Science.gov

Sample records for adaptive image enhancement

  1. Adaptive color contrast enhancement for digital images

    NASA Astrophysics Data System (ADS)

    Wang, Yanfang; Luo, Yupin

    2011-11-01

    Noncanonical illumination that is too dim or with color cast induces degenerated images. To cope with this, we propose a method for color-contrast enhancement. First, intensity, chrominance, and contrast characteristics are explored and integrated in the Naka-Rushton equation to remove underexposure and color cast simultaneously. Motivated by the comparison mechanism in Retinex, the ratio of each pixel to its surroundings is utilized to improve image contrast. Finally, inspired by the two color-opponent dimensions in CIELAB space, a color-enhancement strategy is devised based on the transformation from CIEXYZ to CIELAB color space. For images that suffer from underexposure, color cast, or both problems, our algorithm produces promising results without halo artifacts and corruption of uniform areas.

  2. An adaptive algorithm for low contrast infrared image enhancement

    NASA Astrophysics Data System (ADS)

    Liu, Sheng-dong; Peng, Cheng-yuan; Wang, Ming-jia; Wu, Zhi-guo; Liu, Jia-qi

    2013-08-01

    An adaptive infrared image enhancement algorithm for low contrast is proposed in this paper, to deal with the problem that conventional image enhancement algorithm is not able to effective identify the interesting region when dynamic range is large in image. This algorithm begin with the human visual perception characteristics, take account of the global adaptive image enhancement and local feature boost, not only the contrast of image is raised, but also the texture of picture is more distinct. Firstly, the global image dynamic range is adjusted from the overall, the dynamic range of original image and display grayscale form corresponding relationship, the gray scale of bright object is raised and the the gray scale of dark target is reduced at the same time, to improve the overall image contrast. Secondly, the corresponding filtering algorithm is used on the current point and its neighborhood pixels to extract image texture information, to adjust the brightness of the current point in order to enhance the local contrast of the image. The algorithm overcomes the default that the outline is easy to vague in traditional edge detection algorithm, and ensure the distinctness of texture detail in image enhancement. Lastly, we normalize the global luminance adjustment image and the local brightness adjustment image, to ensure a smooth transition of image details. A lot of experiments is made to compare the algorithm proposed in this paper with other convention image enhancement algorithm, and two groups of vague IR image are taken in experiment. Experiments show that: the contrast ratio of the picture is boosted after handled by histogram equalization algorithm, but the detail of the picture is not clear, the detail of the picture can be distinguished after handled by the Retinex algorithm. The image after deal with by self-adaptive enhancement algorithm proposed in this paper becomes clear in details, and the image contrast is markedly improved in compared with Retinex

  3. Real-time adaptive video image enhancement

    NASA Astrophysics Data System (ADS)

    Garside, John R.; Harrison, Chris G.

    1999-07-01

    As part of a continuing collaboration between the University of Manchester and British Aerospace, a signal processing array has been constructed to demonstrate that it is feasible to compensate a video signal for the degradation caused by atmospheric haze in real-time. Previously reported work has shown good agreement between a simple physical model of light scattering by atmospheric haze and the observed loss of contrast. This model predicts a characteristic relationship between contrast loss in the image and the range from the camera to the scene. For an airborne camera, the slant-range to a point on the ground may be estimated from the airplane's pose, as reported by the inertial navigation system, and the contrast may be obtained from the camera's output. Fusing data from these two streams provides a means of estimating model parameters such as the visibility and the overall illumination of the scene. This knowledge allows the same model to be applied in reverse, thus restoring the contrast lost to atmospheric haze. An efficient approximation of range is vital for a real-time implementation of the method. Preliminary results show that an adaptive approach to fitting the model's parameters, exploiting the temporal correlation between video frames, leads to a robust implementation with a significantly accelerated throughput.

  4. Adaptive enhancement method of infrared image based on scene feature

    NASA Astrophysics Data System (ADS)

    Zhang, Xiao; Bai, Tingzhu; Shang, Fei

    2008-12-01

    All objects emit radiation in amounts related to their temperature and their ability to emit radiation. The infrared image shows the invisible infrared radiation emitted directly. Because of the advantages, the technology of infrared imaging is applied to many kinds of fields. But compared with visible image, the disadvantages of infrared image are obvious. The characteristics of low luminance, low contrast and the inconspicuous difference target and background are the main disadvantages of infrared image. The aim of infrared image enhancement is to improve the interpretability or perception of information in infrared image for human viewers, or to provide 'better' input for other automated image processing techniques. Most of the adaptive algorithm for image enhancement is mainly based on the gray-scale distribution of infrared image, and is not associated with the actual image scene of the features. So the pertinence of infrared image enhancement is not strong, and the infrared image is not conducive to the application of infrared surveillance. In this paper we have developed a scene feature-based algorithm to enhance the contrast of infrared image adaptively. At first, after analyzing the scene feature of different infrared image, we have chosen the feasible parameters to describe the infrared image. In the second place, we have constructed the new histogram distributing base on the chosen parameters by using Gaussian function. In the last place, the infrared image is enhanced by constructing a new form of histogram. Experimental results show that the algorithm has better performance than other methods mentioned in this paper for infrared scene images.

  5. Adaptive fingerprint image enhancement with emphasis on preprocessing of data.

    PubMed

    Bartůnek, Josef Ström; Nilsson, Mikael; Sällberg, Benny; Claesson, Ingvar

    2013-02-01

    This article proposes several improvements to an adaptive fingerprint enhancement method that is based on contextual filtering. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. Five processing blocks comprise the adaptive fingerprint enhancement method, where four of these blocks are updated in our proposed system. Hence, the proposed overall system is novel. The four updated processing blocks are: 1) preprocessing; 2) global analysis; 3) local analysis; and 4) matched filtering. In the preprocessing and local analysis blocks, a nonlinear dynamic range adjustment method is used. In the global analysis and matched filtering blocks, different forms of order statistical filters are applied. These processing blocks yield an improved and new adaptive fingerprint image processing method. The performance of the updated processing blocks is presented in the evaluation part of this paper. The algorithm is evaluated toward the NIST developed NBIS software for fingerprint recognition on FVC databases.

  6. Adaptive neural network for image enhancement

    NASA Astrophysics Data System (ADS)

    Perl, Dan; Marsland, T. A.

    1992-09-01

    ANNIE is a neural network that removes noise and sharpens edges in digital images. For noise removal, ANNIE makes a weighted average of the values of the pixels over a certain neighborhood. For edge sharpening, ANNIE detects edges and applies a correction around them. Although averaging is a simple operation and needs only a two-layer neural network, detecting edges is more complex and demands several hidden layers. Based on Marr's theory of natural vision, the edge detection method uses zero-crossings in the image filtered by the ∇2G operator (where ∇2 is the Laplacian operator and G stands for a two- dimensional Gaussian distribution), and uses two channels with different spatial frequencies. Edge detectors are tuned for vertical and horizontal orientations. Lateral inhibition implemented through one-step recursion achieves both edge relaxation and correlation of the two channels. Training by means of the quickprop algorithm determines the shapes of the weighted averaging filter and the edge correction filters, and the rules for edge relaxation and channel interaction. ANNIE uses pairs of pictures as training patterns: one picture is a reference for the output of the network and the same picture deteriorated by noise and/or blur is the input of the network.

  7. Adaptive Intuitionistic Fuzzy Enhancement of Brain Tumor MR Images

    PubMed Central

    Deng, He; Deng, Wankai; Sun, Xianping; Ye, Chaohui; Zhou, Xin

    2016-01-01

    Image enhancement techniques are able to improve the contrast and visual quality of magnetic resonance (MR) images. However, conventional methods cannot make up some deficiencies encountered by respective brain tumor MR imaging modes. In this paper, we propose an adaptive intuitionistic fuzzy sets-based scheme, called as AIFE, which takes information provided from different MR acquisitions and tries to enhance the normal and abnormal structural regions of the brain while displaying the enhanced results as a single image. The AIFE scheme firstly separates an input image into several sub images, then divides each sub image into object and background areas. After that, different novel fuzzification, hyperbolization and defuzzification operations are implemented on each object/background area, and finally an enhanced result is achieved via nonlinear fusion operators. The fuzzy implementations can be processed in parallel. Real data experiments demonstrate that the AIFE scheme is not only effectively useful to have information from images acquired with different MR sequences fused in a single image, but also has better enhancement performance when compared to conventional baseline algorithms. This indicates that the proposed AIFE scheme has potential for improving the detection and diagnosis of brain tumors. PMID:27786240

  8. Adaptive sigmoid function bihistogram equalization for image contrast enhancement

    NASA Astrophysics Data System (ADS)

    Arriaga-Garcia, Edgar F.; Sanchez-Yanez, Raul E.; Ruiz-Pinales, Jose; Garcia-Hernandez, Ma. de Guadalupe

    2015-09-01

    Contrast enhancement plays a key role in a wide range of applications including consumer electronic applications, such as video surveillance, digital cameras, and televisions. The main goal of contrast enhancement is to increase the quality of images. However, most state-of-the-art methods induce different types of distortion such as intensity shift, wash-out, noise, intensity burn-out, and intensity saturation. In addition, in consumer electronics, simple and fast methods are required in order to be implemented in real time. A bihistogram equalization method based on adaptive sigmoid functions is proposed. It consists of splitting the image histogram into two parts that are equalized independently by using adaptive sigmoid functions. In order to preserve the mean brightness of the input image, the parameter of the sigmoid functions is chosen to minimize the absolute mean brightness metric. Experiments on the Berkeley database have shown that the proposed method improves the quality of images and preserves their mean brightness. An application to improve the colorfulness of images is also presented.

  9. Adaptive image contrast enhancement algorithm for point-based rendering

    NASA Astrophysics Data System (ADS)

    Xu, Shaoping; Liu, Xiaoping P.

    2015-03-01

    Surgical simulation is a major application in computer graphics and virtual reality, and most of the existing work indicates that interactive real-time cutting simulation of soft tissue is a fundamental but challenging research problem in virtual surgery simulation systems. More specifically, it is difficult to achieve a fast enough graphic update rate (at least 30 Hz) on commodity PC hardware by utilizing traditional triangle-based rendering algorithms. In recent years, point-based rendering (PBR) has been shown to offer the potential to outperform the traditional triangle-based rendering in speed when it is applied to highly complex soft tissue cutting models. Nevertheless, the PBR algorithms are still limited in visual quality due to inherent contrast distortion. We propose an adaptive image contrast enhancement algorithm as a postprocessing module for PBR, providing high visual rendering quality as well as acceptable rendering efficiency. Our approach is based on a perceptible image quality technique with automatic parameter selection, resulting in a visual quality comparable to existing conventional PBR algorithms. Experimental results show that our adaptive image contrast enhancement algorithm produces encouraging results both visually and numerically compared to representative algorithms, and experiments conducted on the latest hardware demonstrate that the proposed PBR framework with the postprocessing module is superior to the conventional PBR algorithm and that the proposed contrast enhancement algorithm can be utilized in (or compatible with) various variants of the conventional PBR algorithm.

  10. Low-Light Image Enhancement Using Adaptive Digital Pixel Binning

    PubMed Central

    Yoo, Yoonjong; Im, Jaehyun; Paik, Joonki

    2015-01-01

    This paper presents an image enhancement algorithm for low-light scenes in an environment with insufficient illumination. Simple amplification of intensity exhibits various undesired artifacts: noise amplification, intensity saturation, and loss of resolution. In order to enhance low-light images without undesired artifacts, a novel digital binning algorithm is proposed that considers brightness, context, noise level, and anti-saturation of a local region in the image. The proposed algorithm does not require any modification of the image sensor or additional frame-memory; it needs only two line-memories in the image signal processor (ISP). Since the proposed algorithm does not use an iterative computation, it can be easily embedded in an existing digital camera ISP pipeline containing a high-resolution image sensor. PMID:26121609

  11. Low-Light Image Enhancement Using Adaptive Digital Pixel Binning.

    PubMed

    Yoo, Yoonjong; Im, Jaehyun; Paik, Joonki

    2015-01-01

    This paper presents an image enhancement algorithm for low-light scenes in an environment with insufficient illumination. Simple amplification of intensity exhibits various undesired artifacts: noise amplification, intensity saturation, and loss of resolution. In order to enhance low-light images without undesired artifacts, a novel digital binning algorithm is proposed that considers brightness, context, noise level, and anti-saturation of a local region in the image. The proposed algorithm does not require any modification of the image sensor or additional frame-memory; it needs only two line-memories in the image signal processor (ISP). Since the proposed algorithm does not use an iterative computation, it can be easily embedded in an existing digital camera ISP pipeline containing a high-resolution image sensor. PMID:26121609

  12. Adaptive image enhancement of text images that contain touching or broken characters

    SciTech Connect

    Stubberud, P.; Kalluri, V.; Kanai, J.

    1994-11-29

    Text images that contain touching or broken characters can significantly degrade the accuracy of optical character recognition (OCR) systems. This paper proposes an adaptive image restoration technique that can improve OCR accuracy by enhancing touching or broken character images. The technique begins by processing a distorted text image with an OCR system. Using the distorted text image and output information from the OCR system, an inverse model of the distortion that caused the touching or broken character problem is generated. After generating the inverse model, the unrecognized distorted characters are filtered by the inverse model and then processes by the OCR system. To demonstrate its feasibility, six distorted text images were processed using this technique. Four of the text images, two with touching characters and two with broken characters, were synthesized using mathematical distortion models. The remaining two distorted text images, one with touching characters and one with broken characters, were distorted using a photocopier. The performance of the adaptive image restoration technique was measured using pixel accuracy and OCR improvement. The examples demonstrate that this technique can improve both the pixel and OCR accuracy of text images containing touching or broken characters.

  13. An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

    PubMed

    Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

    2015-01-01

    Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928

  14. An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

    PubMed

    Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

    2015-01-01

    Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

  15. An Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm

    PubMed Central

    Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

    2015-01-01

    Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928

  16. Adaptive and Background-Aware GAL4 Expression Enhancement of Co-registered Confocal Microscopy Images.

    PubMed

    Trapp, Martin; Schulze, Florian; Novikov, Alexey A; Tirian, Laszlo; J Dickson, Barry; Bühler, Katja

    2016-04-01

    GAL4 gene expression imaging using confocal microscopy is a common and powerful technique used to study the nervous system of a model organism such as Drosophila melanogaster. Recent research projects focused on high throughput screenings of thousands of different driver lines, resulting in large image databases. The amount of data generated makes manual assessment tedious or even impossible. The first and most important step in any automatic image processing and data extraction pipeline is to enhance areas with relevant signal. However, data acquired via high throughput imaging tends to be less then ideal for this task, often showing high amounts of background signal. Furthermore, neuronal structures and in particular thin and elongated projections with a weak staining signal are easily lost. In this paper we present a method for enhancing the relevant signal by utilizing a Hessian-based filter to augment thin and weak tube-like structures in the image. To get optimal results, we present a novel adaptive background-aware enhancement filter parametrized with the local background intensity, which is estimated based on a common background model. We also integrate recent research on adaptive image enhancement into our approach, allowing us to propose an effective solution for known problems present in confocal microscopy images. We provide an evaluation based on annotated image data and compare our results against current state-of-the-art algorithms. The results show that our algorithm clearly outperforms the existing solutions. PMID:26743993

  17. Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering.

    PubMed

    Sudeep, P V; Issac Niwas, S; Palanisamy, P; Rajan, Jeny; Xiaojun, Yu; Wang, Xianghong; Luo, Yuemei; Liu, Linbo

    2016-04-01

    Optical coherence tomography (OCT) has continually evolved and expanded as one of the most valuable routine tests in ophthalmology. However, noise (speckle) in the acquired images causes quality degradation of OCT images and makes it difficult to analyze the acquired images. In this paper, an iterative approach based on bilateral filtering is proposed for speckle reduction in multiframe OCT data. Gamma noise model is assumed for the observed OCT image. First, the adaptive version of the conventional bilateral filter is applied to enhance the multiframe OCT data and then the bias due to noise is reduced from each of the filtered frames. These unbiased filtered frames are then refined using an iterative approach. Finally, these refined frames are averaged to produce the denoised OCT image. Experimental results on phantom images and real OCT retinal images demonstrate the effectiveness of the proposed filter. PMID:26907572

  18. Conductivity image enhancement in MREIT using adaptively weighted spatial averaging filter

    PubMed Central

    2014-01-01

    Background In magnetic resonance electrical impedance tomography (MREIT), we reconstruct conductivity images using magnetic flux density data induced by externally injected currents. Since we extract magnetic flux density data from acquired MR phase images, the amount of measurement noise increases in regions of weak MR signals. Especially for local regions of MR signal void, there may occur excessive amounts of noise to deteriorate the quality of reconstructed conductivity images. In this paper, we propose a new conductivity image enhancement method as a postprocessing technique to improve the image quality. Methods Within a magnetic flux density image, the amount of noise varies depending on the position-dependent MR signal intensity. Using the MR magnitude image which is always available in MREIT, we estimate noise levels of measured magnetic flux density data in local regions. Based on the noise estimates, we adjust the window size and weights of a spatial averaging filter, which is applied to reconstructed conductivity images. Without relying on a partial differential equation, the new method is fast and can be easily implemented. Results Applying the novel conductivity image enhancement method to experimental data, we could improve the image quality to better distinguish local regions with different conductivity contrasts. From phantom experiments, the estimated conductivity values had 80% less variations inside regions of homogeneous objects. Reconstructed conductivity images from upper and lower abdominal regions of animals showed much less artifacts in local regions of weak MR signals. Conclusion We developed the fast and simple method to enhance the conductivity image quality by adaptively adjusting the weights and window size of the spatial averaging filter using MR magnitude images. Since the new method is implemented as a postprocessing step, we suggest adopting it without or with other preprocessing methods for application studies where conductivity

  19. Super Resolution Reconstruction Based on Adaptive Detail Enhancement for ZY-3 Satellite Images

    NASA Astrophysics Data System (ADS)

    Zhu, Hong; Song, Weidong; Tan, Hai; Wang, Jingxue; Jia, Di

    2016-06-01

    Super-resolution reconstruction of sequence remote sensing image is a technology which handles multiple low-resolution satellite remote sensing images with complementary information and obtains one or more high resolution images. The cores of the technology are high precision matching between images and high detail information extraction and fusion. In this paper puts forward a new image super resolution model frame which can adaptive multi-scale enhance the details of reconstructed image. First, the sequence images were decomposed into a detail layer containing the detail information and a smooth layer containing the large scale edge information by bilateral filter. Then, a texture detail enhancement function was constructed to promote the magnitude of the medium and small details. Next, the non-redundant information of the super reconstruction was obtained by differential processing of the detail layer, and the initial super resolution construction result was achieved by interpolating fusion of non-redundant information and the smooth layer. At last, the final reconstruction image was acquired by executing a local optimization model on the initial constructed image. Experiments on ZY-3 satellite images of same phase and different phase show that the proposed method can both improve the information entropy and the image details evaluation standard comparing with the interpolation method, traditional TV algorithm and MAP algorithm, which indicate that our method can obviously highlight image details and contains more ground texture information. A large number of experiment results reveal that the proposed method is robust and universal for different kinds of ZY-3 satellite images.

  20. Adapted waveform analysis: a tool for audio, image, and video enhancement

    NASA Astrophysics Data System (ADS)

    Coifman, Ronald R.; Woog, Lionel J.

    1997-02-01

    Adapted wave form analysis, refers to a collection of FFT like adapted transform algorithms. Given a signal these methods provide special matched collections of templates (orthonormal bases) enabling an efficient extraction of structural components. As a result various operations such as denoising, undesirable background suppression, sharpening and enhancement can be achieved efficiently. Perhaps the closest well known example of such coding method is provided by musical notation, where each segment of music is represented by a musical score made up of notes (templates) characterized by their duration, pitch, location and amplitude, our method corresponds to transcribing the music in as few notes as possible. Since noise and static are difficult to describe efficiently we obtain as a byproduct a denoised version of the sound. This transcription in a score can be developed into a mathematical musical orchestration as described below. The extension to images and video is straightforward we describe the image by collections of oscillatory patterns (paint brush strokes) of various sizes, locations, and amplitudes using a variety of orthogonal bases.

  1. Noise correlation-based adaptive polarimetric image representation for contrast enhancement of a polarized beacon in fog

    NASA Astrophysics Data System (ADS)

    Panigrahi, Swapnesh; Fade, Julien; Alouini, Mehdi

    2015-10-01

    We show the use of a simplified snapshot polarimetric camera along with an adaptive image processing for optimal detection of a polarized light beacon through fog. The adaptive representation is derived using theoretical noise analysis of the data at hand and is shown to be optimal in the Maximum likelihood sense. We report that the contrast enhancing optimal representation that depends on the background noise correlation differs in general from standard representations like polarimetric difference image or polarization filtered image. Lastly, we discuss a detection strategy to reduce the false positive counts.

  2. In Vivo Imaging of the Human Retinal Pigment Epithelial Mosaic Using Adaptive Optics Enhanced Indocyanine Green Ophthalmoscopy

    PubMed Central

    Tam, Johnny; Liu, Jianfei; Dubra, Alfredo; Fariss, Robert

    2016-01-01

    Purpose The purpose of this study was to establish that retinal pigment epithelial (RPE) cells take up indocyanine green (ICG) dye following systemic injection and that adaptive optics enhanced indocyanine green ophthalmoscopy (AO-ICG) enables direct visualization of the RPE mosaic in the living human eye. Methods A customized adaptive optics scanning light ophthalmoscope (AOSLO) was used to acquire high-resolution retinal fluorescence images of residual ICG dye in human subjects after intravenous injection at the standard clinical dose. Simultaneously, multimodal AOSLO images were also acquired, which included confocal reflectance, nonconfocal split detection, and darkfield. Imaging was performed in 6 eyes of three healthy subjects with no history of ocular or systemic diseases. In addition, histologic studies in mice were carried out. Results The AO-ICG channel successfully resolved individual RPE cells in human subjects at various time points, including 20 minutes and 2 hours after dye administration. Adaptive optics-ICG images of RPE revealed detail which could be correlated with AO dark-field images of the same cells. Interestingly, there was a marked heterogeneity in the fluorescence of individual RPE cells. Confirmatory histologic studies in mice corroborated the specific uptake of ICG by the RPE layer at a late time point after systemic ICG injection. Conclusions Adaptive optics-enhanced imaging of ICG dye provides a novel way to visualize and assess the RPE mosaic in the living human eye alongside images of the overlying photoreceptors and other cells. PMID:27564519

  3. Edge preserved enhancement of medical images using adaptive fusion-based denoising by shearlet transform and total variation algorithm

    NASA Astrophysics Data System (ADS)

    Gupta, Deep; Anand, Radhey Shyam; Tyagi, Barjeev

    2013-10-01

    Edge preserved enhancement is of great interest in medical images. Noise present in medical images affects the quality, contrast resolution, and most importantly, texture information and can make post-processing difficult also. An enhancement approach using an adaptive fusion algorithm is proposed which utilizes the features of shearlet transform (ST) and total variation (TV) approach. In the proposed method, three different denoised images processed with TV method, shearlet denoising, and edge information recovered from the remnant of the TV method and processed with the ST are fused adaptively. The result of enhanced images processed with the proposed method helps to improve the visibility and detectability of medical images. For the proposed method, different weights are evaluated from the different variance maps of individual denoised image and the edge extracted information from the remnant of the TV approach. The performance of the proposed method is evaluated by conducting various experiments on both the standard images and different medical images such as computed tomography, magnetic resonance, and ultrasound. Experiments show that the proposed method provides an improvement not only in noise reduction but also in the preservation of more edges and image details as compared to the others.

  4. Adaptive enhancement and visualization techniques for 3D THz images of breast cancer tumors

    NASA Astrophysics Data System (ADS)

    Wu, Yuhao; Bowman, Tyler; Gauch, John; El-Shenawee, Magda

    2016-03-01

    This paper evaluates image enhancement and visualization techniques for pulsed terahertz (THz) images of tissue samples. Specifically, our research objective is to effectively differentiate between heterogeneous regions of breast tissues that contain tumors diagnosed as triple negative infiltrating ductal carcinoma (IDC). Tissue slices and blocks of varying thicknesses were prepared and scanned using our lab's THz pulsed imaging system. One of the challenges we have encountered in visualizing the obtained images and differentiating between healthy and cancerous regions of the tissues is that most THz images have a low level of details and narrow contrast, making it difficult to accurately identify and visualize the margins around the IDC. To overcome this problem, we have applied and evaluated a number of image processing techniques to the scanned 3D THz images. In particular, we employed various spatial filtering and intensity transformation techniques to emphasize the small details in the images and adjust the image contrast. For each of these methods, we investigated how varying filter sizes and parameters affect the amount of enhancement applied to the images. Our experimentation shows that several image processing techniques are effective in producing THz images of breast tissue samples that contain distinguishable details, making further segmentation of the different image regions promising.

