver motion of up to approximately 40 mm. Matching profiles with cross-correlation information perform better than with mutual information in terms of robustness and speed. The proposed image registration method has potential clinical impact on and advantages for MR-guided liver therapy.

Investigating Cardiac MRI Based Right Ventricular Contractility As A Novel Non-Invasive Metric of Pulmonary Arterial Pressure

PubMed Central

Menon, Prahlad G; Adhypak, Srilakshmi M; Williams, Ronald B; Doyle, Mark; Biederman, Robert WW

2014-01-01

BACKGROUND We test the hypothesis that cardiac magnetic resonance (CMR) imaging-based indices of four-dimensional (4D) (three dimensions (3D) + time) right ventricle (RV) function have predictive values in ascertaining invasive pulmonary arterial systolic pressure (PASP) measurements from right heart catheterization (RHC) in patients with pulmonary arterial hypertension (PAH). METHODS We studied five patients with idiopathic PAH and two age and sex-matched controls for RV function using a novel contractility index (CI) for amplitude and phase to peak contraction established from analysis of regional shape variation in the RV endocardium over 20 cardiac phases, segmented from CMR images in multiple orientations. RESULTS The amplitude of RV contractility correlated inversely with RV ejection fraction (RVEF; R2 = 0.64, P = 0.03) and PASP (R2 = 0.71, P = 0.02). Phase of peak RV contractility also correlated inversely to RVEF (R2 = 0.499, P = 0.12) and PASP (R2 = 0.66, P = 0.04). CONCLUSIONS RV contractility analyzed from CMR offers promising non-invasive metrics for classification of PAH, which are congruent with invasive pressure measurements. PMID:25624777

A long baseline global stereo matching based upon short baseline estimation

NASA Astrophysics Data System (ADS)

Li, Jing; Zhao, Hong; Li, Zigang; Gu, Feifei; Zhao, Zixin; Ma, Yueyang; Fang, Meiqi

2018-05-01

In global stereo vision, balancing the matching efficiency and computing accuracy seems to be impossible because they contradict each other. In the case of a long baseline, this contradiction becomes more prominent. In order to solve this difficult problem, this paper proposes a novel idea to improve both the efficiency and accuracy in global stereo matching for a long baseline. In this way, the reference images located between the long baseline image pairs are firstly chosen to form the new image pairs with short baselines. The relationship between the disparities of pixels in the image pairs with different baselines is revealed by considering the quantized error so that the disparity search range under the long baseline can be reduced by guidance of the short baseline to gain matching efficiency. Then, the novel idea is integrated into the graph cuts (GCs) to form a multi-step GC algorithm based on the short baseline estimation, by which the disparity map under the long baseline can be calculated iteratively on the basis of the previous matching. Furthermore, the image information from the pixels that are non-occluded under the short baseline but are occluded for the long baseline can be employed to improve the matching accuracy. Although the time complexity of the proposed method depends on the locations of the chosen reference images, it is usually much lower for a long baseline stereo matching than when using the traditional GC algorithm. Finally, the validity of the proposed method is examined by experiments based on benchmark datasets. The results show that the proposed method is superior to the traditional GC method in terms of efficiency and accuracy, and thus it is suitable for long baseline stereo matching.

Optical correlation based pose estimation using bipolar phase grayscale amplitude spatial light modulators

NASA Astrophysics Data System (ADS)

Outerbridge, Gregory John, II

Pose estimation techniques have been developed on both optical and digital correlator platforms to aid in the autonomous rendezvous and docking of spacecraft. This research has focused on the optical architecture, which utilizes high-speed bipolar-phase grayscale-amplitude spatial light modulators as the image and correlation filter devices. The optical approach has the primary advantage of optical parallel processing: an extremely fast and efficient way of performing complex correlation calculations. However, the constraints imposed on optically implementable filters makes optical correlator based posed estimation technically incompatible with the popular weighted composite filter designs successfully used on the digital platform. This research employs a much simpler "bank of filters" approach to optical pose estimation that exploits the inherent efficiency of optical correlation devices. A novel logarithmically mapped optically implementable matched filter combined with a pose search algorithm resulted in sub-degree standard deviations in angular pose estimation error. These filters were extremely simple to generate, requiring no complicated training sets and resulted in excellent performance even in the presence of significant background noise. Common edge detection and scaling of the input image was the only image pre-processing necessary for accurate pose detection at all alignment distances of interest.

Survey of computer vision technology for UVA navigation

NASA Astrophysics Data System (ADS)

Xie, Bo; Fan, Xiang; Li, Sijian

2017-11-01

Navigation based on computer version technology, which has the characteristics of strong independence, high precision and is not susceptible to electrical interference, has attracted more and more attention in the filed of UAV navigation research. Early navigation project based on computer version technology mainly applied to autonomous ground robot. In recent years, the visual navigation system is widely applied to unmanned machine, deep space detector and underwater robot. That further stimulate the research of integrated navigation algorithm based on computer version technology. In China, with many types of UAV development and two lunar exploration, the three phase of the project started, there has been significant progress in the study of visual navigation. The paper expounds the development of navigation based on computer version technology in the filed of UAV navigation research and draw a conclusion that visual navigation is mainly applied to three aspects as follows.(1) Acquisition of UAV navigation parameters. The parameters, including UAV attitude, position and velocity information could be got according to the relationship between the images from sensors and carrier's attitude, the relationship between instant matching images and the reference images and the relationship between carrier's velocity and characteristics of sequential images.(2) Autonomous obstacle avoidance. There are many ways to achieve obstacle avoidance in UAV navigation. The methods based on computer version technology ,including feature matching, template matching, image frames and so on, are mainly introduced. (3) The target tracking, positioning. Using the obtained images, UAV position is calculated by using optical flow method, MeanShift algorithm, CamShift algorithm, Kalman filtering and particle filter algotithm. The paper expounds three kinds of mainstream visual system. (1) High speed visual system. It uses parallel structure, with which image detection and processing are carried out at high speed. The system is applied to rapid response system. (2) The visual system of distributed network. There are several discrete image data acquisition sensor in different locations, which transmit image data to the node processor to increase the sampling rate. (3) The visual system combined with observer. The system combines image sensors with the external observers to make up for lack of visual equipment. To some degree, these systems overcome lacks of the early visual system, including low frequency, low processing efficiency and strong noise. In the end, the difficulties of navigation based on computer version technology in practical application are briefly discussed. (1) Due to the huge workload of image operation , the real-time performance of the system is poor. (2) Due to the large environmental impact , the anti-interference ability of the system is poor.(3) Due to the ability to work in a particular environment, the system has poor adaptability.

Communication: Two-dimensional gas-phase coherent anti-Stokes Raman spectroscopy (2D-CARS): Simultaneous planar imaging and multiplex spectroscopy in a single laser shot

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

Bohlin, Alexis; Kliewer, Christopher J.

2013-01-01

Coherent anti-Stokes Raman spectroscopy (CARS) has been widely used as a powerful tool for chemical sensing, molecular dynamics measurements, and rovibrational spectroscopy since its development over 30 years ago, finding use in fields of study as diverse as combustion diagnostics, cell biology, plasma physics, and the standoff detection of explosives. The capability for acquiring resolved CARS spectra in multiple spatial dimensions within a single laser shot has been a long-standing goal for the study of dynamical processes, but has proven elusive because of both phase-matching and detection considerations. Here, by combining new phase matching and detection schemes with the highmore » efficiency of femtosecond excitation of Raman coherences, we introduce a technique for single-shot two-dimensional (2D) spatial measurements of gas phase CARS spectra. We demonstrate a spectrometer enabling both 2D plane imaging and spectroscopy simultaneously, and present the instantaneous measurement of 15, 000 spatially correlated rotational CARS spectra in N 2 and air over a 2D field of 40 mm 2.« less

Analysis of x-ray hand images for bone age assessment

NASA Astrophysics Data System (ADS)

Serrat, Joan; Vitria, Jordi M.; Villanueva, Juan J.

1990-09-01

In this paper we describe a model-based system for the assessment of skeletal maturity on hand radiographs by the TW2 method. The problem consists in classiflying a set of bones appearing in an image in one of several stages described in an atlas. A first approach consisting in pre-processing segmentation and classification independent phases is also presented. However it is only well suited for well contrasted low noise images without superimposed bones were the edge detection by zero crossing of second directional derivatives is able to extract all bone contours maybe with little gaps and few false edges on the background. Hence the use of all available knowledge about the problem domain is needed to build a rather general system. We have designed a rule-based system for narrow down the rank of possible stages for each bone and guide the analysis process. It calls procedures written in conventional languages for matching stage models against the image and getting features needed in the classification process.

False match elimination for face recognition based on SIFT algorithm

NASA Astrophysics Data System (ADS)

Gu, Xuyuan; Shi, Ping; Shao, Meide

2011-06-01

The SIFT (Scale Invariant Feature Transform) is a well known algorithm used to detect and describe local features in images. It is invariant to image scale, rotation and robust to the noise and illumination. In this paper, a novel method used for face recognition based on SIFT is proposed, which combines the optimization of SIFT, mutual matching and Progressive Sample Consensus (PROSAC) together and can eliminate the false matches of face recognition effectively. Experiments on ORL face database show that many false matches can be eliminated and better recognition rate is achieved.

Tactile priming modulates the activation of the fronto-parietal circuit during tactile angle match and non-match processing: an fMRI study

PubMed Central

Yang, Jiajia; Yu, Yinghua; Kunita, Akinori; Huang, Qiang; Wu, Jinglong; Sawamoto, Nobukatsu; Fukuyama, Hidenao

2014-01-01

The repetition of a stimulus task reduces the neural activity within certain cortical regions responsible for working memory (WM) processing. Although previous evidence has shown that repeated vibrotactile stimuli reduce the activation in the ventrolateral prefrontal cortex, whether the repeated tactile spatial stimuli triggered the priming effect correlated with the same cortical region remains unclear. Therefore, we used event-related functional magnetic resonance imaging (fMRI) and a delayed match-to-sample task to investigate the contributions of the priming effect to tactile spatial WM processing. Fourteen healthy volunteers were asked to encode three tactile angle stimuli during the encoding phase and one tactile angle stimulus during the recognition phase. Then, they answered whether the last angle stimulus was presented during the encoding phase. As expected, both the Match and Non-Match tasks activated a similar cerebral network. The critical new finding was decreased brain activity in the left inferior frontal gyrus (IFG), the right posterior parietal cortex (PPC) and bilateral medial frontal gyri (mFG) for the match task compared to the Non-Match task. Therefore, we suggest that the tactile priming engaged repetition suppression mechanisms during tactile angle matching, and this process decreased the activation of the fronto-parietal circuit, including IFG, mFG and PPC. PMID:25566010

Stereo matching algorithm based on double components model

NASA Astrophysics Data System (ADS)

Zhou, Xiao; Ou, Kejun; Zhao, Jianxin; Mou, Xingang

2018-03-01

The tiny wires are the great threat to the safety of the UAV flight. Because they have only several pixels isolated far from the background, while most of the existing stereo matching methods require a certain area of the support region to improve the robustness, or assume the depth dependence of the neighboring pixels to meet requirement of global or semi global optimization method. So there will be some false alarms even failures when images contains tiny wires. A new stereo matching algorithm is approved in the paper based on double components model. According to different texture types the input image is decomposed into two independent component images. One contains only sparse wire texture image and another contains all remaining parts. Different matching schemes are adopted for each component image pairs. Experiment proved that the algorithm can effectively calculate the depth image of complex scene of patrol UAV, which can detect tiny wires besides the large size objects. Compared with the current mainstream method it has obvious advantages.

Hyper thin 3D edge measurement of honeycomb core structures based on the triangular camera-projector layout & phase-based stereo matching.

PubMed

Jiang, Hongzhi; Zhao, Huijie; Li, Xudong; Quan, Chenggen

2016-03-07

We propose a novel hyper thin 3D edge measurement technique to measure the profile of 3D outer envelope of honeycomb core structures. The width of the edges of the honeycomb core is less than 0.1 mm. We introduce a triangular layout design consisting of two cameras and one projector to measure hyper thin 3D edges and eliminate data interference from the walls. A phase-shifting algorithm and the multi-frequency heterodyne phase-unwrapping principle are applied for phase retrievals on edges. A new stereo matching method based on phase mapping and epipolar constraint is presented to solve correspondence searching on the edges and remove false matches resulting in 3D outliers. Experimental results demonstrate the effectiveness of the proposed method for measuring the 3D profile of honeycomb core structures.

Poor textural image tie point matching via graph theory

NASA Astrophysics Data System (ADS)

Yuan, Xiuxiao; Chen, Shiyu; Yuan, Wei; Cai, Yang

2017-07-01

Feature matching aims to find corresponding points to serve as tie points between images. Robust matching is still a challenging task when input images are characterized by low contrast or contain repetitive patterns, occlusions, or homogeneous textures. In this paper, a novel feature matching algorithm based on graph theory is proposed. This algorithm integrates both geometric and radiometric constraints into an edge-weighted (EW) affinity tensor. Tie points are then obtained by high-order graph matching. Four pairs of poor textural images covering forests, deserts, bare lands, and urban areas are tested. For comparison, three state-of-the-art matching techniques, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), and features from accelerated segment test (FAST), are also used. The experimental results show that the matching recall obtained by SIFT, SURF, and FAST varies from 0 to 35% in different types of poor textures. However, through the integration of both geometry and radiometry and the EW strategy, the recall obtained by the proposed algorithm is better than 50% in all four image pairs. The better matching recall improves the number of correct matches, dispersion, and positional accuracy.

Image Understanding Research

DTIC Science & Technology

1981-09-30

to perform a variety of local arithmetic operations. Our initial task will be to use it for computing 5X5 convolutions common to many low level...report presents the results of applying our relaxation based scene matching systein I1] to a new domain - automatic matching of pairs of images. The task...objects (corners of buildings) within the large image. But we did demonstrate the ability of our system to automatically segment, describe, and match

Topological visual mapping in robotics.

PubMed

Romero, Anna; Cazorla, Miguel

2012-08-01

A key problem in robotics is the construction of a map from its environment. This map could be used in different tasks, like localization, recognition, obstacle avoidance, etc. Besides, the simultaneous location and mapping (SLAM) problem has had a lot of interest in the robotics community. This paper presents a new method for visual mapping, using topological instead of metric information. For that purpose, we propose prior image segmentation into regions in order to group the extracted invariant features in a graph so that each graph defines a single region of the image. Although others methods have been proposed for visual SLAM, our method is complete, in the sense that it makes all the process: it presents a new method for image matching; it defines a way to build the topological map; and it also defines a matching criterion for loop-closing. The matching process will take into account visual features and their structure using the graph transformation matching (GTM) algorithm, which allows us to process the matching and to remove out the outliers. Then, using this image comparison method, we propose an algorithm for constructing topological maps. During the experimentation phase, we will test the robustness of the method and its ability constructing topological maps. We have also introduced new hysteresis behavior in order to solve some problems found building the graph.

Gun bore flaw image matching based on improved SIFT descriptor

NASA Astrophysics Data System (ADS)

Zeng, Luan; Xiong, Wei; Zhai, You

2013-01-01

In order to increase the operation speed and matching ability of SIFT algorithm, the SIFT descriptor and matching strategy are improved. First, a method of constructing feature descriptor based on sector area is proposed. By computing the gradients histogram of location bins which are parted into 6 sector areas, a descriptor with 48 dimensions is constituted. It can reduce the dimension of feature vector and decrease the complexity of structuring descriptor. Second, it introduce a strategy that partitions the circular region into 6 identical sector areas starting from the dominate orientation. Consequently, the computational complexity is reduced due to cancellation of rotation operation for the area. The experimental results indicate that comparing with the OpenCV SIFT arithmetic, the average matching speed of the new method increase by about 55.86%. The matching veracity can be increased even under some variation of view point, illumination, rotation, scale and out of focus. The new method got satisfied results in gun bore flaw image matching. Keywords: Metrology, Flaw image matching, Gun bore, Feature descriptor

Left ventricular volume estimation in cardiac three-dimensional ultrasound: a semiautomatic border detection approach.

PubMed

van Stralen, Marijn; Bosch, Johan G; Voormolen, Marco M; van Burken, Gerard; Krenning, Boudewijn J; van Geuns, Robert-Jan M; Lancée, Charles T; de Jong, Nico; Reiber, Johan H C

2005-10-01

We propose a semiautomatic endocardial border detection method for three-dimensional (3D) time series of cardiac ultrasound (US) data based on pattern matching and dynamic programming, operating on two-dimensional (2D) slices of the 3D plus time data, for the estimation of full cycle left ventricular volume, with minimal user interaction. The presented method is generally applicable to 3D US data and evaluated on data acquired with the Fast Rotating Ultrasound (FRU-) Transducer, developed by Erasmus Medical Center (Rotterdam, the Netherlands), a conventional phased-array transducer, rotating at very high speed around its image axis. The detection is based on endocardial edge pattern matching using dynamic programming, which is constrained by a 3D plus time shape model. It is applied to an automatically selected subset of 2D images of the original data set, for typically 10 equidistant rotation angles and 16 cardiac phases (160 images). Initialization requires the drawing of four contours per patient manually. We evaluated this method on 14 patients against MRI end-diastole and end-systole volumes. Initialization requires the drawing of four contours per patient manually. We evaluated this method on 14 patients against MRI end-diastolic (ED) and end-systolic (ES) volumes. The semiautomatic border detection approach shows good correlations with MRI ED/ES volumes (r = 0.938) and low interobserver variability (y = 1.005x - 16.7, r = 0.943) over full-cycle volume estimations. It shows a high consistency in tracking the user-defined initial borders over space and time. We show that the ease of the acquisition using the FRU-transducer and the semiautomatic endocardial border detection method together can provide a way to quickly estimate the left ventricular volume over the full cardiac cycle using little user interaction.

Image-Based Localization for Indoor Environment Using Mobile Phone

NASA Astrophysics Data System (ADS)

Huang, Y.; Wang, H.; Zhan, K.; Zhao, J.; Gui, P.; Feng, T.

2015-05-01

Real-time indoor localization based on supporting infrastructures like wireless devices and QR codes are usually costly and labor intensive to implement. In this study, we explored a cheap alternative approach based on images for indoor localization. A user can localize him/herself by just shooting a photo of the surrounding indoor environment using the mobile phone. No any other equipment is required. This is achieved by employing image-matching and searching techniques with a dataset of pre-captured indoor images. In the beginning, a database of structured images of the indoor environment is constructed by using image matching and the bundle adjustment algorithm. Then each image's relative pose (its position and orientation) is estimated and the semantic locations of images are tagged. A user's location can then be determined by comparing a photo taken by the mobile phone to the database. This is done by combining quick image searching, matching and the relative orientation. This study also try to explore image acquisition plans and the processing capacity of off-the-shell mobile phones. During the whole pipeline, a collection of indoor images with both rich and poor textures are examined. Several feature detectors are used and compared. Pre-processing of complex indoor photo is also implemented on the mobile phone. The preliminary experimental results prove the feasibility of this method. In the future, we are trying to raise the efficiency of matching between indoor images and explore the fast 4G wireless communication to ensure the speed and accuracy of the localization based on a client-server framework.

Rigid shape matching by segmentation averaging.

PubMed

Wang, Hongzhi; Oliensis, John

2010-04-01

We use segmentations to match images by shape. The new matching technique does not require point-to-point edge correspondence and is robust to small shape variations and spatial shifts. To address the unreliability of segmentations computed bottom-up, we give a closed form approximation to an average over all segmentations. Our method has many extensions, yielding new algorithms for tracking, object detection, segmentation, and edge-preserving smoothing. For segmentation, instead of a maximum a posteriori approach, we compute the "central" segmentation minimizing the average distance to all segmentations of an image. For smoothing, instead of smoothing images based on local structures, we smooth based on the global optimal image structures. Our methods for segmentation, smoothing, and object detection perform competitively, and we also show promising results in shape-based tracking.

Computer face-matching technology using two-dimensional photographs accurately matches the facial gestalt of unrelated individuals with the same syndromic form of intellectual disability.

PubMed

Dudding-Byth, Tracy; Baxter, Anne; Holliday, Elizabeth G; Hackett, Anna; O'Donnell, Sheridan; White, Susan M; Attia, John; Brunner, Han; de Vries, Bert; Koolen, David; Kleefstra, Tjitske; Ratwatte, Seshika; Riveros, Carlos; Brain, Steve; Lovell, Brian C

2017-12-19

Massively parallel genetic sequencing allows rapid testing of known intellectual disability (ID) genes. However, the discovery of novel syndromic ID genes requires molecular confirmation in at least a second or a cluster of individuals with an overlapping phenotype or similar facial gestalt. Using computer face-matching technology we report an automated approach to matching the faces of non-identical individuals with the same genetic syndrome within a database of 3681 images [1600 images of one of 10 genetic syndrome subgroups together with 2081 control images]. Using the leave-one-out method, two research questions were specified: 1) Using two-dimensional (2D) photographs of individuals with one of 10 genetic syndromes within a database of images, did the technology correctly identify more than expected by chance: i) a top match? ii) at least one match within the top five matches? or iii) at least one in the top 10 with an individual from the same syndrome subgroup? 2) Was there concordance between correct technology-based matches and whether two out of three clinical geneticists would have considered the diagnosis based on the image alone? The computer face-matching technology correctly identifies a top match, at least one correct match in the top five and at least one in the top 10 more than expected by chance (P < 0.00001). There was low agreement between the technology and clinicians, with higher accuracy of the technology when results were discordant (P < 0.01) for all syndromes except Kabuki syndrome. Although the accuracy of the computer face-matching technology was tested on images of individuals with known syndromic forms of intellectual disability, the results of this pilot study illustrate the potential utility of face-matching technology within deep phenotyping platforms to facilitate the interpretation of DNA sequencing data for individuals who remain undiagnosed despite testing the known developmental disorder genes.

Photovoltaic panel extraction from very high-resolution aerial imagery using region-line primitive association analysis and template matching

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Sun, Yujie; Wang, Qiao

2018-07-01

In object-based image analysis (OBIA), object classification performance is jointly determined by image segmentation, sample or rule setting, and classifiers. Typically, as a crucial step to obtain object primitives, image segmentation quality significantly influences subsequent feature extraction and analyses. By contrast, template matching extracts specific objects from images and prevents shape defects caused by image segmentation. However, creating or editing templates is tedious and sometimes results in incomplete or inaccurate templates. In this study, we combine OBIA and template matching techniques to address these problems and aim for accurate photovoltaic panel (PVP) extraction from very high-resolution (VHR) aerial imagery. The proposed method is based on the previously proposed region-line primitive association framework, in which complementary information between region (segment) and line (straight line) primitives is utilized to achieve a more powerful performance than routine OBIA. Several novel concepts, including the mutual fitting ratio and best-fitting template based on region-line primitive association analyses, are proposed. Automatic template generation and matching method for PVP extraction from VHR imagery are designed for concept and model validation. Results show that the proposed method can successfully extract PVPs without any user-specified matching template or training sample. High user independency and accuracy are the main characteristics of the proposed method in comparison with routine OBIA and template matching techniques.

WE-G-BRD-07: Automated MR Image Standardization and Auto-Contouring Strategy for MRI-Based Adaptive Brachytherapy for Cervix Cancer

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

Saleh, H Al; Erickson, B; Paulson, E

Purpose: MRI-based adaptive brachytherapy (ABT) is an emerging treatment modality for patients with gynecological tumors. However, MR image intensity non-uniformities (IINU) can vary from fraction to fraction, complicating image interpretation and auto-contouring accuracy. We demonstrate here an automated MR image standardization and auto-contouring strategy for MRI-based ABT of cervix cancer. Methods: MR image standardization consisted of: 1) IINU correction using the MNI N3 algorithm, 2) noise filtering using anisotropic diffusion, and 3) signal intensity normalization using the volumetric median. This post-processing chain was implemented as a series of custom Matlab and Java extensions in MIM (v6.4.5, MIM Software) and wasmore » applied to 3D T2 SPACE images of six patients undergoing MRI-based ABT at 3T. Coefficients of variation (CV=σ/µ) were calculated for both original and standardized images and compared using Mann-Whitney tests. Patient-specific cumulative MR atlases of bladder, rectum, and sigmoid contours were constructed throughout ABT, using original and standardized MR images from all previous ABT fractions. Auto-contouring was performed in MIM two ways: 1) best-match of one atlas image to the daily MR image, 2) multi-match of all previous fraction atlas images to the daily MR image. Dice’s Similarity Coefficients (DSCs) were calculated for auto-generated contours relative to reference contours for both original and standardized MR images and compared using Mann-Whitney tests. Results: Significant improvements in CV were detected following MR image standardization (p=0.0043), demonstrating an improvement in MR image uniformity. DSCs consistently increased for auto-contoured bladder, rectum, and sigmoid following MR image standardization, with the highest DSCs detected when the combination of MR image standardization and multi-match cumulative atlas-based auto-contouring was utilized. Conclusion: MR image standardization significantly improves MR image uniformity. The combination of MR image standardization and multi-match cumulative atlas-based auto-contouring produced the highest DSCs and is a promising strategy for MRI-based ABT for cervix cancer.« less

Matching CCD images to a stellar catalog using locality-sensitive hashing

NASA Astrophysics Data System (ADS)

Liu, Bo; Yu, Jia-Zong; Peng, Qing-Yu

2018-02-01

The usage of a subset of observed stars in a CCD image to find their corresponding matched stars in a stellar catalog is an important issue in astronomical research. Subgraph isomorphic-based algorithms are the most widely used methods in star catalog matching. When more subgraph features are provided, the CCD images are recognized better. However, when the navigation feature database is large, the method requires more time to match the observing model. To solve this problem, this study investigates further and improves subgraph isomorphic matching algorithms. We present an algorithm based on a locality-sensitive hashing technique, which allocates quadrilateral models in the navigation feature database into different hash buckets and reduces the search range to the bucket in which the observed quadrilateral model is located. Experimental results indicate the effectivity of our method.

Two-Phase chief complaint mapping to the UMLS metathesaurus in Korean electronic medical records.

PubMed

Kang, Bo-Yeong; Kim, Dae-Won; Kim, Hong-Gee

2009-01-01

The task of automatically determining the concepts referred to in chief complaint (CC) data from electronic medical records (EMRs) is an essential component of many EMR applications aimed at biosurveillance for disease outbreaks. Previous approaches that have been used for this concept mapping have mainly relied on term-level matching, whereby the medical terms in the raw text and their synonyms are matched with concepts in a terminology database. These previous approaches, however, have shortcomings that limit their efficacy in CC concept mapping, where the concepts for CC data are often represented by associative terms rather than by synonyms. Therefore, herein we propose a concept mapping scheme based on a two-phase matching approach, especially for application to Korean CCs, which uses term-level complete matching in the first phase and concept-level matching based on concept learning in the second phase. The proposed concept-level matching suggests the method to learn all the terms (associative terms as well as synonyms) that represent the concept and predict the most probable concept for a CC based on the learned terms. Experiments on 1204 CCs extracted from 15,618 discharge summaries of Korean EMRs showed that the proposed method gave significantly improved F-measure values compared to the baseline system, with improvements of up to 73.57%.

Real-time UAV trajectory generation using feature points matching between video image sequences

NASA Astrophysics Data System (ADS)

Byun, Younggi; Song, Jeongheon; Han, Dongyeob

2017-09-01

Unmanned aerial vehicles (UAVs), equipped with navigation systems and video capability, are currently being deployed for intelligence, reconnaissance and surveillance mission. In this paper, we present a systematic approach for the generation of UAV trajectory using a video image matching system based on SURF (Speeded up Robust Feature) and Preemptive RANSAC (Random Sample Consensus). Video image matching to find matching points is one of the most important steps for the accurate generation of UAV trajectory (sequence of poses in 3D space). We used the SURF algorithm to find the matching points between video image sequences, and removed mismatching by using the Preemptive RANSAC which divides all matching points to outliers and inliers. The inliers are only used to determine the epipolar geometry for estimating the relative pose (rotation and translation) between image sequences. Experimental results from simulated video image sequences showed that our approach has a good potential to be applied to the automatic geo-localization of the UAVs system

Image registration based on subpixel localization and Cauchy-Schwarz divergence

NASA Astrophysics Data System (ADS)

Ge, Yongxin; Yang, Dan; Zhang, Xiaohong; Lu, Jiwen

2010-07-01

We define a new matching metric-corner Cauchy-Schwarz divergence (CCSD) and present a new approach based on the proposed CCSD and subpixel localization for image registration. First, we detect the corners in an image by a multiscale Harris operator and take them as initial interest points. And then, a subpixel localization technique is applied to determine the locations of the corners and eliminate the false and unstable corners. After that, CCSD is defined to obtain the initial matching corners. Finally, we use random sample consensus to robustly estimate the parameters based on the initial matching. The experimental results demonstrate that the proposed algorithm has a good performance in terms of both accuracy and efficiency.

A difference tracking algorithm based on discrete sine transform

NASA Astrophysics Data System (ADS)

Liu, HaoPeng; Yao, Yong; Lei, HeBing; Wu, HaoKun

2018-04-01

Target tracking is an important field of computer vision. The template matching tracking algorithm based on squared difference matching (SSD) and standard correlation coefficient (NCC) matching is very sensitive to the gray change of image. When the brightness or gray change, the tracking algorithm will be affected by high-frequency information. Tracking accuracy is reduced, resulting in loss of tracking target. In this paper, a differential tracking algorithm based on discrete sine transform is proposed to reduce the influence of image gray or brightness change. The algorithm that combines the discrete sine transform and the difference algorithm maps the target image into a image digital sequence. The Kalman filter predicts the target position. Using the Hamming distance determines the degree of similarity between the target and the template. The window closest to the template is determined the target to be tracked. The target to be tracked updates the template. Based on the above achieve target tracking. The algorithm is tested in this paper. Compared with SSD and NCC template matching algorithms, the algorithm tracks target stably when image gray or brightness change. And the tracking speed can meet the read-time requirement.

Tie Points Extraction for SAR Images Based on Differential Constraints

NASA Astrophysics Data System (ADS)

Xiong, X.; Jin, G.; Xu, Q.; Zhang, H.

2018-04-01

Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

Zero-Extra-Dose PET Delayed Imaging with Data-Driven Attenuation Correction Estimation.

PubMed

Pang, Lifang; Zhu, Wentao; Dong, Yun; Lv, Yang; Shi, Hongcheng

2018-05-08

Delayed positron emission tomography (PET) imaging may improve sensitivity and specificity in lesion detection. We proposed a PET data-driven method to estimate the attenuation map (AM) for the delayed scan without an additional x-ray computed tomography (CT). An emission-attenuation-scatter joint estimation framework was developed. Several practical issues for clinical datasets were addressed. Particularly, the unknown scatter correction was incorporated in the joint estimation algorithm. The scaling problem was solved using prior information from the early CT scan. Fourteen patient datasets were added to evaluate the method. These patients went through two separate PET/CT scans. The delayed CT-based AM served as ground truth for the delayed scan. Standard uptake values (SUVmean and SUVmax) of lesion and normal tissue regions of interests (ROIs) in the early and delayed phase and the respective %DSUV (percentage change of SUVmean at two different time points) were analyzed, all with estimated and the true AM. Three radiologists participated in lesion detection tasks with images reconstructed with both AMs and rated scores for detectability. The mean relative difference of SUVmean in lesion and normal liver tissue were 3.30 and 6.69 %. The average lesion-to-background contrast (detectability) with delayed PET images using CT AM was 60 % higher than that of the earlier PET image, and was 64 % higher when using the data-based AM. %DSUV for lesions and liver backgrounds with CT-based AM were - 0.058 ± 0.25 and - 0.33 ± 0.08 while with data-based AM were - 0.00 ± 0.26 and - 0.28 ± 0.08. Only slight significance difference was found between using CT-based AM and using the data-based AM reconstruction delay phase on %DSUV of lesion. The scores associated with the two AMs matched well consistently. Our method may be used in delayed PET imaging, which allows no secondary CT radiation in delayed phase. The quantitative analysis for lesion detection purpose could be ensured.

Estimation of glacier surface motion by robust phase correlation and point like features of SAR intensity images

NASA Astrophysics Data System (ADS)

Fang, Li; Xu, Yusheng; Yao, Wei; Stilla, Uwe

2016-11-01

For monitoring of glacier surface motion in pole and alpine areas, radar remote sensing is becoming a popular technology accounting for its specific advantages of being independent of weather conditions and sunlight. In this paper we propose a method for glacier surface motion monitoring using phase correlation (PC) based on point-like features (PLF). We carry out experiments using repeat-pass TerraSAR X-band (TSX) and Sentinel-1 C-band (S1C) intensity images of the Taku glacier in Juneau icefield located in southeast Alaska. The intensity imagery is first filtered by an improved adaptive refined Lee filter while the effect of topographic reliefs is removed via SRTM-X DEM. Then, a robust phase correlation algorithm based on singular value decomposition (SVD) and an improved random sample consensus (RANSAC) algorithm is applied to sequential PLF pairs generated by correlation using a 2D sinc function template. The approaches for glacier monitoring are validated by both simulated SAR data and real SAR data from two satellites. The results obtained from these three test datasets confirm the superiority of the proposed approach compared to standard correlation-like methods. By the use of the proposed adaptive refined Lee filter, we achieve a good balance between the suppression of noise and the preservation of local image textures. The presented phase correlation algorithm shows the accuracy of better than 0.25 pixels, when conducting matching tests using simulated SAR intensity images with strong noise. Quantitative 3D motions and velocities of the investigated Taku glacier during a repeat-pass period are obtained, which allows a comprehensive and reliable analysis for the investigation of large-scale glacier surface dynamics.

Evaluation of Existing Image Matching Methods for Deriving Glacier Surface Displacements Globally from Optical Satellite Imagery

NASA Astrophysics Data System (ADS)

Heid, T.; Kääb, A.