  5. Multimodal adaptive optics for depth-enhanced high-resolution ophthalmic imaging

    NASA Astrophysics Data System (ADS)

    Hammer, Daniel X.; Mujat, Mircea; Iftimia, Nicusor V.; Lue, Niyom; Ferguson, R. Daniel

    2010-02-01

    We developed a multimodal adaptive optics (AO) retinal imager for diagnosis of retinal diseases, including glaucoma, diabetic retinopathy (DR), age-related macular degeneration (AMD), and retinitis pigmentosa (RP). The development represents the first ever high performance AO system constructed that combines AO-corrected scanning laser ophthalmoscopy (SLO) and swept source Fourier domain optical coherence tomography (SSOCT) imaging modes in a single compact clinical prototype platform. The SSOCT channel operates at a wavelength of 1 μm for increased penetration and visualization of the choriocapillaris and choroid, sites of major disease activity for DR and wet AMD. The system is designed to operate on a broad clinical population with a dual deformable mirror (DM) configuration that allows simultaneous low- and high-order aberration correction. The system also includes a wide field line scanning ophthalmoscope (LSO) for initial screening, target identification, and global orientation; an integrated retinal tracker (RT) to stabilize the SLO, OCT, and LSO imaging fields in the presence of rotational eye motion; and a high-resolution LCD-based fixation target for presentation to the subject of stimuli and other visual cues. The system was tested in a limited number of human subjects without retinal disease for performance optimization and validation. The system was able to resolve and quantify cone photoreceptors across the macula to within ~0.5 deg (~100-150 μm) of the fovea, image and delineate ten retinal layers, and penetrate to resolve targets deep into the choroid. In addition to instrument hardware development, analysis algorithms were developed for efficient information extraction from clinical imaging sessions, with functionality including automated image registration, photoreceptor counting, strip and montage stitching, and segmentation. The system provides clinicians and researchers with high-resolution, high performance adaptive optics imaging to help

  6. Adaptive optics microscopy enhances image quality in deep layers of CLARITY processed brains of YFP-H mice

    NASA Astrophysics Data System (ADS)

    Reinig, Marc R.; Novack, Samuel W.; Tao, Xiaodong; Ermini, Florian; Bentolila, Laurent A.; Roberts, Dustin G.; MacKenzie-Graham, Allan; Godshalk, S. E.; Raven, M. A.; Kubby, Joel

    2016-03-01

    Optical sectioning of biological tissues has become the method of choice for three-dimensional histological analyses. This is particularly important in the brain were neurons can extend processes over large distances and often whole brain tracing of neuronal processes is desirable. To allow deeper optical penetration, which in fixed tissue is limited by scattering and refractive index mismatching, tissue-clearing procedures such as CLARITY have been developed. CLARITY processed brains have a nearly uniform refractive index and three-dimensional reconstructions at cellular resolution have been published. However, when imaging in deep layers at submicron resolution some limitations caused by residual refractive index mismatching become apparent, as the resulting wavefront aberrations distort the microscopic image. The wavefront can be corrected with adaptive optics. Here, we investigate the wavefront aberrations at different depths in CLARITY processed mouse brains and demonstrate the potential of adaptive optics to enable higher resolution and a better signal-to-noise ratio. Our adaptive optics system achieves high-speed measurement and correction of the wavefront with an open-loop control using a wave front sensor and a deformable mirror. Using adaptive optics enhanced microscopy, we demonstrate improved image quality wavefront, point spread function, and signal to noise in the cortex of YFP-H mice.

  7. Visual acuity-adaptive detail enhancement and shadow noise reduction for iCAM06-based HDR imaging

    NASA Astrophysics Data System (ADS)

    Lee, Geun-Young; Lee, Sung-Hak; Kwon, Hyuk-Ju; Sohng, Kyu-Ik

    2015-04-01

    An image appearance model is extremely useful for high-dynamic-range image (HDRI) rendering. However, the base-detail separation and the tone compression process for tonal control cause degradations in image quality. This study focuses on the de-saturation, reduced contrast, and noise problems in dark regions that occur through HDRI-rendering. First, we discuss de-saturation compensation using a bilateral filter that is based on the visual acuity characteristics of various illuminant levels. The edge stop function of the bilateral filter in iCAM06 is adaptively modified according to the illuminant information. Second, to reduce the magnified noise in the dark regions caused by tone mapping, the shadow regions are detected by an object's intensity and illuminant level, and then the noise of the detected regions is reduced using a luminance-adaptive coring function. Finally, we confirmed the enhanced color saturation, image contrast, and reduced noise in shadow regions through the application of the proposed methods.

  8. Using dual-energy x-ray imaging to enhance automated lung tumor tracking during real-time adaptive radiotherapy

    SciTech Connect

    Menten, Martin J. Fast, Martin F.; Nill, Simeon; Oelfke, Uwe

    2015-12-15

    Purpose: Real-time, markerless localization of lung tumors with kV imaging is often inhibited by ribs obscuring the tumor and poor soft-tissue contrast. This study investigates the use of dual-energy imaging, which can generate radiographs with reduced bone visibility, to enhance automated lung tumor tracking for real-time adaptive radiotherapy. Methods: kV images of an anthropomorphic breathing chest phantom were experimentally acquired and radiographs of actual lung cancer patients were Monte-Carlo-simulated at three imaging settings: low-energy (70 kVp, 1.5 mAs), high-energy (140 kVp, 2.5 mAs, 1 mm additional tin filtration), and clinical (120 kVp, 0.25 mAs). Regular dual-energy images were calculated by weighted logarithmic subtraction of high- and low-energy images and filter-free dual-energy images were generated from clinical and low-energy radiographs. The weighting factor to calculate the dual-energy images was determined by means of a novel objective score. The usefulness of dual-energy imaging for real-time tracking with an automated template matching algorithm was investigated. Results: Regular dual-energy imaging was able to increase tracking accuracy in left–right images of the anthropomorphic phantom as well as in 7 out of 24 investigated patient cases. Tracking accuracy remained comparable in three cases and decreased in five cases. Filter-free dual-energy imaging was only able to increase accuracy in 2 out of 24 cases. In four cases no change in accuracy was observed and tracking accuracy worsened in nine cases. In 9 out of 24 cases, it was not possible to define a tracking template due to poor soft-tissue contrast regardless of input images. The mean localization errors using clinical, regular dual-energy, and filter-free dual-energy radiographs were 3.85, 3.32, and 5.24 mm, respectively. Tracking success was dependent on tumor position, tumor size, imaging beam angle, and patient size. Conclusions: This study has highlighted the influence of

  9. Enhancement tuning and control for high dynamic range images in multi-scale locally adaptive contrast enhancement algorithms

    NASA Astrophysics Data System (ADS)

    Cvetkovic, Sascha D.; Schirris, Johan; de With, Peter H. N.

    2009-01-01

    For real-time imaging in surveillance applications, visibility of details is of primary importance to ensure customer confidence. If we display High Dynamic-Range (HDR) scenes whose contrast spans four or more orders of magnitude on a conventional monitor without additional processing, results are unacceptable. Compression of the dynamic range is therefore a compulsory part of any high-end video processing chain because standard monitors are inherently Low- Dynamic Range (LDR) devices with maximally two orders of display dynamic range. In real-time camera processing, many complex scenes are improved with local contrast enhancements, bringing details to the best possible visibility. In this paper, we show how a multi-scale high-frequency enhancement scheme, in which gain is a non-linear function of the detail energy, can be used for the dynamic range compression of HDR real-time video camera signals. We also show the connection of our enhancement scheme to the processing way of the Human Visual System (HVS). Our algorithm simultaneously controls perceived sharpness, ringing ("halo") artifacts (contrast) and noise, resulting in a good balance between visibility of details and non-disturbance of artifacts. The overall quality enhancement, suitable for both HDR and LDR scenes, is based on a careful selection of the filter types for the multi-band decomposition and a detailed analysis of the signal per frequency band.

  10. Adaptive Image Denoising by Mixture Adaptation

    NASA Astrophysics Data System (ADS)

    Luo, Enming; Chan, Stanley H.; Nguyen, Truong Q.

    2016-10-01

    We propose an adaptive learning procedure to learn patch-based image priors for image denoising. The new algorithm, called the Expectation-Maximization (EM) adaptation, takes a generic prior learned from a generic external database and adapts it to the noisy image to generate a specific prior. Different from existing methods that combine internal and external statistics in ad-hoc ways, the proposed algorithm is rigorously derived from a Bayesian hyper-prior perspective. There are two contributions of this paper: First, we provide full derivation of the EM adaptation algorithm and demonstrate methods to improve the computational complexity. Second, in the absence of the latent clean image, we show how EM adaptation can be modified based on pre-filtering. Experimental results show that the proposed adaptation algorithm yields consistently better denoising results than the one without adaptation and is superior to several state-of-the-art algorithms.

  11. Adaptive multi-level conditional random fields for detection and segmentation of small enhanced pathology in medical images.

    PubMed

    Karimaghaloo, Zahra; Arnold, Douglas L; Arbel, Tal

    2016-01-01

    Detection and segmentation of large structures in an image or within a region of interest have received great attention in the medical image processing domains. However, the problem of small pathology detection and segmentation still remains an unresolved challenge due to the small size of these pathologies, their low contrast and variable position, shape and texture. In many contexts, early detection of these pathologies is critical in diagnosis and assessing the outcome of treatment. In this paper, we propose a probabilistic Adaptive Multi-level Conditional Random Fields (AMCRF) with the incorporation of higher order cliques for detecting and segmenting such pathologies. In the first level of our graphical model, a voxel-based CRF is used to identify candidate lesions. In the second level, in order to further remove falsely detected regions, a new CRF is developed that incorporates higher order textural features, which are invariant to rotation and local intensity distortions. At this level, higher order textures are considered together with the voxel-wise cliques to refine boundaries and is therefore adaptive. The proposed algorithm is tested in the context of detecting enhancing Multiple Sclerosis (MS) lesions in brain MRI, where the problem is further complicated as many of the enhancing voxels are associated with normal structures (i.e. blood vessels) or noise in the MRI. The algorithm is trained and tested on large multi-center clinical trials from Relapsing-Remitting MS patients. The effect of several different parameter learning and inference techniques is further investigated. When tested on 120 cases, the proposed method reaches a lesion detection rate of 90%, with very few false positive lesion counts on average, ranging from 0.17 for very small (3-5 voxels) to 0 for very large (50+ voxels) regions. The proposed model is further tested on a very large clinical trial containing 2770 scans where a high sensitivity of 91% with an average false positive

  12. Smart Image Enhancement Process

    NASA Technical Reports Server (NTRS)

    Jobson, Daniel J. (Inventor); Rahman, Zia-ur (Inventor); Woodell, Glenn A. (Inventor)

    2012-01-01

    Contrast and lightness measures are used to first classify the image as being one of non-turbid and turbid. If turbid, the original image is enhanced to generate a first enhanced image. If non-turbid, the original image is classified in terms of a merged contrast/lightness score based on the contrast and lightness measures. The non-turbid image is enhanced to generate a second enhanced image when a poor contrast/lightness score is associated therewith. When the second enhanced image has a poor contrast/lightness score associated therewith, this image is enhanced to generate a third enhanced image. A sharpness measure is computed for one image that is selected from (i) the non-turbid image, (ii) the first enhanced image, (iii) the second enhanced image when a good contrast/lightness score is associated therewith, and (iv) the third enhanced image. If the selected image is not-sharp, it is sharpened to generate a sharpened image. The final image is selected from the selected image and the sharpened image.

  13. Adaptive wiener image restoration kernel

    DOEpatents

    Yuan, Ding

    2007-06-05

    A method and device for restoration of electro-optical image data using an adaptive Wiener filter begins with constructing imaging system Optical Transfer Function, and the Fourier Transformations of the noise and the image. A spatial representation of the imaged object is restored by spatial convolution of the image using a Wiener restoration kernel.

  14. An innovative technique for contrast enhancement of computed tomography images using normalized gamma-corrected contrast-limited adaptive histogram equalization

    NASA Astrophysics Data System (ADS)

    Al-Ameen, Zohair; Sulong, Ghazali; Rehman, Amjad; Al-Dhelaan, Abdullah; Saba, Tanzila; Al-Rodhaan, Mznah

    2015-12-01

    Image contrast is an essential visual feature that determines whether an image is of good quality. In computed tomography (CT), captured images tend to be low contrast, which is a prevalent artifact that reduces the image quality and hampers the process of extracting its useful information. A common tactic to process such artifact is by using histogram-based techniques. However, although these techniques may improve the contrast for different grayscale imaging applications, the results are mostly unacceptable for CT images due to the presentation of various faults, noise amplification, excess brightness, and imperfect contrast. Therefore, an ameliorated version of the contrast-limited adaptive histogram equalization (CLAHE) is introduced in this article to provide a good brightness with decent contrast for CT images. The novel modification to the aforesaid technique is done by adding an initial phase of a normalized gamma correction function that helps in adjusting the gamma of the processed image to avoid the common errors of the basic CLAHE of the excess brightness and imperfect contrast it produces. The newly developed technique is tested with synthetic and real-degraded low-contrast CT images, in which it highly contributed in producing better quality results. Moreover, a low intricacy technique for contrast enhancement is proposed, and its performance is also exhibited against various versions of histogram-based enhancement technique using three advanced image quality assessment metrics of Universal Image Quality Index (UIQI), Structural Similarity Index (SSIM), and Feature Similarity Index (FSIM). Finally, the proposed technique provided acceptable results with no visible artifacts and outperformed all the comparable techniques.

  15. Retinal Imaging: Adaptive Optics

    NASA Astrophysics Data System (ADS)

    Goncharov, A. S.; Iroshnikov, N. G.; Larichev, Andrey V.

    This chapter describes several factors influencing the performance of ophthalmic diagnostic systems with adaptive optics compensation of human eye aberration. Particular attention is paid to speckle modulation, temporal behavior of aberrations, and anisoplanatic effects. The implementation of a fundus camera with adaptive optics is considered.

  16. AIDA: Adaptive Image Deconvolution Algorithm

    NASA Astrophysics Data System (ADS)

    Hom, Erik; Haase, Sebastian; Marchis, Franck

    2013-10-01

    AIDA is an implementation and extension of the MISTRAL myopic deconvolution method developed by Mugnier et al. (2004) (see J. Opt. Soc. Am. A 21:1841-1854). The MISTRAL approach has been shown to yield object reconstructions with excellent edge preservation and photometric precision when used to process astronomical images. AIDA improves upon the original MISTRAL implementation. AIDA, written in Python, can deconvolve multiple frame data and three-dimensional image stacks encountered in adaptive optics and light microscopic imaging.

  17. Passive adaptive imaging through turbulence

    NASA Astrophysics Data System (ADS)

    Tofsted, David

    2016-05-01

    Standard methods for improved imaging system performance under degrading optical turbulence conditions typically involve active adaptive techniques or post-capture image processing. Here, passive adaptive methods are considered where active sources are disallowed, a priori. Theoretical analyses of short-exposure turbulence impacts indicate that varying aperture sizes experience different degrees of turbulence impacts. Smaller apertures often outperform larger aperture systems as turbulence strength increases. This suggests a controllable aperture system is advantageous. In addition, sub-aperture sampling of a set of training images permits the system to sense tilts in different sub-aperture regions through image acquisition and image cross-correlation calculations. A four sub-aperture pattern supports corrections involving five realizable operating modes (beyond tip and tilt) for removing aberrations over an annular pattern. Progress to date will be discussed regarding development and field trials of a prototype system.

  18. Adaptive processing for enhanced target acquisition

    NASA Astrophysics Data System (ADS)

    Page, Scott F.; Smith, Moira I.; Hickman, Duncan; Bernhardt, Mark; Oxford, William; Watson, Norman; Beath, F.

    2009-05-01

    Conventional air-to-ground target acquisition processes treat the image stream in isolation from external data sources. This ignores information that may be available through modern mission management systems which could be fused into the detection process in order to provide enhanced performance. By way of an example relating to target detection, this paper explores the use of a-priori knowledge and other sensor information in an adaptive architecture with the aim of enhancing performance in decision making. The approach taken here is to use knowledge of target size, terrain elevation, sensor geometry, solar geometry and atmospheric conditions to characterise the expected spatial and radiometric characteristics of a target in terms of probability density functions. An important consideration in the construction of the target probability density functions are the known errors in the a-priori knowledge. Potential targets are identified in the imagery and their spatial and expected radiometric characteristics are used to compute the target likelihood. The adaptive architecture is evaluated alongside a conventional non-adaptive algorithm using synthetic imagery representative of an air-to-ground target acquisition scenario. Lastly, future enhancements to the adaptive scheme are discussed as well as strategies for managing poor quality or absent a-priori information.

  19. Image Enhancement For The Visually Impaired

    NASA Astrophysics Data System (ADS)

    Peli, Eli; Peli, Tamar

    1984-02-01

    Application of image processing for the visually impaired is discussed. Image degradation in the low vision patient's visual system can be specified as a transfer function obtained by measurements of contrast sensitivity. The effectiveness of adaptive image enhancement for printed pictures is demonstrated using an optically simulated cataractous lens.

  20. Hierarchical image enhancement

    NASA Astrophysics Data System (ADS)

    Qi, Wei; Han, Jing; Zhang, Yi; Bai, Lian-fa

    2016-05-01

    Image enhancement is an important technique in computer vision. In this paper, we propose a hierarchical image enhancement approach based on the structure layer and texture layer. In the structure layer, we propose a structure-based method based on GMM, which better exploits structure details with fewer noise. In the texture layer, we present a structure-filtering method to filter unwanted texture with keeping completeness of detected salient structure. Next, we introduce a structure constraint prior to integrate them, leading to an improved enhancement result. Extensive experiments demonstrate that the proposed approach achieves higher quality results than previous approaches.

  1. Wavelet based image visibility enhancement of IR images

    NASA Astrophysics Data System (ADS)

    Jiang, Qin; Owechko, Yuri; Blanton, Brendan

    2016-05-01

    Enhancing the visibility of infrared images obtained in a degraded visibility environment is very important for many applications such as surveillance, visual navigation in bad weather, and helicopter landing in brownout conditions. In this paper, we present an IR image visibility enhancement system based on adaptively modifying the wavelet coefficients of the images. In our proposed system, input images are first filtered by a histogram-based dynamic range filter in order to remove sensor noise and convert the input images into 8-bit dynamic range for efficient processing and display. By utilizing a wavelet transformation, we modify the image intensity distribution and enhance image edges simultaneously. In the wavelet domain, low frequency wavelet coefficients contain original image intensity distribution while high frequency wavelet coefficients contain edge information for the original images. To modify the image intensity distribution, an adaptive histogram equalization technique is applied to the low frequency wavelet coefficients while to enhance image edges, an adaptive edge enhancement technique is applied to the high frequency wavelet coefficients. An inverse wavelet transformation is applied to the modified wavelet coefficients to obtain intensity images with enhanced visibility. Finally, a Gaussian filter is used to remove blocking artifacts introduced by the adaptive techniques. Since wavelet transformation uses down-sampling to obtain low frequency wavelet coefficients, histogram equalization of low-frequency coefficients is computationally more efficient than histogram equalization of the original images. We tested the proposed system with degraded IR images obtained from a helicopter landing in brownout conditions. Our experimental results show that the proposed system is effective for enhancing the visibility of degraded IR images.

  2. Image enhancement by holography.

    NASA Technical Reports Server (NTRS)

    Stroke, G. W.

    1973-01-01

    The speed of the holographic image deblurring method has recently been further enhanced by a new speed in the realization of the powerful holographic image-deblurring filter. The filter makes it possible to carry out the deblurring, in the optical computer used, in times of the order of one second. The experimental achievements using the holographic image-enhancement method are illustrated with examples ranging from out-of-focus or motion-blurred photographs, including 'amateur' photos recorded on Polaroid film, to the sharpening of the best available electron micrographs of viruses. Images recorded with X-rays, notably from rocket-borne photos of the sun, and out-of-focus photographs from cameras in NASA satellites have been similarly deblurred.

  3. Adaptation and visual search in mammographic images.

    PubMed

    Kompaniez-Dunigan, Elysse; Abbey, Craig K; Boone, John M; Webster, Michael A

    2015-05-01

    Radiologists face the visually challenging task of detecting suspicious features within the complex and noisy backgrounds characteristic of medical images. We used a search task to examine whether the salience of target features in x-ray mammograms could be enhanced by prior adaptation to the spatial structure of the images. The observers were not radiologists, and thus had no diagnostic training with the images. The stimuli were randomly selected sections from normal mammograms previously classified with BIRADS Density scores of "fatty" versus "dense," corresponding to differences in the relative quantities of fat versus fibroglandular tissue. These categories reflect conspicuous differences in visual texture, with dense tissue being more likely to obscure lesion detection. The targets were simulated masses corresponding to bright Gaussian spots, superimposed by adding the luminance to the background. A single target was randomly added to each image, with contrast varied over five levels so that they varied from difficult to easy to detect. Reaction times were measured for detecting the target location, before or after adapting to a gray field or to random sequences of a different set of dense or fatty images. Observers were faster at detecting the targets in either dense or fatty images after adapting to the specific background type (dense or fatty) that they were searching within. Thus, the adaptation led to a facilitation of search performance that was selective for the background texture. Our results are consistent with the hypothesis that adaptation allows observers to more effectively suppress the specific structure of the background, thereby heightening visual salience and search efficiency.

  4. Adaptive optical ghost imaging through atmospheric turbulence.

    PubMed

    Shi, Dongfeng; Fan, Chengyu; Zhang, Pengfei; Zhang, Jinghui; Shen, Hong; Qiao, Chunhong; Wang, Yingjian

    2012-12-17

    We demonstrate for the first time (to our knowledge) that a high-quality image can still be obtained in atmospheric turbulence by applying adaptive optical ghost imaging (AOGI) system even when conventional ghost imaging system fails to produce an image. The performance of AOGI under different strength of atmospheric turbulence is investigated by simulation. The influence of adaptive optics system with different numbers of adaptive mirror elements on obtained image quality is also studied.

  5. Adaptive image segmentation by quantization

    NASA Astrophysics Data System (ADS)

    Liu, Hui; Yun, David Y.

    1992-12-01

    Segmentation of images into textural homogeneous regions is a fundamental problem in an image understanding system. Most region-oriented segmentation approaches suffer from the problem of different thresholds selecting for different images. In this paper an adaptive image segmentation based on vector quantization is presented. It automatically segments images without preset thresholds. The approach contains a feature extraction module and a two-layer hierarchical clustering module, a vector quantizer (VQ) implemented by a competitive learning neural network in the first layer. A near-optimal competitive learning algorithm (NOLA) is employed to train the vector quantizer. NOLA combines the advantages of both Kohonen self- organizing feature map (KSFM) and K-means clustering algorithm. After the VQ is trained, the weights of the network and the number of input vectors clustered by each neuron form a 3- D topological feature map with separable hills aggregated by similar vectors. This overcomes the inability to visualize the geometric properties of data in a high-dimensional space for most other clustering algorithms. The second clustering algorithm operates in the feature map instead of the input set itself. Since the number of units in the feature map is much less than the number of feature vectors in the feature set, it is easy to check all peaks and find the `correct' number of clusters, also a key problem in current clustering techniques. In the experiments, we compare our algorithm with K-means clustering method on a variety of images. The results show that our algorithm achieves better performance.

  6. Enhanced image capture through fusion

    NASA Technical Reports Server (NTRS)

    Burt, Peter J.; Hanna, Keith; Kolczynski, Raymond J.

    1993-01-01

    Image fusion may be used to combine images from different sensors, such as IR and visible cameras, to obtain a single composite with extended information content. Fusion may also be used to combine multiple images from a given sensor to form a composite image in which information of interest is enhanced. We present a general method for performing image fusion and show that this method is effective for diverse fusion applications. We suggest that fusion may provide a powerful tool for enhanced image capture with broad utility in image processing and computer vision.

  7. Image Enhancement, Image Quality, and Noise

    NASA Technical Reports Server (NTRS)

    Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.; Hines, Glenn D.

    2005-01-01

    The Multiscale Retinex With Color Restoration (MSRCR) is a non-linear image enhancement algorithm that provides simultaneous dynamic range compression, color constancy and rendition. The overall impact is to brighten up areas of poor contrast/lightness but not at the expense of saturating areas of good contrast/brightness. The downside is that with the poor signal-to-noise ratio that most image acquisition devices have in dark regions, noise can also be greatly enhanced thus affecting overall image quality. In this paper, we will discuss the impact of the MSRCR on the overall quality of an enhanced image as a function of the strength of shadows in an image, and as a function of the root-mean-square (RMS) signal-to-noise (SNR) ratio of the image.