2011-12-01

Automatic matching of images from two different times is a method that is often used to derive glacier surface velocity. Nearly global repeat coverage of the Earth's surface by optical satellite sensors now opens the possibility for global-scale mapping and monitoring of glacier flow with a number of applications in, for example, glacier physics, glacier-related climate change and impact assessment, and glacier hazard management. The purpose of this study is to compare and evaluate different existing image matching methods for glacier flow determination over large scales. The study compares six different matching methods: normalized cross-correlation (NCC), the phase correlation algorithm used in the COSI-Corr software, and four other Fourier methods with different normalizations. We compare the methods over five regions of the world with different representative glacier characteristics: Karakoram, the European Alps, Alaska, Pine Island (Antarctica) and southwest Greenland. Landsat images are chosen for matching because they expand back to 1972, they cover large areas, and at the same time their spatial resolution is as good as 15 m for images after 1999 (ETM+ pan). Cross-correlation on orientation images (CCF-O) outperforms the three similar Fourier methods, both in areas with high and low visual contrast. NCC experiences problems in areas with low visual contrast, areas with thin clouds or changing snow conditions between the images. CCF-O has problems on narrow outlet glaciers where small window sizes (about 16 pixels by 16 pixels or smaller) are needed, and it also obtains fewer correct matches than COSI-Corr in areas with low visual contrast. COSI-Corr has problems on narrow outlet glaciers and it obtains fewer correct matches compared to CCF-O when thin clouds cover the surface, or if one of the images contains snow dunes. In total, we consider CCF-O and COSI-Corr to be the two most robust matching methods for global-scale mapping and monitoring of glacier velocities. If combining CCF-O with locally adaptive template sizes and by filtering the matching results automatically by comparing the displacement matrix to its low pass filtered version, the matching process can be automated to a large degree. This allows the derivation of glacier velocities with minimal (but not without!) user interaction and hence also opens up the possibility of global-scale mapping and monitoring of glacier flow.

High performance embedded system for real-time pattern matching

NASA Astrophysics Data System (ADS)

Sotiropoulou, C.-L.; Luciano, P.; Gkaitatzis, S.; Citraro, S.; Giannetti, P.; Dell'Orso, M.

2017-02-01

In this paper we present an innovative and high performance embedded system for real-time pattern matching. This system is based on the evolution of hardware and algorithms developed for the field of High Energy Physics and more specifically for the execution of extremely fast pattern matching for tracking of particles produced by proton-proton collisions in hadron collider experiments. A miniaturized version of this complex system is being developed for pattern matching in generic image processing applications. The system works as a contour identifier able to extract the salient features of an image. It is based on the principles of cognitive image processing, which means that it executes fast pattern matching and data reduction mimicking the operation of the human brain. The pattern matching can be executed by a custom designed Associative Memory chip. The reference patterns are chosen by a complex training algorithm implemented on an FPGA device. Post processing algorithms (e.g. pixel clustering) are also implemented on the FPGA. The pattern matching can be executed on a 2D or 3D space, on black and white or grayscale images, depending on the application and thus increasing exponentially the processing requirements of the system. We present the firmware implementation of the training and pattern matching algorithm, performance and results on a latest generation Xilinx Kintex Ultrascale FPGA device.

Retrieving quasi-phase-matching structure with discrete layer-peeling method.

PubMed

Zhang, Q W; Zeng, X L; Wang, M; Wang, T Y; Chen, X F

2012-07-02

An approach to reconstruct a quasi-phase-matching grating by using a discrete layer-peeling algorithm is presented. Experimentally measured output spectra of Šolc-type filters, based on uniform and chirped QPM structures, are used in the discrete layer-peeling algorithm. The reconstructed QPM structures are in agreement with the exact structures used in the experiment and the method is verified to be accurate and efficient in quality inspection on quasi-phase-matching grating.

Robust and efficient method for matching features in omnidirectional images

NASA Astrophysics Data System (ADS)

Zhu, Qinyi; Zhang, Zhijiang; Zeng, Dan

2018-04-01

Binary descriptors have been widely used in many real-time applications due to their efficiency. These descriptors are commonly designed for perspective images but perform poorly on omnidirectional images, which are severely distorted. To address this issue, this paper proposes tangent plane BRIEF (TPBRIEF) and adapted log polar grid-based motion statistics (ALPGMS). TPBRIEF projects keypoints to a unit sphere and applies the fixed test set in BRIEF descriptor on the tangent plane of the unit sphere. The fixed test set is then backprojected onto the original distorted images to construct the distortion invariant descriptor. TPBRIEF directly enables keypoint detecting and feature describing on original distorted images, whereas other approaches correct the distortion through image resampling, which introduces artifacts and adds time cost. With ALPGMS, omnidirectional images are divided into circular arches named adapted log polar grids. Whether a match is true or false is then determined by simply thresholding the match numbers in a grid pair where the two matched points located. Experiments show that TPBRIEF greatly improves the feature matching accuracy and ALPGMS robustly removes wrong matches. Our proposed method outperforms the state-of-the-art methods.

Image Mosaic Method Based on SIFT Features of Line Segment

PubMed Central

Zhu, Jun; Ren, Mingwu

2014-01-01

This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling. PMID:24511326

High-performance lighting evaluated by photobiological parameters.

PubMed

Rebec, Katja Malovrh; Gunde, Marta Klanjšek

2014-08-10

The human reception of light includes image-forming and non-image-forming effects which are triggered by spectral distribution and intensity of light. Ideal lighting is similar to daylight, which could be evaluated by spectral or chromaticity match. LED-based and CFL-based lighting were analyzed here, proposed according to spectral and chromaticity match, respectively. The photobiological effects were expressed by effectiveness for blue light hazard, cirtopic activity, and photopic vision. Good spectral match provides light with more similar effects to those obtained by the chromaticity match. The new parameters are useful for better evaluation of complex human responses caused by lighting.

Diagnostic workstation for digital hand atlas in bone age assessment

NASA Astrophysics Data System (ADS)

Cao, Fei; Huang, H. K.; Pietka, Ewa; Gilsanz, Vicente; Ominsky, Steven

1998-06-01

Bone age assessment by a radiological examination of a hand and wrist image is a procedure frequently performed in pediatric patients to evaluate growth disorders, determine growth potential in children and monitor therapy effects. The assessment method currently used in radiological diagnosis is based on atlas matching of the diagnosed hand image with the reference set of atlas patterns, which was developed in 1950s and is not fully applicable for children of today. We intent to implement a diagnostic workstation for creating a new reference set of clinically normal images which will serve as a digital atlas and can be used for a computer-assisted bone age assessment. In this paper, we present the initial data- collection and system setup phase of this five-year research program. We describe the system design, user interface implementation and software tool development for collection, visualization, management and processing of clinically normal hand and wrist images.

Femtowatt incoherent image conversion from mid-infrared light to near-infrared light

NASA Astrophysics Data System (ADS)

Huang, Nan; Liu, Hongjun; Wang, Zhaolu; Han, Jing; Zhang, Shuan

2017-03-01

We report on the experimental conversion imaging of an incoherent continuous-wave dim source from mid-infrared light to near-infrared light with a lowest input power of 31 femtowatt (fW). Incoherent mid-infrared images of light emission from a heat lamp bulb with an adjustable power supply at window wavelengths ranging from 2.9 µm to 3.5 µm are used for upconversion. The sum-frequency generation is realized in a laser cavity with the resonant wavelength of 1064 nm pumped by an LD at 806 nm built around a periodically poled lithium niobate (PPLN) crystal. The converted infrared image in the wavelength range ~785 nm with a resolution of about 120  ×  70 is low-noise detected using a silicon-based camera. By optimizing the system parameters, the upconversion quantum efficiency is predicted to be 28% for correctly polarized, on-axis and phase-matching light.

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.

Improving both imaging speed and spatial resolution in MR-guided neurosurgery

NASA Astrophysics Data System (ADS)

Liu, Haiying; Hall, Walter A.; Truwit, Charles L.

2002-05-01

A robust near real-time MRI based surgical guidance scheme has been developed and used in neurosurgical procedure performed in our combined 1.5 Tesla MR operating room. Because of the increased susceptibility difference in the area of surgical site during surgery, the preferred real- time imaging technique is a single shot imaging sequence based on the concept of the half acquisition with turbo spin echoes (HASTE). In order to maintain sufficient spatial resolution for visualizing the surgical devices, such as a biopsy needle and catheter, we used focused field of view (FOV) in the phase-encoding (PE) direction coupled with an out-volume signal suppression (OVS) technique. The key concept of the method is to minimize the total number of the required phase encoding steps and the effective echo time (TE) as well as the longest TE for the high spatial encoding step. The concept has been first demonstrated with a phantom experiment, which showed when the water was doped with Gd- DTPA to match the relaxation rates of the brain tissue there was a significant spatial blurring primarily along the phase encoding direction if the conventional HASTE technique, and the new scheme indeed minimized the spatial blur in the resulting image and improved the needle visualization as anticipated. Using the new scheme in a typical MR-guided neurobiopsy procedure, the brain biopsy needle was easily seen against the tissue background with minimal blurring due the inevitable T2 signal decay even when the PE direction was set parallel to the needle axis. This MR based guidance technique has practically allowed neurosurgeons to visualize the biopsy needle and to monitor its insertion with a better certainty at near real-time pace.

Matching forensic sketches to mug shot photos.

PubMed

Klare, Brendan F; Li, Zhifeng; Jain, Anil K

2011-03-01

The problem of matching a forensic sketch to a gallery of mug shot images is addressed in this paper. Previous research in sketch matching only offered solutions to matching highly accurate sketches that were drawn while looking at the subject (viewed sketches). Forensic sketches differ from viewed sketches in that they are drawn by a police sketch artist using the description of the subject provided by an eyewitness. To identify forensic sketches, we present a framework called local feature-based discriminant analysis (LFDA). In LFDA, we individually represent both sketches and photos using SIFT feature descriptors and multiscale local binary patterns (MLBP). Multiple discriminant projections are then used on partitioned vectors of the feature-based representation for minimum distance matching. We apply this method to match a data set of 159 forensic sketches against a mug shot gallery containing 10,159 images. Compared to a leading commercial face recognition system, LFDA offers substantial improvements in matching forensic sketches to the corresponding face images. We were able to further improve the matching performance using race and gender information to reduce the target gallery size. Additional experiments demonstrate that the proposed framework leads to state-of-the-art accuracys when matching viewed sketches.

Binocular stereo matching method based on structure tensor

NASA Astrophysics Data System (ADS)

Song, Xiaowei; Yang, Manyi; Fan, Yubo; Yang, Lei

2016-10-01

In a binocular visual system, to recover the three-dimensional information of the object, the most important step is to acquire matching points. Structure tensor is the vector representation of each point in its local neighborhood. Therefore, structure tensor performs well in region detection of local structure, and it is very suitable for detecting specific graphics such as pedestrians, cars and road signs in the image. In this paper, the structure tensor is combined with the luminance information to form the extended structure tensor. The directional derivatives of luminance in x and y directions are calculated, so that the local structure of the image is more prominent. Meanwhile, the Euclidean distance between the eigenvectors of key points is used as the similarity determination metric of key points in the two images. By matching, the coordinates of the matching points in the detected target are precisely acquired. In this paper, experiments were performed on the captured left and right images. After the binocular calibration, image matching was done to acquire the matching points, and then the target depth was calculated according to these matching points. By comparison, it is proved that the structure tensor can accurately acquire the matching points in binocular stereo matching.

Deblurring traffic sign images based on exemplars

PubMed Central

Qiu, Tianshuang; Luan, Shengyang; Song, Haiyu; Wu, Linxiu

2018-01-01

Motion blur appearing in traffic sign images may lead to poor recognition results, and therefore it is of great significance to study how to deblur the images. In this paper, a novel method for deblurring traffic sign is proposed based on exemplars and several related approaches are also made. First, an exemplar dataset construction method is proposed based on multiple-size partition strategy to lower calculation cost of exemplar matching. Second, a matching criterion based on gradient information and entropy correlation coefficient is also proposed to enhance the matching accuracy. Third, L0.5-norm is introduced as the regularization item to maintain the sparsity of blur kernel. Experiments verify the superiority of the proposed approaches and extensive evaluations against state-of-the-art methods demonstrate the effectiveness of the proposed algorithm. PMID:29513677

Modeling respiratory motion for reducing motion artifacts in 4D CT images.

PubMed

Zhang, Yongbin; Yang, Jinzhong; Zhang, Lifei; Court, Laurence E; Balter, Peter A; Dong, Lei

2013-04-01

Four-dimensional computed tomography (4D CT) images have been recently adopted in radiation treatment planning for thoracic and abdominal cancers to explicitly define respiratory motion and anatomy deformation. However, significant image distortions (artifacts) exist in 4D CT images that may affect accurate tumor delineation and the shape representation of normal anatomy. In this study, the authors present a patient-specific respiratory motion model, based on principal component analysis (PCA) of motion vectors obtained from deformable image registration, with the main goal of reducing image artifacts caused by irregular motion during 4D CT acquisition. For a 4D CT image set of a specific patient, the authors calculated displacement vector fields relative to a reference phase, using an in-house deformable image registration method. The authors then used PCA to decompose each of the displacement vector fields into linear combinations of principal motion bases. The authors have demonstrated that the regular respiratory motion of a patient can be accurately represented by a subspace spanned by three principal motion bases and their projections. These projections were parameterized using a spline model to allow the reconstruction of the displacement vector fields at any given phase in a respiratory cycle. Finally, the displacement vector fields were used to deform the reference CT image to synthesize CT images at the selected phase with much reduced image artifacts. The authors evaluated the performance of the in-house deformable image registration method using benchmark datasets consisting of ten 4D CT sets annotated with 300 landmark pairs that were approved by physicians. The initial large discrepancies across the landmark pairs were significantly reduced after deformable registration, and the accuracy was similar to or better than that reported by state-of-the-art methods. The proposed motion model was quantitatively validated on 4D CT images of a phantom and a lung cancer patient by comparing the synthesized images and the original images at different phases. The synthesized images matched well with the original images. The motion model was used to reduce irregular motion artifacts in the 4D CT images of three lung cancer patients. Visual assessment indicated that the proposed approach could reduce severe image artifacts. The shape distortions around the diaphragm and tumor regions were mitigated in the synthesized 4D CT images. The authors have derived a mathematical model to represent the regular respiratory motion from a patient-specific 4D CT set and have demonstrated its application in reducing irregular motion artifacts in 4D CT images. The authors' approach can mitigate shape distortions of anatomy caused by irregular breathing motion during 4D CT acquisition.

Accuracy of DSM based on digital aerial image matching. (Polish Title: Dokładność NMPT tworzonego metodą automatycznego dopasowania cyfrowych zdjęć lotniczych)

NASA Astrophysics Data System (ADS)

Kubalska, J. L.; Preuss, R.

2013-12-01

Digital Surface Models (DSM) are used in GIS data bases as single product more often. They are also necessary to create other products such as3D city models, true-ortho and object-oriented classification. This article presents results of DSM generation for classification of vegetation in urban areas. Source data allowed producing DSM with using of image matching method and ALS data. The creation of DSM from digital images, obtained by Ultra Cam-D digital Vexcel camera, was carried out in Match-T by INPHO. This program optimizes the configuration of images matching process, which ensures high accuracy and minimize gap areas. The analysis of the accuracy of this process was made by comparison of DSM generated in Match-T with DSM generated from ALS data. Because of further purpose of generated DSM it was decided to create model in GRID structure with cell size of 1 m. With this parameter differential model from both DSMs was also built that allowed determining the relative accuracy of the compared models. The analysis indicates that the generation of DSM with multi-image matching method is competitive for the same surface model creation from ALS data. Thus, when digital images with high overlap are available, the additional registration of ALS data seems to be unnecessary.

Phase-matched generation of coherent soft and hard X-rays using IR lasers

DOEpatents

Popmintchev, Tenio V.; Chen, Ming-Chang; Bahabad, Alon; Murnane, Margaret M.; Kapteyn, Henry C.

2013-06-11

Phase-matched high-order harmonic generation of soft and hard X-rays is accomplished using infrared driving lasers in a high-pressure non-linear medium. The pressure of the non-linear medium is increased to multi-atmospheres and a mid-IR (or higher) laser device provides the driving pulse. Based on this scaling, also a general method for global optimization of the flux of phase-matched high-order harmonic generation at a desired wavelength is designed.

Fizeau simultaneous phase-shifting interferometry based on extended source

NASA Astrophysics Data System (ADS)

Wang, Shanshan; Zhu, Qiudong; Hou, Yinlong; Cao, Zheng

2016-09-01

Coaxial Fizeau simultaneous phase-shifting interferometer plays an important role in many fields for its characteristics of long optical path, miniaturization, and elimination of reference surface high-frequency error. Based on the matching of coherence between extended source and interferometer, orthogonal polarization reference wave and measurement wave can be obtained by Fizeau interferometry with Michelson interferometer preposed. Through matching spatial coherence length between preposed interferometer and primary interferometer, high contrast interference fringes can be obtained and additional interference fringes can be eliminated. Thus, the problem of separation of measurement and reference surface in the common optical path Fizeau interferometer is solved. Numerical simulation and principle experiment is conducted to verify the feasibility of extended source interferometer. Simulation platform is established by using the communication technique of DDE (dynamic data exchange) to connect Zemax and Matlab. The modeling of the extended source interferometer is realized by using Zemax. Matlab codes are programmed to automatically rectify the field parameters of the optical system and conveniently calculate the visibility of interference fringes. Combined with the simulation, the experimental platform of the extended source interferometer is established. After experimental research on the influence law of scattering screen granularity to interference fringes, the granularity of scattering screen is determined. Based on the simulation platform and experimental platform, the impacts on phase measurement accuracy of the imaging system aberration and collimation system aberration of the interferometer are analyzed. Compared the visibility relation curves between experimental measurement and simulation result, the experimental result is in line with the theoretical result.

Inverse consistent non-rigid image registration based on robust point set matching

PubMed Central

2014-01-01

Background Robust point matching (RPM) has been extensively used in non-rigid registration of images to robustly register two sets of image points. However, except for the location at control points, RPM cannot estimate the consistent correspondence between two images because RPM is a unidirectional image matching approach. Therefore, it is an important issue to make an improvement in image registration based on RPM. Methods In our work, a consistent image registration approach based on the point sets matching is proposed to incorporate the property of inverse consistency and improve registration accuracy. Instead of only estimating the forward transformation between the source point sets and the target point sets in state-of-the-art RPM algorithms, the forward and backward transformations between two point sets are estimated concurrently in our algorithm. The inverse consistency constraints are introduced to the cost function of RPM and the fuzzy correspondences between two point sets are estimated based on both the forward and backward transformations simultaneously. A modified consistent landmark thin-plate spline registration is discussed in detail to find the forward and backward transformations during the optimization of RPM. The similarity of image content is also incorporated into point matching in order to improve image matching. Results Synthetic data sets, medical images are employed to demonstrate and validate the performance of our approach. The inverse consistent errors of our algorithm are smaller than RPM. Especially, the topology of transformations is preserved well for our algorithm for the large deformation between point sets. Moreover, the distance errors of our algorithm are similar to that of RPM, and they maintain a downward trend as whole, which demonstrates the convergence of our algorithm. The registration errors for image registrations are evaluated also. Again, our algorithm achieves the lower registration errors in same iteration number. The determinant of the Jacobian matrix of the deformation field is used to analyse the smoothness of the forward and backward transformations. The forward and backward transformations estimated by our algorithm are smooth for small deformation. For registration of lung slices and individual brain slices, large or small determinant of the Jacobian matrix of the deformation fields are observed. Conclusions Results indicate the improvement of the proposed algorithm in bi-directional image registration and the decrease of the inverse consistent errors of the forward and the reverse transformations between two images. PMID:25559889

Integration of SAR and AIS for ship detection and identification

NASA Astrophysics Data System (ADS)

Yang, Chan-Su; Kim, Tae-Ho

2012-06-01

This abstract describes the preliminary design concept for an integration system of SAR and AIS data. SAR sensors are used to acquire image data over large coverage area either through the space borne or airborne platforms in UTC. AIS reports should also obtained on the same date as of the SAR acquisition for the purpose to perform integration test. Once both data reports are obtained, one need to match the timings of AIS data acquisition over the SAR image acquisition time with consideration of local time & boundary to extract the closest time signal from AIS report in order to know the AIS based ship positions, but still one cannot be able to distinguish which ships have the AIS transponder after projection of AIS based position onto the SAR image acquisition boundary. As far as integration is concerned, the ship dead-reckoning concept is most important forecasted position which provides the AIS based ship position at the time of SAR image acquisition and also provides the hints for azimuth shift which occurred in SAR image for the case of moving ships which moves in the direction perpendicular to the direction of flight path. Unknown ship's DR estimation is to be carried out based on the initial positions, speed and course over ground, which has already been shorted out from AIS reports, during the step of time matching. This DR based ship's position will be the candidate element for searching the SAR based ship targets for the purpose of identification & matching within the certain boundary around DR. The searching method is performed by means of estimation of minimum distance from ship's DR to SAR based ship position, and once it determines, so the candidate element will look for matching like ship size match of DR based ship's dimension wrt SAR based ship's edge, there may be some error during the matching with SAR based ship edges with actual ship's hull design as per the longitudinal and transverse axis size information obtained from the AIS reports due to blurring effect in SAR based ship signatures, once the conditions are satisfied, candidate element will move & shift over the SAR based ship signature target with the minimum displacement and it is known to be the azimuth shift compensation and this overall methodology are known to be integration of AIS report data over the SAR image acquisition boundary with assessment of time matching. The expected result may provide the good accuracy of the SAR and AIS contact position along with dimension and classification of ships over SAR image. There may be possibilities of matching speed and course from candidate element with SAR based ship signature, but still the challenges are presents in front of us that to estimation of speed and course by means of SAR data, if it may be possible so the expected final result may be more accurate as due to extra matching effects and the results may be used for the near real time performance for ship identification with help of integrated system design based on SAR and AIS data reports.

Reconstructing the microstructure of polyimide-silicalite mixed-matrix membranes and their particle connectivity using FIB-SEM tomography.

PubMed

Diblíková, P; Veselý, M; Sysel, P; Čapek, P

2018-03-01

Properties of a composite material made of a continuous matrix and particles often depend on microscopic details, such as contacts between particles. Focusing on processing raw focused-ion beam scanning electron microscope (FIB-SEM) tomography data, we reconstructed three mixed-matrix membrane samples made of 6FDA-ODA polyimide and silicalite-1 particles. In the first step of image processing, backscattered electron (BSE) and secondary electron (SE) signals were mixed in a ratio that was expected to obtain a segmented 3D image with a realistic volume fraction of silicalite-1. Second, after spatial alignment of the stacked FIB-SEM data, the 3D image was smoothed using adaptive median and anisotropic nonlinear diffusion filters. Third, the image was segmented using the power watershed method coupled with a seeding algorithm based on geodesic reconstruction from the markers. If the resulting volume fraction did not match the target value quantified by chemical analysis of the sample, the BSE and SE signals were mixed in another ratio and the procedure was repeated until the target volume fraction was achieved. Otherwise, the segmented 3D image (replica) was accepted and its microstructure was thoroughly characterized with special attention paid to connectivity of the silicalite phase. In terms of the phase connectivity, Monte Carlo simulations based on the pure-phase permeability values enabled us to calculate the effective permeability tensor, the main diagonal elements of which were compared with the experimental permeability. In line with the hypothesis proposed in our recent paper (Čapek, P. et al. (2014) Comput. Mater. Sci. 89, 142-156), the results confirmed that the existence of particle clusters was a key microstructural feature determining effective permeability. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Nonuniformity correction for an infrared focal plane array based on diamond search block matching.

PubMed

Sheng-Hui, Rong; Hui-Xin, Zhou; Han-Lin, Qin; Rui, Lai; Kun, Qian

2016-05-01

In scene-based nonuniformity correction algorithms, artificial ghosting and image blurring degrade the correction quality severely. In this paper, an improved algorithm based on the diamond search block matching algorithm and the adaptive learning rate is proposed. First, accurate transform pairs between two adjacent frames are estimated by the diamond search block matching algorithm. Then, based on the error between the corresponding transform pairs, the gradient descent algorithm is applied to update correction parameters. During the process of gradient descent, the local standard deviation and a threshold are utilized to control the learning rate to avoid the accumulation of matching error. Finally, the nonuniformity correction would be realized by a linear model with updated correction parameters. The performance of the proposed algorithm is thoroughly studied with four real infrared image sequences. Experimental results indicate that the proposed algorithm can reduce the nonuniformity with less ghosting artifacts in moving areas and can also overcome the problem of image blurring in static areas.

Visual navigation using edge curve matching for pinpoint planetary landing

NASA Astrophysics Data System (ADS)

Cui, Pingyuan; Gao, Xizhen; Zhu, Shengying; Shao, Wei

2018-05-01

Pinpoint landing is challenging for future Mars and asteroid exploration missions. Vision-based navigation scheme based on feature detection and matching is practical and can achieve the required precision. However, existing algorithms are computationally prohibitive and utilize poor-performance measurements, which pose great challenges for the application of visual navigation. This paper proposes an innovative visual navigation scheme using crater edge curves during descent and landing phase. In the algorithm, the edge curves of the craters tracked from two sequential images are utilized to determine the relative attitude and position of the lander through a normalized method. Then, considering error accumulation of relative navigation, a method is developed. That is to integrate the crater-based relative navigation method with crater-based absolute navigation method that identifies craters using a georeferenced database for continuous estimation of absolute states. In addition, expressions of the relative state estimate bias are derived. Novel necessary and sufficient observability criteria based on error analysis are provided to improve the navigation performance, which hold true for similar navigation systems. Simulation results demonstrate the effectiveness and high accuracy of the proposed navigation method.

Comparison of photo-matching algorithms commonly used for photographic capture-recapture studies.

PubMed

Matthé, Maximilian; Sannolo, Marco; Winiarski, Kristopher; Spitzen-van der Sluijs, Annemarieke; Goedbloed, Daniel; Steinfartz, Sebastian; Stachow, Ulrich

2017-08-01

Photographic capture-recapture is a valuable tool for obtaining demographic information on wildlife populations due to its noninvasive nature and cost-effectiveness. Recently, several computer-aided photo-matching algorithms have been developed to more efficiently match images of unique individuals in databases with thousands of images. However, the identification accuracy of these algorithms can severely bias estimates of vital rates and population size. Therefore, it is important to understand the performance and limitations of state-of-the-art photo-matching algorithms prior to implementation in capture-recapture studies involving possibly thousands of images. Here, we compared the performance of four photo-matching algorithms; Wild-ID, I3S Pattern+, APHIS, and AmphIdent using multiple amphibian databases of varying image quality. We measured the performance of each algorithm and evaluated the performance in relation to database size and the number of matching images in the database. We found that algorithm performance differed greatly by algorithm and image database, with recognition rates ranging from 100% to 22.6% when limiting the review to the 10 highest ranking images. We found that recognition rate degraded marginally with increased database size and could be improved considerably with a higher number of matching images in the database. In our study, the pixel-based algorithm of AmphIdent exhibited superior recognition rates compared to the other approaches. We recommend carefully evaluating algorithm performance prior to using it to match a complete database. By choosing a suitable matching algorithm, databases of sizes that are unfeasible to match "by eye" can be easily translated to accurate individual capture histories necessary for robust demographic estimates.

Uniform competency-based local feature extraction for remote sensing images

NASA Astrophysics Data System (ADS)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

Efficient linear phase contrast in scanning transmission electron microscopy with matched illumination and detector interferometry

DOE PAGES

Ophus, Colin; Ciston, Jim; Pierce, Jordan; ...

2016-02-29

The ability to image light elements in soft matter at atomic resolution enables unprecedented insight into the structure and properties of molecular heterostructures and beam-sensitive nanomaterials. In this study, we introduce a scanning transmission electron microscopy technique combining a pre-specimen phase plate designed to produce a probe with structured phase with a high-speed direct electron detector to generate nearly linear contrast images with high efficiency. We demonstrate this method by using both experiment and simulation to simultaneously image the atomic-scale structure of weakly scattering amorphous carbon and strongly scattering gold nanoparticles. Our method demonstrates strong contrast for both materials, makingmore » it a promising candidate for structural determination of heterogeneous soft/hard matter samples even at low electron doses comparable to traditional phase-contrast transmission electron microscopy. Ultimately, simulated images demonstrate the extension of this technique to the challenging problem of structural determination of biological material at the surface of inorganic crystals.« less

Efficient linear phase contrast in scanning transmission electron microscopy with matched illumination and detector interferometry.

PubMed

Ophus, Colin; Ciston, Jim; Pierce, Jordan; Harvey, Tyler R; Chess, Jordan; McMorran, Benjamin J; Czarnik, Cory; Rose, Harald H; Ercius, Peter

2016-02-29

The ability to image light elements in soft matter at atomic resolution enables unprecedented insight into the structure and properties of molecular heterostructures and beam-sensitive nanomaterials. In this study, we introduce a scanning transmission electron microscopy technique combining a pre-specimen phase plate designed to produce a probe with structured phase with a high-speed direct electron detector to generate nearly linear contrast images with high efficiency. We demonstrate this method by using both experiment and simulation to simultaneously image the atomic-scale structure of weakly scattering amorphous carbon and strongly scattering gold nanoparticles. Our method demonstrates strong contrast for both materials, making it a promising candidate for structural determination of heterogeneous soft/hard matter samples even at low electron doses comparable to traditional phase-contrast transmission electron microscopy. Simulated images demonstrate the extension of this technique to the challenging problem of structural determination of biological material at the surface of inorganic crystals.

Efficient linear phase contrast in scanning transmission electron microscopy with matched illumination and detector interferometry

PubMed Central

Ophus, Colin; Ciston, Jim; Pierce, Jordan; Harvey, Tyler R.; Chess, Jordan; McMorran, Benjamin J.; Czarnik, Cory; Rose, Harald H.; Ercius, Peter

2016-01-01

The ability to image light elements in soft matter at atomic resolution enables unprecedented insight into the structure and properties of molecular heterostructures and beam-sensitive nanomaterials. In this study, we introduce a scanning transmission electron microscopy technique combining a pre-specimen phase plate designed to produce a probe with structured phase with a high-speed direct electron detector to generate nearly linear contrast images with high efficiency. We demonstrate this method by using both experiment and simulation to simultaneously image the atomic-scale structure of weakly scattering amorphous carbon and strongly scattering gold nanoparticles. Our method demonstrates strong contrast for both materials, making it a promising candidate for structural determination of heterogeneous soft/hard matter samples even at low electron doses comparable to traditional phase-contrast transmission electron microscopy. Simulated images demonstrate the extension of this technique to the challenging problem of structural determination of biological material at the surface of inorganic crystals. PMID:26923483

QWT: Retrospective and New Applications

NASA Astrophysics Data System (ADS)

Xu, Yi; Yang, Xiaokang; Song, Li; Traversoni, Leonardo; Lu, Wei

Quaternion wavelet transform (QWT) achieves much attention in recent years as a new image analysis tool. In most cases, it is an extension of the real wavelet transform and complex wavelet transform (CWT) by using the quaternion algebra and the 2D Hilbert transform of filter theory, where analytic signal representation is desirable to retrieve phase-magnitude description of intrinsically 2D geometric structures in a grayscale image. In the context of color image processing, however, it is adapted to analyze the image pattern and color information as a whole unit by mapping sequential color pixels to a quaternion-valued vector signal. This paper provides a retrospective of QWT and investigates its potential use in the domain of image registration, image fusion, and color image recognition. It is indicated that it is important for QWT to induce the mechanism of adaptive scale representation of geometric features, which is further clarified through two application instances of uncalibrated stereo matching and optical flow estimation. Moreover, quaternionic phase congruency model is defined based on analytic signal representation so as to operate as an invariant feature detector for image registration. To achieve better localization of edges and textures in image fusion task, we incorporate directional filter bank (DFB) into the quaternion wavelet decomposition scheme to greatly enhance the direction selectivity and anisotropy of QWT. Finally, the strong potential use of QWT in color image recognition is materialized in a chromatic face recognition system by establishing invariant color features. Extensive experimental results are presented to highlight the exciting properties of QWT.

Supervised learning of tools for content-based search of image databases

NASA Astrophysics Data System (ADS)

Delanoy, Richard L.

1996-03-01

A computer environment, called the Toolkit for Image Mining (TIM), is being developed with the goal of enabling users with diverse interests and varied computer skills to create search tools for content-based image retrieval and other pattern matching tasks. Search tools are generated using a simple paradigm of supervised learning that is based on the user pointing at mistakes of classification made by the current search tool. As mistakes are identified, a learning algorithm uses the identified mistakes to build up a model of the user's intentions, construct a new search tool, apply the search tool to a test image, display the match results as feedback to the user, and accept new inputs from the user. Search tools are constructed in the form of functional templates, which are generalized matched filters capable of knowledge- based image processing. The ability of this system to learn the user's intentions from experience contrasts with other existing approaches to content-based image retrieval that base searches on the characteristics of a single input example or on a predefined and semantically- constrained textual query. Currently, TIM is capable of learning spectral and textural patterns, but should be adaptable to the learning of shapes, as well. Possible applications of TIM include not only content-based image retrieval, but also quantitative image analysis, the generation of metadata for annotating images, data prioritization or data reduction in bandwidth-limited situations, and the construction of components for larger, more complex computer vision algorithms.

Cross-matching: a modified cross-correlation underlying threshold energy model and match-based depth perception

PubMed Central

Doi, Takahiro; Fujita, Ichiro

2014-01-01

Three-dimensional visual perception requires correct matching of images projected to the left and right eyes. The matching process is faced with an ambiguity: part of one eye's image can be matched to multiple parts of the other eye's image. This stereo correspondence problem is complicated for random-dot stereograms (RDSs), because dots with an identical appearance produce numerous potential matches. Despite such complexity, human subjects can perceive a coherent depth structure. A coherent solution to the correspondence problem does not exist for anticorrelated RDSs (aRDSs), in which luminance contrast is reversed in one eye. Neurons in the visual cortex reduce disparity selectivity for aRDSs progressively along the visual processing hierarchy. A disparity-energy model followed by threshold nonlinearity (threshold energy model) can account for this reduction, providing a possible mechanism for the neural matching process. However, the essential computation underlying the threshold energy model is not clear. Here, we propose that a nonlinear modification of cross-correlation, which we term “cross-matching,” represents the essence of the threshold energy model. We placed half-wave rectification within the cross-correlation of the left-eye and right-eye images. The disparity tuning derived from cross-matching was attenuated for aRDSs. We simulated a psychometric curve as a function of graded anticorrelation (graded mixture of aRDS and normal RDS); this simulated curve reproduced the match-based psychometric function observed in human near/far discrimination. The dot density was 25% for both simulation and observation. We predicted that as the dot density increased, the performance for aRDSs should decrease below chance (i.e., reversed depth), and the level of anticorrelation that nullifies depth perception should also decrease. We suggest that cross-matching serves as a simple computation underlying the match-based disparity signals in stereoscopic depth perception. PMID:25360107

An improved finger-vein recognition algorithm based on template matching

NASA Astrophysics Data System (ADS)

Liu, Yueyue; Di, Si; Jin, Jian; Huang, Daoping

2016-10-01

Finger-vein recognition has became the most popular biometric identify methods. The investigation on the recognition algorithms always is the key point in this field. So far, there are many applicable algorithms have been developed. However, there are still some problems in practice, such as the variance of the finger position which may lead to the image distortion and shifting; during the identification process, some matching parameters determined according to experience may also reduce the adaptability of algorithm. Focus on above mentioned problems, this paper proposes an improved finger-vein recognition algorithm based on template matching. In order to enhance the robustness of the algorithm for the image distortion, the least squares error method is adopted to correct the oblique finger. During the feature extraction, local adaptive threshold method is adopted. As regard as the matching scores, we optimized the translation preferences as well as matching distance between the input images and register images on the basis of Naoto Miura algorithm. Experimental results indicate that the proposed method can improve the robustness effectively under the finger shifting and rotation conditions.

Monocular correspondence detection for symmetrical objects by template matching

NASA Astrophysics Data System (ADS)

Vilmar, G.; Besslich, Philipp W., Jr.

1990-09-01

We describe a possibility to reconstruct 3-D information from a single view of an 3-D bilateral symmetric object. The symmetry assumption allows us to obtain a " second view" from a different viewpoint by a simple reflection of the monocular image. Therefore we have to solve the correspondence problem in a special case where known feature-based or area-based binocular approaches fail. In principle our approach is based on a frequency domain template matching of the features on the epipolar lines. During a training period our system " learns" the assignment of correspondence models to image features. The object shape is interpolated when no template matches to the image features. This fact is an important advantage of this methodology because no " real world" image holds the symmetry assumption perfectly. To simplify the training process we used single views on human faces (e. g. passport photos) but our system is trainable on any other kind of objects.

Improved photo response non-uniformity (PRNU) based source camera identification.

PubMed

Cooper, Alan J

2013-03-10

The concept of using Photo Response Non-Uniformity (PRNU) as a reliable forensic tool to match an image to a source camera is now well established. Traditionally, the PRNU estimation methodologies have centred on a wavelet based de-noising approach. Resultant filtering artefacts in combination with image and JPEG contamination act to reduce the quality of PRNU estimation. In this paper, it is argued that the application calls for a simplified filtering strategy which at its base level may be realised using a combination of adaptive and median filtering applied in the spatial domain. The proposed filtering method is interlinked with a further two stage enhancement strategy where only pixels in the image having high probabilities of significant PRNU bias are retained. This methodology significantly improves the discrimination between matching and non-matching image data sets over that of the common wavelet filtering approach. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Broadband Phase Retrieval for Image-Based Wavefront Sensing

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A focus-diverse phase-retrieval algorithm has been shown to perform adequately for the purpose of image-based wavefront sensing when (1) broadband light (typically spanning the visible spectrum) is used in forming the images by use of an optical system under test and (2) the assumption of monochromaticity is applied to the broadband image data. Heretofore, it had been assumed that in order to obtain adequate performance, it is necessary to use narrowband or monochromatic light. Some background information, including definitions of terms and a brief description of pertinent aspects of image-based phase retrieval, is prerequisite to a meaningful summary of the present development. Phase retrieval is a general term used in optics to denote estimation of optical imperfections or aberrations of an optical system under test. The term image-based wavefront sensing refers to a general class of algorithms that recover optical phase information, and phase-retrieval algorithms constitute a subset of this class. In phase retrieval, one utilizes the measured response of the optical system under test to produce a phase estimate. The optical response of the system is defined as the image of a point-source object, which could be a star or a laboratory point source. The phase-retrieval problem is characterized as image-based in the sense that a charge-coupled-device camera, preferably of scientific imaging quality, is used to collect image data where the optical system would normally form an image. In a variant of phase retrieval, denoted phase-diverse phase retrieval [which can include focus-diverse phase retrieval (in which various defocus planes are used)], an additional known aberration (or an equivalent diversity function) is superimposed as an aid in estimating unknown aberrations by use of an image-based wavefront-sensing algorithm. Image-based phase-retrieval differs from such other wavefront-sensing methods, such as interferometry, shearing interferometry, curvature wavefront sensing, and Shack-Hartmann sensing, all of which entail disadvantages in comparison with image-based methods. The main disadvantages of these non-image based methods are complexity of test equipment and the need for a wavefront reference.

Using image mapping towards biomedical and biological data sharing

PubMed Central

2013-01-01

Image-based data integration in eHealth and life sciences is typically concerned with the method used for anatomical space mapping, needed to retrieve, compare and analyse large volumes of biomedical data. In mapping one image onto another image, a mechanism is used to match and find the corresponding spatial regions which have the same meaning between the source and the matching image. Image-based data integration is useful for integrating data of various information structures. Here we discuss a broad range of issues related to data integration of various information structures, review exemplary work on image representation and mapping, and discuss the challenges that these techniques may bring. PMID:24059352

Detection of Objects Hidden in Highly Scattering Media Using Time-Gated Imaging Methods

NASA Technical Reports Server (NTRS)

Galland, Pierre A.; Wang, L.; Liang, X.; Ho, P. P.; Alfano, R. R.

2000-01-01

Non-intrusive and non-invasive optical imaging techniques has generated great interest among researchers for their potential applications to biological study, device characterization, surface defect detection, and jet fuel dynamics. Non-linear optical parametric amplification gate (NLOPG) has been used to detect back-scattered images of objects hidden in diluted Intralipid solutions. To directly detect objects hidden in highly scattering media, the diffusive component of light needs to be sorted out from early arrived ballistic and snake photons. In an optical imaging system, images are collected in transmission or back-scattered geometry. The early arrival photons in the transmission approach, always carry the direct information of the hidden object embedded in the turbid medium. In the back-scattered approach, the result is not so forth coming. In the presence of a scattering host, the first arrival photons in back-scattered approach will be directly photons from the host material. In the presentation, NLOPG was applied to acquire time resolved back-scattered images under the phase matching condition. A time-gated amplified signal was obtained through this NLOPG process. The system's gain was approximately 100 times. The time-gate was achieved through phase matching condition where only coherent photons retain their phase. As a result, the diffusive photons, which were the primary contributor to the background, were removed. With a large dynamic range and high resolution, time-gated early light imaging has the potential for improving rocket/aircraft design by determining jets shape and particle sizes. Refinements to these techniques may enable drop size measurements in the highly scattering, optically dense region of multi-element rocket injectors. These types of measurements should greatly enhance the design of stable, and higher performing rocket engines.

Matching Real and Synthetic Panoramic Images Using a Variant of Geometric Hashing

NASA Astrophysics Data System (ADS)

Li-Chee-Ming, J.; Armenakis, C.

2017-05-01

This work demonstrates an approach to automatically initialize a visual model-based tracker, and recover from lost tracking, without prior camera pose information. These approaches are commonly referred to as tracking-by-detection. Previous tracking-by-detection techniques used either fiducials (i.e. landmarks or markers) or the object's texture. The main contribution of this work is the development of a tracking-by-detection algorithm that is based solely on natural geometric features. A variant of geometric hashing, a model-to-image registration algorithm, is proposed that searches for a matching panoramic image from a database of synthetic panoramic images captured in a 3D virtual environment. The approach identifies corresponding features between the matched panoramic images. The corresponding features are to be used in a photogrammetric space resection to estimate the camera pose. The experiments apply this algorithm to initialize a model-based tracker in an indoor environment using the 3D CAD model of the building.

Feasibility of using single photon counting X-ray for lung tumor position estimation based on 4D-CT.

PubMed

Aschenbrenner, Katharina P; Guthier, Christian V; Lyatskaya, Yulia; Boda-Heggemann, Judit; Wenz, Frederik; Hesser, Jürgen W

2017-09-01

In stereotactic body radiation therapy of lung tumors, reliable position estimation of the tumor is necessary in order to minimize normal tissue complication rate. While kV X-ray imaging is frequently used, continuous application during radiotherapy sessions is often not possible due to concerns about the additional dose. Thus, ultra low-dose (ULD) kV X-ray imaging based on a single photon counting detector is suggested. This paper addresses the lower limit of photons to locate the tumor reliably with an accuracy in the range of state-of-the-art methods, i.e. a few millimeters. 18 patient cases with four dimensional CT (4D-CT), which serves as a-priori information, are included in the study. ULD cone beam projections are simulated from the 4D-CTs including Poisson noise. The projections from the breathing phases which correspond to different tumor positions are compared to the ULD projection by means of Poisson log-likelihood (PML) and correlation coefficient (CC), and template matching under these metrics. The results indicate that in full thorax imaging five photons per pixel suffice for a standard deviation in tumor positions of less than half a breathing phase. Around 50 photons per pixel are needed to achieve this accuracy with the field of view restricted to the tumor region. Compared to CC, PML tends to perform better for low photon counts and shifts in patient setup. Template matching only improves the position estimation in high photon counts. The quality of the reconstruction is independent of the projection angle. The accuracy of the proposed ULD single photon counting system is in the range of a few millimeters and therefore comparable to state-of-the-art tumor tracking methods. At the same time, a reduction in photons per pixel by three to four orders of magnitude relative to commercial systems with flatpanel detectors can be achieved. This enables continuous kV image-based position estimation during all fractions since the additional dose to the patient is negligible. Copyright © 2017. Published by Elsevier GmbH.

A new approach for automatic matching of ground control points in urban areas from heterogeneous images

NASA Astrophysics Data System (ADS)

Cong, Chao; Liu, Dingsheng; Zhao, Lingjun

2008-12-01

This paper discusses a new method for the automatic matching of ground control points (GCPs) between satellite remote sensing Image and digital raster graphic (DRG) in urban areas. The key of this method is to automatically extract tie point pairs according to geographic characters from such heterogeneous images. Since there are big differences between such heterogeneous images respect to texture and corner features, more detail analyzations are performed to find similarities and differences between high resolution remote sensing Image and (DRG). Furthermore a new algorithms based on the fuzzy-c means (FCM) method is proposed to extract linear feature in remote sensing Image. Based on linear feature, crossings and corners extracted from these features are chosen as GCPs. On the other hand, similar method was used to find same features from DRGs. Finally, Hausdorff Distance was adopted to pick matching GCPs from above two GCP groups. Experiences shown the method can extract GCPs from such images with a reasonable RMS error.

Deformed Palmprint Matching Based on Stable Regions.

PubMed

Wu, Xiangqian; Zhao, Qiushi

2015-12-01

Palmprint recognition (PR) is an effective technology for personal recognition. A main problem, which deteriorates the performance of PR, is the deformations of palmprint images. This problem becomes more severe on contactless occasions, in which images are acquired without any guiding mechanisms, and hence critically limits the applications of PR. To solve the deformation problems, in this paper, a model for non-linearly deformed palmprint matching is derived by approximating non-linear deformed palmprint images with piecewise-linear deformed stable regions. Based on this model, a novel approach for deformed palmprint matching, named key point-based block growing (KPBG), is proposed. In KPBG, an iterative M-estimator sample consensus algorithm based on scale invariant feature transform features is devised to compute piecewise-linear transformations to approximate the non-linear deformations of palmprints, and then, the stable regions complying with the linear transformations are decided using a block growing algorithm. Palmprint feature extraction and matching are performed over these stable regions to compute matching scores for decision. Experiments on several public palmprint databases show that the proposed models and the KPBG approach can effectively solve the deformation problem in palmprint verification and outperform the state-of-the-art methods.

Optical image transformation and encryption by phase-retrieval-based double random-phase encoding and compressive ghost imaging

NASA Astrophysics Data System (ADS)

Yuan, Sheng; Yang, Yangrui; Liu, Xuemei; Zhou, Xin; Wei, Zhenzhuo

2018-01-01

An optical image transformation and encryption scheme is proposed based on double random-phase encoding (DRPE) and compressive ghost imaging (CGI) techniques. In this scheme, a secret image is first transformed into a binary image with the phase-retrieval-based DRPE technique, and then encoded by a series of random amplitude patterns according to the ghost imaging (GI) principle. Compressive sensing, corrosion and expansion operations are implemented to retrieve the secret image in the decryption process. This encryption scheme takes the advantage of complementary capabilities offered by the phase-retrieval-based DRPE and GI-based encryption techniques. That is the phase-retrieval-based DRPE is used to overcome the blurring defect of the decrypted image in the GI-based encryption, and the CGI not only reduces the data amount of the ciphertext, but also enhances the security of DRPE. Computer simulation results are presented to verify the performance of the proposed encryption scheme.

A multilayer perceptron solution to the match phase problem in rule-based artificial intelligence systems

NASA Technical Reports Server (NTRS)

Sartori, Michael A.; Passino, Kevin M.; Antsaklis, Panos J.

1992-01-01

In rule-based AI planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some 'working memory'. The traditional approach to solve such a 'match phase problem' for production systems is to use the Rete Match Algorithm. Here, a new technique using a multilayer perceptron, a particular artificial neural network model, is presented to solve the match phase problem for rule-based AI systems. A syntax for premise formulas (i.e., the left-hand-sides of the rules) is defined, and working memory is specified. From this, it is shown how to construct a multilayer perceptron that finds all of the rules which can be executed for the current situation in working memory. The complexity of the constructed multilayer perceptron is derived in terms of the maximum number of nodes and the required number of layers. A method for reducing the number of layers to at most three is also presented.

Edge-based correlation image registration for multispectral imaging

DOEpatents

Nandy, Prabal [Albuquerque, NM

2009-11-17

Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

Facial recognition software success rates for the identification of 3D surface reconstructed facial images: implications for patient privacy and security.

PubMed

Mazura, Jan C; Juluru, Krishna; Chen, Joseph J; Morgan, Tara A; John, Majnu; Siegel, Eliot L

2012-06-01

Image de-identification has focused on the removal of textual protected health information (PHI). Surface reconstructions of the face have the potential to reveal a subject's identity even when textual PHI is absent. This study assessed the ability of a computer application to match research subjects' 3D facial reconstructions with conventional photographs of their face. In a prospective study, 29 subjects underwent CT scans of the head and had frontal digital photographs of their face taken. Facial reconstructions of each CT dataset were generated on a 3D workstation. In phase 1, photographs of the 29 subjects undergoing CT scans were added to a digital directory and tested for recognition using facial recognition software. In phases 2-4, additional photographs were added in groups of 50 to increase the pool of possible matches and the test for recognition was repeated. As an internal control, photographs of all subjects were tested for recognition against an identical photograph. Of 3D reconstructions, 27.5% were matched correctly to corresponding photographs (95% upper CL, 40.1%). All study subject photographs were matched correctly to identical photographs (95% lower CL, 88.6%). Of 3D reconstructions, 96.6% were recognized simply as a face by the software (95% lower CL, 83.5%). Facial recognition software has the potential to recognize features on 3D CT surface reconstructions and match these with photographs, with implications for PHI.

Impact of CT attenuation correction method on quantitative respiratory-correlated (4D) PET/CT imaging

PubMed Central

Lee, Tzu-Cheng; Alessio, Adam M.; Wollenweber, Scott D.; Stearns, Charles W.; Bowen, Stephen R.; Kinahan, Paul E.

2015-01-01

Purpose: Respiratory-correlated positron emission tomography (PET/CT) 4D PET/CT is used to mitigate errors from respiratory motion; however, the optimal CT attenuation correction (CTAC) method for 4D PET/CT is unknown. The authors performed a phantom study to evaluate the quantitative performance of CTAC methods for 4D PET/CT in the ground truth setting. Methods: A programmable respiratory motion phantom with a custom movable insert designed to emulate a lung lesion and lung tissue was used for this study. The insert was driven by one of five waveforms: two sinusoidal waveforms or three patient-specific respiratory waveforms. 3DPET and 4DPET images of the phantom under motion were acquired and reconstructed with six CTAC methods: helical breath-hold (3DHEL), helical free-breathing (3DMOT), 4D phase-averaged (4DAVG), 4D maximum intensity projection (4DMIP), 4D phase-matched (4DMATCH), and 4D end-exhale (4DEXH) CTAC. Recovery of SUVmax, SUVmean, SUVpeak, and segmented tumor volume was evaluated as RCmax, RCmean, RCpeak, and RCvol, representing percent difference relative to the static ground truth case. Paired Wilcoxon tests and Kruskal–Wallis ANOVA were used to test for significant differences. Results: For 4DPET imaging, the maximum intensity projection CTAC produced significantly more accurate recovery coefficients than all other CTAC methods (p < 0.0001 over all metrics). Over all motion waveforms, ratios of 4DMIP CTAC recovery were 0.2 ± 5.4, −1.8 ± 6.5, −3.2 ± 5.0, and 3.0 ± 5.9 for RCmax, RCpeak, RCmean, and RCvol. In comparison, recovery coefficients for phase-matched CTAC were −8.4 ± 5.3, −10.5 ± 6.2, −7.6 ± 5.0, and −13.0 ± 7.7 for RCmax, RCpeak, RCmean, and RCvol. When testing differences between phases over all CTAC methods and waveforms, end-exhale phases were significantly more accurate (p = 0.005). However, these differences were driven by the patient-specific respiratory waveforms; when testing patient and sinusoidal waveforms separately, patient waveforms were significantly different between phases (p < 0.0001) while the sinusoidal waveforms were not significantly different (p = 0.98). When considering only the subset of 4DMATCH images that corresponded to the end-exhale image phase, 4DEXH, mean and interquartile range were similar to 4DMATCH but variability was considerably reduced. Conclusions: Comparative advantages in accuracy and precision of SUV metrics and segmented volumes were demonstrated with the use of the maximum intensity projection and end-exhale CT attenuation correction. While respiratory phase-matched CTAC should in theory provide optimal corrections, image artifacts and differences in implementation of 4DCT and 4DPET sorting can degrade the benefit of this approach. These results may be useful to guide the implementation, analysis, and development of respiratory-correlated thoracic PET/CT in the radiation oncology and diagnostic settings. PMID:25563252

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method

PubMed Central

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters – TCCF, Tθ, Tx and Ty are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images. PMID:26601045

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method.

PubMed

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters - T CCF, T θ, T x and T y are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images.

Perception for rugged terrain

NASA Technical Reports Server (NTRS)

Kweon, In SO; Hebert, Martial; Kanade, Takeo

1989-01-01

A three-dimensional perception system for building a geometrical description of rugged terrain environments from range image data is presented with reference to the exploration of the rugged terrain of Mars. An intermediate representation consisting of an elevation map that includes an explicit representation of uncertainty and labeling of the occluded regions is proposed. The locus method used to convert range image to an elevation map is introduced, along with an uncertainty model based on this algorithm. Both the elevation map and the locus method are the basis of a terrain matching algorithm which does not assume any correspondences between range images. The two-stage algorithm consists of a feature-based matching algorithm to compute an initial transform and an iconic terrain matching algorithm to merge multiple range images into a uniform representation. Terrain modeling results on real range images of rugged terrain are presented. The algorithms considered are a fundamental part of the perception system for the Ambler, a legged locomotor.

Characterization of LiBC by phase-contrast scanning transmission electron microscopy.

PubMed

Krumeich, Frank; Wörle, Michael; Reibisch, Philipp; Nesper, Reinhard

2014-08-01

LiBC was used as a model compound for probing the applicability of phase-contrast (PC) imaging in an aberration-corrected scanning transmission electron microscope (STEM) to visualize lithium distributions. In the LiBC structure, boron and carbon are arranged to hetero graphite layers between which lithium is incorporated. The crystal structure is reflected in the PC-STEM images recorded perpendicular to the layers. The experimental images and their defocus dependence match with multi-slice simulations calculated utilizing the reciprocity principle. The observation that a part of the Li positions is not occupied is likely an effect of the intense electron beam triggering Li displacement. Copyright © 2013 Elsevier Ltd. All rights reserved.

Limited-angle tomography for analyzer-based phase-contrast X-ray imaging

PubMed Central

Majidi, Keivan; Wernick, Miles N; Li, Jun; Muehleman, Carol; Brankov, Jovan G

2014-01-01

Multiple-Image Radiography (MIR) is an analyzer-based phase-contrast X-ray imaging method (ABI), which is emerging as a potential alternative to conventional radiography. MIR simultaneously generates three planar parametric images containing information about scattering, refraction and attenuation properties of the object. The MIR planar images are linear tomographic projections of the corresponding object properties, which allows reconstruction of volumetric images using computed tomography (CT) methods. However, when acquiring a full range of linear projections around the tissue of interest is not feasible or the scanning time is limited, limited-angle tomography techniques can be used to reconstruct these volumetric images near the central plane, which is the plane that contains the pivot point of the tomographic movement. In this work, we use computer simulations to explore the applicability of limited-angle tomography to MIR. We also investigate the accuracy of reconstructions as a function of number of tomographic angles for a fixed total radiation exposure. We use this function to find an optimal range of angles over which data should be acquired for limited-angle tomography MIR (LAT-MIR). Next, we apply the LAT-MIR technique to experimentally acquired MIR projections obtained in a cadaveric human thumb study. We compare the reconstructed slices near the central plane to the same slices reconstructed by CT-MIR using the full angular view around the object. Finally, we perform a task-based evaluation of LAT-MIR performance for different numbers of angular views, and use template matching to detect cartilage in the refraction image near the central plane. We use the signal-to-noise ratio of this test as the detectability metric to investigate an optimum range of tomographic angles for detecting soft tissues in LAT-MIR. Both results show that there is an optimum range of angular view for data acquisition where LAT-MIR yields the best performance, comparable to CT-MIR only if one considers volumetric images near the central plane and not the whole volume. PMID:24898008

Limited-angle tomography for analyzer-based phase-contrast x-ray imaging

NASA Astrophysics Data System (ADS)

Majidi, Keivan; Wernick, Miles N.; Li, Jun; Muehleman, Carol; Brankov, Jovan G.

2014-07-01

Multiple-image radiography (MIR) is an analyzer-based phase-contrast x-ray imaging method, which is emerging as a potential alternative to conventional radiography. MIR simultaneously generates three planar parametric images containing information about scattering, refraction and attenuation properties of the object. The MIR planar images are linear tomographic projections of the corresponding object properties, which allows reconstruction of volumetric images using computed tomography (CT) methods. However, when acquiring a full range of linear projections around the tissue of interest is not feasible or the scanning time is limited, limited-angle tomography techniques can be used to reconstruct these volumetric images near the central plane, which is the plane that contains the pivot point of the tomographic movement. In this work, we use computer simulations to explore the applicability of limited-angle tomography to MIR. We also investigate the accuracy of reconstructions as a function of number of tomographic angles for a fixed total radiation exposure. We use this function to find an optimal range of angles over which data should be acquired for limited-angle tomography MIR (LAT-MIR). Next, we apply the LAT-MIR technique to experimentally acquired MIR projections obtained in a cadaveric human thumb study. We compare the reconstructed slices near the central plane to the same slices reconstructed by CT-MIR using the full angular view around the object. Finally, we perform a task-based evaluation of LAT-MIR performance for different numbers of angular views, and use template matching to detect cartilage in the refraction image near the central plane. We use the signal-to-noise ratio of this test as the detectability metric to investigate an optimum range of tomographic angles for detecting soft tissues in LAT-MIR. Both results show that there is an optimum range of angular view for data acquisition where LAT-MIR yields the best performance, comparable to CT-MIR only if one considers volumetric images near the central plane and not the whole volume.

Robust stereo matching with trinary cross color census and triple image-based refinements

NASA Astrophysics Data System (ADS)

Chang, Ting-An; Lu, Xiao; Yang, Jar-Ferr

2017-12-01

For future 3D TV broadcasting systems and navigation applications, it is necessary to have accurate stereo matching which could precisely estimate depth map from two distanced cameras. In this paper, we first suggest a trinary cross color (TCC) census transform, which can help to achieve accurate disparity raw matching cost with low computational cost. The two-pass cost aggregation (TPCA) is formed to compute the aggregation cost, then the disparity map can be obtained by a range winner-take-all (RWTA) process and a white hole filling procedure. To further enhance the accuracy performance, a range left-right checking (RLRC) method is proposed to classify the results as correct, mismatched, or occluded pixels. Then, the image-based refinements for the mismatched and occluded pixels are proposed to refine the classified errors. Finally, the image-based cross voting and a median filter are employed to complete the fine depth estimation. Experimental results show that the proposed semi-global stereo matching system achieves considerably accurate disparity maps with reasonable computation cost.

Laser Covariance Vibrometry for Unsymmetrical Mode Detection

DTIC Science & Technology

2006-09-01

surface rough- ness. Results show that the remote sensing spectra adequately match the structural vibration, including non – imaging spatially...the speckle. 10 profile (cross – section), is an air turbulence effect ignored in this work that will affect both the sensed vibration phase change and...like spike impulse. 13 Chapter three describes optical processing issues. This chapter delineates the image propagation algorithms used for the work

Edge Detection Method Based on Neural Networks for COMS MI Images

NASA Astrophysics Data System (ADS)

Lee, Jin-Ho; Park, Eun-Bin; Woo, Sun-Hee

2016-12-01

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

Fast and accurate face recognition based on image compression

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Blasch, Erik

2017-05-01

Image compression is desired for many image-related applications especially for network-based applications with bandwidth and storage constraints. The face recognition community typical reports concentrate on the maximal compression rate that would not decrease the recognition accuracy. In general, the wavelet-based face recognition methods such as EBGM (elastic bunch graph matching) and FPB (face pattern byte) are of high performance but run slowly due to their high computation demands. The PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) algorithms run fast but perform poorly in face recognition. In this paper, we propose a novel face recognition method based on standard image compression algorithm, which is termed as compression-based (CPB) face recognition. First, all gallery images are compressed by the selected compression algorithm. Second, a mixed image is formed with the probe and gallery images and then compressed. Third, a composite compression ratio (CCR) is computed with three compression ratios calculated from: probe, gallery and mixed images. Finally, the CCR values are compared and the largest CCR corresponds to the matched face. The time cost of each face matching is about the time of compressing the mixed face image. We tested the proposed CPB method on the "ASUMSS face database" (visible and thermal images) from 105 subjects. The face recognition accuracy with visible images is 94.76% when using JPEG compression. On the same face dataset, the accuracy of FPB algorithm was reported as 91.43%. The JPEG-compressionbased (JPEG-CPB) face recognition is standard and fast, which may be integrated into a real-time imaging device.

Optimized atom position and coefficient coding for matching pursuit-based image compression.

PubMed

Shoa, Alireza; Shirani, Shahram

2009-12-01

In this paper, we propose a new encoding algorithm for matching pursuit image coding. We show that coding performance is improved when correlations between atom positions and atom coefficients are both used in encoding. We find the optimum tradeoff between efficient atom position coding and efficient atom coefficient coding and optimize the encoder parameters. Our proposed algorithm outperforms the existing coding algorithms designed for matching pursuit image coding. Additionally, we show that our algorithm results in better rate distortion performance than JPEG 2000 at low bit rates.

Deep Learning for Lowtextured Image Matching

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Fedorenko, V. V.; Fomin, N. A.

2018-05-01

Low-textured objects pose challenges for an automatic 3D model reconstruction. Such objects are common in archeological applications of photogrammetry. Most of the common feature point descriptors fail to match local patches in featureless regions of an object. Hence, automatic documentation of the archeological process using Structure from Motion (SfM) methods is challenging. Nevertheless, such documentation is possible with the aid of a human operator. Deep learning-based descriptors have outperformed most of common feature point descriptors recently. This paper is focused on the development of a new Wide Image Zone Adaptive Robust feature Descriptor (WIZARD) based on the deep learning. We use a convolutional auto-encoder to compress discriminative features of a local path into a descriptor code. We build a codebook to perform point matching on multiple images. The matching is performed using the nearest neighbor search and a modified voting algorithm. We present a new "Multi-view Amphora" (Amphora) dataset for evaluation of point matching algorithms. The dataset includes images of an Ancient Greek vase found at Taman Peninsula in Southern Russia. The dataset provides color images, a ground truth 3D model, and a ground truth optical flow. We evaluated the WIZARD descriptor on the "Amphora" dataset to show that it outperforms the SIFT and SURF descriptors on the complex patch pairs.

Fixed-pattern noise correction method based on improved moment matching for a TDI CMOS image sensor.

PubMed

Xu, Jiangtao; Nie, Huafeng; Nie, Kaiming; Jin, Weimin

2017-09-01

In this paper, an improved moment matching method based on a spatial correlation filter (SCF) and bilateral filter (BF) is proposed to correct the fixed-pattern noise (FPN) of a time-delay-integration CMOS image sensor (TDI-CIS). First, the values of row FPN (RFPN) and column FPN (CFPN) are estimated and added to the original image through SCF and BF, respectively. Then the filtered image will be processed by an improved moment matching method with a moving window. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination, the standard deviation of row mean vector (SDRMV) decreases from 5.6761 LSB to 0.1948 LSB, while the standard deviation of the column mean vector (SDCMV) decreases from 15.2005 LSB to 13.1949LSB. In addition, for different images captured by different TDI-CISs, the average decrease of SDRMV and SDCMV is 5.4922/2.0357 LSB, respectively. Comparative experimental results indicate that the proposed method can effectively correct the FPNs of different TDI-CISs while maintaining image details without any auxiliary equipment.

A novel 3D deformation measurement method under optical microscope for micro-scale bulge-test

NASA Astrophysics Data System (ADS)

Wu, Dan; Xie, Huimin

2017-11-01

A micro-scale 3D deformation measurement method combined with optical microscope is proposed in this paper. The method is based on gratings and phase shifting algorithm. By recording the grating images before and after deformation from two symmetrical angles and calculating the phases of the grating patterns, the 3D deformation field of the specimen can be extracted from the phases of the grating patterns. The proposed method was applied to the micro-scale bulge test. A micro-scale thermal/mechanical coupling bulge-test apparatus matched with the super-depth microscope was exploited. With the gratings fabricated onto the film, the deformed morphology of the bulged film was measured reliably. The experimental results show that the proposed method and the exploited bulge-test apparatus can be used to characterize the thermal/mechanical properties of the films at micro-scale successfully.

Quantitative electron density characterization of soft tissue substitute plastic materials using grating-based x-ray phase-contrast imaging

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

Sarapata, A.; Chabior, M.; Zanette, I.

2014-10-15

Many scientific research areas rely on accurate electron density characterization of various materials. For instance in X-ray optics and radiation therapy, there is a need for a fast and reliable technique to quantitatively characterize samples for electron density. We present how a precise measurement of electron density can be performed using an X-ray phase-contrast grating interferometer in a radiographic mode of a homogenous sample in a controlled geometry. A batch of various plastic materials was characterized quantitatively and compared with calculated results. We found that the measured electron densities closely match theoretical values. The technique yields comparable results between amore » monochromatic and a polychromatic X-ray source. Measured electron densities can be further used to design dedicated X-ray phase contrast phantoms and the additional information on small angle scattering should be taken into account in order to exclude unsuitable materials.« less

Integrity Determination for Image Rendering Vision Navigation

DTIC Science & Technology

2016-03-01

identifying an object within a scene, tracking a SIFT feature between frames or matching images and/or features for stereo vision applications. This... object level, either in 2-D or 3-D, versus individual features. There is a breadth of information, largely from the machine vision community...matching or image rendering image correspondence approach is based upon using either 2-D or 3-D object models or templates to perform object detection or

Respiratory motion compensation algorithm of ultrasound hepatic perfusion data acquired in free-breathing

NASA Astrophysics Data System (ADS)

Wu, Kaizhi; Zhang, Xuming; Chen, Guangxie; Weng, Fei; Ding, Mingyue

2013-10-01

Images acquired in free breathing using contrast enhanced ultrasound exhibit a periodic motion that needs to be compensated for if a further accurate quantification of the hepatic perfusion analysis is to be executed. In this work, we present an algorithm to compensate the respiratory motion by effectively combining the PCA (Principal Component Analysis) method and block matching method. The respiratory kinetics of the ultrasound hepatic perfusion image sequences was firstly extracted using the PCA method. Then, the optimal phase of the obtained respiratory kinetics was detected after normalizing the motion amplitude and determining the image subsequences of the original image sequences. The image subsequences were registered by the block matching method using cross-correlation as the similarity. Finally, the motion-compensated contrast images can be acquired by using the position mapping and the algorithm was evaluated by comparing the TICs extracted from the original image sequences and compensated image subsequences. Quantitative comparisons demonstrated that the average fitting error estimated of ROIs (region of interest) was reduced from 10.9278 +/- 6.2756 to 5.1644 +/- 3.3431 after compensating.

Source mechanism of small long-period events at Mount St. Helens in July 2005 using template matching, phase-weighted stacking, and full-waveform inversion

USGS Publications Warehouse

Matoza, Robin S.; Chouet, Bernard A.; Dawson, Phillip B.; Shearer, Peter M.; Haney, Matthew M.; Waite, Gregory P.; Moran, Seth C.; Mikesell, T. Dylan

2015-01-01

Long-period (LP, 0.5-5 Hz) seismicity, observed at volcanoes worldwide, is a recognized signature of unrest and eruption. Cyclic LP “drumbeating” was the characteristic seismicity accompanying the sustained dome-building phase of the 2004–2008 eruption of Mount St. Helens (MSH), WA. However, together with the LP drumbeating was a near-continuous, randomly occurring series of tiny LP seismic events (LP “subevents”), which may hold important additional information on the mechanism of seismogenesis at restless volcanoes. We employ template matching, phase-weighted stacking, and full-waveform inversion to image the source mechanism of one multiplet of these LP subevents at MSH in July 2005. The signal-to-noise ratios of the individual events are too low to produce reliable waveform-inversion results, but the events are repetitive and can be stacked. We apply network-based template matching to 8 days of continuous velocity waveform data from 29 June to 7 July 2005 using a master event to detect 822 network triggers. We stack waveforms for 359 high-quality triggers at each station and component, using a combination of linear and phase-weighted stacking to produce clean stacks for use in waveform inversion. The derived source mechanism pointsto the volumetric oscillation (~10 m3) of a subhorizontal crack located at shallow depth (~30 m) in an area to the south of Crater Glacier in the southern portion of the breached MSH crater. A possible excitation mechanism is the sudden condensation of metastable steam from a shallow pressurized hydrothermal system as it encounters cool meteoric water in the outer parts of the edifice, perhaps supplied from snow melt.

Cryogenic phased-array for high resolution magnetic resonance imaging (MRI); assessment of clinical and research applications

NASA Astrophysics Data System (ADS)

Ip, Flora S.