  8. Adaptive bilateral filter for sharpness enhancement and noise removal.

    PubMed

    Zhang, Buyue; Allebach, Jan P

    2008-05-01

    In this paper, we present the adaptive bilateral filter (ABF) for sharpness enhancement and noise removal. The ABF sharpens an image by increasing the slope of the edges without producing overshoot or undershoot. It is an approach to sharpness enhancement that is fundamentally different from the unsharp mask (USM). This new approach to slope restoration also differs significantly from previous slope restoration algorithms in that the ABF does not involve detection of edges or their orientation, or extraction of edge profiles. In the ABF, the edge slope is enhanced by transforming the histogram via a range filter with adaptive offset and width. The ABF is able to smooth the noise, while enhancing edges and textures in the image. The parameters of the ABF are optimized with a training procedure. ABF restored images are significantly sharper than those restored by the bilateral filter. Compared with an USM based sharpening method-the optimal unsharp mask (OUM), ABF restored edges are as sharp as those rendered by the OUM, but without the halo artifacts that appear in the OUM restored image. In terms of noise removal, ABF also outperforms the bilateral filter and the OUM. We demonstrate that ABF works well for both natural images and text images. PMID:18390373

  9. Computer Program Helps Enhance Images

    NASA Technical Reports Server (NTRS)

    Stanfill, Daniel F., IV

    1994-01-01

    Pixel Pusher is Macintosh application program for viewing and performing minor enhancements on imagery. Works with color images digitized to 8 bits. Reads image files in JPL's two primary image formats VICAR and PDS as well as in Macintosh PICT format. VICAR (NPO-18076) handles array of image-processing capabilities used for variety of applications, including processing of biomedical images, cartography, imaging of Earth resources, and geological exploration. Pixel Pusher also imports color lookup tables in VICAR format for viewing images in pseudocolor (256 colors). Written in Symantec's Think C.

  10. Digital Image Enhancement of Indic Historical Manuscripts

    NASA Astrophysics Data System (ADS)

    Shi, Zhixin; Setlur, Srirangaraj; Govindaraju, Venu

    Historical documents in Indic scripts can be found on a wide range of media such as paper, palm leaves, and parchment. Palm leaves are believed to be one of the earliest forms of writing media and their use as writing material has been recorded in various parts of the world including India. Ancient palm leaf manuscripts relating to religion, science, medicine, astronomy are still available for reference today due to many ongoing efforts for preservation of ancient documents by libraries and universities around the world. These manuscripts typically last a few centuries but with time the leaves degrade and the writing becomes illegible. Image processing techniques can help enhance the images of these manuscripts so as to enable readability of the written text. In this chapter, we propose methods for enhancing digital images of palm leaf and other historical manuscripts. We approximate the background of a gray-scale image using piece-wise linear and nonlinear models. Normalization algorithms are used on the color channels of the palm leaf image to obtain an enhanced gray-scale image. Experimental results show significant improvement in readability. An adaptive local connectivity map is used to try to segment lines of text from the enhanced images with the objective of facilitating techniques such as keyword spotting or partial OCR and thereby making it possible to index these documents for retrieval from a digital library.

  11. Visual enhancement of unmixed multispectral imagery using adaptive smoothing

    USGS Publications Warehouse

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

    2004-01-01

    Adaptive smoothing (AS) has been previously proposed as a method to smooth uniform regions of an image, retain contrast edges, and enhance edge boundaries. The method is an implementation of the anisotropic diffusion process which results in a gray scale image. This paper discusses modifications to the AS method for application to multi-band data which results in a color segmented image. The process was used to visually enhance the three most distinct abundance fraction images produced by the Lagrange constraint neural network learning-based unmixing of Landsat 7 Enhanced Thematic Mapper Plus multispectral sensor data. A mutual information-based method was applied to select the three most distinct fraction images for subsequent visualization as a red, green, and blue composite. A reported image restoration technique (partial restoration) was applied to the multispectral data to reduce unmixing error, although evaluation of the performance of this technique was beyond the scope of this paper. The modified smoothing process resulted in a color segmented image with homogeneous regions separated by sharpened, coregistered multiband edges. There was improved class separation with the segmented image, which has importance to subsequent operations involving data classification.

  12. Adaptive predictive image coding using local characteristics

    NASA Astrophysics Data System (ADS)

    Hsieh, C. H.; Lu, P. C.; Liou, W. G.

    1989-12-01

    The paper presents an efficient adaptive predictive coding method using the local characteristics of images. In this method, three coding schemes, namely, mean, subsampling combined with fixed DPCM, and ADPCM/PCM, are used and one of these is chosen adaptively based on the local characteristics of images. The prediction parameters of the two-dimensional linear predictor in the ADPCM/PCM are extracted on a block by block basis. Simulation results show that the proposed method is effective in reducing the slope overload distortion and the granular noise at low bit rates, and thus it can improve the visual quality of reconstructed images.

  13. Photographic image enhancement

    NASA Technical Reports Server (NTRS)

    Hite, Gerald E.

    1990-01-01

    Deblurring capabilities would significantly improve the scientific return from Space Shuttle crew-acquired images of the Earth and the safety of Space Shuttle missions. Deblurring techniques were developed and demonstrated on two digitized images that were blurred in different ways. The first was blurred by a Gaussian blurring function analogous to that caused by atmospheric turbulence, while the second was blurred by improper focussing. It was demonstrated, in both cases, that the nature of the blurring (Gaussian and Airy) and the appropriate parameters could be obtained from the Fourier transformation of their images. The difficulties posed by the presence of noise necessitated special consideration. It was demonstrated that a modified Wiener frequency filter judiciously constructed to avoid over emphasis of frequency regions dominated by noise resulted in substantially improved images. Several important areas of future research were identified. Two areas of particular promise are the extraction of blurring information directly from the spatial images and improved noise abatement form investigations of select spatial regions and the elimination of spike noise.

  14. Multiview image sequence enhancement

    NASA Astrophysics Data System (ADS)

    Jovanov, Ljubomir; Luong, Hiêp; Ružic, Tijana; Philips, Wilfried

    2015-03-01

    Realistic visualization is crucial for more intuitive representation of complex data, medical imaging, simulation and entertainment systems. Multiview autostereoscopic displays are great step towards achieving complete immersive user experience. However, providing high quality content for this type of displays is still a great challenge. Due to the different characteristics/settings of the cameras in the multivew setup and varying photometric characteristics of the objects in the scene, the same object may have different appearance in the sequences acquired by the different cameras. Images representing views recorded using different cameras in practice have different local noise, color and sharpness characteristics. View synthesis algorithms introduce artefacts due to errors in disparity estimation/bad occlusion handling or due to erroneous warping function estimation. If the input multivew images are not of sufficient quality and have mismatching color and sharpness characteristics, these artifacts may become even more disturbing. The main goal of our method is to simultaneously perform multiview image sequence denoising, color correction and the improvement of sharpness in slightly blurred regions. Results show that the proposed method significantly reduces the amount of the artefacts in multiview video sequences resulting in a better visual experience.

  15. Helium and Enhanced Image of the Sun

    NASA Video Gallery

    This video blinks between an image in Helium and an enhanced image. The original image is from AIA on SDO and the enhanced image was created at the LM Solar and Astrophysics Laboratory (LMSAL) by D...

  16. Adaptive optics imaging of the retina.

    PubMed

    Battu, Rajani; Dabir, Supriya; Khanna, Anjani; Kumar, Anupama Kiran; Roy, Abhijit Sinha

    2014-01-01

    Adaptive optics is a relatively new tool that is available to ophthalmologists for study of cellular level details. In addition to the axial resolution provided by the spectral-domain optical coherence tomography, adaptive optics provides an excellent lateral resolution, enabling visualization of the photoreceptors, blood vessels and details of the optic nerve head. We attempt a mini review of the current role of adaptive optics in retinal imaging. PubMed search was performed with key words Adaptive optics OR Retina OR Retinal imaging. Conference abstracts were searched from the Association for Research in Vision and Ophthalmology (ARVO) and American Academy of Ophthalmology (AAO) meetings. In total, 261 relevant publications and 389 conference abstracts were identified.

  17. Adaptive optics imaging of the retina

    PubMed Central

    Battu, Rajani; Dabir, Supriya; Khanna, Anjani; Kumar, Anupama Kiran; Roy, Abhijit Sinha

    2014-01-01

    Adaptive optics is a relatively new tool that is available to ophthalmologists for study of cellular level details. In addition to the axial resolution provided by the spectral-domain optical coherence tomography, adaptive optics provides an excellent lateral resolution, enabling visualization of the photoreceptors, blood vessels and details of the optic nerve head. We attempt a mini review of the current role of adaptive optics in retinal imaging. PubMed search was performed with key words Adaptive optics OR Retina OR Retinal imaging. Conference abstracts were searched from the Association for Research in Vision and Ophthalmology (ARVO) and American Academy of Ophthalmology (AAO) meetings. In total, 261 relevant publications and 389 conference abstracts were identified. PMID:24492503

  18. Locally adaptive bilateral clustering for universal image denoising

    NASA Astrophysics Data System (ADS)

    Toh, K. K. V.; Mat Isa, N. A.

    2012-12-01

    This paper presents a novel and efficient locally adaptive denoising method based on clustering of pixels into regions of similar geometric and radiometric structures. Clustering is performed by adaptively segmenting pixels in the local kernel based on their augmented variational series. Then, noise pixels are restored by selectively considering the radiometric and spatial properties of every pixel in the formed clusters. The proposed method is exceedingly robust in conveying reliable local structural information even in the presence of noise. As a result, the proposed method substantially outperforms other state-of-the-art methods in terms of image restoration and computational cost. We support our claims with ample simulated and real data experiments. The relatively fast runtime from extensive simulations also suggests that the proposed method is suitable for a variety of image-based products — either embedded in image capturing devices or applied as image enhancement software.

  19. Block adaptive rate controlled image data compression

    NASA Technical Reports Server (NTRS)

    Rice, R. F.; Hilbert, E.; Lee, J.-J.; Schlutsmeyer, A.

    1979-01-01

    A block adaptive rate controlled (BARC) image data compression algorithm is described. It is noted that in the algorithm's principal rate controlled mode, image lines can be coded at selected rates by combining practical universal noiseless coding techniques with block adaptive adjustments in linear quantization. Compression of any source data at chosen rates of 3.0 bits/sample and above can be expected to yield visual image quality with imperceptible degradation. Exact reconstruction will be obtained if the one-dimensional difference entropy is below the selected compression rate. It is noted that the compressor can also be operated as a floating rate noiseless coder by simply not altering the input data quantization. Here, the universal noiseless coder ensures that the code rate is always close to the entropy. Application of BARC image data compression to the Galileo orbiter mission of Jupiter is considered.

  20. Information-Adaptive Image Encoding and Restoration

    NASA Technical Reports Server (NTRS)

    Park, Stephen K.; Rahman, Zia-ur

    1998-01-01

    The multiscale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. A number of algorithms exist that provide one or more of these features, but not all. In this paper we compare the performance of the MSRCR with techniques that are widely used for image enhancement. Specifically, we compare the MSRCR with color adjustment methods such as gamma correction and gain/offset application, histogram modification techniques such as histogram equalization and manual histogram adjustment, and other more powerful techniques such as homomorphic filtering and 'burning and dodging'. The comparison is carried out by testing the suite of image enhancement methods on a set of diverse images. We find that though some of these techniques work well for some of these images, only the MSRCR performs universally well oil the test set.

  1. Enhancement classification of galaxy images

    NASA Astrophysics Data System (ADS)

    Jenkinson, John

    With the advent of astronomical imaging technology developments, and the increased capacity of digital storage, the production of photographic atlases of the night sky have begun to generate volumes of data which need to be processed autonomously. As part of the Tonantzintla Digital Sky Survey construction, the present work involves software development for the digital image processing of astronomical images, in particular operations that preface feature extraction and classification. Recognition of galaxies in these images is the primary objective of the present work. Many galaxy images have poor resolution or contain faint galaxy features, resulting in the misclassification of galaxies. An enhancement of these images by the method of the Heap transform is proposed, and experimental results are provided which demonstrate the image enhancement to improve the presence of faint galaxy features thereby improving classification accuracy. The feature extraction was performed using morphological features that have been widely used in previous automated galaxy investigations. Principal component analysis was applied to the original and enhanced data sets for a performance comparison between the original and reduced features spaces. Classification was performed by the Support Vector Machine learning algorithm.

  2. Streak image denoising and segmentation using adaptive Gaussian guided filter.

    PubMed

    Jiang, Zhuocheng; Guo, Baoping

    2014-09-10

    In streak tube imaging lidar (STIL), streak images are obtained using a CCD camera. However, noise in the captured streak images can greatly affect the quality of reconstructed 3D contrast and range images. The greatest challenge for streak image denoising is reducing the noise while preserving details. In this paper, we propose an adaptive Gaussian guided filter (AGGF) for noise removal and detail enhancement of streak images. The proposed algorithm is based on a guided filter (GF) and part of an adaptive bilateral filter (ABF). In the AGGF, the details are enhanced by optimizing the offset parameter. AGGF-denoised streak images are significantly sharper than those denoised by the GF. Moreover, the AGGF is a fast linear time algorithm achieved by recursively implementing a Gaussian filter kernel. Experimentally, AGGF demonstrates its capacity to preserve edges and thin structures and outperforms the existing bilateral filter and domain transform filter in terms of both visual quality and peak signal-to-noise ratio performance.

  3. Streak image denoising and segmentation using adaptive Gaussian guided filter.

    PubMed

    Jiang, Zhuocheng; Guo, Baoping

    2014-09-10

    In streak tube imaging lidar (STIL), streak images are obtained using a CCD camera. However, noise in the captured streak images can greatly affect the quality of reconstructed 3D contrast and range images. The greatest challenge for streak image denoising is reducing the noise while preserving details. In this paper, we propose an adaptive Gaussian guided filter (AGGF) for noise removal and detail enhancement of streak images. The proposed algorithm is based on a guided filter (GF) and part of an adaptive bilateral filter (ABF). In the AGGF, the details are enhanced by optimizing the offset parameter. AGGF-denoised streak images are significantly sharper than those denoised by the GF. Moreover, the AGGF is a fast linear time algorithm achieved by recursively implementing a Gaussian filter kernel. Experimentally, AGGF demonstrates its capacity to preserve edges and thin structures and outperforms the existing bilateral filter and domain transform filter in terms of both visual quality and peak signal-to-noise ratio performance. PMID:25321679

  4. Enhancing astronaut performance using sensorimotor adaptability training.

    PubMed

    Bloomberg, Jacob J; Peters, Brian T; Cohen, Helen S; Mulavara, Ajitkumar P

    2015-01-01

    Astronauts experience disturbances in balance and gait function when they return to Earth. The highly plastic human brain enables individuals to modify their behavior to match the prevailing environment. Subjects participating in specially designed variable sensory challenge training programs can enhance their ability to rapidly adapt to novel sensory situations. This is useful in our application because we aim to train astronauts to rapidly formulate effective strategies to cope with the balance and locomotor challenges associated with new gravitational environments-enhancing their ability to "learn to learn." We do this by coupling various combinations of sensorimotor challenges with treadmill walking. A unique training system has been developed that is comprised of a treadmill mounted on a motion base to produce movement of the support surface during walking. This system provides challenges to gait stability. Additional sensory variation and challenge are imposed with a virtual visual scene that presents subjects with various combinations of discordant visual information during treadmill walking. This experience allows them to practice resolving challenging and conflicting novel sensory information to improve their ability to adapt rapidly. Information obtained from this work will inform the design of the next generation of sensorimotor countermeasures for astronauts. PMID:26441561

  5. Enhancing astronaut performance using sensorimotor adaptability training.

    PubMed

    Bloomberg, Jacob J; Peters, Brian T; Cohen, Helen S; Mulavara, Ajitkumar P

    2015-01-01

    Astronauts experience disturbances in balance and gait function when they return to Earth. The highly plastic human brain enables individuals to modify their behavior to match the prevailing environment. Subjects participating in specially designed variable sensory challenge training programs can enhance their ability to rapidly adapt to novel sensory situations. This is useful in our application because we aim to train astronauts to rapidly formulate effective strategies to cope with the balance and locomotor challenges associated with new gravitational environments-enhancing their ability to "learn to learn." We do this by coupling various combinations of sensorimotor challenges with treadmill walking. A unique training system has been developed that is comprised of a treadmill mounted on a motion base to produce movement of the support surface during walking. This system provides challenges to gait stability. Additional sensory variation and challenge are imposed with a virtual visual scene that presents subjects with various combinations of discordant visual information during treadmill walking. This experience allows them to practice resolving challenging and conflicting novel sensory information to improve their ability to adapt rapidly. Information obtained from this work will inform the design of the next generation of sensorimotor countermeasures for astronauts.

  6. Enhancing astronaut performance using sensorimotor adaptability training

    PubMed Central

    Bloomberg, Jacob J.; Peters, Brian T.; Cohen, Helen S.; Mulavara, Ajitkumar P.

    2015-01-01

    Astronauts experience disturbances in balance and gait function when they return to Earth. The highly plastic human brain enables individuals to modify their behavior to match the prevailing environment. Subjects participating in specially designed variable sensory challenge training programs can enhance their ability to rapidly adapt to novel sensory situations. This is useful in our application because we aim to train astronauts to rapidly formulate effective strategies to cope with the balance and locomotor challenges associated with new gravitational environments—enhancing their ability to “learn to learn.” We do this by coupling various combinations of sensorimotor challenges with treadmill walking. A unique training system has been developed that is comprised of a treadmill mounted on a motion base to produce movement of the support surface during walking. This system provides challenges to gait stability. Additional sensory variation and challenge are imposed with a virtual visual scene that presents subjects with various combinations of discordant visual information during treadmill walking. This experience allows them to practice resolving challenging and conflicting novel sensory information to improve their ability to adapt rapidly. Information obtained from this work will inform the design of the next generation of sensorimotor countermeasures for astronauts. PMID:26441561

  7. Stent enhancement in digital x-ray fluoroscopy using an adaptive feature enhancement filter

    NASA Astrophysics Data System (ADS)

    Jiang, Yuhao; Zachary, Josey

    2016-03-01

    Fluoroscopic images belong to the classes of low contrast and high noise. Simply lowering radiation dose will render the images unreadable. Feature enhancement filters can reduce patient dose by acquiring images at low dose settings and then digitally restoring them to the original quality. In this study, a stent contrast enhancement filter is developed to selectively improve the contrast of stent contour without dramatically boosting the image noise including quantum noise and clinical background noise. Gabor directional filter banks are implemented to detect the edges and orientations of the stent. A high orientation resolution of 9° is used. To optimize the use of the information obtained from Gabor filters, a computerized Monte Carlo simulation followed by ROC study is used to find the best nonlinear operator. The next stage of filtering process is to extract symmetrical parts in the stent. The global and local symmetry measures are used. The information gathered from previous two filter stages are used to generate a stent contour map. The contour map is then scaled and added back to the original image to get a contrast enhanced stent image. We also apply a spatio-temporal channelized Hotelling observer model and other numerical measures to characterize the response of the filters and contour map to optimize the selections of parameters for image quality. The results are compared to those filtered by an adaptive unsharp masking filter previously developed. It is shown that stent enhancement filter can effectively improve the stent detection and differentiation in the interventional fluoroscopy.

  8. Perceived Image Quality Improvements from the Application of Image Deconvolution to Retinal Images from an Adaptive Optics Fundus Imager

    NASA Astrophysics Data System (ADS)

    Soliz, P.; Nemeth, S. C.; Erry, G. R. G.; Otten, L. J.; Yang, S. Y.

    Aim: The objective of this project was to apply an image restoration methodology based on wavefront measurements obtained with a Shack-Hartmann sensor and evaluating the restored image quality based on medical criteria.Methods: Implementing an adaptive optics (AO) technique, a fundus imager was used to achieve low-order correction to images of the retina. The high-order correction was provided by deconvolution. A Shack-Hartmann wavefront sensor measures aberrations. The wavefront measurement is the basis for activating a deformable mirror. Image restoration to remove remaining aberrations is achieved by direct deconvolution using the point spread function (PSF) or a blind deconvolution. The PSF is estimated using measured wavefront aberrations. Direct application of classical deconvolution methods such as inverse filtering, Wiener filtering or iterative blind deconvolution (IBD) to the AO retinal images obtained from the adaptive optical imaging system is not satisfactory because of the very large image size, dificulty in modeling the system noise, and inaccuracy in PSF estimation. Our approach combines direct and blind deconvolution to exploit available system information, avoid non-convergence, and time-consuming iterative processes. Results: The deconvolution was applied to human subject data and resulting restored images compared by a trained ophthalmic researcher. Qualitative analysis showed significant improvements. Neovascularization can be visualized with the adaptive optics device that cannot be resolved with the standard fundus camera. The individual nerve fiber bundles are easily resolved as are melanin structures in the choroid. Conclusion: This project demonstrated that computer-enhanced, adaptive optic images have greater detail of anatomical and pathological structures.

  9. Complex adaptation-based LDR image rendering for 3D image reconstruction

    NASA Astrophysics Data System (ADS)

    Lee, Sung-Hak; Kwon, Hyuk-Ju; Sohng, Kyu-Ik

    2014-07-01

    A low-dynamic tone-compression technique is developed for realistic image rendering that can make three-dimensional (3D) images similar to realistic scenes by overcoming brightness dimming in the 3D display mode. The 3D surround provides varying conditions for image quality, illuminant adaptation, contrast, gamma, color, sharpness, and so on. In general, gain/offset adjustment, gamma compensation, and histogram equalization have performed well in contrast compression; however, as a result of signal saturation and clipping effects, image details are removed and information is lost on bright and dark areas. Thus, an enhanced image mapping technique is proposed based on space-varying image compression. The performance of contrast compression is enhanced with complex adaptation in a 3D viewing surround combining global and local adaptation. Evaluating local image rendering in view of tone and color expression, noise reduction, and edge compensation confirms that the proposed 3D image-mapping model can compensate for the loss of image quality in the 3D mode.

  10. High-speed atomic force microscope imaging: Adaptive multiloop mode

    NASA Astrophysics Data System (ADS)

    Ren, Juan; Zou, Qingze; Li, Bo; Lin, Zhiqun

    2014-07-01

    In this paper, an imaging mode (called the adaptive multiloop mode) of atomic force microscope (AFM) is proposed to substantially increase the speed of tapping mode (TM) imaging while preserving the advantages of TM imaging over contact mode (CM) imaging. Due to its superior image quality and less sample disturbances over CM imaging, particularly for soft materials such as polymers, TM imaging is currently the most widely used imaging technique. The speed of TM imaging, however, is substantially (over an order of magnitude) lower than that of CM imaging, becoming the major bottleneck of this technique. Increasing the speed of TM imaging is challenging as a stable probe tapping on the sample surface must be maintained to preserve the image quality, whereas the probe tapping is rather sensitive to the sample topography variation. As a result, the increase of imaging speed can quickly lead to loss of the probe-sample contact and/or annihilation of the probe tapping, resulting in image distortion and/or sample deformation. The proposed adaptive multiloop mode (AMLM) imaging overcomes these limitations of TM imaging through the following three efforts integrated together: First, it is proposed to account for the variation of the TM deflection when quantifying the sample topography; second, an inner-outer feedback control loop to regulate the TM deflection is added on top of the tapping-feedback control loop to improve the sample topography tracking; and, third, an online iterative feedforward controller is augmented to the whole control system to further enhance the topography tracking, where the next-line sample topography is predicted and utilized to reduce the tracking error. The added feedback regulation of the TM deflection ensures the probe-sample interaction force remains near the minimum for maintaining a stable probe-sample interaction. The proposed AMLM imaging is tested and demonstrated by imaging a poly(tert-butyl acrylate) sample in experiments. The

  11. Approach for reconstructing anisoplanatic adaptive optics images.

    PubMed

    Aubailly, Mathieu; Roggemann, Michael C; Schulz, Timothy J

    2007-08-20

    Atmospheric turbulence corrupts astronomical images formed by ground-based telescopes. Adaptive optics systems allow the effects of turbulence-induced aberrations to be reduced for a narrow field of view corresponding approximately to the isoplanatic angle theta(0). For field angles larger than theta(0), the point spread function (PSF) gradually degrades as the field angle increases. We present a technique to estimate the PSF of an adaptive optics telescope as function of the field angle, and use this information in a space-varying image reconstruction technique. Simulated anisoplanatic intensity images of a star field are reconstructed by means of a block-processing method using the predicted local PSF. Two methods for image recovery are used: matrix inversion with Tikhonov regularization, and the Lucy-Richardson algorithm. Image reconstruction results obtained using the space-varying predicted PSF are compared to space invariant deconvolution results obtained using the on-axis PSF. The anisoplanatic reconstruction technique using the predicted PSF provides a significant improvement of the mean squared error between the reconstructed image and the object compared to the deconvolution performed using the on-axis PSF. PMID:17712366

  12. Comparison of various enhanced radar imaging techniques

    NASA Astrophysics Data System (ADS)

    Gupta, Inder J.; Gandhe, Avinash

    1998-09-01

    Recently, many techniques have been proposed to enhance the quality of radar images obtained using SAR and/or ISAR. These techniques include spatially variant apodization (SVA), adaptive sidelobe reduction (ASR), the Capon method, amplitude and phase estimation of sinusoids (APES) and data extrapolation. SVA is a special case of ASR; whereas the APES algorithm is similar to the Capon method except that it provides a better amplitude estimate. In this paper, the ASR technique, the APES algorithm and data extrapolation are used to generate radar images of two experimental targets and an airborne target. It is shown that although for ideal situations (point targets) the APES algorithm provides the best radar images (reduced sidelobe level and sharp main lobe), its performance degrades quickly for real world targets. The ASR algorithm gives radar images with low sidelobes but at the cost of some loss of information about the target. Also, there is not much improvement in radar image resolution. Data extrapolation, on the other hand, improves image resolution. In this case one can reduce the sidelobes by using non-uniform weights. Any loss in the radar image resolution due to non-uniform weights can be compensated by further extrapolating the scattered field data.