Magnetic Resonance (MR) imaging is one of the most powerful tools in diagnostic medicine for soft tissue imaging. Image acquisition techniques and hardware receivers are very important in achieving high contrast and high resolution MR images. An aim of this dissertation is to design single and multi-element room and cryogenic temperature arrays and make assessments of their signal-to-noise ratio (SNR) and SNR gain. In this dissertation, four sets of MR receiver coils are built. They are the receiver-only cryo-coils that are not commercially available. A tuning and matching circuit is attached to each coil. The tuning and matching circuits are simple; however, each device component has to operate at a high magnetic field and cryogenic temperature environment. Remote DC bias of the varactor controls the tuning and matching outside the scanner room. Active detuning of the resonator is done by two p-i-n junction (PIN) diodes. Cooling of the receiver is done by a customized liquid nitrogen cryostat. The first application is to build a 3-Tesla 2x1 horseshoe counter-rotating current (CRC) cryogenic array to image the tibia in a human body. With significant increase in SNR, the surface coil should deliver high contrast and resolution images that can show the trabecular bone and bone marrow structure. This structural image will be used to model the mechanical strength of the bone as well as bone density and chance of fracture. The planar CRC is a unique design of this surface array. The second application is to modify the coil design to 7-Tesla to study the growth of infant rhesus monkey eyes. Fast scan MR images of the infant monkey heads are taken for monitoring shapes of their eyeballs. The monkeys are induced with shortsightedness by eye lenses, and they are scanned periodically to get images of their eyeballs. The field-of-view (FOV) of these images is about five centimeters and the area of interest is two centimeters deep from the surface. Because of these reasons, the MR counter-rotating current coil is sufficient and demonstrated its simplicity over a phased array in this application.

Multi-Sensor Registration of Earth Remotely Sensed Imagery

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Cole-Rhodes, Arlene; Eastman, Roger; Johnson, Kisha; Morisette, Jeffrey; Netanyahu, Nathan S.; Stone, Harold S.; Zavorin, Ilya; Zukor, Dorothy (Technical Monitor)

2001-01-01

Assuming that approximate registration is given within a few pixels by a systematic correction system, we develop automatic image registration methods for multi-sensor data with the goal of achieving sub-pixel accuracy. Automatic image registration is usually defined by three steps; feature extraction, feature matching, and data resampling or fusion. Our previous work focused on image correlation methods based on the use of different features. In this paper, we study different feature matching techniques and present five algorithms where the features are either original gray levels or wavelet-like features, and the feature matching is based on gradient descent optimization, statistical robust matching, and mutual information. These algorithms are tested and compared on several multi-sensor datasets covering one of the EOS Core Sites, the Konza Prairie in Kansas, from four different sensors: IKONOS (4m), Landsat-7/ETM+ (30m), MODIS (500m), and SeaWIFS (1000m).

Accurate documentation in cultural heritage by merging TLS and high-resolution photogrammetric data

NASA Astrophysics Data System (ADS)

Grussenmeyer, Pierre; Alby, Emmanuel; Assali, Pierre; Poitevin, Valentin; Hullo, Jean-François; Smigiel, Eddie

2011-07-01

Several recording techniques are used together in Cultural Heritage Documentation projects. The main purpose of the documentation and conservation works is usually to generate geometric and photorealistic 3D models for both accurate reconstruction and visualization purposes. The recording approach discussed in this paper is based on the combination of photogrammetric dense matching and Terrestrial Laser Scanning (TLS) techniques. Both techniques have pros and cons, and criteria as geometry, texture, accuracy, resolution, recording and processing time are often compared. TLS techniques (time of flight or phase shift systems) are often used for the recording of large and complex objects or sites. Point cloud generation from images by dense stereo or multi-image matching can be used as an alternative or a complementary method to TLS. Compared to TLS, the photogrammetric solution is a low cost one as the acquisition system is limited to a digital camera and a few accessories only. Indeed, the stereo matching process offers a cheap, flexible and accurate solution to get 3D point clouds and textured models. The calibration of the camera allows the processing of distortion free images, accurate orientation of the images, and matching at the subpixel level. The main advantage of this photogrammetric methodology is to get at the same time a point cloud (the resolution depends on the size of the pixel on the object), and therefore an accurate meshed object with its texture. After the matching and processing steps, we can use the resulting data in much the same way as a TLS point cloud, but with really better raster information for textures. The paper will address the automation of recording and processing steps, the assessment of the results, and the deliverables (e.g. PDF-3D files). Visualization aspects of the final 3D models are presented. Two case studies with merged photogrammetric and TLS data are finally presented: - The Gallo-roman Theatre of Mandeure, France); - The Medieval Fortress of Châtel-sur-Moselle, France), where a network of underground galleries and vaults has been recorded.

Parallel algorithm for determining motion vectors in ice floe images by matching edge features

NASA Technical Reports Server (NTRS)

Manohar, M.; Ramapriyan, H. K.; Strong, J. P.

1988-01-01

A parallel algorithm is described to determine motion vectors of ice floes using time sequences of images of the Arctic ocean obtained from the Synthetic Aperture Radar (SAR) instrument flown on-board the SEASAT spacecraft. Researchers describe a parallel algorithm which is implemented on the MPP for locating corresponding objects based on their translationally and rotationally invariant features. The algorithm first approximates the edges in the images by polygons or sets of connected straight-line segments. Each such edge structure is then reduced to a seed point. Associated with each seed point are the descriptions (lengths, orientations and sequence numbers) of the lines constituting the corresponding edge structure. A parallel matching algorithm is used to match packed arrays of such descriptions to identify corresponding seed points in the two images. The matching algorithm is designed such that fragmentation and merging of ice floes are taken into account by accepting partial matches. The technique has been demonstrated to work on synthetic test patterns and real image pairs from SEASAT in times ranging from .5 to 0.7 seconds for 128 x 128 images.

A registration-based segmentation method with application to adiposity analysis of mice microCT images

NASA Astrophysics Data System (ADS)

Bai, Bing; Joshi, Anand; Brandhorst, Sebastian; Longo, Valter D.; Conti, Peter S.; Leahy, Richard M.

2014-04-01

Obesity is a global health problem, particularly in the U.S. where one third of adults are obese. A reliable and accurate method of quantifying obesity is necessary. Visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) are two measures of obesity that reflect different associated health risks, but accurate measurements in humans or rodent models are difficult. In this paper we present an automatic, registration-based segmentation method for mouse adiposity studies using microCT images. We co-register the subject CT image and a mouse CT atlas. Our method is based on surface matching of the microCT image and an atlas. Surface-based elastic volume warping is used to match the internal anatomy. We acquired a whole body scan of a C57BL6/J mouse injected with contrast agent using microCT and created a whole body mouse atlas by manually delineate the boundaries of the mouse and major organs. For method verification we scanned a C57BL6/J mouse from the base of the skull to the distal tibia. We registered the obtained mouse CT image to our atlas. Preliminary results show that we can warp the atlas image to match the posture and shape of the subject CT image, which has significant differences from the atlas. We plan to use this software tool in longitudinal obesity studies using mouse models.

Modifications in SIFT-based 3D reconstruction from image sequence

NASA Astrophysics Data System (ADS)

Wei, Zhenzhong; Ding, Boshen; Wang, Wei

2014-11-01

In this paper, we aim to reconstruct 3D points of the scene from related images. Scale Invariant Feature Transform( SIFT) as a feature extraction and matching algorithm has been proposed and improved for years and has been widely used in image alignment and stitching, image recognition and 3D reconstruction. Because of the robustness and reliability of the SIFT's feature extracting and matching algorithm, we use it to find correspondences between images. Hence, we describe a SIFT-based method to reconstruct 3D sparse points from ordered images. In the process of matching, we make a modification in the process of finding the correct correspondences, and obtain a satisfying matching result. By rejecting the "questioned" points before initial matching could make the final matching more reliable. Given SIFT's attribute of being invariant to the image scale, rotation, and variable changes in environment, we propose a way to delete the multiple reconstructed points occurred in sequential reconstruction procedure, which improves the accuracy of the reconstruction. By removing the duplicated points, we avoid the possible collapsed situation caused by the inexactly initialization or the error accumulation. The limitation of some cases that all reprojected points are visible at all times also does not exist in our situation. "The small precision" could make a big change when the number of images increases. The paper shows the contrast between the modified algorithm and not. Moreover, we present an approach to evaluate the reconstruction by comparing the reconstructed angle and length ratio with actual value by using a calibration target in the scene. The proposed evaluation method is easy to be carried out and with a great applicable value. Even without the Internet image datasets, we could evaluate our own results. In this paper, the whole algorithm has been tested on several image sequences both on the internet and in our shots.

Augmented reality 3D display based on integral imaging

NASA Astrophysics Data System (ADS)

Deng, Huan; Zhang, Han-Le; He, Min-Yang; Wang, Qiong-Hua

2017-02-01

Integral imaging (II) is a good candidate for augmented reality (AR) display, since it provides various physiological depth cues so that viewers can freely change the accommodation and convergence between the virtual three-dimensional (3D) images and the real-world scene without feeling any visual discomfort. We propose two AR 3D display systems based on the theory of II. In the first AR system, a micro II display unit reconstructs a micro 3D image, and the mciro-3D image is magnified by a convex lens. The lateral and depth distortions of the magnified 3D image are analyzed and resolved by the pitch scaling and depth scaling. The magnified 3D image and real 3D scene are overlapped by using a half-mirror to realize AR 3D display. The second AR system uses a micro-lens array holographic optical element (HOE) as an image combiner. The HOE is a volume holographic grating which functions as a micro-lens array for the Bragg-matched light, and as a transparent glass for Bragg mismatched light. A reference beam can reproduce a virtual 3D image from one side and a reference beam with conjugated phase can reproduce the second 3D image from other side of the micro-lens array HOE, which presents double-sided 3D display feature.

Development of a 20-MHz wide-bandwidth PMN-PT single crystal phased-array ultrasound transducer.

PubMed

Wong, Chi-Man; Chen, Yan; Luo, Haosu; Dai, Jiyan; Lam, Kwok-Ho; Chan, Helen Lai-Wa

2017-01-01

In this study, a 20-MHz 64-element phased-array ultrasound transducer with a one-wavelength pitch is developed using a PMN-30%PT single crystal and double-matching layer scheme. High piezoelectric (d 33 >1000pC/N) and electromechanical coupling (k 33 >0.8) properties of the single crystal with an optimized fabrication process involving the photolithography technique have been demonstrated to be suitable for wide-bandwidth (⩾70%) and high-sensitivity (insertion loss ⩽30dB) phased-array transducer application. A -6dBbandwidth of 91% and an insertion loss of 29dBfor the 20-MHz 64-element phased-array transducer were achieved. This result shows that the bandwidth is improved comparing with the investigated high-frequency (⩾20MHz) ultrasound transducers using piezoelectric ceramic and single crystal materials. It shows that this phased-array transducer has potential to improve the resolution of biomedical imaging, theoretically. Based on the hypothesis of resolution improvement, this phased-array transducer is capable for small animal (i.e. mouse and zebrafish) studies. Copyright © 2016 Elsevier B.V. All rights reserved.

Subwavelength nonlinear phase control and anomalous phase matching in plasmonic metasurfaces

NASA Astrophysics Data System (ADS)

Almeida, Euclides; Shalem, Guy; Prior, Yehiam

2016-01-01

Metasurfaces, and in particular those containing plasmonic-based metallic elements, constitute an attractive set of materials with a potential for replacing standard bulky optical elements. In recent years, increasing attention has been focused on their nonlinear optical properties, particularly in the context of second and third harmonic generation and beam steering by phase gratings. Here, we harness the full phase control enabled by subwavelength plasmonic elements to demonstrate a unique metasurface phase matching that is required for efficient nonlinear processes. We discuss the difference between scattering by a grating and by subwavelength phase-gradient elements. We show that for such interfaces an anomalous phase-matching condition prevails, which is the nonlinear analogue of the generalized Snell's law. The subwavelength phase control of optical nonlinearities paves the way for the design of ultrathin, flat nonlinear optical elements. We demonstrate nonlinear metasurface lenses, which act both as generators and as manipulators of the frequency-converted signal.

High resolution telescope

DOEpatents

Massie, Norbert A.; Oster, Yale

1992-01-01

A large effective-aperture, low-cost optical telescope with diffraction-limited resolution enables ground-based observation of near-earth space objects. The telescope has a non-redundant, thinned-aperture array in a center-mount, single-structure space frame. It employs speckle interferometric imaging to achieve diffraction-limited resolution. The signal-to-noise ratio problem is mitigated by moving the wavelength of operation to the near-IR, and the image is sensed by a Silicon CCD. The steerable, single-structure array presents a constant pupil. The center-mount, radar-like mount enables low-earth orbit space objects to be tracked as well as increases stiffness of the space frame. In the preferred embodiment, the array has elemental telescopes with subaperture of 2.1 m in a circle-of-nine configuration. The telescope array has an effective aperture of 12 m which provides a diffraction-limited resolution of 0.02 arc seconds. Pathlength matching of the telescope array is maintained by an electro-optical system employing laser metrology. Speckle imaging relaxes pathlength matching tolerance by one order of magnitude as compared to phased arrays. Many features of the telescope contribute to substantial reduction in costs. These include eliminating the conventional protective dome and reducing on-site construction activites. The cost of the telescope scales with the first power of the aperture rather than its third power as in conventional telescopes.

Phase-space evolution of x-ray coherence in phase-sensitive imaging.

PubMed

Wu, Xizeng; Liu, Hong

2008-08-01

X-ray coherence evolution in the imaging process plays a key role for x-ray phase-sensitive imaging. In this work we present a phase-space formulation for the phase-sensitive imaging. The theory is reformulated in terms of the cross-spectral density and associated Wigner distribution. The phase-space formulation enables an explicit and quantitative account of partial coherence effects on phase-sensitive imaging. The presented formulas for x-ray spectral density at the detector can be used for performing accurate phase retrieval and optimizing the phase-contrast visibility. The concept of phase-space shearing length derived from this phase-space formulation clarifies the spatial coherence requirement for phase-sensitive imaging with incoherent sources. The theory has been applied to x-ray Talbot interferometric imaging as well. The peak coherence condition derived reveals new insights into three-grating-based Talbot-interferometric imaging and gratings-based x-ray dark-field imaging.

Probabilistic seismic history matching using binary images

NASA Astrophysics Data System (ADS)

Davolio, Alessandra; Schiozer, Denis Jose

2018-02-01

Currently, the goal of history-matching procedures is not only to provide a model matching any observed data but also to generate multiple matched models to properly handle uncertainties. One such approach is a probabilistic history-matching methodology based on the discrete Latin Hypercube sampling algorithm, proposed in previous works, which was particularly efficient for matching well data (production rates and pressure). 4D seismic (4DS) data have been increasingly included into history-matching procedures. A key issue in seismic history matching (SHM) is to transfer data into a common domain: impedance, amplitude or pressure, and saturation. In any case, seismic inversions and/or modeling are required, which can be time consuming. An alternative to avoid these procedures is using binary images in SHM as they allow the shape, rather than the physical values, of observed anomalies to be matched. This work presents the incorporation of binary images in SHM within the aforementioned probabilistic history matching. The application was performed with real data from a segment of the Norne benchmark case that presents strong 4D anomalies, including softening signals due to pressure build up. The binary images are used to match the pressurized zones observed in time-lapse data. Three history matchings were conducted using: only well data, well and 4DS data, and only 4DS. The methodology is very flexible and successfully utilized the addition of binary images for seismic objective functions. Results proved the good convergence of the method in few iterations for all three cases. The matched models of the first two cases provided the best results, with similar well matching quality. The second case provided models presenting pore pressure changes according to the expected dynamic behavior (pressurized zones) observed on 4DS data. The use of binary images in SHM is relatively new with few examples in the literature. This work enriches this discussion by presenting a new application to match pressure in a reservoir segment with complex pressure behavior.

Machine Vision for Relative Spacecraft Navigation During Approach to Docking

NASA Technical Reports Server (NTRS)

Chien, Chiun-Hong; Baker, Kenneth

2011-01-01

This paper describes a machine vision system for relative spacecraft navigation during the terminal phase of approach to docking that: 1) matches high contrast image features of the target vehicle, as seen by a camera that is bore-sighted to the docking adapter on the chase vehicle, to the corresponding features in a 3d model of the docking adapter on the target vehicle and 2) is robust to on-orbit lighting. An implementation is provided for the case of the Space Shuttle Orbiter docking to the International Space Station (ISS) with quantitative test results using a full scale, medium fidelity mock-up of the ISS docking adapter mounted on a 6-DOF motion platform at the NASA Marshall Spaceflight Center Flight Robotics Laboratory and qualitative test results using recorded video from the Orbiter Docking System Camera (ODSC) during multiple orbiter to ISS docking missions. The Natural Feature Image Registration (NFIR) system consists of two modules: 1) Tracking which tracks the target object from image to image and estimates the position and orientation (pose) of the docking camera relative to the target object and 2) Acquisition which recognizes the target object if it is in the docking camera Field-of-View and provides an approximate pose that is used to initialize tracking. Detected image edges are matched to the 3d model edges whose predicted location, based on the pose estimate and its first time derivative from the previous frame, is closest to the detected edge1 . Mismatches are eliminated using a rigid motion constraint. The remaining 2d image to 3d model matches are used to make a least squares estimate of the change in relative pose from the previous image to the current image. The changes in position and in attitude are used as data for two Kalman filters whose outputs are smoothed estimate of position and velocity plus attitude and attitude rate that are then used to predict the location of the 3d model features in the next image.

From quantum physics to digital communication: Single sideband continuous phase modulation

NASA Astrophysics Data System (ADS)

Farès, Haïfa; Christian Glattli, D.; Louët, Yves; Palicot, Jacques; Moy, Christophe; Roulleau, Preden

2018-01-01

In the present paper, we propose a new frequency-shift keying continuous phase modulation (FSK-CPM) scheme having, by essence, the interesting feature of single-sideband (SSB) spectrum providing a very compact frequency occupation. First, the original principle, inspired from quantum physics (levitons), is presented. Besides, we address the problem of low-complexity coherent detection of this new waveform, based on orthonormal wave functions used to perform matched filtering for efficient demodulation. Consequently, this shows that the proposed modulation can operate using existing digital communication technology, since only well-known operations are performed (e.g., filtering, integration). This SSB property can be exploited to allow large bit rates transmissions at low carrier frequency without caring about image frequency degradation effects typical of ordinary double-sideband signals. xml:lang="fr"

Ince-gauss based multiple intermodal phase-matched third-harmonic generations in a step-index silica optical fiber

NASA Astrophysics Data System (ADS)

Borne, Adrien; Katsura, Tomotaka; Félix, Corinne; Doppagne, Benjamin; Segonds, Patricia; Bencheikh, Kamel; Levenson, Juan Ariel; Boulanger, Benoit

2016-01-01

Several third-harmonic generation processes were performed in a single step-index germanium-doped silica optical fiber under intermodal phase-matching conditions. The nanosecond fundamental beam range between 1400 and 1600 nm. The transverse distributions of the energy were successfully modeled in the form of Ince-Gauss modes, pointing out some ellipticity of fiber core. From these experiments and theoretical calculations, we discuss the implementation of frequency degenerated triple photon generation that shares the same phase-matching condition as third-harmonic generation, which is its reverse process.

Thin plate spline feature point matching for organ surfaces in minimally invasive surgery imaging

NASA Astrophysics Data System (ADS)

Lin, Bingxiong; Sun, Yu; Qian, Xiaoning

2013-03-01

Robust feature point matching for images with large view angle changes in Minimally Invasive Surgery (MIS) is a challenging task due to low texture and specular reflections in these images. This paper presents a new approach that can improve feature matching performance by exploiting the inherent geometric property of the organ surfaces. Recently, intensity based template image tracking using a Thin Plate Spline (TPS) model has been extended for 3D surface tracking with stereo cameras. The intensity based tracking is also used here for 3D reconstruction of internal organ surfaces. To overcome the small displacement requirement of intensity based tracking, feature point correspondences are used for proper initialization of the nonlinear optimization in the intensity based method. Second, we generate simulated images from the reconstructed 3D surfaces under all potential view positions and orientations, and then extract feature points from these simulated images. The obtained feature points are then filtered and re-projected to the common reference image. The descriptors of the feature points under different view angles are stored to ensure that the proposed method can tolerate a large range of view angles. We evaluate the proposed method with silicon phantoms and in vivo images. The experimental results show that our method is much more robust with respect to the view angle changes than other state-of-the-art methods.

Microwave Imaging Radar Reflectometer System Utilizing Digital Beam Forming

NASA Astrophysics Data System (ADS)

Hu, Fengqi; Li, Meijiao; Domier, Calvin W.; Liu, Xiaoguang; Luhmann, Neville C., Jr.

2016-10-01

Microwave Imaging Reflectometry is a radar-like technique developed to measure the electron density fluctuations in fusion plasmas. Phased Antenna Arrays can serve as electronically controlled ``lenses'' that can generate the required wavefronts by phase shifting and amplitude scaling, which is being realized in the digital domain with higher flexibility and faster processing speed. In the transmitter, the resolution of the phase control is 1.4 degrees and the amplitude control is 0.5 dB/ step. A V-band double-sided, printed bow tie antenna which exhibits 49% bandwidth (46 - 76 GHz) is employed. The antenna is fed by a microstrip transmission line for easy impedance matching. The simple structure and the small antenna are suitable for low cost fabrication, easy circuit integration, and phased antenna array multi-frequency applications. In the receiver part, a sub-array of 32 channels with 200 mil spacing is used to collect the scattered reflected signal from one unit spot on the plasma cutoff surface. Pre-amplification is used to control the noise level of the system and wire bondable components are used to accommodate the small spacing between each channel. After down converting, base band signals are digitized and processed in an FPGA module. U.S. Department of Energy Grant No. DE-FG02-99ER54531.

SU-E-J-36: A Flexible Integration of Key Technologies in Image-Guided Radiotherapy for Accurate Radiotherapy System (ARTS-IGRT).

PubMed

Jia, J; Liu, F; Ren, Q; Pei, X; Cao, R; Wu, Y

2012-06-01

Image-guided radiotherapy (IGRT) is becoming increasingly important in the planning and delivery of radiotherapy. With the aim of implementing the key technologies in a flexible and integrated way in IGRT for accurate radiotherapy system (ARTS), a prototype system named as ARTS-IGRT was designed and completed to apply main principles in image-guided radiotherapy. The basic workflow of the ARTS-IGRT software was completed with five functional modules including management of patient information, X-ray image acquisition, 2D/2D anatomy match, 2D/3D match as well as marker-based match. For 2D/2D match, an image registration method was proposed based on maximization of mutual information with multi-resolution and regions of interest. For the 2D/3D registration, optimizations have been employed to improve the existing digitally reconstructed radiography generation algorithm based on ray-casting, and also an image registration method based on implanted markers with different numbers was adopted for 3D/3D match. In additional, the kV X-Ray imaging on rail device was finished for a better internal anatomy image checking at any angle. Together with an infrared device, a positioning and tracking system was developed as well for accurate patient setup and motion monitoring during each treatment. A lot of tests were carried out based on the head phantom to testify the availability of the improved algorithms. Compared with a set of controlled experiments adopted on the released commercial IGRT platform in the hospital, the functions of both software and hardware were testified comprehensively. The results showed a validity verification of ARTS-IGRT. The accuracy and efficiency of ARTS-IGRT on both software and hardware proved to be valid. And also with a flexible and user-friendly interface it can meet the principles of clinical radiotherapy practice. Supported by the Natural Science Foundation of Anhui Province (11040606Q55) and the National Natural Science Foundation of China (30900386). © 2012 American Association of Physicists in Medicine.

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation

PubMed Central

Nitti, Davide O.; Bovenga, Fabio; Chiaradia, Maria T.; Greco, Mario; Pinelli, Gianpaolo

2015-01-01

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimate UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system. PMID:26225977

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation.

PubMed

Nitti, Davide O; Bovenga, Fabio; Chiaradia, Maria T; Greco, Mario; Pinelli, Gianpaolo

2015-07-28

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

Mapped Landmark Algorithm for Precision Landing

NASA Technical Reports Server (NTRS)

Johnson, Andrew; Ansar, Adnan; Matthies, Larry

2007-01-01

A report discusses a computer vision algorithm for position estimation to enable precision landing during planetary descent. The Descent Image Motion Estimation System for the Mars Exploration Rovers has been used as a starting point for creating code for precision, terrain-relative navigation during planetary landing. The algorithm is designed to be general because it handles images taken at different scales and resolutions relative to the map, and can produce mapped landmark matches for any planetary terrain of sufficient texture. These matches provide a measurement of horizontal position relative to a known landing site specified on the surface map. Multiple mapped landmarks generated per image allow for automatic detection and elimination of bad matches. Attitude and position can be generated from each image; this image-based attitude measurement can be used by the onboard navigation filter to improve the attitude estimate, which will improve the position estimates. The algorithm uses normalized correlation of grayscale images, producing precise, sub-pixel images. The algorithm has been broken into two sub-algorithms: (1) FFT Map Matching (see figure), which matches a single large template by correlation in the frequency domain, and (2) Mapped Landmark Refinement, which matches many small templates by correlation in the spatial domain. Each relies on feature selection, the homography transform, and 3D image correlation. The algorithm is implemented in C++ and is rated at Technology Readiness Level (TRL) 4.

Bin Ratio-Based Histogram Distances and Their Application to Image Classification.

PubMed

Hu, Weiming; Xie, Nianhua; Hu, Ruiguang; Ling, Haibin; Chen, Qiang; Yan, Shuicheng; Maybank, Stephen

2014-12-01

Large variations in image background may cause partial matching and normalization problems for histogram-based representations, i.e., the histograms of the same category may have bins which are significantly different, and normalization may produce large changes in the differences between corresponding bins. In this paper, we deal with this problem by using the ratios between bin values of histograms, rather than bin values' differences which are used in the traditional histogram distances. We propose a bin ratio-based histogram distance (BRD), which is an intra-cross-bin distance, in contrast with previous bin-to-bin distances and cross-bin distances. The BRD is robust to partial matching and histogram normalization, and captures correlations between bins with only a linear computational complexity. We combine the BRD with the ℓ1 histogram distance and the χ(2) histogram distance to generate the ℓ1 BRD and the χ(2) BRD, respectively. These combinations exploit and benefit from the robustness of the BRD under partial matching and the robustness of the ℓ1 and χ(2) distances to small noise. We propose a method for assessing the robustness of histogram distances to partial matching. The BRDs and logistic regression-based histogram fusion are applied to image classification. The experimental results on synthetic data sets show the robustness of the BRDs to partial matching, and the experiments on seven benchmark data sets demonstrate promising results of the BRDs for image classification.

An Improved Algorithm of Congruent Matching Cells (CMC) Method for Firearm Evidence Identifications

PubMed Central

Tong, Mingsi; Song, John; Chu, Wei

2015-01-01

The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for firearm evidence identifications. The CMC method divides the measured image of a surface area, such as a breech face impression from a fired cartridge case, into small correlation cells and uses four identification parameters to identify correlated cell pairs originating from the same firearm. The CMC method was validated by identification tests using both 3D topography images and optical images captured from breech face impressions of 40 cartridge cases fired from a pistol with 10 consecutively manufactured slides. In this paper, we discuss the processing of the cell correlations and propose an improved algorithm of the CMC method which takes advantage of the cell correlations at a common initial phase angle and combines the forward and backward correlations to improve the identification capability. The improved algorithm is tested by 780 pairwise correlations using the same optical images and 3D topography images as the initial validation. PMID:26958441

An Improved Algorithm of Congruent Matching Cells (CMC) Method for Firearm Evidence Identifications.

PubMed

Tong, Mingsi; Song, John; Chu, Wei

2015-01-01

The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for firearm evidence identifications. The CMC method divides the measured image of a surface area, such as a breech face impression from a fired cartridge case, into small correlation cells and uses four identification parameters to identify correlated cell pairs originating from the same firearm. The CMC method was validated by identification tests using both 3D topography images and optical images captured from breech face impressions of 40 cartridge cases fired from a pistol with 10 consecutively manufactured slides. In this paper, we discuss the processing of the cell correlations and propose an improved algorithm of the CMC method which takes advantage of the cell correlations at a common initial phase angle and combines the forward and backward correlations to improve the identification capability. The improved algorithm is tested by 780 pairwise correlations using the same optical images and 3D topography images as the initial validation.

Image-based computer-assisted diagnosis system for benign paroxysmal positional vertigo

NASA Astrophysics Data System (ADS)

Kohigashi, Satoru; Nakamae, Koji; Fujioka, Hiromu

2005-04-01

We develop the image based computer assisted diagnosis system for benign paroxysmal positional vertigo (BPPV) that consists of the balance control system simulator, the 3D eye movement simulator, and the extraction method of nystagmus response directly from an eye movement image sequence. In the system, the causes and conditions of BPPV are estimated by searching the database for record matching with the nystagmus response for the observed eye image sequence of the patient with BPPV. The database includes the nystagmus responses for simulated eye movement sequences. The eye movement velocity is obtained by using the balance control system simulator that allows us to simulate BPPV under various conditions such as canalithiasis, cupulolithiasis, number of otoconia, otoconium size, and so on. Then the eye movement image sequence is displayed on the CRT by the 3D eye movement simulator. The nystagmus responses are extracted from the image sequence by the proposed method and are stored in the database. In order to enhance the diagnosis accuracy, the nystagmus response for a newly simulated sequence is matched with that for the observed sequence. From the matched simulation conditions, the causes and conditions of BPPV are estimated. We apply our image based computer assisted diagnosis system to two real eye movement image sequences for patients with BPPV to show its validity.

Ultrasound of the fingers for human identification using biometrics.

PubMed

Narayanasamy, Ganesh; Fowlkes, J Brian; Kripfgans, Oliver D; Jacobson, Jon A; De Maeseneer, Michel; Schmitt, Rainer M; Carson, Paul L

2008-03-01

It was hypothesized that the use of internal finger structure as imaged using commercially available ultrasound (US) scanners could act as a supplement to standard methods of biometric identification, as well as a means of assessing physiological and cardiovascular status. Anatomical structures in the finger including bone contour, tendon and features along the interphalangeal joint were investigated as potential biometric identifiers. Thirty-six pairs of three-dimensional (3D) gray-scale images of second to fourth finger (index, middle and ring) data taken from 20 individuals were spatially registered using MIAMI-Fuse software developed at our institution and also visually matched by four readers. The image-based registration met the criteria for matching successfully in 14 out of 15 image pairs on the same individual and did not meet criteria for matching in any of the 12 image pairs from different subjects, providing a sensitivity and specificity of 0.93 and 1.00, respectively. Visual matching of all image pairs by four readers yielded 96% successful match. Power Doppler imaging was performed to calculate the change in color pixel density due to physical exercise as a surrogate of stress level and to provide basic physiological information. (E-mail: gnarayan@umich.edu).

a Probability-Based Statistical Method to Extract Water Body of TM Images with Missing Information

NASA Astrophysics Data System (ADS)

Lian, Shizhong; Chen, Jiangping; Luo, Minghai

2016-06-01

Water information cannot be accurately extracted using TM images because true information is lost in some images because of blocking clouds and missing data stripes, thereby water information cannot be accurately extracted. Water is continuously distributed in natural conditions; thus, this paper proposed a new method of water body extraction based on probability statistics to improve the accuracy of water information extraction of TM images with missing information. Different disturbing information of clouds and missing data stripes are simulated. Water information is extracted using global histogram matching, local histogram matching, and the probability-based statistical method in the simulated images. Experiments show that smaller Areal Error and higher Boundary Recall can be obtained using this method compared with the conventional methods.

Research on sparse feature matching of improved RANSAC algorithm

NASA Astrophysics Data System (ADS)

Kong, Xiangsi; Zhao, Xian

2018-04-01

In this paper, a sparse feature matching method based on modified RANSAC algorithm is proposed to improve the precision and speed. Firstly, the feature points of the images are extracted using the SIFT algorithm. Then, the image pair is matched roughly by generating SIFT feature descriptor. At last, the precision of image matching is optimized by the modified RANSAC algorithm,. The RANSAC algorithm is improved from three aspects: instead of the homography matrix, this paper uses the fundamental matrix generated by the 8 point algorithm as the model; the sample is selected by a random block selecting method, which ensures the uniform distribution and the accuracy; adds sequential probability ratio test(SPRT) on the basis of standard RANSAC, which cut down the overall running time of the algorithm. The experimental results show that this method can not only get higher matching accuracy, but also greatly reduce the computation and improve the matching speed.

Phase History Decomposition for efficient Scatterer Classification in SAR Imagery

DTIC Science & Technology

2011-09-15

frequency. Professor Rick Martin provided key advice on frequency parameter estimation and the relationship between likelihood ratio testing and the least...132 6.1.1 Imaging Error Due to Interpolation . . . . . . . . . . . . . . . . . . . . . . . . 135 6.2 Subwindow Design and Weighting... test . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 MF matched filter

SU-E-J-123: Assessing Segmentation Accuracy of Internal Volumes and Sub-Volumes in 4D PET/CT of Lung Tumors Using a Novel 3D Printed Phantom

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

Soultan, D; Murphy, J; James, C

2015-06-15

Purpose: To assess the accuracy of internal target volume (ITV) segmentation of lung tumors for treatment planning of simultaneous integrated boost (SIB) radiotherapy as seen in 4D PET/CT images, using a novel 3D-printed phantom. Methods: The insert mimics high PET tracer uptake in the core and 50% uptake in the periphery, by using a porous design at the periphery. A lung phantom with the insert was placed on a programmable moving platform. Seven breathing waveforms of ideal and patient-specific respiratory motion patterns were fed to the platform, and 4D PET/CT scans were acquired of each of them. CT images weremore » binned into 10 phases, and PET images were binned into 5 phases following the clinical protocol. Two scenarios were investigated for segmentation: a gate 30–70 window, and no gating. The radiation oncologist contoured the outer ITV of the porous insert with on CT images, while the internal void volume with 100% uptake was contoured on PET images for being indistinguishable from the outer volume in CT images. Segmented ITVs were compared to the expected volumes based on known target size and motion. Results: 3 ideal breathing patterns, 2 regular-breathing patient waveforms, and 2 irregular-breathing patient waveforms were used for this study. 18F-FDG was used as the PET tracer. The segmented ITVs from CT closely matched the expected motion for both no gating and gate 30–70 window, with disagreement of contoured ITV with respect to the expected volume not exceeding 13%. PET contours were seen to overestimate volumes in all the cases, up to more than 40%. Conclusion: 4DPET images of a novel 3D printed phantom designed to mimic different uptake values were obtained. 4DPET contours overestimated ITV volumes in all cases, while 4DCT contours matched expected ITV volume values. Investigation of the cause and effects of the discrepancies is undergoing.« less

n-SIFT: n-dimensional scale invariant feature transform.

PubMed

Cheung, Warren; Hamarneh, Ghassan

2009-09-01

We propose the n-dimensional scale invariant feature transform (n-SIFT) method for extracting and matching salient features from scalar images of arbitrary dimensionality, and compare this method's performance to other related features. The proposed features extend the concepts used for 2-D scalar images in the computer vision SIFT technique for extracting and matching distinctive scale invariant features. We apply the features to images of arbitrary dimensionality through the use of hyperspherical coordinates for gradients and multidimensional histograms to create the feature vectors. We analyze the performance of a fully automated multimodal medical image matching technique based on these features, and successfully apply the technique to determine accurate feature point correspondence between pairs of 3-D MRI images and dynamic 3D + time CT data.