  13. Adaptive Optics Imaging in Laser Pointer Maculopathy.

    PubMed

    Sheyman, Alan T; Nesper, Peter L; Fawzi, Amani A; Jampol, Lee M

    2016-08-01

    The authors report multimodal imaging including adaptive optics scanning laser ophthalmoscopy (AOSLO) (Apaeros retinal image system AOSLO prototype; Boston Micromachines Corporation, Boston, MA) in a case of previously diagnosed unilateral acute idiopathic maculopathy (UAIM) that demonstrated features of laser pointer maculopathy. The authors also show the adaptive optics images of a laser pointer maculopathy case previously reported. A 15-year-old girl was referred for the evaluation of a maculopathy suspected to be UAIM. The authors reviewed the patient's history and obtained fluorescein angiography, autofluorescence, optical coherence tomography, infrared reflectance, and AOSLO. The time course of disease and clinical examination did not fit with UAIM, but the linear pattern of lesions was suspicious for self-inflicted laser pointer injury. This was confirmed on subsequent questioning of the patient. The presence of linear lesions in the macula that are best highlighted with multimodal imaging techniques should alert the physician to the possibility of laser pointer injury. AOSLO further characterizes photoreceptor damage in this condition. [Ophthalmic Surg Lasers Imaging Retina. 2016;47:782-785.]. PMID:27548458

  14. Adaptive Optics Imaging in Laser Pointer Maculopathy.

    PubMed

    Sheyman, Alan T; Nesper, Peter L; Fawzi, Amani A; Jampol, Lee M

    2016-08-01

    The authors report multimodal imaging including adaptive optics scanning laser ophthalmoscopy (AOSLO) (Apaeros retinal image system AOSLO prototype; Boston Micromachines Corporation, Boston, MA) in a case of previously diagnosed unilateral acute idiopathic maculopathy (UAIM) that demonstrated features of laser pointer maculopathy. The authors also show the adaptive optics images of a laser pointer maculopathy case previously reported. A 15-year-old girl was referred for the evaluation of a maculopathy suspected to be UAIM. The authors reviewed the patient's history and obtained fluorescein angiography, autofluorescence, optical coherence tomography, infrared reflectance, and AOSLO. The time course of disease and clinical examination did not fit with UAIM, but the linear pattern of lesions was suspicious for self-inflicted laser pointer injury. This was confirmed on subsequent questioning of the patient. The presence of linear lesions in the macula that are best highlighted with multimodal imaging techniques should alert the physician to the possibility of laser pointer injury. AOSLO further characterizes photoreceptor damage in this condition. [Ophthalmic Surg Lasers Imaging Retina. 2016;47:782-785.].

  15. Image enhancement method for fingerprint recognition system.

    PubMed

    Li, Shunshan; Wei, Min; Tang, Haiying; Zhuang, Tiange; Buonocore, Michael

    2005-01-01

    Image enhancement plays an important role in Fingerprint Recognition System. In this paper fingerprint image enhancement method, a refined Gabor filter, is presented. This enhancement method can connect the ridge breaks, ensures the maximal gray values located at the ridge center and has the ability to compensate for the nonlinear deformations. The result shows it can improve the performance of image enhancement.

  16. AIDA: An Adaptive Image Deconvolution Algorithm

    NASA Astrophysics Data System (ADS)

    Hom, Erik; Marchis, F.; Lee, T. K.; Haase, S.; Agard, D. A.; Sedat, J. W.

    2007-10-01

    We recently described an adaptive image deconvolution algorithm (AIDA) for myopic deconvolution of multi-frame and three-dimensional data acquired through astronomical and microscopic imaging [Hom et al., J. Opt. Soc. Am. A 24, 1580 (2007)]. AIDA is a reimplementation and extension of the MISTRAL method developed by Mugnier and co-workers and shown to yield object reconstructions with excellent edge preservation and photometric precision [J. Opt. Soc. Am. A 21, 1841 (2004)]. Written in Numerical Python with calls to a robust constrained conjugate gradient method, AIDA has significantly improved run times over the original MISTRAL implementation. AIDA includes a scheme to automatically balance maximum-likelihood estimation and object regularization, which significantly decreases the amount of time and effort needed to generate satisfactory reconstructions. Here, we present a gallery of results demonstrating the effectiveness of AIDA in processing planetary science images acquired using adaptive-optics systems. Offered as an open-source alternative to MISTRAL, AIDA is available for download and further development at: http://msg.ucsf.edu/AIDA. This work was supported in part by the W. M. Keck Observatory, the National Institutes of Health, NASA, the National Science Foundation Science and Technology Center for Adaptive Optics at UC-Santa Cruz, and the Howard Hughes Medical Institute.

  17. Adaptive EAGLE dynamic solution adaptation and grid quality enhancement

    NASA Technical Reports Server (NTRS)

    Luong, Phu Vinh; Thompson, J. F.; Gatlin, B.; Mastin, C. W.; Kim, H. J.

    1992-01-01

    In the effort described here, the elliptic grid generation procedure in the EAGLE grid code was separated from the main code into a subroutine, and a new subroutine which evaluates several grid quality measures at each grid point was added. The elliptic grid routine can now be called, either by a computational fluid dynamics (CFD) code to generate a new adaptive grid based on flow variables and quality measures through multiple adaptation, or by the EAGLE main code to generate a grid based on quality measure variables through static adaptation. Arrays of flow variables can be read into the EAGLE grid code for use in static adaptation as well. These major changes in the EAGLE adaptive grid system make it easier to convert any CFD code that operates on a block-structured grid (or single-block grid) into a multiple adaptive code.

  18. Introduction to project ALIAS: adaptive-learning image analysis system

    NASA Astrophysics Data System (ADS)

    Bock, Peter

    1992-03-01

    As an alternative to preprogrammed rule-based artificial intelligence, collective learning systems theory postulates a hierarchical network of cellular automata which acquire their knowledge through learning based on a series of trial-and-error interactions with an evaluating environment, much as humans do. The input to the hierarchical network is provided by a set of sensors which perceive the external world. Using both this perceived information and past experience (memory), the learning automata synthesize collections of trial responses, periodically modifying their memories based on internal evaluations or external evaluations from the environment. Based on collective learning systems theory, an adaptive transputer- based image-processing engine comprising a three-layer hierarchical network of 32 learning cells and 33 nonlearning cells has been applied to a difficult image processing task: the scale, phase, and translation-invariant detection of anomalous features in otherwise `normal' images. Known as adaptive learning image analysis system (ALIAS), this parallel-processing engine has been constructed and tested at the Research institute for Applied Knowledge Processing (FAW) in Ulm, Germany under the sponsorship of Robert Bosch GmbH. Results demonstrate excellent detection, discrimination, and localization of anomalies in binary images. Recent enhancements include the ability to process gray-scale images and the automatic supervised segmentation and classification of images. Current research is directed toward the processing of time-series data and the hierarchical extension of ALIAS from the sub-symbolic level to the higher levels of symbolic association.

  19. Self-adaptive iris image acquisition system

    NASA Astrophysics Data System (ADS)

    Dong, Wenbo; Sun, Zhenan; Tan, Tieniu; Qiu, Xianchao

    2008-03-01

    Iris image acquisition is the fundamental step of the iris recognition, but capturing high-resolution iris images in real-time is very difficult. The most common systems have small capture volume and demand users to fully cooperate with machines, which has become the bottleneck of iris recognition's application. In this paper, we aim at building an active iris image acquiring system which is self-adaptive to users. Two low resolution cameras are co-located in a pan-tilt-unit (PTU), for face and iris image acquisition respectively. Once the face camera detects face region in real-time video, the system controls the PTU to move towards the eye region and automatically zooms, until the iris camera captures an clear iris image for recognition. Compared with other similar works, our contribution is that we use low-resolution cameras, which can transmit image data much faster and are much cheaper than the high-resolution cameras. In the system, we use Haar-like cascaded feature to detect faces and eyes, linear transformation to predict the iris camera's position, and simple heuristic PTU control method to track eyes. A prototype device has been established, and experiments show that our system can automatically capture high-quality iris image in the range of 0.6m×0.4m×0.4m in average 3 to 5 seconds.

  20. Bio-inspired color image enhancement

    NASA Astrophysics Data System (ADS)

    Meylan, Laurence; Susstrunk, Sabine

    2004-06-01

    Capturing and rendering an image that fulfills the observer's expectations is a difficult task. This is due to the fact that the signal reaching the eye is processed by a complex mechanism before forming a percept, whereas a capturing device only retains the physical value of light intensities. It is especially difficult to render complex scenes with highly varying luminances. For example, a picture taken inside a room where objects are visible through the windows will not be rendered correctly by a global technique. Either details in the dim room will be hidden in shadow or the objects viewed through the window will be too bright. The image has to be treated locally to resemble more closely to what the observer remembers. The purpose of this work is to develop a technique for rendering images based on human local adaptation. We take inspiration from a model of color vision called Retinex. This model determines the perceived color given spatial relationships of the captured signals. Retinex has been used as a computational model for image rendering. In this article, we propose a new solution inspired by Retinex that is based on a single filter applied to the luminance channel. All parameters are image-dependent so that the process requires no parameter tuning. That makes the method more flexible than other existing ones. The presented results show that our method suitably enhances high dynamic range images.

  1. Real-time fast inverse dose optimization for image guided adaptive radiation therapy-Enhancements to fast inverse dose optimization (FIDO)

    NASA Astrophysics Data System (ADS)

    Goldman, S. P.; Turnbull, D.; Johnson, C.; Chen, J. Z.; Battista, J. J.

    2009-05-01

    A fast, accurate and stable optimization algorithm is very important for inverse planning of intensity-modulated radiation therapy (IMRT), and for implementing dose-adaptive radiotherapy in the future. Conventional numerical search algorithms with positive beam weight constraints generally require numerous iterations and may produce suboptimal dose results due to trapping in local minima regions of the objective function landscape. A direct solution of the inverse problem using conventional quadratic objective functions without positive beam constraints is more efficient but it will result in unrealistic negative beam weights. We review here a direct solution of the inverse problem that is efficient and does not yield unphysical negative beam weights. In fast inverse dose optimization (FIDO) method the objective function for the optimization of a large number of beamlets is reformulated such that the optimization problem is reducible to a linear set of equations. The optimal set of intensities is then found through a matrix inversion, and negative beamlet intensities are avoided without the need for externally imposed ad hoc conditions. In its original version [S. P. Goldman, J. Z. Chen, and J. J. Battista, in Proceedings of the XIVth International Conference on the Use of Computers in Radiation Therapy, 2004, pp. 112-115; S. P. Goldman, J. Z. Chen, and J. J. Battista, Med. Phys. 32, 3007 (2005)], FIDO was tested on single two-dimensional computed tomography (CT) slices with sharp KERMA beams without scatter, in order to establish a proof of concept which demonstrated that FIDO could be a viable method for the optimization of cancer treatment plans. In this paper we introduce the latest advancements in FIDO that now include not only its application to three-dimensional volumes irradiated by beams with full scatter but include as well a complete implementation of clinical dose-volume constraints including maximum and minimum dose as well as equivalent uniform dose

  2. Image enhancement for pattern recognition

    NASA Astrophysics Data System (ADS)

    Huynh, Quyen Q.; Neretti, Nicola; Intrator, Nathan; Dobeck, Gerald J.

    1998-09-01

    We investigate various image enhancement techniques geared towards a specific detector. Our database consists of side- scan sonar images collected at the Naval Surface Warfare Center (NSWC), and the detector we use has proven to have excellent results on these data. We start by investigating various wavelet and wavelet packet denoising methods. Other methods we consider are based on more common filters (Gaussian and DOG filters). In wavelet based denoising we try different approaches, combining techniques that have been successfully used in signal and image denoising. We notice that the performance is mostly affected by the choice of the scale levels to which shrinkage is applied. We demonstrate that wavelet denoising can significantly improve detection performance while keeping low false alarm rates.

  3. Adaptive thresholding of digital subtraction angiography images

    NASA Astrophysics Data System (ADS)

    Sang, Nong; Li, Heng; Peng, Weixue; Zhang, Tianxu

    2005-10-01

    In clinical practice, digital subtraction angiography (DSA) is a powerful technique for the visualization of blood vessels in the human body. Blood vessel segmentation is a main problem for 3D vascular reconstruction. In this paper, we propose a new adaptive thresholding method for the segmentation of DSA images. Each pixel of the DSA images is declared to be a vessel/background point with regard to a threshold and a few local characteristic limits depending on some information contained in the pixel neighborhood window. The size of the neighborhood window is set according to a priori knowledge of the diameter of vessels to make sure that each window contains the background definitely. Some experiments on cerebral DSA images are given, which show that our proposed method yields better results than global thresholding methods and some other local thresholding methods do.

  4. Digital Image Watermarking via Adaptive Logo Texturization.

    PubMed

    Andalibi, Mehran; Chandler, Damon M

    2015-12-01

    Grayscale logo watermarking is a quite well-developed area of digital image watermarking which seeks to embed into the host image another smaller logo image. The key advantage of such an approach is the ability to visually analyze the extracted logo for rapid visual authentication and other visual tasks. However, logos pose new challenges for invisible watermarking applications which need to keep the watermark imperceptible within the host image while simultaneously maintaining robustness to attacks. This paper presents an algorithm for invisible grayscale logo watermarking that operates via adaptive texturization of the logo. The central idea of our approach is to recast the watermarking task into a texture similarity task. We first separate the host image into sufficiently textured and poorly textured regions. Next, for textured regions, we transform the logo into a visually similar texture via the Arnold transform and one lossless rotation; whereas for poorly textured regions, we use only a lossless rotation. The iteration for the Arnold transform and the angle of lossless rotation are determined by a model of visual texture similarity. Finally, for each region, we embed the transformed logo into that region via a standard wavelet-based embedding scheme. We employ a multistep extraction stage, in which an affine parameter estimation is first performed to compensate for possible geometrical transformations. Testing with multiple logos on a database of host images and under a variety of attacks demonstrates that the proposed algorithm yields better overall performance than competing methods.

  5. Incorporating Adaptive Local Information Into Fuzzy Clustering for Image Segmentation.

    PubMed

    Liu, Guoying; Zhang, Yun; Wang, Aimin

    2015-11-01

    Fuzzy c-means (FCM) clustering with spatial constraints has attracted great attention in the field of image segmentation. However, most of the popular techniques fail to resolve misclassification problems due to the inaccuracy of their spatial models. This paper presents a new unsupervised FCM-based image segmentation method by paying closer attention to the selection of local information. In this method, region-level local information is incorporated into the fuzzy clustering procedure to adaptively control the range and strength of interactive pixels. First, a novel dissimilarity function is established by combining region-based and pixel-based distance functions together, in order to enhance the relationship between pixels which have similar local characteristics. Second, a novel prior probability function is developed by integrating the differences between neighboring regions into the mean template of the fuzzy membership function, which adaptively selects local spatial constraints by a tradeoff weight depending upon whether a pixel belongs to a homogeneous region or not. Through incorporating region-based information into the spatial constraints, the proposed method strengthens the interactions between pixels within the same region and prevents over smoothing across region boundaries. Experimental results over synthetic noise images, natural color images, and synthetic aperture radar images show that the proposed method achieves more accurate segmentation results, compared with five state-of-the-art image segmentation methods.

  6. Adaptive Optics Imaging of Solar System Objects

    NASA Technical Reports Server (NTRS)

    Roddier, Francois; Owen, Toby

    1997-01-01

    Most solar system objects have never been observed at wavelengths longer than the R band with an angular resolution better than 1 sec. The Hubble Space Telescope itself has only recently been equipped to observe in the infrared. However, because of its small diameter, the angular resolution is lower than that one can now achieved from the ground with adaptive optics, and time allocated to planetary science is limited. We have been using adaptive optics (AO) on a 4-m class telescope to obtain 0.1 sec resolution images solar system objects at far red and near infrared wavelengths (0.7-2.5 micron) which best discriminate their spectral signatures. Our efforts has been put into areas of research for which high angular resolution is essential, such as the mapping of Titan and of large asteroids, the dynamics and composition of Neptune stratospheric clouds, the infrared photometry of Pluto, Charon, and close satellites previously undetected from the ground.

  7. Adaptive Optics Imaging of Solar System Objects

    NASA Technical Reports Server (NTRS)

    Roddier, Francois; Owen, Toby

    1999-01-01

    Most solar system objects have never been observed at wavelengths longer than the R band with an angular resolution better than 1". The Hubble Space Telescope itself has only recently been equipped to observe in the infrared. However, because of its small diameter, the angular resolution is lower than that one can now achieved from the ground with adaptive optics, and time allocated to planetary science is limited. We have successfully used adaptive optics on a 4-m class telescope to obtain 0.1" resolution images of solar system objects in the far red and near infrared (0.7-2.5 microns), aE wavelengths which best discl"lmlnate their spectral signatures. Our efforts have been put into areas of research for which high angular resolution is essential.

  8. Adaptive line enhancers for fast acquisition

    NASA Technical Reports Server (NTRS)

    Yeh, H.-G.; Nguyen, T. M.

    1994-01-01

    Three adaptive line enhancer (ALE) algorithms and architectures - namely, conventional ALE, ALE with double filtering, and ALE with coherent accumulation - are investigated for fast carrier acquisition in the time domain. The advantages of these algorithms are their simplicity, flexibility, robustness, and applicability to general situations including the Earth-to-space uplink carrier acquisition and tracking of the spacecraft. In the acquisition mode, these algorithms act as bandpass filters; hence, the carrier-to-noise ratio (CNR) is improved for fast acquisition. In the tracking mode, these algorithms simply act as lowpass filters to improve signal-to-noise ratio; hence, better tracking performance is obtained. It is not necessary to have a priori knowledge of the received signal parameters, such as CNR, Doppler, and carrier sweeping rate. The implementation of these algorithms is in the time domain (as opposed to the frequency domain, such as the fast Fourier transform (FFT)). The carrier frequency estimation can be updated in real time at each time sample (as opposed to the batch processing of the FFT). The carrier frequency to be acquired can be time varying, and the noise can be non-Gaussian, nonstationary, and colored.

  9. Adaptive optics retinal imaging: emerging clinical applications.

    PubMed

    Godara, Pooja; Dubis, Adam M; Roorda, Austin; Duncan, Jacque L; Carroll, Joseph

    2010-12-01

    The human retina is a uniquely accessible tissue. Tools like scanning laser ophthalmoscopy and spectral domain-optical coherence tomography provide clinicians with remarkably clear pictures of the living retina. Although the anterior optics of the eye permit such non-invasive visualization of the retina and associated pathology, the same optics induce significant aberrations that obviate cellular-resolution imaging in most cases. Adaptive optics (AO) imaging systems use active optical elements to compensate for aberrations in the optical path between the object and the camera. When applied to the human eye, AO allows direct visualization of individual rod and cone photoreceptor cells, retinal pigment epithelium cells, and white blood cells. AO imaging has changed the way vision scientists and ophthalmologists see the retina, helping to clarify our understanding of retinal structure, function, and the etiology of various retinal pathologies. Here, we review some of the advances that were made possible with AO imaging of the human retina and discuss applications and future prospects for clinical imaging.

  10. Speckle image reconstruction of the adaptive optics solar images.

    PubMed

    Zhong, Libo; Tian, Yu; Rao, Changhui

    2014-11-17

    Speckle image reconstruction, in which the speckle transfer function (STF) is modeled as annular distribution according to the angular dependence of adaptive optics (AO) compensation and the individual STF in each annulus is obtained by the corresponding Fried parameter calculated from the traditional spectral ratio method, is used to restore the solar images corrected by AO system in this paper. The reconstructions of the solar images acquired by a 37-element AO system validate this method and the image quality is improved evidently. Moreover, we found the photometric accuracy of the reconstruction is field dependent due to the influence of AO correction. With the increase of angular separation of the object from the AO lockpoint, the relative improvement becomes approximately more and more effective and tends to identical in the regions far away the central field of view. The simulation results show this phenomenon is mainly due to the disparity of the calculated STF from the real AO STF with the angular dependence.

  11. A NOISE ADAPTIVE FUZZY EQUALIZATION METHOD FOR PROCESSING SOLAR EXTREME ULTRAVIOLET IMAGES

    SciTech Connect

    Druckmueller, M.

    2013-08-15

    A new image enhancement tool ideally suited for the visualization of fine structures in extreme ultraviolet images of the corona is presented in this paper. The Noise Adaptive Fuzzy Equalization method is particularly suited for the exceptionally high dynamic range images from the Atmospheric Imaging Assembly instrument on the Solar Dynamics Observatory. This method produces artifact-free images and gives significantly better results than methods based on convolution or Fourier transform which are often used for that purpose.

  12. Wavelength-adaptive dehazing using histogram merging-based classification for UAV images.

    PubMed

    Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

    2015-03-19

    Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

  13. Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images

    PubMed Central

    Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

    2015-01-01

    Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results. PMID:25808767

  14. Wavelength-adaptive dehazing using histogram merging-based classification for UAV images.

    PubMed

    Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

    2015-01-01

    Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results. PMID:25808767

  15. Adaptive Robotic Welding Using A Rapid Image Pre-Processor

    NASA Astrophysics Data System (ADS)

    Dufour, M.; Begin, G.

    1984-02-01

    The rapid pre-processor initially developed by NRCC and Leigh Instruments Inc. as part of the visual aid system of the space shuttle arm 1 has been adapted to perform real time seam tracking of multipass butt weld and other adaptive welding functions. The weld preparation profile is first enhanced by a projected laser target formed by a line and dots. A standard TV camera is used to observe the target image at an angle. Displacement and distorsion of the target image on a monitor are simple functions of the preparation surface distance and shape respectively. Using the video signal, the pre-processor computes in real time the area and first moments of the white level figure contained within four independent rectangular windows in the field of view of the camera. The shape, size, and position of each window can be changed dynamically for each successive image at the standard 30 images/sec rate, in order to track some target image singularities. Visual sensing and welding are done simultaneously. As an example, it is shown that thin sheet metal welding can be automated using a single window for seam tracking, gap width measurement and torch height estimation. Using a second window, measurement of sheet misalignment and their orientation in space were also achieved. The system can be used at welding speed of up to 1 m/min. Simplicity, speed and effectiveness are the main advantages of this system.

  16. Efficient contrast enhancement using adaptive gamma correction with weighting distribution.

    PubMed

    Huang, Shih-Chia; Cheng, Fan-Chieh; Chiu, Yi-Sheng

    2013-03-01

    This paper proposes an efficient method to modify histograms and enhance contrast in digital images. Enhancement plays a significant role in digital image processing, computer vision, and pattern recognition. We present an automatic transformation technique that improves the brightness of dimmed images via the gamma correction and probability distribution of luminance pixels. To enhance video, the proposed image-enhancement method uses temporal information regarding the differences between each frame to reduce computational complexity. Experimental results demonstrate that the proposed method produces enhanced images of comparable or higher quality than those produced using previous state-of-the-art methods. PMID:23144035

  17. Image enhancement algorithm based on improved lateral inhibition network

    NASA Astrophysics Data System (ADS)

    Yun, Haijiao; Wu, Zhiyong; Wang, Guanjun; Tong, Gang; Yang, Hua

    2016-05-01

    There is often substantial noise and blurred details in the images captured by cameras. To solve this problem, we propose a novel image enhancement algorithm combined with an improved lateral inhibition network. Firstly, we built a mathematical model of a lateral inhibition network in conjunction with biological visual perception; this model helped to realize enhanced contrast and improved edge definition in images. Secondly, we proposed that the adaptive lateral inhibition coefficient adhere to an exponential distribution thus making the model more flexible and more universal. Finally, we added median filtering and a compensation measure factor to build the framework with high pass filtering functionality thus eliminating image noise and improving edge contrast, addressing problems with blurred image edges. Our experimental results show that our algorithm is able to eliminate noise and the blurring phenomena, and enhance the details of visible and infrared images.