Characteristic extraction and matching algorithms of ballistic missile in near-space by hyperspectral image analysis

NASA Astrophysics Data System (ADS)

Lu, Li; Sheng, Wen; Liu, Shihua; Zhang, Xianzhi

2014-10-01

The ballistic missile hyperspectral data of imaging spectrometer from the near-space platform are generated by numerical method. The characteristic of the ballistic missile hyperspectral data is extracted and matched based on two different kinds of algorithms, which called transverse counting and quantization coding, respectively. The simulation results show that two algorithms extract the characteristic of ballistic missile adequately and accurately. The algorithm based on the transverse counting has the low complexity and can be implemented easily compared to the algorithm based on the quantization coding does. The transverse counting algorithm also shows the good immunity to the disturbance signals and speed up the matching and recognition of subsequent targets.

A novel scheme for automatic nonrigid image registration using deformation invariant feature and geometric constraint

NASA Astrophysics Data System (ADS)

Deng, Zhipeng; Lei, Lin; Zhou, Shilin

2015-10-01

Automatic image registration is a vital yet challenging task, particularly for non-rigid deformation images which are more complicated and common in remote sensing images, such as distorted UAV (unmanned aerial vehicle) images or scanning imaging images caused by flutter. Traditional non-rigid image registration methods are based on the correctly matched corresponding landmarks, which usually needs artificial markers. It is a rather challenging task to locate the accurate position of the points and get accurate homonymy point sets. In this paper, we proposed an automatic non-rigid image registration algorithm which mainly consists of three steps: To begin with, we introduce an automatic feature point extraction method based on non-linear scale space and uniform distribution strategy to extract the points which are uniform distributed along the edge of the image. Next, we propose a hybrid point matching algorithm using DaLI (Deformation and Light Invariant) descriptor and local affine invariant geometric constraint based on triangulation which is constructed by K-nearest neighbor algorithm. Based on the accurate homonymy point sets, the two images are registrated by the model of TPS (Thin Plate Spline). Our method is demonstrated by three deliberately designed experiments. The first two experiments are designed to evaluate the distribution of point set and the correctly matching rate on synthetic data and real data respectively. The last experiment is designed on the non-rigid deformation remote sensing images and the three experimental results demonstrate the accuracy, robustness, and efficiency of the proposed algorithm compared with other traditional methods.

A flexible and robust approach for segmenting cell nuclei from 2D microscopy images using supervised learning and template matching

PubMed Central

Chen, Cheng; Wang, Wei; Ozolek, John A.; Rohde, Gustavo K.

2013-01-01

We describe a new supervised learning-based template matching approach for segmenting cell nuclei from microscopy images. The method uses examples selected by a user for building a statistical model which captures the texture and shape variations of the nuclear structures from a given dataset to be segmented. Segmentation of subsequent, unlabeled, images is then performed by finding the model instance that best matches (in the normalized cross correlation sense) local neighborhood in the input image. We demonstrate the application of our method to segmenting nuclei from a variety of imaging modalities, and quantitatively compare our results to several other methods. Quantitative results using both simulated and real image data show that, while certain methods may work well for certain imaging modalities, our software is able to obtain high accuracy across several imaging modalities studied. Results also demonstrate that, relative to several existing methods, the template-based method we propose presents increased robustness in the sense of better handling variations in illumination, variations in texture from different imaging modalities, providing more smooth and accurate segmentation borders, as well as handling better cluttered nuclei. PMID:23568787

Patterns of diagnostic imaging and associated radiation exposure among long-term survivors of young adult cancer: a population-based cohort study.

PubMed

Daly, Corinne; Urbach, David R; Stukel, Thérèse A; Nathan, Paul C; Deitel, Wayne; Paszat, Lawrence F; Wilton, Andrew S; Baxter, Nancy N

2015-09-03

Survivors of young adult malignancies are at risk of accumulated exposures to radiation from repetitive diagnostic imaging. We designed a population-based cohort study to describe patterns of diagnostic imaging and cumulative diagnostic radiation exposure among survivors of young adult cancer during a survivorship time period where surveillance imaging is not typically warranted. Young adults aged 20-44 diagnosed with invasive malignancy in Ontario from 1992-1999 who lived at least 5 years from diagnosis were identified using the Ontario Cancer Registry and matched 5 to 1 to randomly selected cancer-free persons. We determined receipt of 5 modalities of diagnostic imaging and associated radiation dose received by survivors and controls from years 5-15 after diagnosis or matched referent date through administrative data. Matched pairs were censored six months prior to evidence of recurrence. 20,911 survivors and 104,524 controls had a median of 13.5 years observation. Survivors received all modalities of diagnostic imaging at significantly higher rates than controls. Survivors received CT at a 3.49-fold higher rate (95% Confidence Interval [CI]:3.37, 3.62) than controls in years 5 to 15 after diagnosis. Survivors received a mean radiation dose of 26 miliSieverts solely from diagnostic imaging in the same time period, a 4.57-fold higher dose than matched controls (95% CI: 4.39, 4.81). Long-term survivors of young adult cancer have a markedly higher rate of diagnostic imaging over time than matched controls, imaging associated with substantial radiation exposure, during a time period when surveillance is not routinely recommended.

Chromatic blur perception in the presence of luminance contrast.

PubMed

Jennings, Ben J; Kingdom, Frederick A A

2017-06-01

Hel-Or showed that blurring the chromatic but not the luminance layer of an image of a natural scene failed to elicit any impression of blur. Subsequent studies have suggested that this effect is due either to chromatic blur being masked by spatially contiguous luminance edges in the scene (Journal of Vision 13 (2013) 14), or to a relatively compressed transducer function for chromatic blur (Journal of Vision 15 (2015) 6). To test between the two explanations we conducted experiments using as stimuli both images of natural scenes as well as simple edges. First, we found that in color-and-luminance images of natural scenes more chromatic blur was needed to perceptually match a given level of blur in an isoluminant, i.e. colour-only scene. However, when the luminance layer in the scene was rotated relative to the chromatic layer, thus removing the colour-luminance edge correlations, the matched blur levels were near equal. Both results are consistent with Sharman et al.'s explanation. Second, when observers matched the blurs of luminance-only with isoluminant scenes, the matched blurs were equal, against Kingdom et al.'s prediction. Third, we measured the perceived blur in a square-wave as a function of (i) contrast (ii) number of luminance edges and (iii) the relative spatial phase between the colour and luminance edges. We found that the perceived chromatic blur was dependent on both relative phase and the number of luminance edges, or dependent on the luminance contrast if only a single edge is present. We conclude that this Hel-Or effect is largely due to masking of chromatic blur by spatially contiguous luminance edges. Copyright © 2017 Elsevier Ltd. All rights reserved.

Least Median of Squares Filtering of Locally Optimal Point Matches for Compressible Flow Image Registration

PubMed Central

Castillo, Edward; Castillo, Richard; White, Benjamin; Rojo, Javier; Guerrero, Thomas

2012-01-01

Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized, nonlinear least squares, compressible flow model that describes the displacement of a single voxel that lends itself to a simple grid search (block matching) optimization strategy. Spatially inaccurate grid search point matches, corresponding to erroneous local minimizers of the nonlinear compressible flow model, are removed by a novel filtering approach based on least median of squares fitting and the forward search outlier detection method. The spatial accuracy of the method is measured using ten thoracic CT image sets and large samples of expert determined landmarks (available at www.dir-lab.com). The LFC method produces an average error within the intra-observer error on eight of the ten cases, indicating that the method is capable of achieving a high spatial accuracy for thoracic CT registration. PMID:22797602

Block Adjustment and Image Matching of WORLDVIEW-3 Stereo Pairs and Accuracy Evaluation

NASA Astrophysics Data System (ADS)

Zuo, C.; Xiao, X.; Hou, Q.; Li, B.

2018-05-01

WorldView-3, as a high-resolution commercial earth observation satellite, which is launched by Digital Global, provides panchromatic imagery of 0.31 m resolution. The positioning accuracy is less than 3.5 meter CE90 without ground control, which can use for large scale topographic mapping. This paper presented the block adjustment for WorldView-3 based on RPC model and achieved the accuracy of 1 : 2000 scale topographic mapping with few control points. On the base of stereo orientation result, this paper applied two kinds of image matching algorithm for DSM extraction: LQM and SGM. Finally, this paper compared the accuracy of the point cloud generated by the two image matching methods with the reference data which was acquired by an airborne laser scanner. The results showed that the RPC adjustment model of WorldView-3 image with small number of GCPs could satisfy the requirement of Chinese Surveying and Mapping regulations for 1 : 2000 scale topographic maps. And the point cloud result obtained through WorldView-3 stereo image matching had higher elevation accuracy, the RMS error of elevation for bare ground area is 0.45 m, while for buildings the accuracy can almost reach 1 meter.

Spot the match – wildlife photo-identification using information theory

PubMed Central

Speed, Conrad W; Meekan, Mark G; Bradshaw, Corey JA

2007-01-01

Background Effective approaches for the management and conservation of wildlife populations require a sound knowledge of population demographics, and this is often only possible through mark-recapture studies. We applied an automated spot-recognition program (I3S) for matching natural markings of wildlife that is based on a novel information-theoretic approach to incorporate matching uncertainty. Using a photo-identification database of whale sharks (Rhincodon typus) as an example case, the information criterion (IC) algorithm we developed resulted in a parsimonious ranking of potential matches of individuals in an image library. Automated matches were compared to manual-matching results to test the performance of the software and algorithm. Results Validation of matched and non-matched images provided a threshold IC weight (approximately 0.2) below which match certainty was not assured. Most images tested were assigned correctly; however, scores for the by-eye comparison were lower than expected, possibly due to the low sample size. The effect of increasing horizontal angle of sharks in images reduced matching likelihood considerably. There was a negative linear relationship between the number of matching spot pairs and matching score, but this relationship disappeared when using the IC algorithm. Conclusion The software and use of easily applied information-theoretic scores of match parsimony provide a reliable and freely available method for individual identification of wildlife, with wide applications and the potential to improve mark-recapture studies without resorting to invasive marking techniques. PMID:17227581

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.

PubMed

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-28

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database

PubMed Central

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-01

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m. PMID:26828496

Quantitative evaluation of susceptibility effects caused by dental materials in head magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Strocchi, S.; Ghielmi, M.; Basilico, F.; Macchi, A.; Novario, R.; Ferretti, R.; Binaghi, E.

2016-03-01

This work quantitatively evaluates the effects induced by susceptibility characteristics of materials commonly used in dental practice on the quality of head MR images in a clinical 1.5T device. The proposed evaluation procedure measures the image artifacts induced by susceptibility in MR images by providing an index consistent with the global degradation as perceived by the experts. Susceptibility artifacts were evaluated in a near-clinical setup, using a phantom with susceptibility and geometric characteristics similar to that of a human head. We tested different dentist materials, called PAL Keramit, Ti6Al4V-ELI, Keramit NP, ILOR F, Zirconia and used different clinical MR acquisition sequences, such as "classical" SE and fast, gradient, and diffusion sequences. The evaluation is designed as a matching process between reference and artifacts affected images recording the same scene. The extent of the degradation induced by susceptibility is then measured in terms of similarity with the corresponding reference image. The matching process involves a multimodal registration task and the use an adequate similarity index psychophysically validated, based on correlation coefficient. The proposed analyses are integrated within a computer-supported procedure that interactively guides the users in the different phases of the evaluation method. 2-Dimensional and 3-dimensional indexes are used for each material and each acquisition sequence. From these, we drew a ranking of the materials, averaging the results obtained. Zirconia and ILOR F appear to be the best choice from the susceptibility artefacts point of view, followed, in order, by PAL Keramit, Ti6Al4V-ELI and Keramit NP.

Sensitivity analysis for future space missions with segmented telescopes for high-contrast imaging

NASA Astrophysics Data System (ADS)

Leboulleux, Lucie; Pueyo, Laurent; Sauvage, Jean-François; Mazoyer, Johan; Soummer, Remi; Fusco, Thierry; Sivaramakrishnan, Anand

2018-01-01

The detection and analysis of biomarkers on earth-like planets using direct-imaging will require both high-contrast imaging and spectroscopy at very close angular separation (10^10 star to planet flux ratio at a few 0.1”). This goal can only be achieved with large telescopes in space to overcome atmospheric turbulence, often combined with a coronagraphic instrument with wavefront control. Large segmented space telescopes such as studied for the LUVOIR mission will generate segment-level instabilities and cophasing errors in addition to local mirror surface errors and other aberrations of the overall optical system. These effects contribute directly to the degradation of the final image quality and contrast. We present an analytical model that produces coronagraphic images of a segmented pupil telescope in the presence of segment phasing aberrations expressed as Zernike polynomials. This model relies on a pair-based projection of the segmented pupil and provides results that match an end-to-end simulation with an rms error on the final contrast of ~3%. This analytical model can be applied both to static and dynamic modes, and either in monochromatic or broadband light. It retires the need for end-to-end Monte-Carlo simulations that are otherwise needed to build a rigorous error budget, by enabling quasi-instantaneous analytical evaluations. The ability to invert directly the analytical model provides direct constraints and tolerances on all segments-level phasing and aberrations.

A novel retinal vessel extraction algorithm based on matched filtering and gradient vector flow

NASA Astrophysics Data System (ADS)

Yu, Lei; Xia, Mingliang; Xuan, Li

2013-10-01

The microvasculature network of retina plays an important role in the study and diagnosis of retinal diseases (age-related macular degeneration and diabetic retinopathy for example). Although it is possible to noninvasively acquire high-resolution retinal images with modern retinal imaging technologies, non-uniform illumination, the low contrast of thin vessels and the background noises all make it difficult for diagnosis. In this paper, we introduce a novel retinal vessel extraction algorithm based on gradient vector flow and matched filtering to segment retinal vessels with different likelihood. Firstly, we use isotropic Gaussian kernel and adaptive histogram equalization to smooth and enhance the retinal images respectively. Secondly, a multi-scale matched filtering method is adopted to extract the retinal vessels. Then, the gradient vector flow algorithm is introduced to locate the edge of the retinal vessels. Finally, we combine the results of matched filtering method and gradient vector flow algorithm to extract the vessels at different likelihood levels. The experiments demonstrate that our algorithm is efficient and the intensities of vessel images exactly represent the likelihood of the vessels.

Evolutionary Fuzzy Block-Matching-Based Camera Raw Image Denoising.

PubMed

Yang, Chin-Chang; Guo, Shu-Mei; Tsai, Jason Sheng-Hong

2017-09-01

An evolutionary fuzzy block-matching-based image denoising algorithm is proposed to remove noise from a camera raw image. Recently, a variance stabilization transform is widely used to stabilize the noise variance, so that a Gaussian denoising algorithm can be used to remove the signal-dependent noise in camera sensors. However, in the stabilized domain, the existed denoising algorithm may blur too much detail. To provide a better estimate of the noise-free signal, a new block-matching approach is proposed to find similar blocks by the use of a type-2 fuzzy logic system (FLS). Then, these similar blocks are averaged with the weightings which are determined by the FLS. Finally, an efficient differential evolution is used to further improve the performance of the proposed denoising algorithm. The experimental results show that the proposed denoising algorithm effectively improves the performance of image denoising. Furthermore, the average performance of the proposed method is better than those of two state-of-the-art image denoising algorithms in subjective and objective measures.

Colorization and Automated Segmentation of Human T2 MR Brain Images for Characterization of Soft Tissues

PubMed Central

Attique, Muhammad; Gilanie, Ghulam; Hafeez-Ullah; Mehmood, Malik S.; Naweed, Muhammad S.; Ikram, Masroor; Kamran, Javed A.; Vitkin, Alex

2012-01-01

Characterization of tissues like brain by using magnetic resonance (MR) images and colorization of the gray scale image has been reported in the literature, along with the advantages and drawbacks. Here, we present two independent methods; (i) a novel colorization method to underscore the variability in brain MR images, indicative of the underlying physical density of bio tissue, (ii) a segmentation method (both hard and soft segmentation) to characterize gray brain MR images. The segmented images are then transformed into color using the above-mentioned colorization method, yielding promising results for manual tracing. Our color transformation incorporates the voxel classification by matching the luminance of voxels of the source MR image and provided color image by measuring the distance between them. The segmentation method is based on single-phase clustering for 2D and 3D image segmentation with a new auto centroid selection method, which divides the image into three distinct regions (gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using prior anatomical knowledge). Results have been successfully validated on human T2-weighted (T2) brain MR images. The proposed method can be potentially applied to gray-scale images from other imaging modalities, in bringing out additional diagnostic tissue information contained in the colorized image processing approach as described. PMID:22479421

Quantitative differential phase contrast imaging at high resolution with radially asymmetric illumination.

PubMed

Lin, Yu-Zi; Huang, Kuang-Yuh; Luo, Yuan

2018-06-15

Half-circle illumination-based differential phase contrast (DPC) microscopy has been utilized to recover phase images through a pair of images along multiple axes. Recently, the half-circle based DPC using 12-axis measurements significantly provides a circularly symmetric phase transfer function to improve accuracy for more stable phase recovery. Instead of using half-circle-based DPC, we propose a new scheme of DPC under radially asymmetric illumination to achieve circularly symmetric phase transfer function and enhance the accuracy of phase recovery in a more stable and efficient fashion. We present the design, implementation, and experimental image data demonstrating the ability of our method to obtain quantitative phase images of microspheres, as well as live fibroblast cell samples.

3D-shape of objects with straight line-motion by simultaneous projection of color coded patterns

NASA Astrophysics Data System (ADS)

Flores, Jorge L.; Ayubi, Gaston A.; Di Martino, J. Matías; Castillo, Oscar E.; Ferrari, Jose A.

2018-05-01

In this work, we propose a novel technique to retrieve the 3D shape of dynamic objects by the simultaneous projection of a fringe pattern and a homogeneous light pattern which are both coded in two of the color channels of a RGB image. The fringe pattern, red channel, is used to retrieve the phase by phase-shift algorithms with arbitrary phase-step, while the homogeneous pattern, blue channel, is used to match pixels from the test object in consecutive images, which are acquired at different positions, and thus, to determine the speed of the object. The proposed method successfully overcomes the standard requirement of projecting fringes of two different frequencies; one frequency to extract object information and the other one to retrieve the phase. Validation experiments are presented.

Anharmonic phonon-polariton dynamics in ferroelectric LiNbO3 studied with single-shot pump-probe imaging spectroscopy

NASA Astrophysics Data System (ADS)

Kuribayashi, T.; Motoyama, T.; Arashida, Y.; Katayama, I.; Takeda, J.

2018-05-01

We demonstrate that single-shot pump-probe imaging spectroscopy with an echelon mirror enables us to disclose the ferroelectric phonon-polariton dynamics across a wide temperature range from 10 K to 375 K while avoiding the photorefractive effects that appear prominently at low temperatures. The E-mode phonon-polaritons corresponding to the two transverse optical modes, TO1 and TO3, up to ˜7 THz were induced in LiNbO3 through an impulsive stimulated Raman scattering process. Subsequently, using single-shot pump-probe imaging spectroscopy over a minimal cumulative time, we successfully visualized the phonon-polariton dynamics in time-wavelength space even at low temperatures. We found that the phase-matching condition significantly affected the observed temperature-dependent phonon-polariton frequency shift. The anharmonicity of the TO1 and TO3 modes was then evaluated based on an anharmonic model involving higher-order interactions with acoustic phonons while eliminating the influence of the frequency shift due to the phase-matching condition. The observed wavenumber-dependent damping rate was analyzed by considering the bilinear coupling of the TO1 or TO3 modes with the thermally activated relaxation mode. We found that the phonon-polariton with a higher frequency and wavenumber had a higher damping rate at high temperatures because of its frequent interaction with the thermally activated relaxation mode and acoustic phonons. The TO3 mode displayed greater bilinear coupling than the TO1 mode, which may also have contributed to the observed high damping rate. Thus, using our unique single-shot spectroscopy technique, we could reveal the overall anharmonic characteristics of the E-mode phonon-polaritons arising from both the acoustic phonons and the relaxation mode.

Impact of CT attenuation correction method on quantitative respiratory-correlated (4D) PET/CT imaging

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

Nyflot, Matthew J., E-mail: nyflot@uw.edu; Lee, Tzu-Cheng; Alessio, Adam M.

Purpose: Respiratory-correlated positron emission tomography (PET/CT) 4D PET/CT is used to mitigate errors from respiratory motion; however, the optimal CT attenuation correction (CTAC) method for 4D PET/CT is unknown. The authors performed a phantom study to evaluate the quantitative performance of CTAC methods for 4D PET/CT in the ground truth setting. Methods: A programmable respiratory motion phantom with a custom movable insert designed to emulate a lung lesion and lung tissue was used for this study. The insert was driven by one of five waveforms: two sinusoidal waveforms or three patient-specific respiratory waveforms. 3DPET and 4DPET images of the phantommore » under motion were acquired and reconstructed with six CTAC methods: helical breath-hold (3DHEL), helical free-breathing (3DMOT), 4D phase-averaged (4DAVG), 4D maximum intensity projection (4DMIP), 4D phase-matched (4DMATCH), and 4D end-exhale (4DEXH) CTAC. Recovery of SUV{sub max}, SUV{sub mean}, SUV{sub peak}, and segmented tumor volume was evaluated as RC{sub max}, RC{sub mean}, RC{sub peak}, and RC{sub vol}, representing percent difference relative to the static ground truth case. Paired Wilcoxon tests and Kruskal–Wallis ANOVA were used to test for significant differences. Results: For 4DPET imaging, the maximum intensity projection CTAC produced significantly more accurate recovery coefficients than all other CTAC methods (p < 0.0001 over all metrics). Over all motion waveforms, ratios of 4DMIP CTAC recovery were 0.2 ± 5.4, −1.8 ± 6.5, −3.2 ± 5.0, and 3.0 ± 5.9 for RC{sub max}, RC{sub peak}, RC{sub mean}, and RC{sub vol}. In comparison, recovery coefficients for phase-matched CTAC were −8.4 ± 5.3, −10.5 ± 6.2, −7.6 ± 5.0, and −13.0 ± 7.7 for RC{sub max}, RC{sub peak}, RC{sub mean}, and RC{sub vol}. When testing differences between phases over all CTAC methods and waveforms, end-exhale phases were significantly more accurate (p = 0.005). However, these differences were driven by the patient-specific respiratory waveforms; when testing patient and sinusoidal waveforms separately, patient waveforms were significantly different between phases (p < 0.0001) while the sinusoidal waveforms were not significantly different (p = 0.98). When considering only the subset of 4DMATCH images that corresponded to the end-exhale image phase, 4DEXH, mean and interquartile range were similar to 4DMATCH but variability was considerably reduced. Conclusions: Comparative advantages in accuracy and precision of SUV metrics and segmented volumes were demonstrated with the use of the maximum intensity projection and end-exhale CT attenuation correction. While respiratory phase-matched CTAC should in theory provide optimal corrections, image artifacts and differences in implementation of 4DCT and 4DPET sorting can degrade the benefit of this approach. These results may be useful to guide the implementation, analysis, and development of respiratory-correlated thoracic PET/CT in the radiation oncology and diagnostic settings.« less

Automated Image Registration Using Morphological Region of Interest Feature Extraction

NASA Technical Reports Server (NTRS)

Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

2005-01-01

With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

Inspection of aeronautical mechanical parts with a pan-tilt-zoom camera: an approach guided by the computer-aided design model

NASA Astrophysics Data System (ADS)

Viana, Ilisio; Orteu, Jean-José; Cornille, Nicolas; Bugarin, Florian

2015-11-01

We focus on quality control of mechanical parts in aeronautical context using a single pan-tilt-zoom (PTZ) camera and a computer-aided design (CAD) model of the mechanical part. We use the CAD model to create a theoretical image of the element to be checked, which is further matched with the sensed image of the element to be inspected, using a graph theory-based approach. The matching is carried out in two stages. First, the two images are used to create two attributed graphs representing the primitives (ellipses and line segments) in the images. In the second stage, the graphs are matched using a similarity function built from the primitive parameters. The similarity scores of the matching are injected in the edges of a bipartite graph. A best-match-search procedure in the bipartite graph guarantees the uniqueness of the match solution. The method achieves promising performance in tests with synthetic data including missing elements, displaced elements, size changes, and combinations of these cases. The results open good prospects for using the method with realistic data.

Phase matched parametric amplification via four-wave mixing in optical microfibers.

PubMed

Abdul Khudus, Muhammad I M; De Lucia, Francesco; Corbari, Costantino; Lee, Timothy; Horak, Peter; Sazio, Pier; Brambilla, Gilberto

2016-02-15

Four-wave mixing (FWM) based parametric amplification in optical microfibers (OMFs) is demonstrated over a wavelength range of over 1000 nm by exploiting their tailorable dispersion characteristics to achieve phase matching. Simulations indicate that for any set of wavelengths satisfying the FWM energy conservation condition there are two diameters at which phase matching in the fundamental mode can occur. Experiments with a high-power pulsed source working in conjunction with a periodically poled silica fiber (PPSF), producing both fundamental and second harmonic signals, are undertaken to investigate the possibility of FWM parametric amplification in OMFs. Large increases of idler output power at the third harmonic wavelength were recorded for diameters close to the two phase matching diameters. A total amplification of more than 25 dB from the initial signal was observed in a 6 mm long optical microfiber, after accounting for the thermal drift of the PPSF and other losses in the system.

Multiple Semantic Matching on Augmented N-partite Graph for Object Co-segmentation.

PubMed

Wang, Chuan; Zhang, Hua; Yang, Liang; Cao, Xiaochun; Xiong, Hongkai

2017-09-08

Recent methods for object co-segmentation focus on discovering single co-occurring relation of candidate regions representing the foreground of multiple images. However, region extraction based only on low and middle level information often occupies a large area of background without the help of semantic context. In addition, seeking single matching solution very likely leads to discover local parts of common objects. To cope with these deficiencies, we present a new object cosegmentation framework, which takes advantages of semantic information and globally explores multiple co-occurring matching cliques based on an N-partite graph structure. To this end, we first propose to incorporate candidate generation with semantic context. Based on the regions extracted from semantic segmentation of each image, we design a merging mechanism to hierarchically generate candidates with high semantic responses. Secondly, all candidates are taken into consideration to globally formulate multiple maximum weighted matching cliques, which complements the discovery of part of the common objects induced by a single clique. To facilitate the discovery of multiple matching cliques, an N-partite graph, which inherently excludes intralinks between candidates from the same image, is constructed to separate multiple cliques without additional constraints. Further, we augment the graph with an additional virtual node in each part to handle irrelevant matches when the similarity between two candidates is too small. Finally, with the explored multiple cliques, we statistically compute pixel-wise co-occurrence map for each image. Experimental results on two benchmark datasets, i.e., iCoseg and MSRC datasets, achieve desirable performance and demonstrate the effectiveness of our proposed framework.

Design of compactly supported wavelet to match singularities in medical images

NASA Astrophysics Data System (ADS)

Fung, Carrson C.; Shi, Pengcheng

2002-11-01

Analysis and understanding of medical images has important clinical values for patient diagnosis and treatment, as well as technical implications for computer vision and pattern recognition. One of the most fundamental issues is the detection of object boundaries or singularities, which is often the basis for further processes such as organ/tissue recognition, image registration, motion analysis, measurement of anatomical and physiological parameters, etc. The focus of this work involved taking a correlation based approach toward edge detection, by exploiting some of desirable properties of wavelet analysis. This leads to the possibility of constructing a bank of detectors, consisting of multiple wavelet basis functions of different scales which are optimal for specific types of edges, in order to optimally detect all the edges in an image. Our work involved developing a set of wavelet functions which matches the shape of the ramp and pulse edges. The matching algorithm used focuses on matching the edges in the frequency domain. It was proven that this technique could create matching wavelets applicable at all scales. Results have shown that matching wavelets can be obtained for the pulse edge while the ramp edge requires another matching algorithm.

Optomechanical design and analysis of a self-adaptive mounting method for optimizing phase matching of large potassium dihydrogen phosphate converter

NASA Astrophysics Data System (ADS)

Zhang, Zheng; Tian, Menjiya; Quan, Xusong; Pei, Guoqing; Wang, Hui; Liu, Tianye; Long, Kai; Xiong, Zhao; Rong, Yiming

2017-11-01

Surface control and phase matching of large laser conversion optics are urgent requirements and huge challenges in high-power solid-state laser facilities. A self-adaptive, nanocompensating mounting configuration of a large aperture potassium dihydrogen phosphate (KDP) frequency doubler is proposed based on a lever-type surface correction mechanism. A mechanical, numerical, and optical model is developed and employed to evaluate comprehensive performance of this mounting method. The results validate the method's advantages of surface adjustment and phase matching improvement. In addition, the optimal value of the modulation force is figured out through a series of simulations and calculations.

3D temporal subtraction on multislice CT images using nonlinear warping technique

NASA Astrophysics Data System (ADS)

Ishida, Takayuki; Katsuragawa, Shigehiko; Kawashita, Ikuo; Kim, Hyounseop; Itai, Yoshinori; Awai, Kazuo; Li, Qiang; Doi, Kunio

2007-03-01

The detection of very subtle lesions and/or lesions overlapped with vessels on CT images is a time consuming and difficult task for radiologists. In this study, we have developed a 3D temporal subtraction method to enhance interval changes between previous and current multislice CT images based on a nonlinear image warping technique. Our method provides a subtraction CT image which is obtained by subtraction of a previous CT image from a current CT image. Reduction of misregistration artifacts is important in the temporal subtraction method. Therefore, our computerized method includes global and local image matching techniques for accurate registration of current and previous CT images. For global image matching, we selected the corresponding previous section image for each current section image by using 2D cross-correlation between a blurred low-resolution current CT image and a blurred previous CT image. For local image matching, we applied the 3D template matching technique with translation and rotation of volumes of interests (VOIs) which were selected in the current and the previous CT images. The local shift vector for each VOI pair was determined when the cross-correlation value became the maximum in the 3D template matching. The local shift vectors at all voxels were determined by interpolation of shift vectors of VOIs, and then the previous CT image was nonlinearly warped according to the shift vector for each voxel. Finally, the warped previous CT image was subtracted from the current CT image. The 3D temporal subtraction method was applied to 19 clinical cases. The normal background structures such as vessels, ribs, and heart were removed without large misregistration artifacts. Thus, interval changes due to lung diseases were clearly enhanced as white shadows on subtraction CT images.

Epipolar Rectification for CARTOSAT-1 Stereo Images Using SIFT and RANSAC

NASA Astrophysics Data System (ADS)

Akilan, A.; Sudheer Reddy, D.; Nagasubramanian, V.; Radhadevi, P. V.; Varadan, G.

2014-11-01

Cartosat-1 provides stereo images of spatial resolution 2.5 m with high fidelity of geometry. Stereo camera on the spacecraft has look angles of +26 degree and -5 degree respectively that yields effective along track stereo. Any DSM generation algorithm can use the stereo images for accurate 3D reconstruction and measurement of ground. Dense match points and pixel-wise matching are prerequisite in DSM generation to capture discontinuities and occlusions for accurate 3D modelling application. Epipolar image matching reduces the computational effort from two dimensional area searches to one dimensional. Thus, epipolar rectification is preferred as a pre-processing step for accurate DSM generation. In this paper we explore a method based on SIFT and RANSAC for epipolar rectification of cartosat-1 stereo images.

Integrating image quality in 2nu-SVM biometric match score fusion.

PubMed

Vatsa, Mayank; Singh, Richa; Noore, Afzel

2007-10-01

This paper proposes an intelligent 2nu-support vector machine based match score fusion algorithm to improve the performance of face and iris recognition by integrating the quality of images. The proposed algorithm applies redundant discrete wavelet transform to evaluate the underlying linear and non-linear features present in the image. A composite quality score is computed to determine the extent of smoothness, sharpness, noise, and other pertinent features present in each subband of the image. The match score and the corresponding quality score of an image are fused using 2nu-support vector machine to improve the verification performance. The proposed algorithm is experimentally validated using the FERET face database and the CASIA iris database. The verification performance and statistical evaluation show that the proposed algorithm outperforms existing fusion algorithms.

Measuring the Refractive Index of Bovine Corneal Stromal Cells Using Quantitative Phase Imaging

PubMed Central

Gardner, Steven J.; White, Nick; Albon, Julie; Knupp, Carlo; Kamma-Lorger, Christina S.; Meek, Keith M.

2015-01-01

The cornea is the primary refractive lens in the eye and transmits >90% of incident visible light. It has been suggested that the development of postoperative corneal haze could be due to an increase in light scattering from activated corneal stromal cells. Quiescent keratocytes are thought to produce crystallins that match the refractive index of their cytoplasm to the surrounding extracellular material, reducing the amount of light scattering. To test this, we measured the refractive index (RI) of bovine corneal stromal cells, using quantitative phase imaging of live cells in vitro, together with confocal microscopy. The RI of quiescent keratocytes (RI = 1.381 ± 0.004) matched the surrounding matrix, thus supporting the hypothesis that keratocyte cytoplasm does not scatter light in the normal cornea. We also observed that the RI drops after keratocyte activation (RI = 1.365 ± 0.003), leading to a mismatch with the surrounding intercellular matrix. Theoretical scattering models showed that this mismatch would reduce light transmission in the cornea. We conclude that corneal transparency depends on the matching of refractive indices between quiescent keratocytes and the surrounding tissue, and that after surgery or wounding, the resulting RI mismatch between the activated cells and their surrounds significantly contributes to light scattering. PMID:26488650

Autocorrelation techniques for soft photogrammetry

NASA Astrophysics Data System (ADS)

Yao, Wu

In this thesis research is carried out on image processing, image matching searching strategies, feature type and image matching, and optimal window size in image matching. To make comparisons, the soft photogrammetry package SoftPlotter is used. Two aerial photographs from the Iowa State University campus high flight 94 are scanned into digital format. In order to create a stereo model from them, interior orientation, single photograph rectification and stereo rectification are done. Two new image matching methods, multi-method image matching (MMIM) and unsquare window image matching are developed and compared. MMIM is used to determine the optimal window size in image matching. Twenty four check points from four different types of ground features are used for checking the results from image matching. Comparison between these four types of ground feature shows that the methods developed here improve the speed and the precision of image matching. A process called direct transformation is described and compared with the multiple steps in image processing. The results from image processing are consistent with those from SoftPlotter. A modified LAN image header is developed and used to store the information about the stereo model and image matching. A comparison is also made between cross correlation image matching (CCIM), least difference image matching (LDIM) and least square image matching (LSIM). The quality of image matching in relation to ground features are compared using two methods developed in this study, the coefficient surface for CCIM and the difference surface for LDIM. To reduce the amount of computation in image matching, the best-track searching algorithm, developed in this research, is used instead of the whole range searching algorithm.