  18. Retinal imaging using adaptive optics technology☆

    PubMed Central

    Kozak, Igor

    2014-01-01

    Adaptive optics (AO) is a technology used to improve the performance of optical systems by reducing the effect of wave front distortions. Retinal imaging using AO aims to compensate for higher order aberrations originating from the cornea and the lens by using deformable mirror. The main application of AO retinal imaging has been to assess photoreceptor cell density, spacing, and mosaic regularity in normal and diseased eyes. Apart from photoreceptors, the retinal pigment epithelium, retinal nerve fiber layer, retinal vessel wall and lamina cribrosa can also be visualized with AO technology. Recent interest in AO technology in eye research has resulted in growing number of reports and publications utilizing this technology in both animals and humans. With the availability of first commercially available instruments we are making transformation of AO technology from a research tool to diagnostic instrument. The current challenges include imaging eyes with less than perfect optical media, formation of normative databases for acquired images such as cone mosaics, and the cost of the technology. The opportunities for AO will include more detailed diagnosis with description of some new findings in retinal diseases and glaucoma as well as expansion of AO into clinical trials which has already started. PMID:24843304

  19. Retinal imaging using adaptive optics technology.

    PubMed

    Kozak, Igor

    2014-04-01

    Adaptive optics (AO) is a technology used to improve the performance of optical systems by reducing the effect of wave front distortions. Retinal imaging using AO aims to compensate for higher order aberrations originating from the cornea and the lens by using deformable mirror. The main application of AO retinal imaging has been to assess photoreceptor cell density, spacing, and mosaic regularity in normal and diseased eyes. Apart from photoreceptors, the retinal pigment epithelium, retinal nerve fiber layer, retinal vessel wall and lamina cribrosa can also be visualized with AO technology. Recent interest in AO technology in eye research has resulted in growing number of reports and publications utilizing this technology in both animals and humans. With the availability of first commercially available instruments we are making transformation of AO technology from a research tool to diagnostic instrument. The current challenges include imaging eyes with less than perfect optical media, formation of normative databases for acquired images such as cone mosaics, and the cost of the technology. The opportunities for AO will include more detailed diagnosis with description of some new findings in retinal diseases and glaucoma as well as expansion of AO into clinical trials which has already started. PMID:24843304

  20. Extreme Adaptive Optics Planet Imager: XAOPI

    SciTech Connect

    Macintosh, B A; Graham, J; Poyneer, L; Sommargren, G; Wilhelmsen, J; Gavel, D; Jones, S; Kalas, P; Lloyd, J; Makidon, R; Olivier, S; Palmer, D; Patience, J; Perrin, M; Severson, S; Sheinis, A; Sivaramakrishnan, A; Troy, M; Wallace, K

    2003-09-17

    Ground based adaptive optics is a potentially powerful technique for direct imaging detection of extrasolar planets. Turbulence in the Earth's atmosphere imposes some fundamental limits, but the large size of ground-based telescopes compared to spacecraft can work to mitigate this. We are carrying out a design study for a dedicated ultra-high-contrast system, the eXtreme Adaptive Optics Planet Imager (XAOPI), which could be deployed on an 8-10m telescope in 2007. With a 4096-actuator MEMS deformable mirror it should achieve Strehl >0.9 in the near-IR. Using an innovative spatially filtered wavefront sensor, the system will be optimized to control scattered light over a large radius and suppress artifacts caused by static errors. We predict that it will achieve contrast levels of 10{sup 7}-10{sup 8} at angular separations of 0.2-0.8 inches around a large sample of stars (R<7-10), sufficient to detect Jupiter-like planets through their near-IR emission over a wide range of ages and masses. We are constructing a high-contrast AO testbed to verify key concepts of our system, and present preliminary results here, showing an RMS wavefront error of <1.3 nm with a flat mirror.

  1. A model for radar images and its application to adaptive digital filtering of multiplicative noise.

    PubMed

    Frost, V S; Stiles, J A; Shanmugan, K S; Holtzman, J C

    1982-02-01

    Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.

  2. Adaptive Optics Imaging of Exoplanet Host Stars

    NASA Astrophysics Data System (ADS)

    Herman, Miranda; Waaler, Mason; Patience, Jennifer; Ward-Duong, Kimberly; Rajan, Abhijith; McCarthy, Don; Kulesa, Craig; Wilson, Paul A.

    2016-01-01

    With the Arizona Infrared imager and Echelle Spectrograph (ARIES) instrument on the 6.5m MMT telescope, we obtained high angular resolution adaptive optics images of 12 exoplanet host stars. The targets are all systems with exoplanets in extremely close orbits such that the planets transit the host stars and cause regular brightness changes in the stars. The transit depth of the light curve is used to infer the radius and, in combination with radial velocity measurements, the density of the planet, but the results can be biased if the light from the host star is the combined light of a pair of stars in a binary system or a chance alignment of two stars. Given the high frequency of binary star systems and the increasing number of transit exoplanet discoveries from Kepler, K2, and anticipated discoveries with the Transiting Exoplanet Survey Satellite (TESS), this is a crucial point to consider when interpreting exoplanet properties. Companions were identified around five of the twelve targets at separations close enough that the brightness measurements of these host stars are in fact the combined brightness of two stars. Images of the resolved stellar systems and reanalysis of the exoplanet properties accounting for the presence of two stars are presented.

  3. Color image enhancement based on HVS and MSRCR

    NASA Astrophysics Data System (ADS)

    Xue, Rong kun; Li, Yu feng

    2015-10-01

    Due to inclement weather caused frequently, such as clouds, fog , rain etc. The light intensity on the illuminated objects falls sharply, it make the scenes captured unclear, poor visual quality and low contrast degree. To improve the overall quality of these images, especially the bad illuminated images, the paper propose a new color image enhancement algorithm which is based on multi-scale Retinex theory with color recovering factor (MSRCR) and the human visual system (HVS). It can effectively solve the problem of the color balance of digital images by removing the influence of light and obtain component images reflected the reflex of the object surface, meanwhile, reduce the impact of non-artificial factors and overcome the Ringing effect and human interference. Through comparison and contrast among experiments, that combined evaluated parameters on enhancement image, such as variance, average gradient, sharpness and so forth with the traditional image enhancement methods, such as histogram enhancement, adaptive histogram enhancement, the MSRCR algorithm is proved to be effective in image contrast, detail enhancement and color fidelity, etc.

  4. Adaptive Optics Imaging and Spectroscopy of Neptune

    NASA Technical Reports Server (NTRS)

    Johnson, Lindley (Technical Monitor); Sromovsky, Lawrence A.

    2005-01-01

    OBJECTIVES: We proposed to use high spectral resolution imaging and spectroscopy of Neptune in visible and near-IR spectral ranges to advance our understanding of Neptune s cloud structure. We intended to use the adaptive optics (AO) system at Mt. Wilson at visible wavelengths to try to obtain the first groundbased observations of dark spots on Neptune; we intended to use A 0 observations at the IRTF to obtain near-IR R=2000 spatially resolved spectra and near-IR A0 observations at the Keck observatory to obtain the highest spatial resolution studies of cloud feature dynamics and atmospheric motions. Vertical structure of cloud features was to be inferred from the wavelength dependent absorption of methane and hydrogen,

  5. An adaptive PCA fusion method for remote sensing images

    NASA Astrophysics Data System (ADS)

    Guo, Qing; Li, An; Zhang, Hongqun; Feng, Zhongkui

    2014-10-01

    The principal component analysis (PCA) method is a popular fusion method used for its efficiency and high spatial resolution improvement. However, the spectral distortion is often found in PCA. In this paper, we propose an adaptive PCA method to enhance the spectral quality of the fused image. The amount of spatial details of the panchromatic (PAN) image injected into each band of the multi-spectral (MS) image is appropriately determined by a weighting matrix, which is defined by the edges of the PAN image, the edges of the MS image and the proportions between MS bands. In order to prove the effectiveness of the proposed method, the qualitative visual and quantitative analyses are introduced. The correlation coefficient (CC), the spectral discrepancy (SPD), and the spectral angle mapper (SAM) are used to measure the spectral quality of each fused band image. Q index is calculated to evaluate the global spectral quality of all the fused bands as a whole. The spatial quality is evaluated by the average gradient (AG) and the standard deviation (STD). Experimental results show that the proposed method improves the spectral quality very much comparing to the original PCA method while maintaining the high spatial quality of the original PCA.

  6. Contrast enhancement algorithm considering surrounding information by illumination image

    NASA Astrophysics Data System (ADS)

    Song, Ki Sun; Kang, Hee; Kang, Moon Gi

    2014-09-01

    We propose a contrast enhancement algorithm considering surrounding information by illumination image. Conventional contrast enhancement techniques can be classified as a retinex-based method and a tone mapping function-based method. However, many retinex methods suffer from high-computational costs or halo artifacts. To cope with these problems, efficient edge-preserving smoothing methods have been researched. Tone mapping function-based methods are limited in terms of enhancement since they are applied without considering surrounding information. To solve these problems, we estimate an illumination image with local adaptive smoothness, and then utilize it as surrounding information. The local adaptive smoothness is calculated by using illumination image properties and an edge-adaptive filter based on the just noticeable difference model. Additionally, we employ a resizing method instead of a blur kernel to reduce the computational cost of illumination estimation. The estimated illumination image is incorporated with the tone mapping function to address the limitations of the tone mapping function-based method. With this approach, the amount of local contrast enhancement is increased. Experimental results show that the proposed algorithm enhances both global and local contrasts and produces better performance in objective evaluation metrics while preventing a halo artifact.

  7. Remote sensing image subpixel mapping based on adaptive differential evolution.

    PubMed

    Zhong, Yanfei; Zhang, Liangpei

    2012-10-01

    In this paper, a novel subpixel mapping algorithm based on an adaptive differential evolution (DE) algorithm, namely, adaptive-DE subpixel mapping (ADESM), is developed to perform the subpixel mapping task for remote sensing images. Subpixel mapping may provide a fine-resolution map of class labels from coarser spectral unmixing fraction images, with the assumption of spatial dependence. In ADESM, to utilize DE, the subpixel mapping problem is transformed into an optimization problem by maximizing the spatial dependence index. The traditional DE algorithm is an efficient and powerful population-based stochastic global optimizer in continuous optimization problems, but it cannot be applied to the subpixel mapping problem in a discrete search space. In addition, it is not an easy task to properly set control parameters in DE. To avoid these problems, this paper utilizes an adaptive strategy without user-defined parameters, and a reversible-conversion strategy between continuous space and discrete space, to improve the classical DE algorithm. During the process of evolution, they are further improved by enhanced evolution operators, e.g., mutation, crossover, repair, exchange, insertion, and an effective local search to generate new candidate solutions. Experimental results using different types of remote images show that the ADESM algorithm consistently outperforms the previous subpixel mapping algorithms in all the experiments. Based on sensitivity analysis, ADESM, with its self-adaptive control parameter setting, is better than, or at least comparable to, the standard DE algorithm, when considering the accuracy of subpixel mapping, and hence provides an effective new approach to subpixel mapping for remote sensing imagery.

  8. Assessing the enhancement of image sharpness

    NASA Astrophysics Data System (ADS)

    Bouzit, Samira; MacDonald, Lindsay W.

    2006-01-01

    This study investigated four different image sharpness enhancement methods. Two methods applied standard sharpening filters (Sharpen and Sharpen More) in PhotoShop and the other two were based on adjustment of the image power spectrum using the human visual contrast sensitivity function. A psychophysical experiment was conducted with 25 observers, the results of which are presented and discussed. Five conclusions are drawn from this experiment: (1) Performance of the sharpening methods; (2) Image dependence; (3) Influence of two different colour spaces on sharpness manipulation; (4) Correlation between perceived image sharpness and image preference; and (5) Effect of image sharpness enhancement on the image power spectrum.

  9. Gabor filter based fingerprint image enhancement

    NASA Astrophysics Data System (ADS)

    Wang, Jin-Xiang

    2013-03-01

    Fingerprint recognition technology has become the most reliable biometric technology due to its uniqueness and invariance, which has been most convenient and most reliable technique for personal authentication. The development of Automated Fingerprint Identification System is an urgent need for modern information security. Meanwhile, fingerprint preprocessing algorithm of fingerprint recognition technology has played an important part in Automatic Fingerprint Identification System. This article introduces the general steps in the fingerprint recognition technology, namely the image input, preprocessing, feature recognition, and fingerprint image enhancement. As the key to fingerprint identification technology, fingerprint image enhancement affects the accuracy of the system. It focuses on the characteristics of the fingerprint image, Gabor filters algorithm for fingerprint image enhancement, the theoretical basis of Gabor filters, and demonstration of the filter. The enhancement algorithm for fingerprint image is in the windows XP platform with matlab.65 as a development tool for the demonstration. The result shows that the Gabor filter is effective in fingerprint image enhancement technology.

  10. Enhancement of Electrolaryngeal Speech by Adaptive Filtering.

    ERIC Educational Resources Information Center

    Espy-Wilson, Carol Y.; Chari, Venkatesh R.; MacAuslan, Joel M.; Huang, Caroline B.; Walsh, Michael J.

    1998-01-01

    A study tested the quality and intelligibility, as judged by several listeners, of four users' electrolaryngeal speech, with and without filtering to compensate for perceptually objectionable acoustic characteristics. Results indicated that an adaptive filtering technique produced a noticeable improvement in the quality of the Transcutaneous…

  11. Millimeter-wave sensor image enhancement

    NASA Technical Reports Server (NTRS)

    Wilson, William J.; Suess, Helmut

    1989-01-01

    Images from an airborne, scanning radiometer operating at a frequency of 98 GHz have been analyzed. The millimeter-wave images were obtained in 1985-1986 using the JPL millimeter-wave imaging sensor. The goal of this study was to enhance the information content of these images and make their interpretation easier. A visual-interpretative approach was used for information extraction from the images. This included application of nonlinear transform techniques for noise reduction and for color, contrast, and edge enhancement. Results of using the techniques on selected millimeter-wave images are discussed.

  12. Millimeter-wave Sensor Image Enhancement

    NASA Technical Reports Server (NTRS)

    Wilson, William J.; Suess, Helmut

    1988-01-01

    Images of an airborne scanning radiometer operating at a frequency of 98 GHz were analyzed. The mm wave images were obtained using the JPL mm wave imaging sensor. The goal was to enhance the information content of these images and make their interpretation easier for human analysis. A visual interpretative approach was used for information extraction from the images. This included application of nonlinear transform techniques for noise reduction and for color, contrast, and edge enhancement. Results of the techniques on selected mm wave images are shown.

  13. Edge adaptive intra field de-interlacing of video images

    NASA Astrophysics Data System (ADS)

    Lachine, Vladimir; Smith, Gregory; Lee, Louie

    2013-02-01

    Expanding image by an arbitrary scale factor and thereby creating an enlarged image is a crucial image processing operation. De-interlacing is an example of such operation where a video field is enlarged in vertical direction with 1 to 2 scale factor. The most advanced de-interlacing algorithms use a few consequent input fields to generate one output frame. In order to save hardware resources in video processors, missing lines in each field may be generated without reference to the other fields. Line doubling, known as "bobbing", is the simplest intra field de-interlacing method. However, it may generate visual artifacts. For example, interpolation of an inserted line from a few neighboring lines by vertical filter may produce such visual artifacts as "jaggies." In this work we present edge adaptive image up-scaling and/or enhancement algorithm, which can produce "jaggies" free video output frames. As a first step, an edge and its parameters in each interpolated pixel are detected from gradient squared tensor based on local signal variances. Then, according to the edge parameters including orientation, anisotropy and variance strength, the algorithm determines footprint and frequency response of two-dimensional interpolation filter for the output pixel. Filter's coefficients are defined by edge parameters, so that quality of the output frame is controlled by local content. The proposed method may be used for image enlargement or enhancement (for example, anti-aliasing without resampling). It has been hardware implemented in video display processor for intra field de-interlacing of video images.

  14. Frame selection performance limits for statistical image reconstruction of adaptive optics compensated images

    NASA Astrophysics Data System (ADS)

    Ford, Stephen D.

    1994-12-01

    The U.S. Air Force uses adaptive optics systems to collect images of extended objects beyond the atmosphere. These systems use wavefront sensors and deformable mirrors to compensate for atmospheric turbulence induced aberrations. Adaptive optics greatly enhance image quality, however, wavefront aberrations are not completely eliminated. Therefore, post-detection processing techniques are employed to further improve the compensated images. Typically, many short exposure images are collected, recentered to compensate for tilt, and then averaged to overcome randomness in the images and improve signal-to-noise ratio. Experience shows that some short exposure images in a data set are better than others. Frame selection exploits this fact by using a quality metric to discard low quality frames. A composite image is then created by averaging only the best frames. Performance limits associated with the frame selection technique are investigated in this thesis. Limits imposed by photon noise result in a minimum object brightness of visual magnitude +8 for point sources and +4 for a typical satellite model. Effective average point spread functions for point source and extended objects after frame selection processing are almost identical across a wide range of conditions. This discovery allows the use of deconvolution techniques to sharpen images after using the frame selection technique. A new post-detection processing method, frame weighting, is investigated and may offer some improvement for dim objects during poor atmospheric seeing. Frame selection is demonstrated for the first time on actual imagery from an adaptive optics system. Data analysis indicates that signal-to-noise ratio improvements are degraded for exposure times longer than that allowed to 'freeze' individual realizations of the turbulence effects.

  15. Infrared image enhancement using Cellular Automata

    NASA Astrophysics Data System (ADS)

    Qi, Wei; Han, Jing; Zhang, Yi; Bai, Lian-fa

    2016-05-01

    Image enhancement is a crucial technique for infrared images. The clear image details are important for improving the quality of infrared images in computer vision. In this paper, we propose a new enhancement method based on two priors via Cellular Automata. First, we directly learn the gradient distribution prior from the images via Cellular Automata. Second, considering the importance of image details, we propose a new gradient distribution error to encode the structure information via Cellular Automata. Finally, an iterative method is applied to remap the original image based on two priors, further improving the quality of enhanced image. Our method is simple in implementation, easy to understand, extensible to accommodate other vision tasks, and produces more accurate results. Experiments show that the proposed method performs better than other methods using qualitative and quantitative measures.

  16. Image enhancement based on gamma map processing

    NASA Astrophysics Data System (ADS)

    Tseng, Chen-Yu; Wang, Sheng-Jyh; Chen, Yi-An

    2010-05-01

    This paper proposes a novel image enhancement technique based on Gamma Map Processing (GMP). In this approach, a base gamma map is directly generated according to the intensity image. After that, a sequence of gamma map processing is performed to generate a channel-wise gamma map. Mapping through the estimated gamma, image details, colorfulness, and sharpness of the original image are automatically improved. Besides, the dynamic range of the images can be virtually expanded.

  17. Image Watermarking Based on Adaptive Models of Human Visual Perception

    NASA Astrophysics Data System (ADS)

    Khawne, Amnach; Hamamoto, Kazuhiko; Chitsobhuk, Orachat

    This paper proposes a digital image watermarking based on adaptive models of human visual perception. The algorithm exploits the local activities estimated from wavelet coefficients of each subband to adaptively control the luminance masking. The adaptive luminance is thus delicately combined with the contrast masking and edge detection and adopted as a visibility threshold. With the proposed combination of adaptive visual sensitivity parameters, the proposed perceptual model can be more appropriate to the different characteristics of various images. The weighting function is chosen such that the fidelity, imperceptibility and robustness could be preserved without making any perceptual difference to the image quality.

  18. Concurrent enhancement of percolation and synchronization in adaptive networks.

    PubMed

    Eom, Young-Ho; Boccaletti, Stefano; Caldarelli, Guido

    2016-06-02

    Co-evolutionary adaptive mechanisms are not only ubiquitous in nature, but also beneficial for the functioning of a variety of systems. We here consider an adaptive network of oscillators with a stochastic, fitness-based, rule of connectivity, and show that it self-organizes from fragmented and incoherent states to connected and synchronized ones. The synchronization and percolation are associated to abrupt transitions, and they are concurrently (and significantly) enhanced as compared to the non-adaptive case. Finally we provide evidence that only partial adaptation is sufficient to determine these enhancements. Our study, therefore, indicates that inclusion of simple adaptive mechanisms can efficiently describe some emergent features of networked systems' collective behaviors, and suggests also self-organized ways to control synchronization and percolation in natural and social systems.

  19. Concurrent enhancement of percolation and synchronization in adaptive networks

    PubMed Central

    Eom, Young-Ho; Boccaletti, Stefano; Caldarelli, Guido

    2016-01-01

    Co-evolutionary adaptive mechanisms are not only ubiquitous in nature, but also beneficial for the functioning of a variety of systems. We here consider an adaptive network of oscillators with a stochastic, fitness-based, rule of connectivity, and show that it self-organizes from fragmented and incoherent states to connected and synchronized ones. The synchronization and percolation are associated to abrupt transitions, and they are concurrently (and significantly) enhanced as compared to the non-adaptive case. Finally we provide evidence that only partial adaptation is sufficient to determine these enhancements. Our study, therefore, indicates that inclusion of simple adaptive mechanisms can efficiently describe some emergent features of networked systems’ collective behaviors, and suggests also self-organized ways to control synchronization and percolation in natural and social systems. PMID:27251577

  20. Concurrent enhancement of percolation and synchronization in adaptive networks

    NASA Astrophysics Data System (ADS)

    Eom, Young-Ho; Boccaletti, Stefano; Caldarelli, Guido

    2016-06-01

    Co-evolutionary adaptive mechanisms are not only ubiquitous in nature, but also beneficial for the functioning of a variety of systems. We here consider an adaptive network of oscillators with a stochastic, fitness-based, rule of connectivity, and show that it self-organizes from fragmented and incoherent states to connected and synchronized ones. The synchronization and percolation are associated to abrupt transitions, and they are concurrently (and significantly) enhanced as compared to the non-adaptive case. Finally we provide evidence that only partial adaptation is sufficient to determine these enhancements. Our study, therefore, indicates that inclusion of simple adaptive mechanisms can efficiently describe some emergent features of networked systems’ collective behaviors, and suggests also self-organized ways to control synchronization and percolation in natural and social systems.

  1. Concurrent enhancement of percolation and synchronization in adaptive networks.

    PubMed

    Eom, Young-Ho; Boccaletti, Stefano; Caldarelli, Guido

    2016-01-01

    Co-evolutionary adaptive mechanisms are not only ubiquitous in nature, but also beneficial for the functioning of a variety of systems. We here consider an adaptive network of oscillators with a stochastic, fitness-based, rule of connectivity, and show that it self-organizes from fragmented and incoherent states to connected and synchronized ones. The synchronization and percolation are associated to abrupt transitions, and they are concurrently (and significantly) enhanced as compared to the non-adaptive case. Finally we provide evidence that only partial adaptation is sufficient to determine these enhancements. Our study, therefore, indicates that inclusion of simple adaptive mechanisms can efficiently describe some emergent features of networked systems' collective behaviors, and suggests also self-organized ways to control synchronization and percolation in natural and social systems. PMID:27251577

  2. Contrast enhancement in microscopy of human thyroid tumors by means of acousto-optic adaptive spatial filtering

    NASA Astrophysics Data System (ADS)

    Yushkov, Konstantin B.; Molchanov, Vladimir Y.; Belousov, Pavel V.; Abrosimov, Aleksander Y.

    2016-01-01

    We report a method for edge enhancement in the images of transparent samples using analog image processing in coherent light. The experimental technique is based on adaptive spatial filtering with an acousto-optic tunable filter in a telecentric optical system. We demonstrate processing of microscopic images of unstained and stained histological sections of human thyroid tumor with improved contrast.

  3. Extreme learning machine and adaptive sparse representation for image classification.

    PubMed

    Cao, Jiuwen; Zhang, Kai; Luo, Minxia; Yin, Chun; Lai, Xiaoping

    2016-09-01

    Recent research has shown the speed advantage of extreme learning machine (ELM) and the accuracy advantage of sparse representation classification (SRC) in the area of image classification. Those two methods, however, have their respective drawbacks, e.g., in general, ELM is known to be less robust to noise while SRC is known to be time-consuming. Consequently, ELM and SRC complement each other in computational complexity and classification accuracy. In order to unify such mutual complementarity and thus further enhance the classification performance, we propose an efficient hybrid classifier to exploit the advantages of ELM and SRC in this paper. More precisely, the proposed classifier consists of two stages: first, an ELM network is trained by supervised learning. Second, a discriminative criterion about the reliability of the obtained ELM output is adopted to decide whether the query image can be correctly classified or not. If the output is reliable, the classification will be performed by ELM; otherwise the query image will be fed to SRC. Meanwhile, in the stage of SRC, a sub-dictionary that is adaptive to the query image instead of the entire dictionary is extracted via the ELM output. The computational burden of SRC thus can be reduced. Extensive experiments on handwritten digit classification, landmark recognition and face recognition demonstrate that the proposed hybrid classifier outperforms ELM and SRC in classification accuracy with outstanding computational efficiency.

  4. Extreme learning machine and adaptive sparse representation for image classification.

    PubMed

    Cao, Jiuwen; Zhang, Kai; Luo, Minxia; Yin, Chun; Lai, Xiaoping

    2016-09-01

    Recent research has shown the speed advantage of extreme learning machine (ELM) and the accuracy advantage of sparse representation classification (SRC) in the area of image classification. Those two methods, however, have their respective drawbacks, e.g., in general, ELM is known to be less robust to noise while SRC is known to be time-consuming. Consequently, ELM and SRC complement each other in computational complexity and classification accuracy. In order to unify such mutual complementarity and thus further enhance the classification performance, we propose an efficient hybrid classifier to exploit the advantages of ELM and SRC in this paper. More precisely, the proposed classifier consists of two stages: first, an ELM network is trained by supervised learning. Second, a discriminative criterion about the reliability of the obtained ELM output is adopted to decide whether the query image can be correctly classified or not. If the output is reliable, the classification will be performed by ELM; otherwise the query image will be fed to SRC. Meanwhile, in the stage of SRC, a sub-dictionary that is adaptive to the query image instead of the entire dictionary is extracted via the ELM output. The computational burden of SRC thus can be reduced. Extensive experiments on handwritten digit classification, landmark recognition and face recognition demonstrate that the proposed hybrid classifier outperforms ELM and SRC in classification accuracy with outstanding computational efficiency. PMID:27389571

  5. Real-time digital image enhancement

    NASA Technical Reports Server (NTRS)

    Woods, R. E.; Gonzalez, R. C.

    1981-01-01

    A programmable system for enhancing monocular and stereographic images at video rates is presented. The system provides both automatic and interactive enhancement modes based on histogram modification and intensity mapping techniques. Experimental results which illustrate enhancement capabilities under a variety of scene types and conditions are described.

  6. Nonequilibrium Enhances Adaptation Efficiency of Stochastic Biochemical Systems

    PubMed Central

    Jia, Chen; Qian, Minping

    2016-01-01

    Adaptation is a crucial biological function possessed by many sensory systems. Early work has shown that some influential equilibrium models can achieve accurate adaptation. However, recent studies indicate that there are close relationships between adaptation and nonequilibrium. In this paper, we provide an explanation of these two seemingly contradictory results based on Markov models with relatively simple networks. We show that as the nonequilibrium driving becomes stronger, the system under consideration will undergo a phase transition along a fixed direction: from non-adaptation to simple adaptation then to oscillatory adaptation, while the transition in the opposite direction is forbidden. This indicates that although adaptation may be observed in equilibrium systems, it tends to occur in systems far away from equilibrium. In addition, we find that nonequilibrium will improve the performance of adaptation by enhancing the adaptation efficiency. All these results provide a deeper insight into the connection between adaptation and nonequilibrium. Finally, we use a more complicated network model of bacterial chemotaxis to validate the main results of this paper. PMID:27195482

  7. Optimum wavelet based masking for the contrast enhancement of medical images using enhanced cuckoo search algorithm.

    PubMed

    Daniel, Ebenezer; Anitha, J

    2016-04-01

    Unsharp masking techniques are a prominent approach in contrast enhancement. Generalized masking formulation has static scale value selection, which limits the gain of contrast. In this paper, we propose an Optimum Wavelet Based Masking (OWBM) using Enhanced Cuckoo Search Algorithm (ECSA) for the contrast improvement of medical images. The ECSA can automatically adjust the ratio of nest rebuilding, using genetic operators such as adaptive crossover and mutation. First, the proposed contrast enhancement approach is validated quantitatively using Brain Web and MIAS database images. Later, the conventional nest rebuilding of cuckoo search optimization is modified using Adaptive Rebuilding of Worst Nests (ARWN). Experimental results are analyzed using various performance matrices, and our OWBM shows improved results as compared with other reported literature.

  8. Optimum wavelet based masking for the contrast enhancement of medical images using enhanced cuckoo search algorithm.

    PubMed

    Daniel, Ebenezer; Anitha, J

    2016-04-01

    Unsharp masking techniques are a prominent approach in contrast enhancement. Generalized masking formulation has static scale value selection, which limits the gain of contrast. In this paper, we propose an Optimum Wavelet Based Masking (OWBM) using Enhanced Cuckoo Search Algorithm (ECSA) for the contrast improvement of medical images. The ECSA can automatically adjust the ratio of nest rebuilding, using genetic operators such as adaptive crossover and mutation. First, the proposed contrast enhancement approach is validated quantitatively using Brain Web and MIAS database images. Later, the conventional nest rebuilding of cuckoo search optimization is modified using Adaptive Rebuilding of Worst Nests (ARWN). Experimental results are analyzed using various performance matrices, and our OWBM shows improved results as compared with other reported literature. PMID:26945462

  9. Image contrast enhancement based on a local standard deviation model

    SciTech Connect

    Chang, Dah-Chung; Wu, Wen-Rong

    1996-12-31

    The adaptive contrast enhancement (ACE) algorithm is a widely used image enhancement method, which needs a contrast gain to adjust high frequency components of an image. In the literature, the gain is usually inversely proportional to the local standard deviation (LSD) or is a constant. But these cause two problems in practical applications, i.e., noise overenhancement and ringing artifact. In this paper a new gain is developed based on Hunt`s Gaussian image model to prevent the two defects. The new gain is a nonlinear function of LSD and has the desired characteristic emphasizing the LSD regions in which details are concentrated. We have applied the new ACE algorithm to chest x-ray images and the simulations show the effectiveness of the proposed algorithm.

  10. A New Adaptive Image Denoising Method Based on Neighboring Coefficients

    NASA Astrophysics Data System (ADS)

    Biswas, Mantosh; Om, Hari

    2016-03-01

    Many good techniques have been discussed for image denoising that include NeighShrink, improved adaptive wavelet denoising method based on neighboring coefficients (IAWDMBNC), improved wavelet shrinkage technique for image denoising (IWST), local adaptive wiener filter (LAWF), wavelet packet thresholding using median and wiener filters (WPTMWF), adaptive image denoising method based on thresholding (AIDMT). These techniques are based on local statistical description of the neighboring coefficients in a window. These methods however do not give good quality of the images since they cannot modify and remove too many small wavelet coefficients simultaneously due to the threshold. In this paper, a new image denoising method is proposed that shrinks the noisy coefficients using an adaptive threshold. Our method overcomes these drawbacks and it has better performance than the NeighShrink, IAWDMBNC, IWST, LAWF, WPTMWF, and AIDMT denoising methods.

  11. Adaptive methods of two-scale edge detection in post-enhancement visual pattern processing

    NASA Astrophysics Data System (ADS)

    Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

    2008-04-01

    Adaptive methods are defined and experimentally studied for a two-scale edge detection process that mimics human visual perception of edges and is inspired by the parvo-cellular (P) and magno-cellular (M) physiological subsystems of natural vision. This two-channel processing consists of a high spatial acuity/coarse contrast channel (P) and a coarse acuity/fine contrast (M) channel. We perform edge detection after a very strong non-linear image enhancement that uses smart Retinex image processing. Two conditions that arise from this enhancement demand adaptiveness in edge detection. These conditions are the presence of random noise further exacerbated by the enhancement process, and the equally random occurrence of dense textural visual information. We examine how to best deal with both phenomena with an automatic adaptive computation that treats both high noise and dense textures as too much information, and gracefully shifts from a smallscale to medium-scale edge pattern priorities. This shift is accomplished by using different edge-enhancement schemes that correspond with the (P) and (M) channels of the human visual system. We also examine the case of adapting to a third image condition, namely too little visual information, and automatically adjust edge detection sensitivities when sparse feature information is encountered. When this methodology is applied to a sequence of images of the same scene but with varying exposures and lighting conditions, this edge-detection process produces pattern constancy that is very useful for several imaging applications that rely on image classification in variable imaging conditions.

  12. Fingerprint image enhancement using CNN filtering techniques.

    PubMed

    Saatci, Ertugrul; Tavsanoglu, Vedat

    2003-12-01

    Due to noisy acquisition devices and variation in impression conditions, the ridgelines of fingerprint images are mostly corrupted by various kinds of noise causing cracks, scratches and bridges in the ridges as well as blurs. These cause matching errors in fingerprint recognition. For an effective recognition the correct ridge pattern is essential which requires the enhancement of fingerprint images. Segment by segment analysis of the fingerprint pattern yields various ridge direction and frequencies. By selecting a directional filter with correct filter parameters to match ridge features at each point, we can effectively enhance fingerprint ridges. This paper proposes a fingerprint image enhancement based on CNN Gabor-Type filters.

  13. Enhanced Video Surveillance (EVS) with speckle imaging

    SciTech Connect

    Carrano, C J

    2004-01-13

    Enhanced Video Surveillance (EVS) with Speckle Imaging is a high-resolution imaging system that substantially improves resolution and contrast in images acquired over long distances. This technology will increase image resolution up to an order of magnitude or greater for video surveillance systems. The system's hardware components are all commercially available and consist of a telescope or large-aperture lens assembly, a high-performance digital camera, and a personal computer. The system's software, developed at LLNL, extends standard speckle-image-processing methods (used in the astronomical community) to solve the atmospheric blurring problem associated with imaging over medium to long distances (hundreds of meters to tens of kilometers) through horizontal or slant-path turbulence. This novel imaging technology will not only enhance national security but also will benefit law enforcement, security contractors, and any private or public entity that uses video surveillance to protect their assets.

  14. Image Sensors Enhance Camera Technologies

    NASA Technical Reports Server (NTRS)

    2010-01-01

    In the 1990s, a Jet Propulsion Laboratory team led by Eric Fossum researched ways of improving complementary metal-oxide semiconductor (CMOS) image sensors in order to miniaturize cameras on spacecraft while maintaining scientific image quality. Fossum s team founded a company to commercialize the resulting CMOS active pixel sensor. Now called the Aptina Imaging Corporation, based in San Jose, California, the company has shipped over 1 billion sensors for use in applications such as digital cameras, camera phones, Web cameras, and automotive cameras. Today, one of every three cell phone cameras on the planet feature Aptina s sensor technology.

  15. Cardiac Imaging Techniques for Physicians: Late Enhancement

    PubMed Central

    Kellman, Peter; Arai, Andrew E.

    2012-01-01

    Late enhancement imaging is used to diagnose and characterize a wide range of ischemic and non-ischemic cardiomyopathies, and its use has become ubiquitous in the cardiac MR exam. As the use of late enhancement imaging has matured and the span of applications has widened, the demands on image quality have grown. The characterization of sub-endocardial MI now includes the accurate quantification of scar size, shape, and characterization of borders which have been shown to have prognostic significance. More diverse patterns of late enhancement including patchy, mid-wall, sub-epicardial, or diffuse enhancement are of interest in diagnosing non-ischemic cardiomyopathies. As clinicians are examining late enhancement images for more subtle indication of fibrosis, the demand for lower artifacts has increased. A range of new techniques have emerged to improve the speed and quality of late enhancement imaging including: methods for acquisition during free breathing, and fat water separated imaging for characterizing fibro-fatty infiltration and reduction of artifacts related to the presence of fat. Methods for quantification of T1 and extracellular volume fraction are emerging to tackle the issue of discriminating globally diffuse fibrosis from normal healthy tissue which is challenging using conventional late enhancement methods. The aim of this review will be to describe the current state of the art and to provide a guide to various clinical protocols that are commonly used. PMID:22903654

  16. Combined terahertz imaging system for enhanced imaging quality

    NASA Astrophysics Data System (ADS)

    Dolganova, Irina N.; Zaytsev, Kirill I.; Metelkina, Anna A.; Yakovlev, Egor V.; Karasik, Valeriy E.; Yurchenko, Stanislav O.

    2016-06-01

    An improved terahertz (THz) imaging system is proposed for enhancing image quality. Imaging scheme includes THz source and detection system operated in active mode as well as in passive one. In order to homogeneously illuminate the object plane the THz reshaper is proposed. The form and internal structure of the reshaper were studied by the numerical simulation. Using different test-objects we compare imaging quality in active and passive THz imaging modes. Imaging contrast and modulation transfer functions in active and passive imaging modes show drawbacks of them in high and low spatial frequencies, respectively. The experimental results confirm the benefit of combining both imaging modes into hybrid one. The proposed algorithm of making hybrid THz image is an effective approach of retrieving maximum information about the remote object.

  17. Hierarchical Segmentation Enhances Diagnostic Imaging

    NASA Technical Reports Server (NTRS)

    2007-01-01

    Bartron Medical Imaging LLC (BMI), of New Haven, Connecticut, gained a nonexclusive license from Goddard Space Flight Center to use the RHSEG software in medical imaging. To manage image data, BMI then licensed two pattern-matching software programs from NASA's Jet Propulsion Laboratory that were used in image analysis and three data-mining and edge-detection programs from Kennedy Space Center. More recently, BMI made NASA history by being the first company to partner with the Space Agency through a Cooperative Research and Development Agreement to develop a 3-D version of RHSEG. With U.S. Food and Drug Administration clearance, BMI will sell its Med-Seg imaging system with the 2-D version of the RHSEG software to analyze medical imagery from CAT and PET scans, MRI, ultrasound, digitized X-rays, digitized mammographies, dental X-rays, soft tissue analyses, moving object analyses, and soft-tissue slides such as Pap smears for the diagnoses and management of diseases. Extending the software's capabilities to three dimensions will eventually enable production of pixel-level views of a tumor or lesion, early identification of plaque build-up in arteries, and identification of density levels of microcalcification in mammographies.

  18. Adaptive SVD-Based Digital Image Watermarking

    NASA Astrophysics Data System (ADS)

    Shirvanian, Maliheh; Torkamani Azar, Farah

    Digital data utilization along with the increase popularity of the Internet has facilitated information sharing and distribution. However, such applications have also raised concern about copyright issues and unauthorized modification and distribution of digital data. Digital watermarking techniques which are proposed to solve these problems hide some information in digital media and extract it whenever needed to indicate the data owner. In this paper a new method of image watermarking based on singular value decomposition (SVD) of images is proposed which considers human visual system prior to embedding watermark by segmenting the original image into several blocks of different sizes, with more density in the edges of the image. In this way the original image quality is preserved in the watermarked image. Additional advantages of the proposed technique are large capacity of watermark embedding and robustness of the method against different types of image manipulation techniques.

  19. An enhanced fast scanning algorithm for image segmentation

    NASA Astrophysics Data System (ADS)

    Ismael, Ahmed Naser; Yusof, Yuhanis binti

    2015-12-01

    Segmentation is an essential and important process that separates an image into regions that have similar characteristics or features. This will transform the image for a better image analysis and evaluation. An important benefit of segmentation is the identification of region of interest in a particular image. Various algorithms have been proposed for image segmentation and this includes the Fast Scanning algorithm which has been employed on food, sport and medical images. It scans all pixels in the image and cluster each pixel according to the upper and left neighbor pixels. The clustering process in Fast Scanning algorithm is performed by merging pixels with similar neighbor based on an identified threshold. Such an approach will lead to a weak reliability and shape matching of the produced segments. This paper proposes an adaptive threshold function to be used in the clustering process of the Fast Scanning algorithm. This function used the gray'value in the image's pixels and variance Also, the level of the image that is more the threshold are converted into intensity values between 0 and 1, and other values are converted into intensity values zero. The proposed enhanced Fast Scanning algorithm is realized on images of the public and private transportation in Iraq. Evaluation is later made by comparing the produced images of proposed algorithm and the standard Fast Scanning algorithm. The results showed that proposed algorithm is faster in terms the time from standard fast scanning.

  20. Coherent Image Layout using an Adaptive Visual Vocabulary

    SciTech Connect

    Dillard, Scott E.; Henry, Michael J.; Bohn, Shawn J.; Gosink, Luke J.

    2013-03-06

    When querying a huge image database containing millions of images, the result of the query may still contain many thousands of images that need to be presented to the user. We consider the problem of arranging such a large set of images into a visually coherent layout, one that places similar images next to each other. Image similarity is determined using a bag-of-features model, and the layout is constructed from a hierarchical clustering of the image set by mapping an in-order traversal of the hierarchy tree into a space-filling curve. This layout method provides strong locality guarantees so we are able to quantitatively evaluate performance using standard image retrieval benchmarks. Performance of the bag-of-features method is best when the vocabulary is learned on the image set being clustered. Because learning a large, discriminative vocabulary is a computationally demanding task, we present a novel method for efficiently adapting a generic visual vocabulary to a particular dataset. We evaluate our clustering and vocabulary adaptation methods on a variety of image datasets and show that adapting a generic vocabulary to a particular set of images improves performance on both hierarchical clustering and image retrieval tasks.

  1. Digital enhancement of flow field images

    NASA Technical Reports Server (NTRS)

    Kudlinski, Robert A.; Park, Stephen K.

    1988-01-01

    Most photographs of experimentally generated fluid flow fields have inherently poor photographic quality, specifically low contrast. Thus, there is a need to establish a process for quickly and accurately enhancing these photographs to provide improved versions for physical interpretation, analysis, and publication. A sequence of digital image processing techniques which have been demonstrated to effectively enhance such photographs is described.

  2. Real-time 3D adaptive filtering for portable imaging systems

    NASA Astrophysics Data System (ADS)

    Bockenbach, Olivier; Ali, Murtaza; Wainwright, Ian; Nadeski, Mark

    2015-03-01

    Portable imaging devices have proven valuable for emergency medical services both in the field and hospital environments and are becoming more prevalent in clinical settings where the use of larger imaging machines is impractical. 3D adaptive filtering is one of the most advanced techniques aimed at noise reduction and feature enhancement, but is computationally very demanding and hence often not able to run with sufficient performance on a portable platform. In recent years, advanced multicore DSPs have been introduced that attain high processing performance while maintaining low levels of power dissipation. These processors enable the implementation of complex algorithms like 3D adaptive filtering, improving the image quality of portable medical imaging devices. In this study, the performance of a 3D adaptive filtering algorithm on a digital signal processor (DSP) is investigated. The performance is assessed by filtering a volume of size 512x256x128 voxels sampled at a pace of 10 MVoxels/sec.

  3. Enhanced integral imaging system using image floating technique

    NASA Astrophysics Data System (ADS)

    Min, Sung-Wook; Kim, Joohwan; Lee, Byoungho

    2005-09-01

    Enhanced integral imaging system based on the image floating method is proposed. The integral imaging is one of the most promising methods among the autostereoscopic displays and the integrated image has the volumetric characteristics unlike the other stereoscopic images. The image floating is a common 3D display technique, which uses a big convex lens or a concave mirror to exhibit the image of a real object to the observer. The image floating method can be used to emphasize the viewing characteristics of the volumetric image and the noise image which is located on the fixed plane can be eliminated by the floating lens through the control of the focal length. In this paper, the solution of the seam noise and the image flipping of the integral imaging system is proposed using the image floating method. Moreover, the advanced techniques of the integral imaging system can be directly applied to the proposed system. The proposed system can be successfully applied to many 3D applications such as 3D television.

  4. Robust algebraic image enhancement for intelligent control systems

    NASA Technical Reports Server (NTRS)

    Lerner, Bao-Ting; Morrelli, Michael

    1993-01-01

    Robust vision capability for intelligent control systems has been an elusive goal in image processing. The computationally intensive techniques a necessary for conventional image processing make real-time applications, such as object tracking and collision avoidance difficult. In order to endow an intelligent control system with the needed vision robustness, an adequate image enhancement subsystem capable of compensating for the wide variety of real-world degradations, must exist between the image capturing and the object recognition subsystems. This enhancement stage must be adaptive and must operate with consistency in the presence of both statistical and shape-based noise. To deal with this problem, we have developed an innovative algebraic approach which provides a sound mathematical framework for image representation and manipulation. Our image model provides a natural platform from which to pursue dynamic scene analysis, and its incorporation into a vision system would serve as the front-end to an intelligent control system. We have developed a unique polynomial representation of gray level imagery and applied this representation to develop polynomial operators on complex gray level scenes. This approach is highly advantageous since polynomials can be manipulated very easily, and are readily understood, thus providing a very convenient environment for image processing. Our model presents a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets.

  5. Towards Adaptive High-Resolution Images Retrieval Schemes

    NASA Astrophysics Data System (ADS)

    Kourgli, A.; Sebai, H.; Bouteldja, S.; Oukil, Y.

    2016-06-01

    Nowadays, content-based image-retrieval techniques constitute powerful tools for archiving and mining of large remote sensing image databases. High spatial resolution images are complex and differ widely in their content, even in the same category. All images are more or less textured and structured. During the last decade, different approaches for the retrieval of this type of images have been proposed. They differ mainly in the type of features extracted. As these features are supposed to efficiently represent the query image, they should be adapted to all kind of images contained in the database. However, if the image to recognize is somewhat or very structured, a shape feature will be somewhat or very effective. While if the image is composed of a single texture, a parameter reflecting the texture of the image will reveal more efficient. This yields to use adaptive schemes. For this purpose, we propose to investigate this idea to adapt the retrieval scheme to image nature. This is achieved by making some preliminary analysis so that indexing stage becomes supervised. First results obtained show that by this way, simple methods can give equal performances to those obtained using complex methods such as the ones based on the creation of bag of visual word using SIFT (Scale Invariant Feature Transform) descriptors and those based on multi scale features extraction using wavelets and steerable pyramids.

  6. Tooling Techniques Enhance Medical Imaging

    NASA Technical Reports Server (NTRS)

    2012-01-01

    They can release as much energy as tens of billions of hydrogen bombs exploding at the same time. They send protons and electrons rocketing at near the speed of light. They heat gas in the Sun s atmosphere to tens of millions of degrees Celsius. They send a blast of gas and particles toward Earth, posing a danger to spacecraft and astronauts outside the planet s magnetosphere, in rare cases even knocking out radio communications and power grids on the ground. They are so-called solar eruptive events, made up of solar flares and the often associated coronal mass ejections. Because of the scientific mystery of how these solar eruptions are produced on the Sun with such scale and force, and also the major role they play in space weather that can impact life on Earth, NASA researchers have innovated new methods of gathering information about these violent events. One NASA mission, the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) has significantly advanced understanding of solar flares since its launch in 2002. RHESSI scientists use the spacecraft s imaging spectrometer to piece together pictures of solar flares from the high-energy X-ray and gamma-ray radiation they emit. While there is still much to be learned, data gathered by RHESSI has revealed how magnetic fields in the vast expanse of the solar atmosphere may be the force that drives the immense explosions. The instrument has imaged around 50,000 flares to date, providing information that may explain not only the workings of solar flares but also of much more massive energy releases from distant objects like black holes and quasars. We have been able to make images from X-rays with much finer resolution and greater sensitivity than have ever been made before, says Brian Dennis, RHESSI Mission Scientist and astrophysicist in the Solar Physics Laboratory at Goddard Space Flight Center. The key to RHESSI s unprecedented capabilities lie in a set of essential components a NASA partner created for the

  7. Digital speech enhancement based on DTOMP and adaptive quantile

    NASA Astrophysics Data System (ADS)

    Wang, Anna; Zhou, Xiaoxing; Xue, Changliang; Sun, Xiyan; Sun, Hongying

    2013-03-01

    Compressed Sensing (CS) that can effectively extract the information contained in the signal is a new sampling theory based on signal sparseness. This paper applies CS theory in digital speech signal enhancement processing, proposes an adaptive quantile method for the noise power estimation and combines the improved double-threshold orthogonal matching pursuit algorithm for speech reconstruction, then achieves speech enhancement processing. Compared with the simulation results of the spectral subtraction and the subspace algorithm, the experiment results verify the feasibility and effectiveness of the algorithm proposed in this paper applied to speech enhancement processing.

  8. Adaptive filtering image preprocessing for smart FPA technology

    NASA Astrophysics Data System (ADS)

    Brooks, Geoffrey W.

    1995-05-01

    This paper discusses two applications of adaptive filters for image processing on parallel architectures. The first, based on the results of previously accomplished work, summarizes the analyses of various adaptive filters implemented for pixel-level image prediction. FIR filters, fixed and adaptive IIR filters, and various variable step size algorithms were compared with a focus on algorithm complexity against the ability to predict future pixel values. A gaussian smoothing operation with varying spatial and temporal constants were also applied for comparisons of random noise reductions. The second application is a suggestion to use memory-adaptive IIR filters for detecting and tracking motion within an image. Objects within an image are made of edges, or segments, with varying degrees of motion. An application has been previously published that describes FIR filters connecting pixels and using correlations to determine motion and direction. This implementation seems limited to detecting motion coinciding with FIR filter operation rate and the associated harmonics. Upgrading the FIR structures with adaptive IIR structures can eliminate these limitations. These and any other pixel-level adaptive filtering application require data memory for filter parameters and some basic computational capability. Tradeoffs have to be made between chip real estate and these desired features. System tradeoffs will also have to be made as to where it makes the most sense to do which level of processing. Although smart pixels may not be ready to implement adaptive filters, applications such as these should give the smart pixel designer some long range goals.

  9. Use of image enhancement during lithotripsy.

    PubMed

    Dawson, C; Corry, D A; Bowsher, W G; Nockler, I B; Whitfield, H N

    1996-08-01

    Renal excursion during breathing is inevitable and is a cause of poor localization during extracorporeal shock-wave lithotripsy (SWL), which in theory might lead to poor treatment results. Eighty-one patients underwent lithotripsy treatment with and without the use of an image enhancement system designed for use with the Dornier MPL9000 lithotripter. This device contains a memory incorporated into a separate differential grayscale monitor, which allows the stone image to be stored. Shockwave release is enabled only when this image corresponds to the real-time image on the lithotripter ultrasound monitor. No improvement in success rates was found using this system, although upper-pole stones appeared to be fragmented more successfully. Overall, the results were favorable in both groups after a single treatment. Further work is needed to establish whether image enhancement is capable of improving the success rates and reducing the side effects of lithotripsy by better targeting.

  10. Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging.

    PubMed

    Cua, Michelle; Wahl, Daniel J; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J; Jian, Yifan; Sarunic, Marinko V

    2016-09-07

    Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems.