Use of localized performance-based functions for the specification and correction of hybrid imaging systems

NASA Astrophysics Data System (ADS)

Lisson, Jerold B.; Mounts, Darryl I.; Fehniger, Michael J.

1992-08-01

Localized wavefront performance analysis (LWPA) is a system that allows the full utilization of the system optical transfer function (OTF) for the specification and acceptance of hybrid imaging systems. We show that LWPA dictates the correction of wavefront errors with the greatest impact on critical imaging spatial frequencies. This is accomplished by the generation of an imaging performance map-analogous to a map of the optic pupil error-using a local OTF. The resulting performance map a function of transfer function spatial frequency is directly relatable to the primary viewing condition of the end-user. In addition to optimizing quality for the viewer it will be seen that the system has the potential for an improved matching of the optical and electronic bandpass of the imager and for the development of more realistic acceptance specifications. 1. LOCAL WAVEFRONT PERFORMANCE ANALYSIS The LWPA system generates a local optical quality factor (LOQF) in the form of a map analogous to that used for the presentation and evaluation of wavefront errors. In conjunction with the local phase transfer function (LPTF) it can be used for maximally efficient specification and correction of imaging system pupil errors. The LOQF and LPTF are respectively equivalent to the global modulation transfer function (MTF) and phase transfer function (PTF) parts of the OTF. The LPTF is related to difference of the average of the errors in separated regions of the pupil. Figure

Quantitative ultrasonic testing of acoustically anisotropic materials with verification on austenitic and dissimilar weld joints

NASA Astrophysics Data System (ADS)

Boller, C.; Pudovikov, S.; Bulavinov, A.

2012-05-01

Austenitic stainless steel materials are widely used in a variety of industry sectors. In particular, the material is qualified to meet the design criteria of high quality in safety related applications. For example, the primary loop of the most of the nuclear power plants in the world, due to high durability and corrosion resistance, is made of this material. Certain operating conditions may cause a range of changes in the integrity of the component, and therefore require nondestructive testing at reasonable intervals. These in-service inspections are often performed using ultrasonic techniques, in particular when cracking is of specific concern. However, the coarse, dendritic grain structure of the weld material, formed during the welding process, is extreme and unpredictably anisotropic. Such structure is no longer direction-independent to the ultrasonic wave propagation; therefore, the ultrasonic beam deflects and redirects and the wave front becomes distorted. Thus, the use of conventional ultrasonic testing techniques using fixed beam angles is very limited and the application of ultrasonic Phased Array techniques becomes desirable. The "Sampling Phased Array" technique, invented and developed by Fraunhofer IZFP, allows the acquisition of time signals (A-scans) for each individual transducer element of the array along with fast image reconstruction techniques based on synthetic focusing algorithms. The reconstruction considers the sound propagation from each image pixel to the individual sensor element. For anisotropic media, where the sound beam is deflected and the sound path is not known a-priori, a novel phase adjustment technique called "Reverse Phase Matching" is implemented. By taking into account the anisotropy and inhomogeneity of the weld structure, a ray tracing algorithm for modeling the acoustic wave propagation and calculating the sound propagation time is applied. This technique can be utilized for 2D and 3D real time image reconstruction. The "Gradient Constant Descent Method" (GECDM), an iterative algorithm, is implemented, which is essential for examination of inhomogeneous anisotropic media having unknown properties (elastic constants). The Sampling Phased Array technique with Reverse Phase Matching extended by GECDM-technique determines unknown elastic constants and provides reliable and efficient quantitative flaw detection in the austenitic welds. The validation of ray-tracing algorithm and GECDM-method is performed by number of experiments on test specimens with artificial as well as natural material flaws. A mechanized system for ultrasonic testing of stainless steel and dissimilar welds is developed. The system works on both conventional and Sampling Phased Array techniques. The new frontend ultrasonic unit with optical data link allows the 3D visualization of the inspection results in real time.

Detection of urban expansion in an urban-rural landscape with multitemporal QuickBird images

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio; Li, Guiying

2011-01-01

Accurately detecting urban expansion with remote sensing techniques is a challenge due to the complexity of urban landscapes. This paper explored methods for detecting urban expansion with multitemporal QuickBird images in Lucas do Rio Verde, Mato Grosso, Brazil. Different techniques, including image differencing, principal component analysis (PCA), and comparison of classified impervious surface images with the matched filtering method, were used to examine urbanization detection. An impervious surface image classified with the hybrid method was used to modify the urbanization detection results. As a comparison, the original multispectral image and segmentation-based mean-spectral images were used during the detection of urbanization. This research indicates that the comparison of classified impervious surface images with matched filtering method provides the best change detection performance, followed by the image differencing method based on segmentation-based mean spectral images. The PCA is not a good method for urban change detection in this study. Shadows and high spectral variation within the impervious surfaces represent major challenges to the detection of urban expansion when high spatial resolution images are used. PMID:21799706

Bilateral filtering using the full noise covariance matrix applied to x-ray phase-contrast computed tomography.

PubMed

Allner, S; Koehler, T; Fehringer, A; Birnbacher, L; Willner, M; Pfeiffer, F; Noël, P B

2016-05-21

The purpose of this work is to develop an image-based de-noising algorithm that exploits complementary information and noise statistics from multi-modal images, as they emerge in x-ray tomography techniques, for instance grating-based phase-contrast CT and spectral CT. Among the noise reduction methods, image-based de-noising is one popular approach and the so-called bilateral filter is a well known algorithm for edge-preserving filtering. We developed a generalization of the bilateral filter for the case where the imaging system provides two or more perfectly aligned images. The proposed generalization is statistically motivated and takes the full second order noise statistics of these images into account. In particular, it includes a noise correlation between the images and spatial noise correlation within the same image. The novel generalized three-dimensional bilateral filter is applied to the attenuation and phase images created with filtered backprojection reconstructions from grating-based phase-contrast tomography. In comparison to established bilateral filters, we obtain improved noise reduction and at the same time a better preservation of edges in the images on the examples of a simulated soft-tissue phantom, a human cerebellum and a human artery sample. The applied full noise covariance is determined via cross-correlation of the image noise. The filter results yield an improved feature recovery based on enhanced noise suppression and edge preservation as shown here on the example of attenuation and phase images captured with grating-based phase-contrast computed tomography. This is supported by quantitative image analysis. Without being bound to phase-contrast imaging, this generalized filter is applicable to any kind of noise-afflicted image data with or without noise correlation. Therefore, it can be utilized in various imaging applications and fields.

X-ray fast tomography and its applications in dynamical phenomena studies in geosciences at Advanced Photon Source

NASA Astrophysics Data System (ADS)

Xiao, Xianghui; Fusseis, Florian; De Carlo, Francesco

2012-10-01

State-of-art synchrotron radiation based micro-computed tomography provides high spatial and temporal resolution. This matches the needs of many research problems in geosciences. In this letter we report the current capabilities in microtomography at sector 2BM at the Advanced Photon Source (APS) of Argonne National Laboratory. The beamline is well suited to routinely acquire three-dimensional data of excellent quality with sub-micron resolution. Fast cameras in combination with a polychromatic beam allow time-lapse experiments with temporal resolutions of down to 200 ms. Data processing utilizes quantitative phase retrieval to optimize contrast in phase contrast tomographic data. The combination of these capabilities with purpose-designed experimental cells allows for a wide range of dynamic studies on geoscientific topics, two of which are summarized here. In the near future, new experimental cells capable of simulating conditions in most geological reservoirs will be available for general use. Ultimately, these advances will be matched by a new wide-field imaging beam line, which will be constructed as part of the APS upgrade. It is expected that even faster tomography with larger field of view can be conducted at this beam line, creating new opportunities for geoscientific studies.

Integration of prior knowledge into dense image matching for video surveillance

NASA Astrophysics Data System (ADS)

Menze, M.; Heipke, C.

2014-08-01

Three-dimensional information from dense image matching is a valuable input for a broad range of vision applications. While reliable approaches exist for dedicated stereo setups they do not easily generalize to more challenging camera configurations. In the context of video surveillance the typically large spatial extent of the region of interest and repetitive structures in the scene render the application of dense image matching a challenging task. In this paper we present an approach that derives strong prior knowledge from a planar approximation of the scene. This information is integrated into a graph-cut based image matching framework that treats the assignment of optimal disparity values as a labelling task. Introducing the planar prior heavily reduces ambiguities together with the search space and increases computational efficiency. The results provide a proof of concept of the proposed approach. It allows the reconstruction of dense point clouds in more general surveillance camera setups with wider stereo baselines.

Hybrid-Based Dense Stereo Matching

NASA Astrophysics Data System (ADS)

Chuang, T. Y.; Ting, H. W.; Jaw, J. J.

2016-06-01

Stereo matching generating accurate and dense disparity maps is an indispensable technique for 3D exploitation of imagery in the fields of Computer vision and Photogrammetry. Although numerous solutions and advances have been proposed in the literature, occlusions, disparity discontinuities, sparse texture, image distortion, and illumination changes still lead to problematic issues and await better treatment. In this paper, a hybrid-based method based on semi-global matching is presented to tackle the challenges on dense stereo matching. To ease the sensitiveness of SGM cost aggregation towards penalty parameters, a formal way to provide proper penalty estimates is proposed. To this end, the study manipulates a shape-adaptive cross-based matching with an edge constraint to generate an initial disparity map for penalty estimation. Image edges, indicating the potential locations of occlusions as well as disparity discontinuities, are approved by the edge drawing algorithm to ensure the local support regions not to cover significant disparity changes. Besides, an additional penalty parameter 𝑃𝑒 is imposed onto the energy function of SGM cost aggregation to specifically handle edge pixels. Furthermore, the final disparities of edge pixels are found by weighting both values derived from the SGM cost aggregation and the U-SURF matching, providing more reliable estimates at disparity discontinuity areas. Evaluations on Middlebury stereo benchmarks demonstrate satisfactory performance and reveal the potency of the hybrid-based dense stereo matching method.

Long term landslide monitoring with Ground Based SAR

NASA Astrophysics Data System (ADS)

Monserrat, Oriol; Crosetto, Michele; Luzi, Guido; Gili, Josep; Moya, Jose; Corominas, Jordi

2014-05-01

In the last decade, Ground-Based (GBSAR) has proven to be a reliable microwave Remote Sensing technique in several application fields, especially for unstable slopes monitoring. GBSAR can provide displacement measurements over few squared kilometres areas and with a very high spatial and temporal resolution. This work is focused on the use of GBSAR technique for long term landslide monitoring based on a particular data acquisition configuration, which is called discontinuous GBSAR (D-GBSAR). In the most commonly used GBSAR configuration, the radar is left installed in situ, acquiring data periodically, e.g. every few minutes. Deformations are estimated by processing sets of GBSAR images acquired during several weeks or months, without moving the system. By contrast, in the D-GBSAR the radar is installed and dismounted at each measurement campaign, revisiting a given site periodically. This configuration is useful to monitor slow deformation phenomena. In this work, two alternative ways for exploiting the D-GBSAR technique will be presented: the DInSAR technique and the Amplitude based Technique. The former is based on the exploitation of the phase component of the acquired SAR images and it allows providing millimetric precision on the deformation estimates. However, this technique presents several limitations like the reduction of measurable points with an increase in the period of observation, the ambiguous nature of the phase measurements, and the influence of the atmospheric phase component that can make it non applicable in some cases, specially when working in natural environments. The second approach, that is based on the use of the amplitude component of GB-SAR images combined with a image matching technique, will allow the estimation of the displacements over specific targets avoiding two of the limitations commented above: the phase unwrapping and atmosphere contribution but reducing the deformation measurement precision. Two successful examples of D-GBSAR landslide monitoring will be analysed and discussed: the first example is based on DInSAR and concerns to an urban landslide located in Barberà de la Conca (Catalonia, Spain). This village has experienced deformations since 2011 that have caused cracks in the church and several buildings. The results of a one year and half monitoring will be shown. The second example is based on the amplitude based approach and concerns to the active landslide of Vallcebre (Eastern Pyrenees, Spain). For this site, the results of eight campaigns during a period of 19 months were performed. During this period displacements of up to 80 cm were measured.

Multiple template-based fluoroscopic tracking of lung tumor mass without implanted fiducial markers

NASA Astrophysics Data System (ADS)

Cui, Ying; Dy, Jennifer G.; Sharp, Gregory C.; Alexander, Brian; Jiang, Steve B.

2007-10-01

Precise lung tumor localization in real time is particularly important for some motion management techniques, such as respiratory gating or beam tracking with a dynamic multi-leaf collimator, due to the reduced clinical tumor volume (CTV) to planning target volume (PTV) margin and/or the escalated dose. There might be large uncertainties in deriving tumor position from external respiratory surrogates. While tracking implanted fiducial markers has sufficient accuracy, this procedure may not be widely accepted due to the risk of pneumothorax. Previously, we have developed a technique to generate gating signals from fluoroscopic images without implanted fiducial markers using a template matching method (Berbeco et al 2005 Phys. Med. Biol. 50 4481-90, Cui et al 2007 Phys. Med. Biol. 52 741-55). In this paper, we present an extension of this method to multiple-template matching for directly tracking the lung tumor mass in fluoroscopy video. The basic idea is as follows: (i) during the patient setup session, a pair of orthogonal fluoroscopic image sequences are taken and processed off-line to generate a set of reference templates that correspond to different breathing phases and tumor positions; (ii) during treatment delivery, fluoroscopic images are continuously acquired and processed; (iii) the similarity between each reference template and the processed incoming image is calculated; (iv) the tumor position in the incoming image is then estimated by combining the tumor centroid coordinates in reference templates with proper weights based on the measured similarities. With different handling of image processing and similarity calculation, two such multiple-template tracking techniques have been developed: one based on motion-enhanced templates and Pearson's correlation score while the other based on eigen templates and mean-squared error. The developed techniques have been tested on six sequences of fluoroscopic images from six lung cancer patients against the reference tumor positions manually determined by a radiation oncologist. The tumor centroid coordinates automatically detected using both methods agree well with the manually marked reference locations. The eigenspace tracking method performs slightly better than the motion-enhanced method, with average localization errors less than 2 pixels (1 mm) and the error at a 95% confidence level of about 2-4 pixels (1-2 mm). This work demonstrates the feasibility of direct tracking of a lung tumor mass in fluoroscopic images without implanted fiducial markers using multiple reference templates.

a Robust Descriptor Based on Spatial and Frequency Structural Information for Visible and Thermal Infrared Image Matching

NASA Astrophysics Data System (ADS)

Fu, Z.; Qin, Q.; Wu, C.; Chang, Y.; Luo, B.

2017-09-01

Due to the differences of imaging principles, image matching between visible and thermal infrared images still exist new challenges and difficulties. Inspired by the complementary spatial and frequency information of geometric structural features, a robust descriptor is proposed for visible and thermal infrared images matching. We first divide two different spatial regions to the region around point of interest, using the histogram of oriented magnitudes, which corresponds to the 2-D structural shape information to describe the larger region and the edge oriented histogram to describe the spatial distribution for the smaller region. Then the two vectors are normalized and combined to a higher feature vector. Finally, our proposed descriptor is obtained by applying principal component analysis (PCA) to reduce the dimension of the combined high feature vector to make our descriptor more robust. Experimental results showed that our proposed method was provided with significant improvements in correct matching numbers and obvious advantages by complementing information within spatial and frequency structural information.

Registration of 2D to 3D joint images using phase-based mutual information

NASA Astrophysics Data System (ADS)

Dalvi, Rupin; Abugharbieh, Rafeef; Pickering, Mark; Scarvell, Jennie; Smith, Paul

2007-03-01

Registration of two dimensional to three dimensional orthopaedic medical image data has important applications particularly in the area of image guided surgery and sports medicine. Fluoroscopy to computer tomography (CT) registration is an important case, wherein digitally reconstructed radiographs derived from the CT data are registered to the fluoroscopy data. Traditional registration metrics such as intensity-based mutual information (MI) typically work well but often suffer from gross misregistration errors when the image to be registered contains a partial view of the anatomy visible in the target image. Phase-based MI provides a robust alternative similarity measure which, in addition to possessing the general robustness and noise immunity that MI provides, also employs local phase information in the registration process which makes it less susceptible to the aforementioned errors. In this paper, we propose using the complex wavelet transform for computing image phase information and incorporating that into a phase-based MI measure for image registration. Tests on a CT volume and 6 fluoroscopy images of the knee are presented. The femur and the tibia in the CT volume were individually registered to the fluoroscopy images using intensity-based MI, gradient-based MI and phase-based MI. Errors in the coordinates of fiducials present in the bone structures were used to assess the accuracy of the different registration schemes. Quantitative results demonstrate that the performance of intensity-based MI was the worst. Gradient-based MI performed slightly better, while phase-based MI results were the best consistently producing the lowest errors.

High energy x-ray phase contrast CT using glancing-angle grating interferometers

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

Sarapata, A., E-mail: adrian.sarapata@tum.de; Stayman, J. W.; Siewerdsen, J. H.

Purpose: The authors present initial progress toward a clinically compatible x-ray phase contrast CT system, using glancing-angle x-ray grating interferometry to provide high contrast soft tissue images at estimated by computer simulation dose levels comparable to conventional absorption based CT. Methods: DPC-CT scans of a joint phantom and of soft tissues were performed in order to answer several important questions from a clinical setup point of view. A comparison between high and low fringe visibility systems is presented. The standard phase stepping method was compared with sliding window interlaced scanning. Using estimated dose values obtained with a Monte-Carlo code themore » authors studied the dependence of the phase image contrast on exposure time and dose. Results: Using a glancing angle interferometer at high x-ray energy (∼45 keV mean value) in combination with a conventional x-ray tube the authors achieved fringe visibility values of nearly 50%, never reported before. High fringe visibility is shown to be an indispensable parameter for a potential clinical scanner. Sliding window interlaced scanning proved to have higher SNRs and CNRs in a region of interest and to also be a crucial part of a low dose CT system. DPC-CT images of a soft tissue phantom at exposures in the range typical for absorption based CT of musculoskeletal extremities were obtained. Assuming a human knee as the CT target, good soft tissue phase contrast could be obtained at an estimated absorbed dose level around 8 mGy, similar to conventional CT. Conclusions: DPC-CT with glancing-angle interferometers provides improved soft tissue contrast over absorption CT even at clinically compatible dose levels (estimated by a Monte-Carlo computer simulation). Further steps in image processing, data reconstruction, and spectral matching could make the technique fully clinically compatible. Nevertheless, due to its increased scan time and complexity the technique should be thought of not as replacing, but as complimentary to conventional CT, to be used in specific applications.« less

An Integrated Photogrammetric and Photoclinometric Approach for Pixel-Resolution 3d Modelling of Lunar Surface

NASA Astrophysics Data System (ADS)

Liu, W. C.; Wu, B.

2018-04-01

High-resolution 3D modelling of lunar surface is important for lunar scientific research and exploration missions. Photogrammetry is known for 3D mapping and modelling from a pair of stereo images based on dense image matching. However dense matching may fail in poorly textured areas and in situations when the image pair has large illumination differences. As a result, the actual achievable spatial resolution of the 3D model from photogrammetry is limited by the performance of dense image matching. On the other hand, photoclinometry (i.e., shape from shading) is characterised by its ability to recover pixel-wise surface shapes based on image intensity and imaging conditions such as illumination and viewing directions. More robust shape reconstruction through photoclinometry can be achieved by incorporating images acquired under different illumination conditions (i.e., photometric stereo). Introducing photoclinometry into photogrammetric processing can therefore effectively increase the achievable resolution of the mapping result while maintaining its overall accuracy. This research presents an integrated photogrammetric and photoclinometric approach for pixel-resolution 3D modelling of the lunar surface. First, photoclinometry is interacted with stereo image matching to create robust and spatially well distributed dense conjugate points. Then, based on the 3D point cloud derived from photogrammetric processing of the dense conjugate points, photoclinometry is further introduced to derive the 3D positions of the unmatched points and to refine the final point cloud. The approach is able to produce one 3D point for each image pixel within the overlapping area of the stereo pair so that to obtain pixel-resolution 3D models. Experiments using the Lunar Reconnaissance Orbiter Camera - Narrow Angle Camera (LROC NAC) images show the superior performances of the approach compared with traditional photogrammetric technique. The results and findings from this research contribute to optimal exploitation of image information for high-resolution 3D modelling of the lunar surface, which is of significance for the advancement of lunar and planetary mapping.

Stereotactic ultrasound for target volume definition in a patient with prostate cancer and bilateral total hip replacement.

PubMed

Boda-Heggemann, Judit; Haneder, Stefan; Ehmann, Michael; Sihono, Dwi Seno Kuncoro; Wertz, Hansjörg; Mai, Sabine; Kegel, Stefan; Heitmann, Sigrun; von Swietochowski, Sandra; Lohr, Frank; Wenz, Frederik

2015-01-01

Target-volume definition for prostate cancer in patients with bilateral metal total hip replacements (THRs) is a challenge because of metal artifacts in the planning computed tomography (CT) scans. Magnetic resonance imaging (MRI) can be used for matching and prostate delineation; however, at a spatial and temporal distance from the planning CT, identical rectal and vesical filling is difficult to achieve. In addition, MRI may also be impaired by metal artifacts, even resulting in spatial image distortion. Here, we present a method to define prostate target volumes based on ultrasound images acquired during CT simulation and online-matched to the CT data set directly at the planning CT. A 78-year-old patient with cT2cNxM0 prostate cancer with bilateral metal THRs was referred to external beam radiation therapy. T2-weighted MRI was performed on the day of the planning CT with preparation according to a protocol for reproducible bladder and rectal filling. The planning CT was obtained with the immediate acquisition of a 3-dimensional ultrasound data set with a dedicated stereotactic ultrasound system for online intermodality image matching referenced to the isocenter by ceiling-mounted infrared cameras. MRI (offline) and ultrasound images (online) were thus both matched to the CT images for planning. Daily image guided radiation therapy (IGRT) was performed with transabdominal ultrasound and compared with cone beam CT. Because of variations in bladder and rectal filling and metal-induced image distortion in MRI, soft-tissue-based matching of the MRI to CT was not sufficient for unequivocal prostate target definition. Ultrasound-based images could be matched, and prostate, seminal vesicles, and target volumes were reliably defined. Daily IGRT could be successfully completed with transabdominal ultrasound with good accordance between cone beam CT and ultrasound. For prostate cancer patients with bilateral THRs causing artifacts in planning CTs, ultrasound referenced to the isocenter of the CT simulator and acquired with intermodal online coregistration directly at the planning CT is a fast and easy method to reliably delineate the prostate and target volumes and for daily IGRT. Copyright © 2015 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

A convergence algorithm for correlation of breech face images based on the congruent matching cells (CMC) method.

PubMed

Chen, Zhe; Song, John; Chu, Wei; Soons, Johannes A; Zhao, Xuezeng

2017-11-01

The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for accurate firearm evidence identification and error rate estimation. The CMC method is based on the principle of discretization. The toolmark image of the reference sample is divided into correlation cells. Each cell is registered to the cell-sized area of the compared image that has maximum surface topography similarity. For each resulting cell pair, one parameter quantifies the similarity of the cell surface topography and three parameters quantify the pattern congruency of the registration position and orientation. An identification (declared match) requires a significant number of CMCs, that is, cell pairs that meet both similarity and pattern congruency requirements. The use of cell correlations reduces the effects of "invalid regions" in the compared image pairs and increases the correlation accuracy. The identification accuracy of the CMC method can be further improved by considering a feature named "convergence," that is, the tendency of the x-y registration positions of the correlated cell pairs to converge at the correct registration angle when comparing same-source samples at different relative orientations. In this paper, the difference of the convergence feature between known matching (KM) and known non-matching (KNM) image pairs is characterized, based on which an improved algorithm is developed for breech face image correlations using the CMC method. Its advantage is demonstrated by comparison with three existing CMC algorithms using four datasets. The datasets address three different brands of consecutively manufactured pistol slides, with significant differences in the distribution overlap of cell pair topography similarity for KM and KNM image pairs. For the same CMC threshold values, the convergence algorithm demonstrates noticeably improved results by reducing the number of false-positive or false-negative CMCs in a comparison. Published by Elsevier B.V.

A novel iris patterns matching algorithm of weighted polar frequency correlation

NASA Astrophysics Data System (ADS)

Zhao, Weijie; Jiang, Linhua

2014-11-01

Iris recognition is recognized as one of the most accurate techniques for biometric authentication. In this paper, we present a novel correlation method - Weighted Polar Frequency Correlation(WPFC) - to match and evaluate two iris images, actually it can also be used for evaluating the similarity of any two images. The WPFC method is a novel matching and evaluating method for iris image matching, which is complete different from the conventional methods. For instance, the classical John Daugman's method of iris recognition uses 2D Gabor wavelets to extract features of iris image into a compact bit stream, and then matching two bit streams with hamming distance. Our new method is based on the correlation in the polar coordinate system in frequency domain with regulated weights. The new method is motivated by the observation that the pattern of iris that contains far more information for recognition is fine structure at high frequency other than the gross shapes of iris images. Therefore, we transform iris images into frequency domain and set different weights to frequencies. Then calculate the correlation of two iris images in frequency domain. We evaluate the iris images by summing the discrete correlation values with regulated weights, comparing the value with preset threshold to tell whether these two iris images are captured from the same person or not. Experiments are carried out on both CASIA database and self-obtained images. The results show that our method is functional and reliable. Our method provides a new prospect for iris recognition system.

Novel techniques for data decomposition and load balancing for parallel processing of vision systems: Implementation and evaluation using a motion estimation system

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Computer vision systems employ a sequence of vision algorithms in which the output of an algorithm is the input of the next algorithm in the sequence. Algorithms that constitute such systems exhibit vastly different computational characteristics, and therefore, require different data decomposition techniques and efficient load balancing techniques for parallel implementation. However, since the input data for a task is produced as the output data of the previous task, this information can be exploited to perform knowledge based data decomposition and load balancing. Presented here are algorithms for a motion estimation system. The motion estimation is based on the point correspondence between the involved images which are a sequence of stereo image pairs. Researchers propose algorithms to obtain point correspondences by matching feature points among stereo image pairs at any two consecutive time instants. Furthermore, the proposed algorithms employ non-iterative procedures, which results in saving considerable amounts of computation time. The system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from consecutive time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters.

Threshold secret sharing scheme based on phase-shifting interferometry.

PubMed

Deng, Xiaopeng; Shi, Zhengang; Wen, Wei

2016-11-01

We propose a new method for secret image sharing with the (3,N) threshold scheme based on phase-shifting interferometry. The secret image, which is multiplied with an encryption key in advance, is first encrypted by using Fourier transformation. Then, the encoded image is shared into N shadow images based on the recording principle of phase-shifting interferometry. Based on the reconstruction principle of phase-shifting interferometry, any three or more shadow images can retrieve the secret image, while any two or fewer shadow images cannot obtain any information of the secret image. Thus, a (3,N) threshold secret sharing scheme can be implemented. Compared with our previously reported method, the algorithm of this paper is suited for not only a binary image but also a gray-scale image. Moreover, the proposed algorithm can obtain a larger threshold value t. Simulation results are presented to demonstrate the feasibility of the proposed method.

Motor-symptom laterality affects acquisition in Parkinson's disease: A cognitive and functional magnetic resonance imaging study.

PubMed

Huang, Pei; Tan, Yu-Yan; Liu, Dong-Qiang; Herzallah, Mohammad M; Lapidow, Elizabeth; Wang, Ying; Zang, Yu-Feng; Gluck, Mark A; Chen, Sheng-Di

2017-07-01

Asymmetric onset of motor symptoms in PD can affect cognitive function. We examined whether motor-symptom laterality could affect feedback-based associative learning and explored its underlying neural mechanism by functional magnetic resonance imaging in PD patients. We recruited 63 early-stage medication-naïve PD patients (29 left-onset medication-naïve patients, 34 right-onset medication-naïve patients) and 38 matched normal controls. Subjects completed an acquired equivalence task (including acquisition, retention, and generalization) and resting-state functional magnetic resonance imaging scans. Learning accuracy and response time in each phase of the task were recorded for behavioral measures. Regional homogeneity was used to analyze resting-state functional magnetic resonance imaging data, with regional homogeneity lateralization to evaluate hemispheric functional asymmetry in the striatum. Left-onset patients made significantly more errors in acquisition (feedback-based associative learning) than right-onset patients and normal controls, whereas right-onset patients performed as well as normal controls. There was no significant difference among these three groups in the accuracy of either retention or generalization phase. The three groups did not show significant differences in response time. In the left-onset group, there was an inverse relationship between acquisition errors and regional homogeneity in the right dorsal rostral putamen. There were no significant regional homogeneity changes in either the left or the right dorsal rostral putamen in right-onset patients when compared to controls. Motor-symptom laterality could affect feedback-based associative learning in PD, with left-onset medication-naïve patients being selectively impaired. Dysfunction in the right dorsal rostral putamen may underlie the observed deficit in associative learning in patients with left-sided onset.© 2016 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment.

PubMed

Mezgec, Simon; Eftimov, Tome; Bucher, Tamara; Koroušić Seljak, Barbara

2018-04-06

The present study tested the combination of an established and a validated food-choice research method (the 'fake food buffet') with a new food-matching technology to automate the data collection and analysis. The methodology combines fake-food image recognition using deep learning and food matching and standardization based on natural language processing. The former is specific because it uses a single deep learning network to perform both the segmentation and the classification at the pixel level of the image. To assess its performance, measures based on the standard pixel accuracy and Intersection over Union were applied. Food matching firstly describes each of the recognized food items in the image and then matches the food items with their compositional data, considering both their food names and their descriptors. The final accuracy of the deep learning model trained on fake-food images acquired by 124 study participants and providing fifty-five food classes was 92·18 %, while the food matching was performed with a classification accuracy of 93 %. The present findings are a step towards automating dietary assessment and food-choice research. The methodology outperforms other approaches in pixel accuracy, and since it is the first automatic solution for recognizing the images of fake foods, the results could be used as a baseline for possible future studies. As the approach enables a semi-automatic description of recognized food items (e.g. with respect to FoodEx2), these can be linked to any food composition database that applies the same classification and description system.

Iris Matching Based on Personalized Weight Map.

PubMed

Dong, Wenbo; Sun, Zhenan; Tan, Tieniu

2011-09-01

Iris recognition typically involves three steps, namely, iris image preprocessing, feature extraction, and feature matching. The first two steps of iris recognition have been well studied, but the last step is less addressed. Each human iris has its unique visual pattern and local image features also vary from region to region, which leads to significant differences in robustness and distinctiveness among the feature codes derived from different iris regions. However, most state-of-the-art iris recognition methods use a uniform matching strategy, where features extracted from different regions of the same person or the same region for different individuals are considered to be equally important. This paper proposes a personalized iris matching strategy using a class-specific weight map learned from the training images of the same iris class. The weight map can be updated online during the iris recognition procedure when the successfully recognized iris images are regarded as the new training data. The weight map reflects the robustness of an encoding algorithm on different iris regions by assigning an appropriate weight to each feature code for iris matching. Such a weight map trained by sufficient iris templates is convergent and robust against various noise. Extensive and comprehensive experiments demonstrate that the proposed personalized iris matching strategy achieves much better iris recognition performance than uniform strategies, especially for poor quality iris images.

Design considerations for quasi-phase-matching in doubly resonant lithium niobate hexagonal micro-resonators

NASA Astrophysics Data System (ADS)

Sono, Tleyane J.; Riziotis, Christos; Mailis, Sakellaris; Eason, Robert W.

2017-09-01

Fabrication capabilities of high optical quality hexagonal superstructures by chemical etching of inverted ferroelectric domains in lithium niobate platform suggests a route for efficient implementation of compact hexagonal microcavities. Such nonlinear optical hexagonal micro-resonators are proposed as a platform for second harmonic generation (SHG) by the combined mechanisms of total internal reflection (TIR) and quasi-phase-matching (QPM). The proposed scheme for SHG via TIR-QPM in a hexagonal microcavity can improve the efficiency and also the compactness of SHG devices compared to traditional linear-type based devices. A simple theoretical model based on six-bounce trajectory and phase matching conditions was capable for obtaining the optimal cavity size. Furthermore numerical simulation results based on finite difference time domain beam propagation method analysis confirmed the solutions obtained by demonstrating resonant operation of the microcavity for the second harmonic wave produced by TIR-QPM. Design aspects, optimization issues and characteristics of the proposed nonlinear device are presented.