  11. Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging

    NASA Astrophysics Data System (ADS)

    Cua, Michelle; Wahl, Daniel J.; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J.; Jian, Yifan; Sarunic, Marinko V.

    2016-09-01

    Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems.

  12. Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging.

    PubMed

    Cua, Michelle; Wahl, Daniel J; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J; Jian, Yifan; Sarunic, Marinko V

    2016-01-01

    Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems. PMID:27599635

  13. Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging

    PubMed Central

    Cua, Michelle; Wahl, Daniel J.; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J.; Jian, Yifan; Sarunic, Marinko V.

    2016-01-01

    Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems. PMID:27599635

  14. New perspectives on image enhancement for the visually impaired

    NASA Astrophysics Data System (ADS)

    Peli, Eli

    1991-02-01

    Image enhancement as an aid for the visually impaired may be used to improve visibility of broadcast TV programs and to provide a portable visual aid. Initial work in this area was based on a linear model. The finite dynamic range available in the video display and contamination of the enhanced image by high spatial frequency noise limited the usefulness of this model. I propose a new enhancement method to address some of the limitations of the original model. It considers the nonlinear response of the visual system and requires enhancement of sub-threshold spatial information only. This modification increases the dynamic range available by decreasing the range previously used by the linear models to enhance visible details. Implementation of an image-enhancing visual aid in a head-mounted binocular full-field virtual vision device may cause substantial difficulties. Adaptation for the patient may be difficult due to head movement and interaction of the vestibular system response with the head-mounted display. I propose an alternate bioptic design in which the display is positioned above or below the line of sight to be examined intermittently possibly in a freeze-frame mode. Such implementation is also likely to be less expensive enabling more users access to the device. 1.

  15. Adaptive non-local means method for speckle reduction in ultrasound images

    NASA Astrophysics Data System (ADS)

    Ai, Ling; Ding, Mingyue; Zhang, Xuming

    2016-03-01

    Noise removal is a crucial step to enhance the quality of ultrasound images. However, some existing despeckling methods cannot ensure satisfactory restoration performance. In this paper, an adaptive non-local means (ANLM) filter is proposed for speckle noise reduction in ultrasound images. The distinctive property of the proposed method lies in that the decay parameter will not take the fixed value for the whole image but adapt itself to the variation of the local features in the ultrasound images. In the proposed method, the pre-filtered image will be obtained using the traditional NLM method. Based on the pre-filtered result, the local gradient will be computed and it will be utilized to determine the decay parameter adaptively for each image pixel. The final restored image will be produced by the ANLM method using the obtained decay parameters. Simulations on the synthetic image show that the proposed method can deliver sufficient speckle reduction while preserving image details very well and it outperforms the state-of-the-art despeckling filters in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). Experiments on the clinical ultrasound image further demonstrate the practicality and advantage of the proposed method over the compared filtering methods.

  16. Probing the functions of contextual modulation by adapting images rather than observers

    PubMed Central

    Webster, Michael A.

    2014-01-01

    Countless visual aftereffects have illustrated how visual sensitivity and perception can be biased by adaptation to the recent temporal context. This contextual modulation has been proposed to serve a variety of functions, but the actual benefits of adaptation remain uncertain. We describe an approach we have recently developed for exploring these benefits by adapting images instead of observers, to simulate how images should appear under theoretically optimal states of adaptation. This allows the long-term consequences of adaptation to be evaluated in ways that are difficult to probe by adapting observers, and provides a common framework for understanding how visual coding changes when the environment or the observer changes, or for evaluating how the effects of temporal context depend on different models of visual coding or the adaptation processes. The approach is illustrated for the specific case of adaptation to color, for which the initial neural coding and adaptation processes are relatively well understood, but can in principle be applied to examine the consequences of adaptation for any stimulus dimension. A simple calibration that adjusts each neuron’s sensitivity according to the stimulus level it is exposed to is sufficient to normalize visual coding and generate a host of benefits, from increased efficiency to perceptual constancy to enhanced discrimination. This temporal normalization may also provide an important precursor for the effective operation of contextual mechanisms operating across space or feature dimensions. To the extent that the effects of adaptation can be predicted, images from new environments could be “pre-adapted” to match them to the observer, eliminating the need for observers to adapt. PMID:25281412

  17. Discrete adaptive zone light elements (DAZLE): a new approach to adaptive imaging

    NASA Astrophysics Data System (ADS)

    Kellogg, Robert L.; Escuti, Michael J.

    2007-09-01

    New advances in Liquid Crystal Spatial Light Modulators (LCSLM) offer opportunities for large adaptive optics in the midwave infrared spectrum. A light focusing adaptive imaging system, using the zero-order diffraction state of a polarizer-free liquid crystal polarization grating modulator to create millions of high transmittance apertures, is envisioned in a system called DAZLE (Discrete Adaptive Zone Light Elements). DAZLE adaptively selects large sets of LCSLM apertures using the principles of coded masks, embodied in a hybrid Discrete Fresnel Zone Plate (DFZP) design. Issues of system architecture, including factors of LCSLM aperture pattern and adaptive control, image resolution and focal plane array (FPA) matching, and trade-offs between filter bandwidths, background photon noise, and chromatic aberration are discussed.

  18. A Contrast Enhancement Method for HDR Image Using a Modified Image Formation Model

    NASA Astrophysics Data System (ADS)

    Yun, Byoung-Ju; Hong, Hee-Dong; Choi, Ho-Hyoung

    Poor illumination and viewing conditions have negativeinfluences on the quality of an image, especially the contrast of the dark and bright region. Thus, captured and displayed images usually need contrast enhancement. Histogram-based or gamma correction-based methods are generally utilized for this. However, these methods are global contrast enhancement method, and since the sensitivity of the human eye changes locally according to the position of the object and the illumination in the scene, the global contrast enhancement methods have a limit. The spatial adaptive method is needed to overcome these limitations and it has led to the development of an integrated surround retinex (ISR), and estimation of dominant chromaticity (EDC) methods. However, these methods are based on Gray-World Assumption, and they use a general image formation model, so the color constancy is known to get poor results, shown through graying-out, halo-artifacts (ringing effects), and the dominated color. This paper presents a contrast enhancement method using a modified image formation model in which the image is divided into three components: global illumination, local illumination and reflectance. After applying the power constant value to control the contrast in the resulting image, the output image is obtained from their product to avoid or minimize a color distortion, based on the sRGB color representation. The experimental results show that the proposed method yields better performances than conventional methods.

  19. Investigation of self-adaptive LED surgical lighting based on entropy contrast enhancing method

    NASA Astrophysics Data System (ADS)

    Liu, Peng; Wang, Huihui; Zhang, Yaqin; Shen, Junfei; Wu, Rengmao; Zheng, Zhenrong; Li, Haifeng; Liu, Xu

    2014-05-01

    Investigation was performed to explore the possibility of enhancing contrast by varying the spectral distribution (SPD) of the surgical lighting. The illumination scenes with different SPDs were generated by the combination of a self-adaptive white light optimization method and the LED ceiling system, the images of biological sample are taken by a CCD camera and then processed by an 'Entropy' based contrast evaluation model which is proposed specific for surgery occasion. Compared with the neutral white LED based and traditional algorithm based image enhancing methods, the illumination based enhancing method turns out a better performance in contrast enhancing and improves the average contrast value about 9% and 6%, respectively. This low cost method is simple, practicable, and thus may provide an alternative solution for the expensive visual facility medical instruments.

  20. Climate change adaptation among Tibetan pastoralists: challenges in enhancing local adaptation through policy support.

    PubMed

    Fu, Yao; Grumbine, R Edward; Wilkes, Andreas; Wang, Yun; Xu, Jian-Chu; Yang, Yong-Ping

    2012-10-01

    While researchers are aware that a mix of Local Ecological Knowledge (LEK), community-based resource management institutions, and higher-level institutions and policies can facilitate pastoralists' adaptation to climate change, policy makers have been slow to understand these linkages. Two critical issues are to what extent these factors play a role, and how to enhance local adaptation through government support. We investigated these issues through a case study of two pastoral communities on the Tibetan Plateau in China employing an analytical framework to understand local climate adaptation processes. We concluded that LEK and community-based institutions improve adaptation outcomes for Tibetan pastoralists through shaping and mobilizing resource availability to reduce risks. Higher-level institutions and policies contribute by providing resources from outside communities. There are dynamic interrelationships among these factors that can lead to support, conflict, and fragmentation. Government policy could enhance local adaptation through improvement of supportive relationships among these factors. While central government policies allow only limited room for overt integration of local knowledge/institutions, local governments often have some flexibility to buffer conflicts. In addition, government policies to support market-based economic development have greatly benefited adaptation outcomes for pastoralists. Overall, in China, there are still questions over how to create innovative institutions that blend LEK and community-based institutions with government policy making.

  1. Microarray image enhancement by denoising using stationary wavelet transform.

    PubMed

    Wang, X H; Istepanian, Robert S H; Song, Yong Hua

    2003-12-01

    Microarray imaging is considered an important tool for large scale analysis of gene expression. The accuracy of the gene expression depends on the experiment itself and further image processing. It's well known that the noises introduced during the experiment will greatly affect the accuracy of the gene expression. How to eliminate the effect of the noise constitutes a challenging problem in microarray analysis. Traditionally, statistical methods are used to estimate the noises while the microarray images are being processed. In this paper, we present a new approach to deal with the noise inherent in the microarray image processing procedure. That is, to denoise the image noises before further image processing using stationary wavelet transform (SWT). The time invariant characteristic of SWT is particularly useful in image denoising. The testing result on sample microarray images has shown an enhanced image quality. The results also show that it has a superior performance than conventional discrete wavelet transform and widely used adaptive Wiener filter in this procedure.

  2. Enhanced weak-signal sensitivity in two-photon microscopy by adaptive illumination.

    PubMed

    Chu, Kengyeh K; Lim, Daryl; Mertz, Jerome

    2007-10-01

    We describe a technique to enhance both the weak-signal relative sensitivity and the dynamic range of a laser scanning optical microscope. The technique is based on maintaining a fixed detection power by fast feedback control of the illumination power, thereby transferring high measurement resolution to weak signals while virtually eliminating the possibility of image saturation. We analyze and demonstrate the benefits of adaptive illumination in two-photon fluorescence microscopy.

  3. Enhancing forensic science with spectroscopic imaging

    NASA Astrophysics Data System (ADS)

    Ricci, Camilla; Kazarian, Sergei G.

    2006-09-01

    This presentation outlines the research we are developing in the area of Fourier Transform Infrared (FTIR) spectroscopic imaging with the focus on materials of forensic interest. FTIR spectroscopic imaging has recently emerged as a powerful tool for characterisation of heterogeneous materials. FTIR imaging relies on the ability of the military-developed infrared array detector to simultaneously measure spectra from thousands of different locations in a sample. Recently developed application of FTIR imaging using an ATR (Attenuated Total Reflection) mode has demonstrated the ability of this method to achieve spatial resolution beyond the diffraction limit of infrared light in air. Chemical visualisation with enhanced spatial resolution in micro-ATR mode broadens the range of materials studied with FTIR imaging with applications to pharmaceutical formulations or biological samples. Macro-ATR imaging has also been developed for chemical imaging analysis of large surface area samples and was applied to analyse the surface of human skin (e.g. finger), counterfeit tablets, textile materials (clothing), etc. This approach demonstrated the ability of this imaging method to detect trace materials attached to the surface of the skin. This may also prove as a valuable tool in detection of traces of explosives left or trapped on the surfaces of different materials. This FTIR imaging method is substantially superior to many of the other imaging methods due to inherent chemical specificity of infrared spectroscopy and fast acquisition times of this technique. Our preliminary data demonstrated that this methodology will provide the means to non-destructive detection method that could relate evidence to its source. This will be important in a wider crime prevention programme. In summary, intrinsic chemical specificity and enhanced visualising capability of FTIR spectroscopic imaging open a window of opportunities for counter-terrorism and crime-fighting, with applications ranging

  4. On pre-image iterations for speech enhancement.

    PubMed

    Leitner, Christina; Pernkopf, Franz

    2015-01-01

    In this paper, we apply kernel PCA for speech enhancement and derive pre-image iterations for speech enhancement. Both methods make use of a Gaussian kernel. The kernel variance serves as tuning parameter that has to be adapted according to the SNR and the desired degree of de-noising. We develop a method to derive a suitable value for the kernel variance from a noise estimate to adapt pre-image iterations to arbitrary SNRs. In experiments, we compare the performance of kernel PCA and pre-image iterations in terms of objective speech quality measures and automatic speech recognition. The speech data is corrupted by white and colored noise at 0, 5, 10, and 15 dB SNR. As a benchmark, we provide results of the generalized subspace method, of spectral subtraction, and of the minimum mean-square error log-spectral amplitude estimator. In terms of the scores of the PEASS (Perceptual Evaluation Methods for Audio Source Separation) toolbox, the proposed methods achieve a similar performance as the reference methods. The speech recognition experiments show that the utterances processed by pre-image iterations achieve a consistently better word recognition accuracy than the unprocessed noisy utterances and than the utterances processed by the generalized subspace method. PMID:26085973

  5. Multiscale image enhancement of chromosome banding patterns

    NASA Astrophysics Data System (ADS)

    Wu, Qiang; Castleman, Kenneth R.

    1996-10-01

    Visual examination of chromosome banding patterns is an important means of chromosome analysis. Cytogeneticists compare their patient's chromosome image against the prototype normal/abnormal human chromosome banding patterns. Automated chromosome analysis instruments facilitate this by digitally enhancing the chromosome images. Currently available systems employing traditional highpass/bandpass filtering and/or histogram equalization are approximately equivalent to photomicroscopy in their ability to support the detection of band pattern alterations. Improvements in chromosome image display quality, particularly in the detail of the banding pattern, would significantly increase the cost-effectiveness of these systems. In this paper we present our work on the use of multiscale transform and derivative filtering for image enhancement of chromosome banding patterns. A steerable pyramid representation of the chromosome image is generated by a multiscale transform. The derivative filters are designed to detect the bands of a chromosome, and the steerable pyramid transform is chosen based on its desirable properties of shift and rotation invariance. By processing the transform coefficients that correspond to the bands of the chromosome in the pyramid representation, contrast enhancement of the chromosome bands can be achieved with designed flexibility in scale, orientation and location. Compared with existing chromosome image enhancement techniques, this new approach offers the advantage of selective chromosome banding pattern enhancement that allows designated detail analysis. Experimental results indicate improved enhancement capabilities and promise more effective visual aid to comparison of chromosomes to the prototypes and to each other. This will increase the ability of automated chromosome analysis instruments to assist the evaluation of chromosome abnormalities in clinical samples.

  6. Image enhancement on the INVIS integrated night vision surveillance and observation system

    NASA Astrophysics Data System (ADS)

    Dijk, Judith; Schutte, Klamer; Toet, Alexander; Hogervorst, Maarten

    2010-04-01

    We present the design and first field trial results of the INVIS integrated night vision surveillance and observation system, in particular for the image enhancement techniques implemented. The INVIS is an all-day-andnight all-weather navigation and surveillance tool, combining three-band cameras. We present a processing pipeline for this system. The image quality of all individual sensor signals is enhanced through Dynamic Noise Reduction and Dynamic Super Resolution. The quality of the thermal image can be enhanced through Scene-Based Non-Uniformity Correction (SBNUC). The images are fused using natural tone mapping techniques. The contrast in the image can be improved using Local Adaptive Contrast Enhancement, applied before or after the tone mapping. These results show that the image enhancement techniques have an added value for image fusion systems.

  7. Contrast-based sensorless adaptive optics for retinal imaging.

    PubMed

    Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T O; He, Zheng; Metha, Andrew

    2015-09-01

    Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes.

  8. Contrast-based sensorless adaptive optics for retinal imaging

    PubMed Central

    Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T.O.; He, Zheng; Metha, Andrew

    2015-01-01

    Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes. PMID:26417525

  9. Rapid inversion of velocity map images for adaptive femtosecond control

    NASA Astrophysics Data System (ADS)

    Rallis, C.; Andrews, P.; Averin, R.; Jochim, B.; Gregerson, N.; Wells, E.; Zohrabi, M.; de, S.; Gaire, B.; Carnes, K. D.; Ben-Itzhak, I.; Bergues, B.; Kling, M. F.

    2011-05-01

    We report techniques developed to utilize three dimensional momentum information as feedback in adaptive femtosecond control of molecular systems. Velocity map imaging of the dissociating ions following interaction with an intense ultrafast laser pulse provides raw data. In order to recover momentum information, however, the two-dimensional image must be inverted to reconstruct the three-dimensional photofragment distribution. Using a variation of the onion-peeling technique, we invert 1054 × 1040 pixel images in under 1 second. This rapid inversion allows a slice of the momentum distribution to be used as feedback in a closed-loop adaptive control scheme. We report techniques developed to utilize three dimensional momentum information as feedback in adaptive femtosecond control of molecular systems. Velocity map imaging of the dissociating ions following interaction with an intense ultrafast laser pulse provides raw data. In order to recover momentum information, however, the two-dimensional image must be inverted to reconstruct the three-dimensional photofragment distribution. Using a variation of the onion-peeling technique, we invert 1054 × 1040 pixel images in under 1 second. This rapid inversion allows a slice of the momentum distribution to be used as feedback in a closed-loop adaptive control scheme. This work supported by National Science Foundation award PHY-0969687 and the Chemical Sciences, Geosciences, and Biosciences Division, Office of Basic Energy Science, Office of Science, US Department of Energy.

  10. Fingerprint image enhancement by differential hysteresis processing.

    PubMed

    Blotta, Eduardo; Moler, Emilce

    2004-05-10

    A new method to enhance defective fingerprints images through image digital processing tools is presented in this work. When the fingerprints have been taken without any care, blurred and in some cases mostly illegible, as in the case presented here, their classification and comparison becomes nearly impossible. A combination of spatial domain filters, including a technique called differential hysteresis processing (DHP), is applied to improve these kind of images. This set of filtering methods proved to be satisfactory in a wide range of cases by uncovering hidden details that helped to identify persons. Dactyloscopy experts from Policia Federal Argentina and the EAAF have validated these results. PMID:15062948

  11. An enhanced sub-image encryption method

    NASA Astrophysics Data System (ADS)

    Wang, Xing-Yuan; Zhang, Ying-Qian; Liu, Lin-Tao

    2016-11-01

    Recently a parallel sub-image encryption method is proposed by Mirzaei et al., which is based on a total shuffling and parallel encryption algorithm. In this paper, we firstly show that the method can be attacked by chosen plaintext attack and then propose an enhanced sub-image algorithm, which can completely resist the chosen plaintext attack. Moreover, our improved algorithm can reduce the encryption time dramatically. The experimental results also prove that the improved encryption algorithm is secure enough. So the improved method can be used in image transmission system.

  12. Fingerprint image enhancement by differential hysteresis processing.

    PubMed

    Blotta, Eduardo; Moler, Emilce

    2004-05-10

    A new method to enhance defective fingerprints images through image digital processing tools is presented in this work. When the fingerprints have been taken without any care, blurred and in some cases mostly illegible, as in the case presented here, their classification and comparison becomes nearly impossible. A combination of spatial domain filters, including a technique called differential hysteresis processing (DHP), is applied to improve these kind of images. This set of filtering methods proved to be satisfactory in a wide range of cases by uncovering hidden details that helped to identify persons. Dactyloscopy experts from Policia Federal Argentina and the EAAF have validated these results.

  13. Locally tuned inverse sine nonlinear technique for color image enhancement

    NASA Astrophysics Data System (ADS)

    Arigela, Saibabu; Asari, Vijayan K.

    2013-02-01

    In this paper, a novel inverse sine nonlinear transformation based image enhancement technique is proposed to improve the visual quality of images captured in extreme lighting conditions. This method is adaptive, local and simple. The proposed technique consists of four main stages namely histogram adjustment, dynamic range compression, contrast enhancement and nonlinear color restoration. Histogram adjustment on each spectral band is performed to belittle the effect of illumination. Dynamic range compression is accomplished by an inverse sine nonlinear function with a locally tunable image dependent parameter based on the local statistics of each pixel's neighborhood regions of the luminance image. A nonlinear color restoration process based on the chromatic information and luminance of the original image is employed. A statistical quantitative evaluation is performed with the state of the art techniques to analyze and compare the performance of the proposed technique. The proposed technique is also tested on face detection in complex lighting conditions. The results of this technique on images captured in hazy/foggy weather environment are also presented. The evaluation results confirm that the proposed method can be applied to surveillance, security applications in complex lighting environments.

  14. Adaptive optics and phase diversity imaging for responsive space applications.

    SciTech Connect

    Smith, Mark William; Wick, David Victor

    2004-11-01

    The combination of phase diversity and adaptive optics offers great flexibility. Phase diverse images can be used to diagnose aberrations and then provide feedback control to the optics to correct the aberrations. Alternatively, phase diversity can be used to partially compensate for aberrations during post-detection image processing. The adaptive optic can produce simple defocus or more complex types of phase diversity. This report presents an analysis, based on numerical simulations, of the efficiency of different modes of phase diversity with respect to compensating for specific aberrations during post-processing. It also comments on the efficiency of post-processing versus direct aberration correction. The construction of a bench top optical system that uses a membrane mirror as an active optic is described. The results of characterization tests performed on the bench top optical system are presented. The work described in this report was conducted to explore the use of adaptive optics and phase diversity imaging for responsive space applications.

  15. Regional contrast enhancement and data compression for digital mammographic images

    NASA Astrophysics Data System (ADS)

    Chen, Ji; Flynn, Michael J.; Rebner, Murray

    1993-07-01

    The wide dynamic range of mammograms poses problems for displaying images on an electronic monitor and printing images through a laser printer. In addition, digital mammograms require a large amount of storage and network transmission bandwidth. We applied contrast enhancement and data compression to the segmented images to solve these problems. Using both image intensity and Gaussian filtered images, we separated the original image into three regions: the interior region, the skinline transition region, and the exterior region. In the transition region, unsharp masking process was applied and an adaptive density shift was used to simulate the process of highlighting with a spot light. The exterior region was set to a high density to reduce glare. The interior and skinline regions are the diagnostically informative areas that need to be preserved. Visually lossless coding was done for the interior by the wavelet or subband transform coding method. This was used because there are no block artifacts and a lowpass filtered image is generated by the transform. The exterior region can be represented by a bit-plane image containing only the labeling information or represented by the lower resolution transform coefficients. Therefore, by applying filters of different scales, we can accomplish region segmentation and data compression.

  16. Polarization imaging with enhanced spatial resolution

    NASA Astrophysics Data System (ADS)

    Peinado, A.; Lizana, A.; Iemmi, C.; Campos, J.

    2015-03-01

    We present the design and the experimental implementation of a new imaging set-up, based on Liquid Crystal technology, able to obtain super-resolved polarimetric images of polarimetric samples when the resolution is detector limited. The proposed set-up is a combination of two modules. One of them is an imaging Stokes polarimeter, based on Ferroelectric Liquid Crystal cells, which is used to analyze the polarization spatial distribution of an incident beam. The other module is used to obtain high resolved intensity images of the sample in an optical system whose resolution is mainly limited by the CCD pixel geometry. It contains a calibrated Parallel Aligned Liquid Crystal on Silicon display employed to introduce controlled linear phases. As a result, a set of different low resolved intensity images with sub-pixel displacements are captured by the CCD. By properly combining these images and after applying a deconvolution process, a super-resolved intensity image of the object is obtained. Finally, the combination of the two different optical modules permits to employ super-resolved images during the polarimetric data reduction calculation, leading to a final polarization image with enhanced spatial resolution. The proposed optical set-up performance is implemented and experimentally validated by providing super-resolved images of an amplitude resolution test and a birefringent resolution test. A significant improvement in the spatial resolution (by a factor of 1.4) of the obtained polarimetric images, in comparison with the images obtained with the regular imaging system, is clearly observed when applying our proposed technique.

  17. Financial incentives enhance adaptation to a sensorimotor transformation.

    PubMed

    Gajda, Kathrin; Sülzenbrück, Sandra; Heuer, Herbert

    2016-10-01

    Adaptation to sensorimotor transformations has received much attention in recent years. However, the role of motivation and its relation to the implicit and explicit processes underlying adaptation has been neglected thus far. Here, we examine the influence of extrinsic motivation on adaptation to a visuomotor rotation by way of providing financial incentives for accurate movements. Participants in the experimental group "bonus" received a defined amount of money for high end-point accuracy in a visuomotor rotation task; participants in the control group "no bonus" did not receive a financial incentive. Results showed better overall adaptation to the visuomotor transformation in participants who were extrinsically motivated. However, there was no beneficial effect of financial incentives on the implicit component, as assessed by the after-effects, and on separately assessed explicit knowledge. These findings suggest that the positive influence of financial incentives on adaptation is due to a component which cannot be measured by after-effects or by our test of explicit knowledge. A likely candidate is model-free learning based on reward-prediction errors, which could be enhanced by the financial bonuses. PMID:27271505

  18. Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology

    PubMed Central

    Wu, Shibin; Xie, Yaoqin

    2013-01-01

    A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII). PMID:24416072

  19. Performance of the Gemini Planet Imager's adaptive optics system.

    PubMed

    Poyneer, Lisa A; Palmer, David W; Macintosh, Bruce; Savransky, Dmitry; Sadakuni, Naru; Thomas, Sandrine; Véran, Jean-Pierre; Follette, Katherine B; Greenbaum, Alexandra Z; Ammons, S Mark; Bailey, Vanessa P; Bauman, Brian; Cardwell, Andrew; Dillon, Daren; Gavel, Donald; Hartung, Markus; Hibon, Pascale; Perrin, Marshall D; Rantakyrö, Fredrik T; Sivaramakrishnan, Anand; Wang, Jason J

    2016-01-10

    The Gemini Planet Imager's adaptive optics (AO) subsystem was designed specifically to facilitate high-contrast imaging. A definitive description of the system's algorithms and technologies as built is given. 564 AO telemetry measurements from the Gemini Planet Imager Exoplanet Survey campaign are analyzed. The modal gain optimizer tracks changes in atmospheric conditions. Science observations show that image quality can be improved with the use of both the spatially filtered wavefront sensor and linear-quadratic-Gaussian control of vibration. The error budget indicates that for all targets and atmospheric conditions AO bandwidth error is the largest term.