X-Ray Phase Imaging for Breast Cancer Detection

DTIC Science & Technology

2012-09-01

the Gerchberg-Saxton algorithm in the Fresnel diffraction regime, and is much more robust against image noise than the TIE-based method. For details...developed efficient coding with the software modules for the image registration, flat-filed correction , and phase retrievals. In addition, we...X, Liu H. 2010. Performance analysis of the attenuation-partition based iterative phase retrieval algorithm for in-line phase-contrast imaging

Social computing for image matching

PubMed Central

Rivas, Alberto; Sánchez-Torres, Ramiro; Rodríguez, Sara

2018-01-01

One of the main technological trends in the last five years is mass data analysis. This trend is due in part to the emergence of concepts such as social networks, which generate a large volume of data that can provide added value through their analysis. This article is focused on a business and employment-oriented social network. More specifically, it focuses on the analysis of information provided by different users in image form. The images are analyzed to detect whether other existing users have posted or talked about the same image, even if the image has undergone some type of modification such as watermarks or color filters. This makes it possible to establish new connections among unknown users by detecting what they are posting or whether they are talking about the same images. The proposed solution consists of an image matching algorithm, which is based on the rapid calculation and comparison of hashes. However, there is a computationally expensive aspect in charge of revoking possible image transformations. As a result, the image matching process is supported by a distributed forecasting system that enables or disables nodes to serve all the possible requests. The proposed system has shown promising results for matching modified images, especially when compared with other existing systems. PMID:29813082

WE-G-BRD-06: Volumetric Cine MRI (VC-MRI) Estimated Based On Prior Knowledge for On-Board Target Localization

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

Harris, W; Yin, F; Cai, J

Purpose: To develop a technique to generate on-board VC-MRI using patient prior 4D-MRI, motion modeling and on-board 2D-cine MRI for real-time 3D target verification of liver and lung radiotherapy. Methods: The end-expiration phase images of a 4D-MRI acquired during patient simulation are used as patient prior images. Principal component analysis (PCA) is used to extract 3 major respiratory deformation patterns from the Deformation Field Maps (DFMs) generated between end-expiration phase and all other phases. On-board 2D-cine MRI images are acquired in the axial view. The on-board VC-MRI at any instant is considered as a deformation of the prior MRI atmore » the end-expiration phase. The DFM is represented as a linear combination of the 3 major deformation patterns. The coefficients of the deformation patterns are solved by matching the corresponding 2D slice of the estimated VC-MRI with the acquired single 2D-cine MRI. The method was evaluated using both XCAT (a computerized patient model) simulation of lung cancer patients and MRI data from a real liver cancer patient. The 3D-MRI at every phase except end-expiration phase was used to simulate the ground-truth on-board VC-MRI at different instances, and the center-tumor slice was selected to simulate the on-board 2D-cine images. Results: Image subtraction of ground truth with estimated on-board VC-MRI shows fewer differences than image subtraction of ground truth with prior image. Excellent agreement between profiles was achieved. The normalized cross correlation coefficients between the estimated and ground-truth in the axial, coronal and sagittal views for each time step were >= 0.982, 0.905, 0.961 for XCAT data and >= 0.998, 0.911, 0.9541 for patient data. For XCAT data, the maximum-Volume-Percent-Difference between ground-truth and estimated tumor volumes was 1.6% and the maximum-Center-of-Mass-Shift was 0.9 mm. Conclusion: Preliminary studies demonstrated the feasibility to estimate real-time VC-MRI for on-board target localization before or during radiotherapy treatments. National Institutes of Health Grant No. R01-CA184173; Varian Medical System.« less

Efficient moving target analysis for inverse synthetic aperture radar images via joint speeded-up robust features and regular moment

NASA Astrophysics Data System (ADS)

Yang, Hongxin; Su, Fulin

2018-01-01

We propose a moving target analysis algorithm using speeded-up robust features (SURF) and regular moment in inverse synthetic aperture radar (ISAR) image sequences. In our study, we first extract interest points from ISAR image sequences by SURF. Different from traditional feature point extraction methods, SURF-based feature points are invariant to scattering intensity, target rotation, and image size. Then, we employ a bilateral feature registering model to match these feature points. The feature registering scheme can not only search the isotropic feature points to link the image sequences but also reduce the error matching pairs. After that, the target centroid is detected by regular moment. Consequently, a cost function based on correlation coefficient is adopted to analyze the motion information. Experimental results based on simulated and real data validate the effectiveness and practicability of the proposed method.

X-ray phase-contrast imaging at 100 keV on a conventional source

PubMed Central

Thüring, T.; Abis, M.; Wang, Z.; David, C.; Stampanoni, M.

2014-01-01

X-ray grating interferometry is a promising imaging technique sensitive to attenuation, refraction and scattering of the radiation. Applications of this technique in the energy range between 80 and 150 keV pose severe technical challenges, and are still mostly unexplored. Phase-contrast X-ray imaging at such high energies is of relevant scientific and industrial interest, in particular for the investigation of strongly absorbing or thick materials as well as for medical imaging. Here we show the successful implementation of a Talbot-Lau interferometer operated at 100 keV using a conventional X-ray tube and a compact geometry, with a total length of 54 cm. We present the edge-on illumination of the gratings in order to overcome the current fabrication limits. Finally, the curved structures match the beam divergence and allow a large field of view on a short and efficient setup. PMID:24903579

Coupled binary embedding for large-scale image retrieval.

PubMed

Zheng, Liang; Wang, Shengjin; Tian, Qi

2014-08-01

Visual matching is a crucial step in image retrieval based on the bag-of-words (BoW) model. In the baseline method, two keypoints are considered as a matching pair if their SIFT descriptors are quantized to the same visual word. However, the SIFT visual word has two limitations. First, it loses most of its discriminative power during quantization. Second, SIFT only describes the local texture feature. Both drawbacks impair the discriminative power of the BoW model and lead to false positive matches. To tackle this problem, this paper proposes to embed multiple binary features at indexing level. To model correlation between features, a multi-IDF scheme is introduced, through which different binary features are coupled into the inverted file. We show that matching verification methods based on binary features, such as Hamming embedding, can be effectively incorporated in our framework. As an extension, we explore the fusion of binary color feature into image retrieval. The joint integration of the SIFT visual word and binary features greatly enhances the precision of visual matching, reducing the impact of false positive matches. Our method is evaluated through extensive experiments on four benchmark datasets (Ukbench, Holidays, DupImage, and MIR Flickr 1M). We show that our method significantly improves the baseline approach. In addition, large-scale experiments indicate that the proposed method requires acceptable memory usage and query time compared with other approaches. Further, when global color feature is integrated, our method yields competitive performance with the state-of-the-arts.

Noise in x-ray grating-based phase-contrast imaging.

PubMed

Weber, Thomas; Bartl, Peter; Bayer, Florian; Durst, Jürgen; Haas, Wilhelm; Michel, Thilo; Ritter, André; Anton, Gisela

2011-07-01

Grating-based x-ray phase-contrast imaging is a fast developing new modality not only for medical imaging, but as well for other fields such as material sciences. While these many possible applications arise, the knowledge of the noise behavior is essential. In this work, the authors used a least squares fitting algorithm to calculate the noise behavior of the three quantities absorption, differential phase, and dark-field image. Further, the calculated error formula of the differential phase image was verified by measurements. Therefore, a Talbot interferometer was setup, using a microfocus x-ray tube as source and a Timepix detector for photon counting. Additionally, simulations regarding this topic were performed. It turned out that the variance of the reconstructed phase is only dependent of the total number of photons used to generate the phase image and the visibility of the experimental setup. These results could be evaluated in measurements as well as in simulations. Furthermore, the correlation between absorption and dark-field image was calculated. These results provide the understanding of the noise characteristics of grating-based phase-contrast imaging and will help to improve image quality.

Structural Acoustic UXO Detection and Identification in Marine Environments

DTIC Science & Technology

2016-05-01

BOSS Buried Object Scanning Sonar DVL Doppler Velocity Log EW East/West IMU Inertial Measurement Unit NRL Naval Research Laboratory NSWC-PCD... Inertial Measurement Unit (IMU) to time-delay and coherently sum matched-filtered phase histories from subsurface focal points over a large number of... Measurement Unit (IMU) systems. In our imaging algorithm, the 2D depth image of a target, i.e. one mapped over x and z or y and z, presents the

Joint sparse coding based spatial pyramid matching for classification of color medical image.

PubMed

Shi, Jun; Li, Yi; Zhu, Jie; Sun, Haojie; Cai, Yin

2015-04-01

Although color medical images are important in clinical practice, they are usually converted to grayscale for further processing in pattern recognition, resulting in loss of rich color information. The sparse coding based linear spatial pyramid matching (ScSPM) and its variants are popular for grayscale image classification, but cannot extract color information. In this paper, we propose a joint sparse coding based SPM (JScSPM) method for the classification of color medical images. A joint dictionary can represent both the color information in each color channel and the correlation between channels. Consequently, the joint sparse codes calculated from a joint dictionary can carry color information, and therefore this method can easily transform a feature descriptor originally designed for grayscale images to a color descriptor. A color hepatocellular carcinoma histological image dataset was used to evaluate the performance of the proposed JScSPM algorithm. Experimental results show that JScSPM provides significant improvements as compared with the majority voting based ScSPM and the original ScSPM for color medical image classification. Copyright © 2014 Elsevier Ltd. All rights reserved.

Application of Time-Frequency Domain Transform to Three-Dimensional Interpolation of Medical Images.

PubMed

Lv, Shengqing; Chen, Yimin; Li, Zeyu; Lu, Jiahui; Gao, Mingke; Lu, Rongrong

2017-11-01

Medical image three-dimensional (3D) interpolation is an important means to improve the image effect in 3D reconstruction. In image processing, the time-frequency domain transform is an efficient method. In this article, several time-frequency domain transform methods are applied and compared in 3D interpolation. And a Sobel edge detection and 3D matching interpolation method based on wavelet transform is proposed. We combine wavelet transform, traditional matching interpolation methods, and Sobel edge detection together in our algorithm. What is more, the characteristics of wavelet transform and Sobel operator are used. They deal with the sub-images of wavelet decomposition separately. Sobel edge detection 3D matching interpolation method is used in low-frequency sub-images under the circumstances of ensuring high frequency undistorted. Through wavelet reconstruction, it can get the target interpolation image. In this article, we make 3D interpolation of the real computed tomography (CT) images. Compared with other interpolation methods, our proposed method is verified to be effective and superior.

A New Test Method of Circuit Breaker Spring Telescopic Characteristics Based Image Processing

NASA Astrophysics Data System (ADS)

Huang, Huimin; Wang, Feifeng; Lu, Yufeng; Xia, Xiaofei; Su, Yi

2018-06-01

This paper applied computer vision technology to the fatigue condition monitoring of springs, and a new telescopic characteristics test method is proposed for circuit breaker operating mechanism spring based on image processing technology. High-speed camera is utilized to capture spring movement image sequences when high voltage circuit breaker operated. Then the image-matching method is used to obtain the deformation-time curve and speed-time curve, and the spring expansion and deformation parameters are extracted from it, which will lay a foundation for subsequent spring force analysis and matching state evaluation. After performing simulation tests at the experimental site, this image analyzing method could solve the complex problems of traditional mechanical sensor installation and monitoring online, status assessment of the circuit breaker spring.

Benchmarking the x-ray phase contrast imaging for ICF DT ice characterization using roughened surrogates

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

Dewald, E; Kozioziemski, B; Moody, J

2008-06-26

We use x-ray phase contrast imaging to characterize the inner surface roughness of DT ice layers in capsules planned for future ignition experiments. It is therefore important to quantify how well the x-ray data correlates with the actual ice roughness. We benchmarked the accuracy of our system using surrogates with fabricated roughness characterized with high precision standard techniques. Cylindrical artifacts with azimuthally uniform sinusoidal perturbations with 100 um period and 1 um amplitude demonstrated 0.02 um accuracy limited by the resolution of the imager and the source size of our phase contrast system. Spherical surrogates with random roughness close tomore » that required for the DT ice for a successful ignition experiment were used to correlate the actual surface roughness to that obtained from the x-ray measurements. When comparing average power spectra of individual measurements, the accuracy mode number limits of the x-ray phase contrast system benchmarked against surface characterization performed by Atomic Force Microscopy are 60 and 90 for surrogates smoother and rougher than the required roughness for the ice. These agreement mode number limits are >100 when comparing matching individual measurements. We will discuss the implications for interpreting DT ice roughness data derived from phase-contrast x-ray imaging.« less

Scalable Integrated Region-Based Image Retrieval Using IRM and Statistical Clustering.

ERIC Educational Resources Information Center

Wang, James Z.; Du, Yanping

Statistical clustering is critical in designing scalable image retrieval systems. This paper presents a scalable algorithm for indexing and retrieving images based on region segmentation. The method uses statistical clustering on region features and IRM (Integrated Region Matching), a measure developed to evaluate overall similarity between images…

Ranging through Gabor logons-a consistent, hierarchical approach.

PubMed

Chang, C; Chatterjee, S

1993-01-01

In this work, the correspondence problem in stereo vision is handled by matching two sets of dense feature vectors. Inspired by biological evidence, these feature vectors are generated by a correlation between a bank of Gabor sensors and the intensity image. The sensors consist of two-dimensional Gabor filters at various scales (spatial frequencies) and orientations, which bear close resemblance to the receptive field profiles of simple V1 cells in visual cortex. A hierarchical, stochastic relaxation method is then used to obtain the dense stereo disparities. Unlike traditional hierarchical methods for stereo, feature based hierarchical processing yields consistent disparities. To avoid false matchings due to static occlusion, a dual matching, based on the imaging geometry, is used.

Mobile Visual Search Based on Histogram Matching and Zone Weight Learning

NASA Astrophysics Data System (ADS)

Zhu, Chuang; Tao, Li; Yang, Fan; Lu, Tao; Jia, Huizhu; Xie, Xiaodong

2018-01-01

In this paper, we propose a novel image retrieval algorithm for mobile visual search. At first, a short visual codebook is generated based on the descriptor database to represent the statistical information of the dataset. Then, an accurate local descriptor similarity score is computed by merging the tf-idf weighted histogram matching and the weighting strategy in compact descriptors for visual search (CDVS). At last, both the global descriptor matching score and the local descriptor similarity score are summed up to rerank the retrieval results according to the learned zone weights. The results show that the proposed approach outperforms the state-of-the-art image retrieval method in CDVS.

Research and implementation of finger-vein recognition algorithm

NASA Astrophysics Data System (ADS)

Pang, Zengyao; Yang, Jie; Chen, Yilei; Liu, Yin

2017-06-01

In finger vein image preprocessing, finger angle correction and ROI extraction are important parts of the system. In this paper, we propose an angle correction algorithm based on the centroid of the vein image, and extract the ROI region according to the bidirectional gray projection method. Inspired by the fact that features in those vein areas have similar appearance as valleys, a novel method was proposed to extract center and width of palm vein based on multi-directional gradients, which is easy-computing, quick and stable. On this basis, an encoding method was designed to determine the gray value distribution of texture image. This algorithm could effectively overcome the edge of the texture extraction error. Finally, the system was equipped with higher robustness and recognition accuracy by utilizing fuzzy threshold determination and global gray value matching algorithm. Experimental results on pairs of matched palm images show that, the proposed method has a EER with 3.21% extracts features at the speed of 27ms per image. It can be concluded that the proposed algorithm has obvious advantages in grain extraction efficiency, matching accuracy and algorithm efficiency.

Identity-level representations affect unfamiliar face matching performance in sequential but not simultaneous tasks.

PubMed

Menon, Nadia; White, David; Kemp, Richard I

2015-01-01

According to cognitive and neurological models of the face-processing system, faces are represented at two levels of abstraction. First, image-based pictorial representations code a particular instance of a face and include information that is unrelated to identity-such as lighting, pose, and expression. Second, at a more abstract level, identity-specific representations combine information from various encounters with a single face. Here we tested whether identity-level representations mediate unfamiliar face matching performance. Across three experiments we manipulated identity attributions to pairs of target images and measured the effect on subsequent identification decisions. Participants were instructed that target images were either two photos of the same person (1ID condition) or photos of two different people (2ID condition). This manipulation consistently affected performance in sequential matching: 1ID instructions improved accuracy on "match" trials and caused participants to adopt a more liberal response bias than the 2ID condition. However, this manipulation did not affect performance in simultaneous matching. We conclude that identity-level representations, generated in working memory, influence the amount of variation tolerated between images, when making identity judgements in sequential face matching.

Stereo using monocular cues within the tensor voting framework.

PubMed

Mordohai, Philippos; Medioni, Gérard

2006-06-01

We address the fundamental problem of matching in two static images. The remaining challenges are related to occlusion and lack of texture. Our approach addresses these difficulties within a perceptual organization framework, considering both binocular and monocular cues. Initially, matching candidates for all pixels are generated by a combination of matching techniques. The matching candidates are then embedded in disparity space, where perceptual organization takes place in 3D neighborhoods and, thus, does not suffer from problems associated with scanline or image neighborhoods. The assumption is that correct matches produce salient, coherent surfaces, while wrong ones do not. Matching candidates that are consistent with the surfaces are kept and grouped into smooth layers. Thus, we achieve surface segmentation based on geometric and not photometric properties. Surface overextensions, which are due to occlusion, can be corrected by removing matches whose projections are not consistent in color with their neighbors of the same surface in both images. Finally, the projections of the refined surfaces on both images are used to obtain disparity hypotheses for unmatched pixels. The final disparities are selected after a second tensor voting stage, during which information is propagated from more reliable pixels to less reliable ones. We present results on widely used benchmark stereo pairs.

4D MR imaging using robust internal respiratory signal

NASA Astrophysics Data System (ADS)

Hui, CheukKai; Wen, Zhifei; Stemkens, Bjorn; Tijssen, R. H. N.; van den Berg, C. A. T.; Hwang, Ken-Pin; Beddar, Sam

2016-05-01

The purpose of this study is to investigate the feasibility of using internal respiratory (IR) surrogates to sort four-dimensional (4D) magnetic resonance (MR) images. The 4D MR images were constructed by acquiring fast 2D cine MR images sequentially, with each slice scanned for more than one breathing cycle. The 4D volume was then sorted retrospectively using the IR signal. In this study, we propose to use multiple low-frequency components in the Fourier space as well as the anterior body boundary as potential IR surrogates. From these potential IR surrogates, we used a clustering algorithm to identify those that best represented the respiratory pattern to derive the IR signal. A study with healthy volunteers was performed to assess the feasibility of the proposed IR signal. We compared this proposed IR signal with the respiratory signal obtained using respiratory bellows. Overall, 99% of the IR signals matched the bellows signals. The average difference between the end inspiration times in the IR signal and bellows signal was 0.18 s in this cohort of matching signals. For the acquired images corresponding to the other 1% of non-matching signal pairs, the respiratory motion shown in the images was coherent with the respiratory phases determined by the IR signal, but not the bellows signal. This suggested that the IR signal determined by the proposed method could potentially correct the faulty bellows signal. The sorted 4D images showed minimal mismatched artefacts and potential clinical applicability. The proposed IR signal therefore provides a feasible alternative to effectively sort MR images in 4D.

A position and attitude vision measurement system for wind tunnel slender model

NASA Astrophysics Data System (ADS)

Cheng, Lei; Yang, Yinong; Xue, Bindang; Zhou, Fugen; Bai, Xiangzhi

2014-11-01

A position and attitude vision measurement system for drop test slender model in wind tunnel is designed and developed. The system used two high speed cameras, one is put to the side of the model and another is put to the position where the camera can look up the model. Simple symbols are set on the model. The main idea of the system is based on image matching technique between the 3D-digital model projection image and the image captured by the camera. At first, we evaluate the pitch angles, the roll angles and the position of the centroid of a model through recognizing symbols in the images captured by the side camera. And then, based on the evaluated attitude info, giving a series of yaw angles, a series of projection images of the 3D-digital model are obtained. Finally, these projection images are matched with the image which captured by the looking up camera, and the best match's projection images corresponds to the yaw angle is the very yaw angle of the model. Simulation experiments are conducted and the results show that the maximal error of attitude measurement is less than 0.05°, which can meet the demand of test in wind tunnel.

Model-based conifer crown surface reconstruction from multi-ocular high-resolution aerial imagery

NASA Astrophysics Data System (ADS)

Sheng, Yongwei

2000-12-01

Tree crown parameters such as width, height, shape and crown closure are desirable in forestry and ecological studies, but they are time-consuming and labor intensive to measure in the field. The stereoscopic capability of high-resolution aerial imagery provides a way to crown surface reconstruction. Existing photogrammetric algorithms designed to map terrain surfaces, however, cannot adequately extract crown surfaces, especially for steep conifer crowns. Considering crown surface reconstruction in a broader context of tree characterization from aerial images, we develop a rigorous perspective tree image formation model to bridge image-based tree extraction and crown surface reconstruction, and an integrated model-based approach to conifer crown surface reconstruction. Based on the fact that most conifer crowns are in a solid geometric form, conifer crowns are modeled as a generalized hemi-ellipsoid. Both the automatic and semi-automatic approaches are investigated to optimal tree model development from multi-ocular images. The semi-automatic 3D tree interpreter developed in this thesis is able to efficiently extract reliable tree parameters and tree models in complicated tree stands. This thesis starts with a sophisticated stereo matching algorithm, and incorporates tree models to guide stereo matching. The following critical problems are addressed in the model-based surface reconstruction process: (1) the problem of surface model composition from tree models, (2) the occlusion problem in disparity prediction from tree models, (3) the problem of integrating the predicted disparities into image matching, (4) the tree model edge effect reduction on the disparity map, (5) the occlusion problem in orthophoto production, and (6) the foreshortening problem in image matching, which is very serious for conifer crown surfaces. Solutions to the above problems are necessary for successful crown surface reconstruction. The model-based approach was applied to recover the canopy surface of a dense redwood stand using tri-ocular high-resolution images scanned from 1:2,400 aerial photographs. The results demonstrate the approach's ability to reconstruct complicated stands. The model-based approach proposed in this thesis is potentially applicable to other surfaces recovering problems with a priori knowledge about objects.

TH-CD-207A-04: Optimized Respiratory Gating for Abnormal Breathers in Pancreatic SBRT

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

Campbell, W; Miften, M; Schefter, T

Purpose: Pancreatic SBRT is uniquely challenging due to both the erratic/unstable motion of the pancreas and the close proximity of the radiosensitive small bowel. Respiratory gating can mitigate this effect, but the irregularity of motion severely affects traditional phase-based gating. The purpose of this study was to analyze real-time motion data of pancreatic tumors to optimize the efficacy and accuracy of respiratory gating, with the overall goal of enabling dose escalated pancreatic SBRT. Methods: Fifteen pancreatic SBRT patients received 30–33 Gy in 5 fractions on a Varian TrueBeam STx unit. Abdominal compression was used to reduce the amplitude of tumormore » motion, and daily cone-beam computed tomography (CBCT) scans were acquired prior to each treatment for target localization purposes. For this study, breathing data (phase and amplitude) were collected during each CBCT scan using Varian’s Real-Time Position Management system. An in-house template matching technique was used to track the superior-inferior motion of implanted fiducial markers in CBCT projection images. Using tumor motion and breathing data, phase-based or amplitude-based respiratory gating was simulated for all 75 fractions, targeting either end-exhalation or end-inhalation phases of breathing. Results: For the average patient, gating at end-exhalation offered the best reductions in effective motion for equal duty cycles. However, optimal central phase angle varied widely (range: 0–92%, mean±SD: 49±12%), and phase-based gating windows typically associated with end-exhalation (i.e., “30–70%”) were rarely ideal. Amplitude-based gating significantly outperformed phase-based gating, with average effective ranges for amplitude-based gating 25% lower than phase-based gating ranges (as much as 73% lower). Amplitude-based gating was consistently better suited to accommodate abnormal breathing patterns. For both phase-based and amplitude-based gating, end-exhalation provided significantly better results than end-inhalation. Conclusion: Amplitude-based gating reliably outperformed phase-based gating, and end-exhalation was more suitable than end-inhalation. These results will be used to guide future dose-escalation trials. Research funding provided by Varian Medical Systems to Miften and Jones.« less

Gaussian mixed model in support of semiglobal matching leveraged by ground control points

NASA Astrophysics Data System (ADS)

Ma, Hao; Zheng, Shunyi; Li, Chang; Li, Yingsong; Gui, Li

2017-04-01

Semiglobal matching (SGM) has been widely applied in large aerial images because of its good tradeoff between complexity and robustness. The concept of ground control points (GCPs) is adopted to make SGM more robust. We model the effect of GCPs as two data terms for stereo matching between high-resolution aerial epipolar images in an iterative scheme. One term based on GCPs is formulated by Gaussian mixture model, which strengths the relation between GCPs and the pixels to be estimated and encodes some degree of consistency between them with respect to disparity values. Another term depends on pixel-wise confidence, and we further design a confidence updating equation based on three rules. With this confidence-based term, the assignment of disparity can be heuristically selected among disparity search ranges during the iteration process. Several iterations are sufficient to bring out satisfactory results according to our experiments. Experimental results validate that the proposed method outperforms surface reconstruction, which is a representative variant of SGM and behaves excellently on aerial images.

The Potential of Using Brain Images for Authentication

PubMed Central

Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition. PMID:25126604

The potential of using brain images for authentication.

PubMed

Chen, Fanglin; Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition.

Quantification of signal detection performance degradation induced by phase-retrieval in propagation-based x-ray phase-contrast imaging

NASA Astrophysics Data System (ADS)

Chou, Cheng-Ying; Anastasio, Mark A.

2016-04-01

In propagation-based X-ray phase-contrast (PB XPC) imaging, the measured image contains a mixture of absorption- and phase-contrast. To obtain separate images of the projected absorption and phase (i.e., refractive) properties of a sample, phase retrieval methods can be employed. It has been suggested that phase-retrieval can always improve image quality in PB XPC imaging. However, when objective (task-based) measures of image quality are employed, this is not necessarily true and phase retrieval can be detrimental. In this work, signal detection theory is utilized to quantify the performance of a Hotelling observer (HO) for detecting a known signal in a known background. Two cases are considered. In the first case, the HO acts directly on the measured intensity data. In the second case, the HO acts on either the retrieved phase or absorption image. We demonstrate that the performance of the HO is superior when acting on the measured intensity data. The loss of task-specific information induced by phase-retrieval is quantified by computing the efficiency of the HO as the ratio of the test statistic signal-to-noise ratio (SNR) for the two cases. The effect of the system geometry on this efficiency is systematically investigated. Our findings confirm that phase-retrieval can impair signal detection performance in XPC imaging.

Thermal imaging as a biometrics approach to facial signature authentication.

PubMed

Guzman, A M; Goryawala, M; Wang, Jin; Barreto, A; Andrian, J; Rishe, N; Adjouadi, M

2013-01-01

A new thermal imaging framework with unique feature extraction and similarity measurements for face recognition is presented. The research premise is to design specialized algorithms that would extract vasculature information, create a thermal facial signature and identify the individual. The proposed algorithm is fully integrated and consolidates the critical steps of feature extraction through the use of morphological operators, registration using the Linear Image Registration Tool and matching through unique similarity measures designed for this task. The novel approach at developing a thermal signature template using four images taken at various instants of time ensured that unforeseen changes in the vasculature over time did not affect the biometric matching process as the authentication process relied only on consistent thermal features. Thirteen subjects were used for testing the developed technique on an in-house thermal imaging system. The matching using the similarity measures showed an average accuracy of 88.46% for skeletonized signatures and 90.39% for anisotropically diffused signatures. The highly accurate results obtained in the matching process clearly demonstrate the ability of the thermal infrared system to extend in application to other thermal imaging based systems. Empirical results applying this approach to an existing database of thermal images proves this assertion.

Development of machine-vision system for gap inspection of muskmelon grafted seedlings.

PubMed

Liu, Siyao; Xing, Zuochang; Wang, Zifan; Tian, Subo; Jahun, Falalu Rabiu

2017-01-01

Grafting robots have been developed in the world, but some auxiliary works such as gap-inspecting for grafted seedlings still need to be done by human. An machine-vision system of gap inspection for grafted muskmelon seedlings was developed in this study. The image acquiring system consists of a CCD camera, a lens and a front white lighting source. The image of inspected gap was processed and analyzed by software of HALCON 12.0. The recognition algorithm for the system is based on principle of deformable template matching. A template should be created from an image of qualified grafted seedling gap. Then the gap image of the grafted seedling will be compared with the created template to determine their matching degree. Based on the similarity between the gap image of grafted seedling and the template, the matching degree will be 0 to 1. The less similar for the grafted seedling gap with the template the smaller of matching degree. Thirdly, the gap will be output as qualified or unqualified. If the matching degree of grafted seedling gap and the template is less than 0.58, or there is no match is found, the gap will be judged as unqualified; otherwise the gap will be qualified. Finally, 100 muskmelon seedlings were grafted and inspected to test the gap inspection system. Results showed that the gap inspection machine-vision system could recognize the gap qualification correctly as 98% of human vision. And the inspection speed of this system can reach 15 seedlings·min-1. The gap inspection process in grafting can be fully automated with this developed machine-vision system, and the gap inspection system will be a key step of a fully-automatic grafting robots.

Strategies for registering range images from unknown camera positions

NASA Astrophysics Data System (ADS)

Bernardini, Fausto; Rushmeier, Holly E.

2000-03-01

We describe a project to construct a 3D numerical model of Michelangelo's Florentine Pieta to be used in a study of the sculpture. Here we focus on the registration of the range images used to construct the model. The major challenge was the range of length scales involved. A resolution of 1 mm or less required for the 2.25 m tall piece. To achieve this resolution, we could only acquire an area of 20 by 20 cm per scan. A total of approximately 700 images were required. Ideally, a tracker would be attached to the scanner to record position and pose. The use of a tracker was not possible in the field. Instead, we used a crude-to-fine approach to registering the meshes to one another. The crudest level consisted of pairwise manual registration, aided by texture maps containing laser dots that were projected onto the sculpture. This crude alignment was refined by an automatic registration of laser dot centers. In this phase, we found that consistency constraints on dot matches were essential to obtaining accurate results. The laser dot alignment was refined by an automatic registration of laser dot centers. In this phase, we found that consistency constraints on dot matches were essential to obtaining accurate results. The laser dot alignment was further refined using a variation of the ICP algorithm developed by Besl and McKay. In the application of ICP to global registration, we developed a method to avoid one class of local minima by finding a set of points, rather than the single point, that matches each candidate point.

GPU implementation of prior image constrained compressed sensing (PICCS)

NASA Astrophysics Data System (ADS)

Nett, Brian E.; Tang, Jie; Chen, Guang-Hong

2010-04-01

The Prior Image Constrained Compressed Sensing (PICCS) algorithm (Med. Phys. 35, pg. 660, 2008) has been applied to several computed tomography applications with both standard CT systems and flat-panel based systems designed for guiding interventional procedures and radiation therapy treatment delivery. The PICCS algorithm typically utilizes a prior image which is reconstructed via the standard Filtered Backprojection (FBP) reconstruction algorithm. The algorithm then iteratively solves for the image volume that matches the measured data, while simultaneously assuring the image is similar to the prior image. The PICCS algorithm has demonstrated utility in several applications including: improved temporal resolution reconstruction, 4D respiratory phase specific reconstructions for radiation therapy, and cardiac reconstruction from data acquired on an interventional C-arm. One disadvantage of the PICCS algorithm, just as other iterative algorithms, is the long computation times typically associated with reconstruction. In order for an algorithm to gain clinical acceptance reconstruction must be achievable in minutes rather than hours. In this work the PICCS algorithm has been implemented on the GPU in order to significantly reduce the reconstruction time of the PICCS algorithm. The Compute Unified Device Architecture (CUDA) was used in this implementation.

A segmentation and point-matching enhanced efficient deformable image registration method for dose accumulation between HDR CT images.

PubMed

Zhen, Xin; Chen, Haibin; Yan, Hao; Zhou, Linghong; Mell, Loren K; Yashar, Catheryn M; Jiang, Steve; Jia, Xun; Gu, Xuejun; Cervino, Laura

2015-04-07

Deformable image registration (DIR) of fractional high-dose-rate (HDR) CT images is challenging due to the presence of applicators in the brachytherapy image. Point-to-point correspondence fails because of the undesired deformation vector fields (DVF) propagated from the applicator region (AR) to the surrounding tissues, which can potentially introduce significant DIR errors in dose mapping. This paper proposes a novel segmentation and point-matching enhanced efficient DIR (named SPEED) scheme to facilitate dose accumulation among HDR treatment fractions. In SPEED, a semi-automatic seed point generation approach is developed to obtain the incremented fore/background point sets to feed the random walks algorithm, which is used to segment and remove the AR, leaving empty AR cavities in the HDR CT images. A feature-based 'thin-plate-spline robust point matching' algorithm is then employed for AR cavity surface points matching. With the resulting mapping, a DVF defining on each voxel is estimated by B-spline approximation, which serves as the initial DVF for the subsequent Demons-based DIR between the AR-free HDR CT images. The calculated DVF via Demons combined with the initial one serve as the final DVF to map doses between HDR fractions. The segmentation and registration accuracy are quantitatively assessed by nine clinical HDR cases from three gynecological cancer patients. The quantitative analysis and visual inspection of the DIR results indicate that SPEED can suppress the impact of applicator on DIR, and accurately register HDR CT images as well as deform and add interfractional HDR doses.

Hardware Overview of the Microwave Imaging Reflectometry (MIR) on DIII-D

NASA Astrophysics Data System (ADS)

Hu, Xing; Muscatello, Chirstopher; Domier, Calvin; Luhmann, Neville; Ren, Xiaoxin; Spear, Alexander; Tobias, Benjamin; Yu, Liubing; University of California Davis Collaboration; Princeton Plasma Physics Laboratory Collaboration

2013-10-01

UC Davis in collaboration with PPPL has developed and installed a 12 by 4 (48) channel MIR system on DIII-D to measure 2-D structure of density fluctuations. In the transmitter path, a four-frequency probing beam is generated by mixing the 65 GHz Gunn oscillator signal with two different 0.5 ~ 9 GHz signals. Carefully designed imaging optics shape the beam to ensure the probing beam wavefront matches the cutoff surfaces. In the receiver path, large aperture imaging optics collect the reflected beam and focus it onto the mini lens antenna array, which provides improved LO coupling and antenna performance over earlier imaging systems. The reflected signal is down-converted for the first time on the array and goes into the innovative electronics for a second down-conversion. Low frequency LOs for the IQ mixer are generated by mixing two reference signals from phase-locked circuits. The double down-converted signal is mixed with the low frequency LOs yielding in-phase and quadrature components of the phase and thus density fluctuation information.

Optical measurements in evolving dispersed pipe flows

NASA Astrophysics Data System (ADS)

Voulgaropoulos, Victor; Angeli, Panagiota

2017-12-01

Optical laser-based techniques and an extensive data analysis methodology have been developed to acquire flow and separation characteristics of concentrated liquid-liquid dispersions. A helical static mixer was used at the inlet of an acrylic 4 m long horizontal pipe to actuate the dispersed flows at low mixture velocities. The organic (913 kg m^{-3}, 0.0046 Pa s) and aqueous phases (1146 kg m^{-3}, 0.0084 Pa s) were chosen to have matched refractive indices. Measurements were conducted at 15 and 135 equivalent pipe diameters downstream the inlet. Planar laser induced fluorescence (PLIF) measurements illustrated the flow structures and provided the local in-situ holdup profiles. It was found that along the pipe the drops segregate and in some cases coalesce either with other drops or with the corresponding continuous phase. A multi-level threshold algorithm was developed to measure the drop sizes from the PLIF images. The velocity profiles in the aqueous phase were measured with particle image velocimetry (PIV), while the settling velocities of the organic dispersed drops were acquired with particle tracking velocimetry (PTV). It was also possible to capture coalescence events of a drop with an interface over time and to acquire the instantaneous velocity and vorticity fields in the coalescing drop.

[Algorithm of locally adaptive region growing based on multi-template matching applied to automated detection of hemorrhages].

PubMed

Gao, Wei-Wei; Shen, Jian-Xin; Wang, Yu-Liang; Liang, Chun; Zuo, Jing

2013-02-01

In order to automatically detect hemorrhages in fundus images, and develop an automated diabetic retinopathy screening system, a novel algorithm named locally adaptive region growing based on multi-template matching was established and studied. Firstly, spectral signature of major anatomical structures in fundus was studied, so that the right channel among RGB channels could be selected for different segmentation objects. Secondly, the fundus image was preprocessed by means of HSV brightness correction and contrast limited adaptive histogram equalization (CLAHE). Then, seeds of region growing were founded out by removing optic disc and vessel from the resulting image of normalized cross-correlation (NCC) template matching on the previous preprocessed image with several templates. Finally, locally adaptive region growing segmentation was used to find out the exact contours of hemorrhages, and the automated detection of the lesions was accomplished. The approach was tested on 90 different resolution fundus images with variable color, brightness and quality. Results suggest that the approach could fast and effectively detect hemorrhages in fundus images, and it is stable and robust. As a result, the approach can meet the clinical demands.

Experiments with a novel content-based image retrieval software: can we eliminate classification systems in adolescent idiopathic scoliosis?

PubMed

Menon, K Venugopal; Kumar, Dinesh; Thomas, Tessamma

2014-02-01

Study Design Preliminary evaluation of new tool. Objective To ascertain whether the newly developed content-based image retrieval (CBIR) software can be used successfully to retrieve images of similar cases of adolescent idiopathic scoliosis (AIS) from a database to help plan treatment without adhering to a classification scheme. Methods Sixty-two operated cases of AIS were entered into the newly developed CBIR database. Five new cases of different curve patterns were used as query images. The images were fed into the CBIR database that retrieved similar images from the existing cases. These were analyzed by a senior surgeon for conformity to the query image. Results Within the limits of variability set for the query system, all the resultant images conformed to the query image. One case had no similar match in the series. The other four retrieved several images that were matching with the query. No matching case was left out in the series. The postoperative images were then analyzed to check for surgical strategies. Broad guidelines for treatment could be derived from the results. More precise query settings, inclusion of bending films, and a larger database will enhance accurate retrieval and better decision making. Conclusion The CBIR system is an effective tool for accurate documentation and retrieval of scoliosis images. Broad guidelines for surgical strategies can be made from the postoperative images of the existing cases without adhering to any classification scheme.

The selection of the optimal baseline in the front-view monocular vision system

NASA Astrophysics Data System (ADS)

Xiong, Bincheng; Zhang, Jun; Zhang, Daimeng; Liu, Xiaomao; Tian, Jinwen

2018-03-01

In the front-view monocular vision system, the accuracy of solving the depth field is related to the length of the inter-frame baseline and the accuracy of image matching result. In general, a longer length of the baseline can lead to a higher precision of solving the depth field. However, at the same time, the difference between the inter-frame images increases, which increases the difficulty in image matching and the decreases matching accuracy and at last may leads to the failure of solving the depth field. One of the usual practices is to use the tracking and matching method to improve the matching accuracy between images, but this algorithm is easy to cause matching drift between images with large interval, resulting in cumulative error in image matching, and finally the accuracy of solving the depth field is still very low. In this paper, we propose a depth field fusion algorithm based on the optimal length of the baseline. Firstly, we analyze the quantitative relationship between the accuracy of the depth field calculation and the length of the baseline between frames, and find the optimal length of the baseline by doing lots of experiments; secondly, we introduce the inverse depth filtering technique for sparse SLAM, and solve the depth field under the constraint of the optimal length of the baseline. By doing a large number of experiments, the results show that our algorithm can effectively eliminate the mismatch caused by image changes, and can still solve the depth field correctly in the large baseline scene. Our algorithm is superior to the traditional SFM algorithm in time and space complexity. The optimal baseline obtained by a large number of experiments plays a guiding role in the calculation of the depth field in front-view monocular.

Cellphone based mobile colposcope for the evaluation of women with abnormal cervical cancer screening

NASA Astrophysics Data System (ADS)

Kahn, Bruce S.; Kass, Alex J.; Waalen, Jill; Levitz, David

2015-03-01

Objective: Compare an inexpensive cell-phone based Mobile Colposcope, with a standard colposcope in the evaluation of women with abnormal Pap smear screening. Methodology: The study was a prospective, parallel noninferiority trial. Thirty women underwent colposcopy for the evaluation of an abnormal Pap smear. After application of acetic acid, images of the cervix were obtained with both a standard colposcope and the Mobile Colposcope. An additional set of images using both devices were obtained using the red-free (green filter) mode. Eight experienced gynecologists then evaluated 100 paired images (plain and green filter) from two different sites in random order using a web based assessment program. After reviewing each set of paired images, the expert would make an assessment of: 1) normal (no biopsy/ random biopsy), or 2) abnormal. For abnormal images, the expert then electronically marked the site(s) on the image where a biopsy was recommended. In image analysis, the cervical image was divided into 12 radial sectors and the marked sites for biopsy on the matched pairs were compared. Matched pairs that were considered normal, or those where biopsy site recommendations were within +/- 30° were considered equivalent; unmatched biopsy sites were considered non-equivalent. Results were compared using Wilcoxon Matched Pairs Signed Ranks Test. Expert assessment of Mobile Colposcope images compared with assessment by standard colposcope is currently onging. Conclusions: if the Mobile Colposcope demonstrates non-inferiority to imaging obtained with a standard colposcope and due to its low cost, it has the potential help improve cervical cancer screening in low resource settings.

Heterogeneous iris image hallucination using sparse representation on a learned heterogeneous patch dictionary

NASA Astrophysics Data System (ADS)

Li, Yung-Hui; Zheng, Bo-Ren; Ji, Dai-Yan; Tien, Chung-Hao; Liu, Po-Tsun

2014-09-01

Cross sensor iris matching may seriously degrade the recognition performance because of the sensor mis-match problem of iris images between the enrollment and test stage. In this paper, we propose two novel patch-based heterogeneous dictionary learning method to attack this problem. The first method applies the latest sparse representation theory while the second method tries to learn the correspondence relationship through PCA in heterogeneous patch space. Both methods learn the basic atoms in iris textures across different image sensors and build connections between them. After such connections are built, at test stage, it is possible to hallucinate (synthesize) iris images across different sensors. By matching training images with hallucinated images, the recognition rate can be successfully enhanced. The experimental results showed the satisfied results both visually and in terms of recognition rate. Experimenting with an iris database consisting of 3015 images, we show that the EER is decreased 39.4% relatively by the proposed method.

Role of phase instabilities in the early response of bulk fused silica during laser-induced breakdown

NASA Astrophysics Data System (ADS)

Demange, P.; Negres, R. A.; Raman, R. N.; Colvin, J. D.; Demos, S. G.

2011-08-01

We report on the experimental and hydrocode modeling investigation of the early material response to localized energy deposition via nanosecond laser pulses in bulk fused silica. A time-resolved microscope system was used to acquire transient images with adequate spatial and temporal resolution to resolve the material behavior from the onset of the process. These images revealed a high-pressure shock front propagating at twice the speed of sound at ambient conditions and bounding a region of modified material at delays up to one nanosecond. Hydrocode simulations matching the experimental conditions were also performed and indicated initial pressures of ˜40 GPa and temperatures of ˜1 eV at the absorption region. Both the simulations and the image data show a clear boundary between distinct material phases, a hot plasma and solid silica, with a suggestion that growth of perturbations at the Rayleigh-Taylor unstable interface between the two phases is the seed mechanism for the growth of cracks into the stressed solid.

Stereo matching and view interpolation based on image domain triangulation.

PubMed

Fickel, Guilherme Pinto; Jung, Claudio R; Malzbender, Tom; Samadani, Ramin; Culbertson, Bruce

2013-09-01

This paper presents a new approach for stereo matching and view interpolation problems based on triangular tessellations suitable for a linear array of rectified cameras. The domain of the reference image is initially partitioned into triangular regions using edge and scale information, aiming to place vertices along image edges and increase the number of triangles in textured regions. A region-based matching algorithm is then used to find an initial disparity for each triangle, and a refinement stage is applied to change the disparity at the vertices of the triangles, generating a piecewise linear disparity map. A simple post-processing procedure is applied to connect triangles with similar disparities generating a full 3D mesh related to each camera (view), which are used to generate new synthesized views along the linear camera array. With the proposed framework, view interpolation reduces to the trivial task of rendering polygonal meshes, which can be done very fast, particularly when GPUs are employed. Furthermore, the generated views are hole-free, unlike most point-based view interpolation schemes that require some kind of post-processing procedures to fill holes.

A Novel BA Complex Network Model on Color Template Matching

PubMed Central

Han, Risheng; Yue, Guangxue; Ding, Hui

2014-01-01

A novel BA complex network model of color space is proposed based on two fundamental rules of BA scale-free network model: growth and preferential attachment. The scale-free characteristic of color space is discovered by analyzing evolving process of template's color distribution. And then the template's BA complex network model can be used to select important color pixels which have much larger effects than other color pixels in matching process. The proposed BA complex network model of color space can be easily integrated into many traditional template matching algorithms, such as SSD based matching and SAD based matching. Experiments show the performance of color template matching results can be improved based on the proposed algorithm. To the best of our knowledge, this is the first study about how to model the color space of images using a proper complex network model and apply the complex network model to template matching. PMID:25243235

A novel BA complex network model on color template matching.

PubMed

Han, Risheng; Shen, Shigen; Yue, Guangxue; Ding, Hui

2014-01-01

A novel BA complex network model of color space is proposed based on two fundamental rules of BA scale-free network model: growth and preferential attachment. The scale-free characteristic of color space is discovered by analyzing evolving process of template's color distribution. And then the template's BA complex network model can be used to select important color pixels which have much larger effects than other color pixels in matching process. The proposed BA complex network model of color space can be easily integrated into many traditional template matching algorithms, such as SSD based matching and SAD based matching. Experiments show the performance of color template matching results can be improved based on the proposed algorithm. To the best of our knowledge, this is the first study about how to model the color space of images using a proper complex network model and apply the complex network model to template matching.

An improved principal component analysis based region matching method for fringe direction estimation

NASA Astrophysics Data System (ADS)

He, A.; Quan, C.

2018-04-01

The principal component analysis (PCA) and region matching combined method is effective for fringe direction estimation. However, its mask construction algorithm for region matching fails in some circumstances, and the algorithm for conversion of orientation to direction in mask areas is computationally-heavy and non-optimized. We propose an improved PCA based region matching method for the fringe direction estimation, which includes an improved and robust mask construction scheme, and a fast and optimized orientation-direction conversion algorithm for the mask areas. Along with the estimated fringe direction map, filtered fringe pattern by automatic selective reconstruction modification and enhanced fast empirical mode decomposition (ASRm-EFEMD) is used for Hilbert spiral transform (HST) to demodulate the phase. Subsequently, windowed Fourier ridge (WFR) method is used for the refinement of the phase. The robustness and effectiveness of proposed method are demonstrated by both simulated and experimental fringe patterns.

Phase Equilibrium and Crystal Growth Studies on AgGaSe2 and Related Nonlinear Optical Materials

DTIC Science & Technology

1989-09-01

identify by block number) IELD GROUP SUB-GROUP - "°Silver selenogallate, AgGaSe2, nonlinear optical materials, infrared materials, optical defects 19...materials has unique nonlinear infrared optical properties( 1-4 ) including high nonlinear coefficients, and the ability to be phase matched through a...have a milky appearance in thin section or when viewed with a commercial infrared image converter. Microscopic examination of AgGaSe2 in both reflected

Four dimensional magnetic resonance imaging with retrospective k-space reordering: A feasibility study

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

Liu, Yilin; Yin, Fang-Fang; Cai, Jing, E-mail: jing.cai@duke.edu

Purpose: Current four dimensional magnetic resonance imaging (4D-MRI) techniques lack sufficient temporal/spatial resolution and consistent tumor contrast. To overcome these limitations, this study presents the development and initial evaluation of a new strategy for 4D-MRI which is based on retrospective k-space reordering. Methods: We simulated a k-space reordered 4D-MRI on a 4D digital extended cardiac-torso (XCAT) human phantom. A 2D echo planar imaging MRI sequence [frame rate (F) = 0.448 Hz; image resolution (R) = 256 × 256; number of k-space segments (N{sub KS}) = 4] with sequential image acquisition mode was assumed for the simulation. Image quality of themore » simulated “4D-MRI” acquired from the XCAT phantom was qualitatively evaluated, and tumor motion trajectories were compared to input signals. In particular, mean absolute amplitude differences (D) and cross correlation coefficients (CC) were calculated. Furthermore, to evaluate the data sufficient condition for the new 4D-MRI technique, a comprehensive simulation study was performed using 30 cancer patients’ respiratory profiles to study the relationships between data completeness (C{sub p}) and a number of impacting factors: the number of repeated scans (N{sub R}), number of slices (N{sub S}), number of respiratory phase bins (N{sub P}), N{sub KS}, F, R, and initial respiratory phase at image acquisition (P{sub 0}). As a proof-of-concept, we implemented the proposed k-space reordering 4D-MRI technique on a T2-weighted fast spin echo MR sequence and tested it on a healthy volunteer. Results: The simulated 4D-MRI acquired from the XCAT phantom matched closely to the original XCAT images. Tumor motion trajectories measured from the simulated 4D-MRI matched well with input signals (D = 0.83 and 0.83 mm, and CC = 0.998 and 0.992 in superior–inferior and anterior–posterior directions, respectively). The relationship between C{sub p} and N{sub R} was found best represented by an exponential function (C{sub P}=100(1−e{sup −0.18N{sub R}}), when N{sub S} = 30, N{sub P} = 6). At a C{sub P} value of 95%, the relative error in tumor volume was 0.66%, indicating that N{sub R} at a C{sub P} value of 95% (N{sub R,95%}) is sufficient. It was found that N{sub R,95%} is approximately linearly proportional to N{sub P} (r = 0.99), and nearly independent of all other factors. The 4D-MRI images of the healthy volunteer clearly demonstrated respiratory motion in the diaphragm region with minimal motion induced noise or aliasing. Conclusions: It is feasible to generate respiratory correlated 4D-MRI by retrospectively reordering k-space based on respiratory phase. This new technology may lead to the next generation 4D-MRI with high spatiotemporal resolution and optimal tumor contrast, holding great promises to improve the motion management in radiotherapy of mobile cancers.« less

SU-E-J-59: Feasibility of Markerless Tumor Tracking by Sequential Dual-Energy Fluoroscopy On a Clinical Tumor Tracking System

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

Dhont, J; Poels, K; Verellen, D

2015-06-15

Purpose: To evaluate the feasibility of markerless tumor tracking through the implementation of a novel dual-energy imaging approach into the clinical dynamic tracking (DT) workflow of the Vero SBRT system. Methods: Two sequential 20 s (11 Hz) fluoroscopy sequences were acquired at the start of one fraction for 7 patients treated for primary and metastatic lung cancer with DT on the Vero system. Sequences were acquired using 2 on-board kV imaging systems located at ±45° from the MV beam axis, at respectively 60 kVp (3.2 mAs) and 120 kVp (2.0 mAs). Offline, a normalized cross-correlation algorithm was applied to matchmore » the high (HE) and low energy (LE) images. Per breathing phase (inhale, exhale, maximum inhale and maximum exhale), the 5 best-matching HE and LE couples were extracted for DE subtraction. A contrast analysis according to gross tumor volume was conducted based on contrast-to-noise ratio (CNR). Improved tumor visibility was quantified using an improvement ratio. Results: Using the implanted fiducial as a benchmark, HE-LE sequence matching was effective for 13 out of 14 imaging angles. Overlying bony anatomy was removed on all DE images. With the exception of two imaging angles, the DE images showed no significantly improved tumor visibility compared to HE images, with an improvement ratio averaged over all patients of 1.46 ± 1.64. Qualitatively, it was observed that for those imaging angles that showed no significantly improved CNR, the tumor tissue could not be reliably visualized on neither HE nor DE images due to a total or partial overlap with other soft tissue. Conclusion: Dual-energy subtraction imaging by sequential orthogonal fluoroscopy was shown feasible by implementing an additional LE fluoroscopy sequence. However, for most imaging angles, DE images did not provide improved tumor visibility over single-energy images. Optimizing imaging angles is likely to improve tumor visibility and the efficacy of dual-energy imaging. This work was in part sponsored by corporate funding from BrainLAB AG.(BrainLAB AG, Feldkirchen, Germany)« less

WE-G-18C-05: Characterization of Cross-Vendor, Cross-Field Strength MR Image Intensity Variations

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

Paulson, E; Prah, D

2014-06-15

Purpose: Variations in MR image intensity and image intensity nonuniformity (IINU) can challenge the accuracy of intensity-based image segmentation and registration algorithms commonly applied in radiotherapy. The goal of this work was to characterize MR image intensity variations across scanner vendors and field strengths commonly used in radiotherapy. Methods: ACR-MRI phantom images were acquired at 1.5T and 3.0T on GE (450w and 750, 23.1), Siemens (Espree and Verio, VB17B), and Philips (Ingenia, 4.1.3) scanners using commercial spin-echo sequences with matched parameters (TE/TR: 20/500 ms, rBW: 62.5 kHz, TH/skip: 5/5mm). Two radiofrequency (RF) coil combinations were used for each scanner: bodymore » coil alone, and combined body and phased-array head coils. Vendorspecific B1- corrections (PURE/Pre-Scan Normalize/CLEAR) were applied in all head coil cases. Images were transferred offline, corrected for IINU using the MNI N3 algorithm, and normalized. Coefficients of variation (CV=σ/μ) and peak image uniformity (PIU = 1−(Smax−Smin)/(Smax+Smin)) estimates were calculated for one homogeneous phantom slice. Kruskal-Wallis and Wilcoxon matched-pairs tests compared mean MR signal intensities and differences between original and N3 image CV and PIU. Results: Wide variations in both MR image intensity and IINU were observed across scanner vendors, field strengths, and RF coil configurations. Applying the MNI N3 correction for IINU resulted in significant improvements in both CV and PIU (p=0.0115, p=0.0235). However, wide variations in overall image intensity persisted, requiring image normalization to improve consistency across vendors, field strengths, and RF coils. These results indicate that B1- correction routines alone may be insufficient in compensating for IINU and image scaling, warranting additional corrections prior to use of MR images in radiotherapy. Conclusions: MR image intensities and IINU vary as a function of scanner vendor, field strength, and RF coil configuration. A two-step strategy consisting of MNI N3 correction followed by normalization was required to improve MR image consistency. Funding provided by Advancing a Healthier Wisconsin.« less

Face matching impairment in developmental prosopagnosia.

PubMed

White, David; Rivolta, Davide; Burton, A Mike; Al-Janabi, Shahd; Palermo, Romina

2017-02-01

Developmental prosopagnosia (DP) is commonly referred to as 'face blindness', a term that implies a perceptual basis to the condition. However, DP presents as a deficit in face recognition and is diagnosed using memory-based tasks. Here, we test face identification ability in six people with DP, who are severely impaired on face memory tasks, using tasks that do not rely on memory. First, we compared DP to control participants on a standardized test of unfamiliar face matching using facial images taken on the same day and under standardized studio conditions (Glasgow Face Matching Test; GFMT). Scores for DP participants did not differ from normative accuracy scores on the GFMT. Second, we tested face matching performance on a test created using images that were sourced from the Internet and so varied substantially due to changes in viewing conditions and in a person's appearance (Local Heroes Test; LHT). DP participants showed significantly poorer matching accuracy on the LHT than control participants, for both unfamiliar and familiar face matching. Interestingly, this deficit is specific to 'match' trials, suggesting that people with DP may have particular difficulty in matching images of the same person that contain natural day-to-day variations in appearance. We discuss these results in the broader context of individual differences in face matching ability.

CONEDEP: COnvolutional Neural network based Earthquake DEtection and Phase Picking

NASA Astrophysics Data System (ADS)

Zhou, Y.; Huang, Y.; Yue, H.; Zhou, S.; An, S.; Yun, N.

2017-12-01

We developed an automatic local earthquake detection and phase picking algorithm based on Fully Convolutional Neural network (FCN). The FCN algorithm detects and segments certain features (phases) in 3 component seismograms to realize efficient picking. We use STA/LTA algorithm and template matching algorithm to construct the training set from seismograms recorded 1 month before and after the Wenchuan earthquake. Precise P and S phases are identified and labeled to construct the training set. Noise data are produced by combining back-ground noise and artificial synthetic noise to form the equivalent scale of noise set as the signal set. Training is performed on GPUs to achieve efficient convergence. Our algorithm has significantly improved performance in terms of the detection rate and precision in comparison with STA/LTA and template matching algorithms.

Noise in x-ray grating-based phase-contrast imaging

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

Weber, Thomas; Bartl, Peter; Bayer, Florian

Purpose: Grating-based x-ray phase-contrast imaging is a fast developing new modality not only for medical imaging, but as well for other fields such as material sciences. While these many possible applications arise, the knowledge of the noise behavior is essential. Methods: In this work, the authors used a least squares fitting algorithm to calculate the noise behavior of the three quantities absorption, differential phase, and dark-field image. Further, the calculated error formula of the differential phase image was verified by measurements. Therefore, a Talbot interferometer was setup, using a microfocus x-ray tube as source and a Timepix detector for photonmore » counting. Additionally, simulations regarding this topic were performed. Results: It turned out that the variance of the reconstructed phase is only dependent of the total number of photons used to generate the phase image and the visibility of the experimental setup. These results could be evaluated in measurements as well as in simulations. Furthermore, the correlation between absorption and dark-field image was calculated. Conclusions: These results provide the understanding of the noise characteristics of grating-based phase-contrast imaging and will help to improve image quality.« less

Combining Monte Carlo methods with coherent wave optics for the simulation of phase-sensitive X-ray imaging

PubMed Central

Peter, Silvia; Modregger, Peter; Fix, Michael K.; Volken, Werner; Frei, Daniel; Manser, Peter; Stampanoni, Marco

2014-01-01

Phase-sensitive X-ray imaging shows a high sensitivity towards electron density variations, making it well suited for imaging of soft tissue matter. However, there are still open questions about the details of the image formation process. Here, a framework for numerical simulations of phase-sensitive X-ray imaging is presented, which takes both particle- and wave-like properties of X-rays into consideration. A split approach is presented where we combine a Monte Carlo method (MC) based sample part with a wave optics simulation based propagation part, leading to a framework that takes both particle- and wave-like properties into account. The framework can be adapted to different phase-sensitive imaging methods and has been validated through comparisons with experiments for grating interferometry and propagation-based imaging. The validation of the framework shows that the combination of wave optics and MC has been successfully implemented and yields good agreement between measurements and simulations. This demonstrates that the physical processes relevant for developing a deeper understanding of scattering in the context of phase-sensitive imaging are modelled in a sufficiently accurate manner. The framework can be used for the simulation of phase-sensitive X-ray imaging, for instance for the simulation of grating interferometry or propagation-based imaging. PMID:24763652

Efficient structure from motion for oblique UAV images based on maximal spanning tree expansion

NASA Astrophysics Data System (ADS)

Jiang, San; Jiang, Wanshou

2017-10-01

The primary contribution of this paper is an efficient Structure from Motion (SfM) solution for oblique unmanned aerial vehicle (UAV) images. First, an algorithm, considering spatial relationship constraints between image footprints, is designed for match pair selection with the assistance of UAV flight control data and oblique camera mounting angles. Second, a topological connection network (TCN), represented by an undirected weighted graph, is constructed from initial match pairs, which encodes the overlap areas and intersection angles into edge weights. Then, an algorithm, termed MST-Expansion, is proposed to extract the match graph from the TCN, where the TCN is first simplified by a maximum spanning tree (MST). By further analysis of the local structure in the MST, expansion operations are performed on the vertices of the MST for match graph enhancement, which is achieved by introducing critical connections in the expansion directions. Finally, guided by the match graph, an efficient SfM is proposed. Under extensive analysis and comparison, its performance is verified by using three oblique UAV datasets captured with different multi-camera systems. Experimental results demonstrate that the efficiency of image matching is improved, with speedup ratios ranging from 19 to 35, and competitive orientation accuracy is achieved from both relative bundle adjustment (BA) without GCPs (Ground Control Points) and absolute BA with GCPs. At the same time, images in the three datasets are successfully oriented. For the orientation of oblique UAV images, the proposed method can be a more efficient solution.

Quantitative phase imaging using grating-based quadrature phase interferometer

NASA Astrophysics Data System (ADS)

Wu, Jigang; Yaqoob, Zahid; Heng, Xin; Cui, Xiquan; Yang, Changhuei

2007-02-01

In this paper, we report the use of holographic gratings, which act as the free-space equivalent of the 3x3 fiber-optic coupler, to perform full field phase imaging. By recording two harmonically-related gratings in the same holographic plate, we are able to obtain nontrivial phase shift between different output ports of the gratings-based Mach-Zehnder interferometer. The phase difference can be adjusted by changing the relative phase of the recording beams when recording the hologram. We have built a Mach-Zehnder interferometer using harmonically-related holographic gratings with 600 and 1200 lines/mm spacing. Two CCD cameras at the output ports of the gratings-based Mach-Zehnder interferometer are used to record the full-field quadrature interferograms, which are subsequently processed to reconstruct the phase image. The imaging system has ~12X magnification with ~420μmx315μm field-of-view. To demonstrate the capability of our system, we have successfully performed phase imaging of a pure phase object and a paramecium caudatum.

Incremental Multi-view 3D Reconstruction Starting from Two Images Taken by a Stereo Pair of Cameras

NASA Astrophysics Data System (ADS)

El hazzat, Soulaiman; Saaidi, Abderrahim; Karam, Antoine; Satori, Khalid

2015-03-01

In this paper, we present a new method for multi-view 3D reconstruction based on the use of a binocular stereo vision system constituted of two unattached cameras to initialize the reconstruction process. Afterwards , the second camera of stereo vision system (characterized by varying parameters) moves to capture more images at different times which are used to obtain an almost complete 3D reconstruction. The first two projection matrices are estimated by using a 3D pattern with known properties. After that, 3D scene points are recovered by triangulation of the matched interest points between these two images. The proposed approach is incremental. At each insertion of a new image, the camera projection matrix is estimated using the 3D information already calculated and new 3D points are recovered by triangulation from the result of the matching of interest points between the inserted image and the previous image. For the refinement of the new projection matrix and the new 3D points, a local bundle adjustment is performed. At first, all projection matrices are estimated, the matches between consecutive images are detected and Euclidean sparse 3D reconstruction is obtained. So, to increase the number of matches and have a more dense reconstruction, the Match propagation algorithm, more suitable for interesting movement of the camera, was applied on the pairs of consecutive images. The experimental results show the power and robustness of the proposed approach.

Robust, Efficient Depth Reconstruction With Hierarchical Confidence-Based Matching.

PubMed

Sun, Li; Chen, Ke; Song, Mingli; Tao, Dacheng; Chen, Gang; Chen, Chun

2017-07-01

In recent years, taking photos and capturing videos with mobile devices have become increasingly popular. Emerging applications based on the depth reconstruction technique have been developed, such as Google lens blur. However, depth reconstruction is difficult due to occlusions, non-diffuse surfaces, repetitive patterns, and textureless surfaces, and it has become more difficult due to the unstable image quality and uncontrolled scene condition in the mobile setting. In this paper, we present a novel hierarchical framework with multi-view confidence-based matching for robust, efficient depth reconstruction in uncontrolled scenes. Particularly, the proposed framework combines local cost aggregation with global cost optimization in a complementary manner that increases efficiency and accuracy. A depth map is efficiently obtained in a coarse-to-fine manner by using an image pyramid. Moreover, confidence maps are computed to robustly fuse multi-view matching cues, and to constrain the stereo matching on a finer scale. The proposed framework has been evaluated with challenging indoor and outdoor scenes, and has achieved robust and efficient depth reconstruction.

Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR)

PubMed Central

Kalantari, Faraz; Li, Tianfang; Jin, Mingwu; Wang, Jing

2016-01-01

In conventional 4D positron emission tomography (4D-PET), images from different frames are reconstructed individually and aligned by registration methods. Two issues that arise with this approach are as follows: 1) the reconstruction algorithms do not make full use of projection statistics; and 2) the registration between noisy images can result in poor alignment. In this study, we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) methods for motion estimation/correction in 4D-PET. A modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM-TV) was used to obtain a primary motion-compensated PET (pmc-PET) from all projection data, using Demons derived deformation vector fields (DVFs) as initial motion vectors. A motion model update was performed to obtain an optimal set of DVFs in the pmc-PET and other phases, by matching the forward projection of the deformed pmc-PET with measured projections from other phases. The OSEM-TV image reconstruction was repeated using updated DVFs, and new DVFs were estimated based on updated images. A 4D-XCAT phantom with typical FDG biodistribution was generated to evaluate the performance of the SMEIR algorithm in lung and liver tumors with different contrasts and different diameters (10 to 40 mm). The image quality of the 4D-PET was greatly improved by the SMEIR algorithm. When all projections were used to reconstruct 3D-PET without motion compensation, motion blurring artifacts were present, leading up to 150% tumor size overestimation and significant quantitative errors, including 50% underestimation of tumor contrast and 59% underestimation of tumor uptake. Errors were reduced to less than 10% in most images by using the SMEIR algorithm, showing its potential in motion estimation/correction in 4D-PET. PMID:27385378

Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR)

NASA Astrophysics Data System (ADS)

Kalantari, Faraz; Li, Tianfang; Jin, Mingwu; Wang, Jing

2016-08-01

In conventional 4D positron emission tomography (4D-PET), images from different frames are reconstructed individually and aligned by registration methods. Two issues that arise with this approach are as follows: (1) the reconstruction algorithms do not make full use of projection statistics; and (2) the registration between noisy images can result in poor alignment. In this study, we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) methods for motion estimation/correction in 4D-PET. A modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM-TV) was used to obtain a primary motion-compensated PET (pmc-PET) from all projection data, using Demons derived deformation vector fields (DVFs) as initial motion vectors. A motion model update was performed to obtain an optimal set of DVFs in the pmc-PET and other phases, by matching the forward projection of the deformed pmc-PET with measured projections from other phases. The OSEM-TV image reconstruction was repeated using updated DVFs, and new DVFs were estimated based on updated images. A 4D-XCAT phantom with typical FDG biodistribution was generated to evaluate the performance of the SMEIR algorithm in lung and liver tumors with different contrasts and different diameters (10-40 mm). The image quality of the 4D-PET was greatly improved by the SMEIR algorithm. When all projections were used to reconstruct 3D-PET without motion compensation, motion blurring artifacts were present, leading up to 150% tumor size overestimation and significant quantitative errors, including 50% underestimation of tumor contrast and 59% underestimation of tumor uptake. Errors were reduced to less than 10% in most images by using the SMEIR algorithm, showing its potential in motion estimation/correction in 4D-PET.

Optical colour image watermarking based on phase-truncated linear canonical transform and image decomposition

NASA Astrophysics Data System (ADS)

Su, Yonggang; Tang, Chen; Li, Biyuan; Lei, Zhenkun

2018-05-01

This paper presents a novel optical colour image watermarking scheme based on phase-truncated linear canonical transform (PT-LCT) and image decomposition (ID). In this proposed scheme, a PT-LCT-based asymmetric cryptography is designed to encode the colour watermark into a noise-like pattern, and an ID-based multilevel embedding method is constructed to embed the encoded colour watermark into a colour host image. The PT-LCT-based asymmetric cryptography, which can be optically implemented by double random phase encoding with a quadratic phase system, can provide a higher security to resist various common cryptographic attacks. And the ID-based multilevel embedding method, which can be digitally implemented by a computer, can make the information of the colour watermark disperse better in the colour host image. The proposed colour image watermarking scheme possesses high security and can achieve a higher robustness while preserving the watermark’s invisibility. The good performance of the proposed scheme has been demonstrated by extensive experiments and comparison with other relevant schemes.

Intelligent retrieval of medical images from the Internet

NASA Astrophysics Data System (ADS)

Tang, Yau-Kuo; Chiang, Ted T.

1996-05-01

The object of this study is using Internet resources to provide a cost-effective, user-friendly method to access the medical image archive system and to provide an easy method for the user to identify the images required. This paper describes the prototype system architecture, the implementation, and results. In the study, we prototype the Intelligent Medical Image Retrieval (IMIR) system as a Hypertext Transport Prototype server and provide Hypertext Markup Language forms for user, as an Internet client, using browser to enter image retrieval criteria for review. We are developing the intelligent retrieval engine, with the capability to map the free text search criteria to the standard terminology used for medical image identification. We evaluate retrieved records based on the number of the free text entries matched and their relevance level to the standard terminology. We are in the integration and testing phase. We have collected only a few different types of images for testing and have trained a few phrases to map the free text to the standard medical terminology. Nevertheless, we are able to demonstrate the IMIR's ability to search, retrieve, and review medical images from the archives using general Internet browser. The prototype also uncovered potential problems in performance, security, and accuracy. Additional studies and enhancements will make the system clinically operational.

Recording Approach of Heritage Sites Based on Merging Point Clouds from High Resolution Photogrammetry and Terrestrial Laser Scanning

NASA Astrophysics Data System (ADS)

Grussenmeyer, P.; Alby, E.; Landes, T.; Koehl, M.; Guillemin, S.; Hullo, J. F.; Assali, P.; Smigiel, E.

2012-07-01

Different approaches and tools are required in Cultural Heritage Documentation to deal with the complexity of monuments and sites. The documentation process has strongly changed in the last few years, always driven by technology. Accurate documentation is closely relied to advances of technology (imaging sensors, high speed scanning, automation in recording and processing data) for the purposes of conservation works, management, appraisal, assessment of the structural condition, archiving, publication and research (Patias et al., 2008). We want to focus in this paper on the recording aspects of cultural heritage documentation, especially the generation of geometric and photorealistic 3D models for accurate reconstruction and visualization purposes. The selected approaches are based on the combination of photogrammetric dense matching and Terrestrial Laser Scanning (TLS) techniques. Both techniques have pros and cons and recent advances have changed the way of the recording approach. The choice of the best workflow relies on the site configuration, the performances of the sensors, and criteria as geometry, accuracy, resolution, georeferencing, texture, and of course processing time. TLS techniques (time of flight or phase shift systems) are widely used for recording large and complex objects and sites. Point cloud generation from images by dense stereo or multi-view matching can be used as an alternative or as a complementary method to TLS. Compared to TLS, the photogrammetric solution is a low cost one, as the acquisition system is limited to a high-performance digital camera and a few accessories only. Indeed, the stereo or multi-view matching process offers a cheap, flexible and accurate solution to get 3D point clouds. Moreover, the captured images might also be used for models texturing. Several software packages are available, whether web-based, open source or commercial. The main advantage of this photogrammetric or computer vision based technology is to get at the same time a point cloud (the resolution depends on the size of the pixel on the object), and therefore an accurate meshed object with its texture. After matching and processing steps, we can use the resulting data in much the same way as a TLS point cloud, but in addition with radiometric information for textures. The discussion in this paper reviews recording and important processing steps as geo-referencing and data merging, the essential assessment of the results, and examples of deliverables from projects of the Photogrammetry and Geomatics Group (INSA Strasbourg, France).