  20. Adaptation of web pages and images for mobile applications

    NASA Astrophysics Data System (ADS)

    Kopf, Stephan; Guthier, Benjamin; Lemelson, Hendrik; Effelsberg, Wolfgang

    2009-02-01

    In this paper, we introduce our new visualization service which presents web pages and images on arbitrary devices with differing display resolutions. We analyze the layout of a web page and simplify its structure and formatting rules. The small screen of a mobile device is used much better this way. Our new image adaptation service combines several techniques. In a first step, border regions which do not contain relevant semantic content are identified. Cropping is used to remove these regions. Attention objects are identified in a second step. We use face detection, text detection and contrast based saliency maps to identify these objects and combine them into a region of interest. Optionally, the seam carving technique can be used to remove inner parts of an image. Additionally, we have developed a software tool to validate, add, delete, or modify all automatically extracted data. This tool also simulates different mobile devices, so that the user gets a feeling of how an adapted web page will look like. We have performed user studies to evaluate our web and image adaptation approach. Questions regarding software ergonomics, quality of the adapted content, and perceived benefit of the adaptation were asked.

  1. Resolution enhancement in medical ultrasound imaging.

    PubMed

    Ploquin, Marie; Basarab, Adrian; Kouamé, Denis

    2015-01-01

    Image resolution enhancement is a problem of considerable interest in all medical imaging modalities. Unlike general purpose imaging or video processing, for a very long time, medical image resolution enhancement has been based on optimization of the imaging devices. Although some recent works purport to deal with image postprocessing, much remains to be done regarding medical image enhancement via postprocessing, especially in ultrasound imaging. We face a resolution improvement issue in the case of medical ultrasound imaging. We propose to investigate this problem using multidimensional autoregressive (AR) models. Noting that the estimation of the envelope of an ultrasound radio frequency (RF) signal is very similar to the estimation of classical Fourier-based power spectrum estimation, we theoretically show that a domain change and a multidimensional AR model can be used to achieve super-resolution in ultrasound imaging provided the order is estimated correctly. Here, this is done by means of a technique that simultaneously estimates the order and the parameters of a multidimensional model using relevant regression matrix factorization. Doing so, the proposed method specifically fits ultrasound imaging and provides an estimated envelope. Moreover, an expression that links the theoretical image resolution to both the image acquisition features (such as the point spread function) and a postprocessing feature (the AR model) order is derived. The overall contribution of this work is threefold. First, it allows for automatic resolution improvement. Through a simple model and without any specific manual algorithmic parameter tuning, as is used in common methods, the proposed technique simply and exclusively uses the ultrasound RF signal as input and provides the improved B-mode as output. Second, it allows for the a priori prediction of the improvement in resolution via the knowledge of the parametric model order before actual processing. Finally, to achieve the

  2. Limitations to adaptive optics image quality in rodent eyes.

    PubMed

    Zhou, Xiaolin; Bedggood, Phillip; Metha, Andrew

    2012-08-01

    Adaptive optics (AO) retinal image quality of rodent eyes is inferior to that of human eyes, despite the promise of greater numerical aperture. This paradox challenges several assumptions commonly made in AO imaging, assumptions which may be invalidated by the very high power and dioptric thickness of the rodent retina. We used optical modeling to compare the performance of rat and human eyes under conditions that tested the validity of these assumptions. Results showed that AO image quality in the human eye is robust to positioning errors of the AO corrector and to differences in imaging depth and wavelength compared to the wavefront beacon. In contrast, image quality in the rat eye declines sharply with each of these manipulations, especially when imaging off-axis. However, some latitude does exist to offset these manipulations against each other to produce good image quality.

  3. Stochastic processes, estimation theory and image enhancement

    NASA Technical Reports Server (NTRS)

    Assefi, T.

    1978-01-01

    An introductory account of stochastic processes, estimation theory, and image enhancement is presented. The book is primarily intended for first-year graduate students and practicing engineers and scientists whose work requires an acquaintance with the theory. Fundamental concepts of probability were reviewed that are required to support the main topics. The appendices discuss the remaining mathematical background.

  4. Cost-effective forensic image enhancement

    NASA Astrophysics Data System (ADS)

    Dalrymple, Brian E.

    1998-12-01

    In 1977, a paper was presented at the SPIE conference in Reston, Virginia, detailing the computer enhancement of the Zapruder film. The forensic value of this examination in a major homicide investigation was apparent to the viewer. Equally clear was the potential for extracting evidence which is beyond the reach of conventional detection techniques. The cost of this technology in 1976, however, was prohibitive, and well beyond the means of most police agencies. Twenty-two years later, a highly efficient means of image enhancement is easily within the grasp of most police agencies, not only for homicides but for any case application. A PC workstation combined with an enhancement software package allows a forensic investigator to fully exploit digital technology. The goal of this approach is the optimization of the signal to noise ratio in images. Obstructive backgrounds may be diminished or eliminated while weak signals are optimized by the use of algorithms including Fast Fourier Transform, Histogram Equalization and Image Subtraction. An added benefit is the speed with which these processes are completed and the results known. The efficacy of forensic image enhancement is illustrated through case applications.

  5. Mesh adaptation technique for Fourier-domain fluorescence lifetime imaging

    SciTech Connect

    Soloviev, Vadim Y.

    2006-11-15

    A novel adaptive mesh technique in the Fourier domain is introduced for problems in fluorescence lifetime imaging. A dynamical adaptation of the three-dimensional scheme based on the finite volume formulation reduces computational time and balances the ill-posed nature of the inverse problem. Light propagation in the medium is modeled by the telegraph equation, while the lifetime reconstruction algorithm is derived from the Fredholm integral equation of the first kind. Stability and computational efficiency of the method are demonstrated by image reconstruction of two spherical fluorescent objects embedded in a tissue phantom.

  6. Modular on-board adaptive imaging

    NASA Technical Reports Server (NTRS)

    Eskenazi, R.; Williams, D. S.

    1978-01-01

    Feature extraction involves the transformation of a raw video image to a more compact representation of the scene in which relevant information about objects of interest is retained. The task of the low-level processor is to extract object outlines and pass the data to the high-level process in a format that facilitates pattern recognition tasks. Due to the immense computational load caused by processing a 256x256 image, even a fast minicomputer requires a few seconds to complete this low-level processing. It is, therefore, necessary to consider hardware implementation of these low-level functions to achieve real-time processing speeds. The considered project had the objective to implement a system in which the continuous feature extraction process is not affected by the dynamic changes in the scene, varying lighting conditions, or object motion relative to the cameras. Due to the high bandwidth (3.5 MHz) and serial nature of the TV data, a pipeline processing scheme was adopted as the overall architecture of this system. Modularity in the system is achieved by designing circuits that are generic within the overall system.

  7. Retinex image enhancement via a learned dictionary

    NASA Astrophysics Data System (ADS)

    Chang, Huibin; Ng, Michael K.; Wang, Wei; Zeng, Tieyong

    2015-01-01

    The main aim of this paper is to study image enhancement by using sparse and redundant representations of the reflectance component in the Retinex model over a learned dictionary. This approach is different from existing variational methods, and the advantage of this approach is that the reflectance component in the Retinex model can be represented with more details by the dictionary. A variational method based on the dynamic dictionaries is adopted here, where it changes with respect to iterations of the enhancement algorithm. Numerical examples are also reported to demonstrate that the proposed methods can provide better visual quality of the enhanced high-contrast images than the other variational methods, i.e., revealing more details in the low-light part.

  8. Wavefront sensorless adaptive optics fluorescence biomicroscope for in vivo retinal imaging in mice.

    PubMed

    Wahl, Daniel J; Jian, Yifan; Bonora, Stefano; Zawadzki, Robert J; Sarunic, Marinko V

    2016-01-01

    Cellular-resolution in vivo fluorescence imaging is a valuable tool for longitudinal studies of retinal function in vision research. Wavefront sensorless adaptive optics (WSAO) is a developing technology that enables high-resolution imaging of the mouse retina. In place of the conventional method of using a Shack-Hartmann wavefront sensor to measure the aberrations directly, WSAO uses an image quality metric and a search algorithm to drive the shape of the adaptive element (i.e. deformable mirror). WSAO is a robust approach to AO and it is compatible with a compact, low-cost lens-based system. In this report, we demonstrated a hill-climbing algorithm for WSAO with a variable focus lens and deformable mirror for non-invasive in vivo imaging of EGFP (enhanced green fluorescent protein) labelled ganglion cells and microglia cells in the mouse retina.

  9. Wavefront sensorless adaptive optics fluorescence biomicroscope for in vivo retinal imaging in mice

    PubMed Central

    Wahl, Daniel J.; Jian, Yifan; Bonora, Stefano; Zawadzki, Robert J.; Sarunic, Marinko V.

    2015-01-01

    Cellular-resolution in vivo fluorescence imaging is a valuable tool for longitudinal studies of retinal function in vision research. Wavefront sensorless adaptive optics (WSAO) is a developing technology that enables high-resolution imaging of the mouse retina. In place of the conventional method of using a Shack-Hartmann wavefront sensor to measure the aberrations directly, WSAO uses an image quality metric and a search algorithm to drive the shape of the adaptive element (i.e. deformable mirror). WSAO is a robust approach to AO and it is compatible with a compact, low-cost lens-based system. In this report, we demonstrated a hill-climbing algorithm for WSAO with a variable focus lens and deformable mirror for non-invasive in vivo imaging of EGFP (enhanced green fluorescent protein) labelled ganglion cells and microglia cells in the mouse retina. PMID:26819812

  10. Adaptive optics technology for high-resolution retinal imaging.

    PubMed

    Lombardo, Marco; Serrao, Sebastiano; Devaney, Nicholas; Parravano, Mariacristina; Lombardo, Giuseppe

    2012-12-27

    Adaptive optics (AO) is a technology used to improve the performance of optical systems by reducing the effects of optical aberrations. The direct visualization of the photoreceptor cells, capillaries and nerve fiber bundles represents the major benefit of adding AO to retinal imaging. Adaptive optics is opening a new frontier for clinical research in ophthalmology, providing new information on the early pathological changes of the retinal microstructures in various retinal diseases. We have reviewed AO technology for retinal imaging, providing information on the core components of an AO retinal camera. The most commonly used wavefront sensing and correcting elements are discussed. Furthermore, we discuss current applications of AO imaging to a population of healthy adults and to the most frequent causes of blindness, including diabetic retinopathy, age-related macular degeneration and glaucoma. We conclude our work with a discussion on future clinical prospects for AO retinal imaging.

  11. Adaptive Optics Technology for High-Resolution Retinal Imaging

    PubMed Central

    Lombardo, Marco; Serrao, Sebastiano; Devaney, Nicholas; Parravano, Mariacristina; Lombardo, Giuseppe

    2013-01-01

    Adaptive optics (AO) is a technology used to improve the performance of optical systems by reducing the effects of optical aberrations. The direct visualization of the photoreceptor cells, capillaries and nerve fiber bundles represents the major benefit of adding AO to retinal imaging. Adaptive optics is opening a new frontier for clinical research in ophthalmology, providing new information on the early pathological changes of the retinal microstructures in various retinal diseases. We have reviewed AO technology for retinal imaging, providing information on the core components of an AO retinal camera. The most commonly used wavefront sensing and correcting elements are discussed. Furthermore, we discuss current applications of AO imaging to a population of healthy adults and to the most frequent causes of blindness, including diabetic retinopathy, age-related macular degeneration and glaucoma. We conclude our work with a discussion on future clinical prospects for AO retinal imaging. PMID:23271600

  12. Enhanced detectability of small objects in correlated clutter using an improved 2-D adaptive lattice algorithm.

    PubMed

    Ffrench, P A; Zeidler, J H; Ku, W H

    1997-01-01

    Two-dimensional (2-D) adaptive filtering is a technique that can be applied to many image processing applications. This paper will focus on the development of an improved 2-D adaptive lattice algorithm (2-D AL) and its application to the removal of correlated clutter to enhance the detectability of small objects in images. The two improvements proposed here are increased flexibility in the calculation of the reflection coefficients and a 2-D method to update the correlations used in the 2-D AL algorithm. The 2-D AL algorithm is shown to predict correlated clutter in image data and the resulting filter is compared with an ideal Wiener-Hopf filter. The results of the clutter removal will be compared to previously published ones for a 2-D least mean square (LMS) algorithm. 2-D AL is better able to predict spatially varying clutter than the 2-D LMS algorithm, since it converges faster to new image properties. Examples of these improvements are shown for a spatially varying 2-D sinusoid in white noise and simulated clouds. The 2-D LMS and 2-D AL algorithms are also shown to enhance a mammogram image for the detection of small microcalcifications and stellate lesions.

  13. Adaptive k-space sampling design for edge-enhanced DCE-MRI using compressed sensing.

    PubMed

    Raja, Rajikha; Sinha, Neelam

    2014-09-01

    The critical challenge in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the trade-off between spatial and temporal resolution due to the limited availability of acquisition time. To address this, it is imperative to under-sample k-space and to develop specific reconstruction techniques. Our proposed method reconstructs high-quality images from under-sampled dynamic k-space data by proposing two main improvements; i) design of an adaptive k-space sampling lattice and ii) edge-enhanced reconstruction technique. A high-resolution data set obtained before the start of the dynamic phase is utilized. The sampling pattern is designed to adapt to the nature of k-space energy distribution obtained from the static high-resolution data. For image reconstruction, the well-known compressed sensing-based total variation (TV) minimization constrained reconstruction scheme is utilized by incorporating the gradient information obtained from the static high-resolution data. The proposed method is tested on seven real dynamic time series consisting of 2 breast data sets and 5 abdomen data sets spanning 1196 images in all. For data availability of only 10%, performance improvement is seen across various quality metrics. Average improvements in Universal Image Quality Index and Structural Similarity Index Metric of up to 28% and 24% on breast data and about 17% and 9% on abdomen data, respectively, are obtained for the proposed method as against the baseline TV reconstruction with variable density random sampling pattern.

  14. Image enhancement based on edge boosting algorithm

    NASA Astrophysics Data System (ADS)

    Ngernplubpla, Jaturon; Chitsobhuk, Orachat

    2015-12-01

    In this paper, a technique for image enhancement based on proposed edge boosting algorithm to reconstruct high quality image from a single low resolution image is described. The difficulty in single-image super-resolution is that the generic image priors resided in the low resolution input image may not be sufficient to generate the effective solutions. In order to achieve a success in super-resolution reconstruction, efficient prior knowledge should be estimated. The statistics of gradient priors in terms of priority map based on separable gradient estimation, maximum likelihood edge estimation, and local variance are introduced. The proposed edge boosting algorithm takes advantages of these gradient statistics to select the appropriate enhancement weights. The larger weights are applied to the higher frequency details while the low frequency details are smoothed. From the experimental results, the significant performance improvement quantitatively and perceptually is illustrated. It can be seen that the proposed edge boosting algorithm demonstrates high quality results with fewer artifacts, sharper edges, superior texture areas, and finer detail with low noise.

  15. Techniques for radar imaging using a wideband adaptive array

    NASA Astrophysics Data System (ADS)

    Curry, Mark Andrew

    A microwave imaging approach is simulated and validated experimentally that uses a small, wideband adaptive array. The experimental 12-element linear array and microwave receiver uses stepped frequency CW signals from 2--3 GHz and receives backscattered energy from short range objects in a +/-90° field of view. Discone antenna elements are used due to their wide temporal bandwidth, isotropic azimuth beam pattern and fixed phase center. It is also shown that these antennas have very low mutual coupling, which significantly reduces the calibration requirements. The MUSIC spectrum is used as a calibration tool. Spatial resampling is used to correct the dispersion effects, which if not compensated causes severe reduction in detection and resolution for medium and large off-axis angles. Fourier processing provides range resolution and the minimum variance spectral estimate is employed to resolve constant range targets for improved angular resolution. Spatial smoothing techniques are used to generate signal plus interference covariance matrices at each range bin. Clutter affects the angular resolution of the array due to the increase in rank of the signal plus clutter covariance matrix, whereas at the same time the rank of this matrix is reduced for closely spaced scatterers due to signal coherence. A method is proposed to enhance angular resolution in the presence of clutter by an approximate signal subspace projection (ASSP) that maps the received signal space to a lower effective rank approximation. This projection operator has a scalar control parameter that is a function of the signal and clutter amplitude estimates. These operations are accomplished without using eigendecomposition. The low sidelobe levels allow the imaging of the integrated backscattering from the absorber cones in the chamber. This creates a fairly large clutter signature for testing ASSP. We can easily resolve 2 dihedrals placed at about 70% of a beamwidth apart, with a signal to clutter ratio

  16. Application of Fuzzy Reasoning for Filtering and Enhancement of Ultrasonic Images

    NASA Technical Reports Server (NTRS)

    Sacha, J. P.; Cios, K. J.; Roth, D. J.; Berke, L.; Vary, A.

    1994-01-01

    This paper presents a new type of an adaptive fuzzy operator for detection of isolated abnormalities, and enhancement of raw ultrasonic images. Fuzzy sets used in decision rules are defined for each image based on empirical statistics of the color intensities. Examples of the method are also presented in the paper.

  17. Speckle reduction in ultrasound images using nonisotropic adaptive filtering.

    PubMed

    Eom, Kie B

    2011-10-01

    In this article, a speckle reduction approach for ultrasound imaging that preserves important features such as edges, corners and point targets is presented. Speckle reduction is an important problem in coherent imaging, such as ultrasound imaging or synthetic aperture radar, and many speckle reduction algorithms have been developed. Speckle is a non-additive and non-white process and the reduction of speckle without blurring sharp features is known to be difficult. The new speckle reduction algorithm presented in this article utilizes a nonhomogeneous filter that adapts to the proximity and direction of the nearest important features. To remove speckle without blurring important features, the location and direction of edges in the image are estimated. Then for each pixel in the image, the distance and angle to the nearest edge are efficiently computed by a two-pass algorithm and stored in distance and angle maps. Finally for each pixel, an adaptive directional filter aligned to the nearest edge is applied. The shape and orientation of the adaptive filter are determined from the distance and angle maps. The new speckle reduction algorithm is tested with both synthesized and real ultrasound images. The performance of the new algorithm is also compared with those of other speckle reduction approaches and it is shown that the new algorithm performs favorably in reducing speckle without blurring important features.

  18. High-resolution adaptive imaging with a single photodiode

    PubMed Central

    Soldevila, F.; Salvador-Balaguer, E.; Clemente, P.; Tajahuerce, E.; Lancis, J.

    2015-01-01

    During the past few years, the emergence of spatial light modulators operating at the tens of kHz has enabled new imaging modalities based on single-pixel photodetectors. The nature of single-pixel imaging enforces a reciprocal relationship between frame rate and image size. Compressive imaging methods allow images to be reconstructed from a number of projections that is only a fraction of the number of pixels. In microscopy, single-pixel imaging is capable of producing images with a moderate size of 128 × 128 pixels at frame rates under one Hz. Recently, there has been considerable interest in the development of advanced techniques for high-resolution real-time operation in applications such as biological microscopy. Here, we introduce an adaptive compressive technique based on wavelet trees within this framework. In our adaptive approach, the resolution of the projecting patterns remains deliberately small, which is crucial to avoid the demanding memory requirements of compressive sensing algorithms. At pattern projection rates of 22.7 kHz, our technique would enable to obtain 128 × 128 pixel images at frame rates around 3 Hz. In our experiments, we have demonstrated a cost-effective solution employing a commercial projection display. PMID:26382114

  19. High-resolution adaptive imaging with a single photodiode

    NASA Astrophysics Data System (ADS)

    Soldevila, F.; Salvador-Balaguer, E.; Clemente, P.; Tajahuerce, E.; Lancis, J.

    2015-09-01

    During the past few years, the emergence of spatial light modulators operating at the tens of kHz has enabled new imaging modalities based on single-pixel photodetectors. The nature of single-pixel imaging enforces a reciprocal relationship between frame rate and image size. Compressive imaging methods allow images to be reconstructed from a number of projections that is only a fraction of the number of pixels. In microscopy, single-pixel imaging is capable of producing images with a moderate size of 128 × 128 pixels at frame rates under one Hz. Recently, there has been considerable interest in the development of advanced techniques for high-resolution real-time operation in applications such as biological microscopy. Here, we introduce an adaptive compressive technique based on wavelet trees within this framework. In our adaptive approach, the resolution of the projecting patterns remains deliberately small, which is crucial to avoid the demanding memory requirements of compressive sensing algorithms. At pattern projection rates of 22.7 kHz, our technique would enable to obtain 128 × 128 pixel images at frame rates around 3 Hz. In our experiments, we have demonstrated a cost-effective solution employing a commercial projection display.

  20. An image adaptive, wavelet-based watermarking of digital images

    NASA Astrophysics Data System (ADS)

    Agreste, Santa; Andaloro, Guido; Prestipino, Daniela; Puccio, Luigia

    2007-12-01

    In digital management, multimedia content and data can easily be used in an illegal way--being copied, modified and distributed again. Copyright protection, intellectual and material rights protection for authors, owners, buyers, distributors and the authenticity of content are crucial factors in solving an urgent and real problem. In such scenario digital watermark techniques are emerging as a valid solution. In this paper, we describe an algorithm--called WM2.0--for an invisible watermark: private, strong, wavelet-based and developed for digital images protection and authenticity. Using discrete wavelet transform (DWT) is motivated by good time-frequency features and well-matching with human visual system directives. These two combined elements are important in building an invisible and robust watermark. WM2.0 works on a dual scheme: watermark embedding and watermark detection. The watermark is embedded into high frequency DWT components of a specific sub-image and it is calculated in correlation with the image features and statistic properties. Watermark detection applies a re-synchronization between the original and watermarked image. The correlation between the watermarked DWT coefficients and the watermark signal is calculated according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has shown to be resistant against geometric, filtering and StirMark attacks with a low rate of false alarm.

  1. eXtreme Adaptive Optics Planet Imager: Overview and status

    SciTech Connect

    Macintosh, B A; Bauman, B; Evans, J W; Graham, J; Lockwood, C; Poyneer, L; Dillon, D; Gavel, D; Green, J; Lloyd, J; Makidon, R; Olivier, S; Palmer, D; Perrin, M; Severson, S; Sheinis, A; Sivaramakrishnan, A; Sommargren, G; Soumer, R; Troy, M; Wallace, K; Wishnow, E

    2004-08-18

    As adaptive optics (AO) matures, it becomes possible to envision AO systems oriented towards specific important scientific goals rather than general-purpose systems. One such goal for the next decade is the direct imaging detection of extrasolar planets. An 'extreme' adaptive optics (ExAO) system optimized for extrasolar planet detection will have very high actuator counts and rapid update rates - designed for observations of bright stars - and will require exquisite internal calibration at the nanometer level. In addition to extrasolar planet detection, such a system will be capable of characterizing dust disks around young or mature stars, outflows from evolved stars, and high Strehl ratio imaging even at visible wavelengths. The NSF Center for Adaptive Optics has carried out a detailed conceptual design study for such an instrument, dubbed the eXtreme Adaptive Optics Planet Imager or XAOPI. XAOPI is a 4096-actuator AO system, notionally for the Keck telescope, capable of achieving contrast ratios >10{sup 7} at angular separations of 0.2-1'. ExAO system performance analysis is quite different than conventional AO systems - the spatial and temporal frequency content of wavefront error sources is as critical as their magnitude. We present here an overview of the XAOPI project, and an error budget highlighting the key areas determining achievable contrast. The most challenging requirement is for residual static errors to be less than 2 nm over the controlled range of spatial frequencies. If this can be achieved, direct imaging of extrasolar planets will be feasible within this decade.

  2. Implementation of Multispectral Image Classification on a Remote Adaptive Computer

    NASA Technical Reports Server (NTRS)

    Figueiredo, Marco A.; Gloster, Clay S.; Stephens, Mark; Graves, Corey A.; Nakkar, Mouna

    1999-01-01

    As the demand for higher performance computers for the processing of remote sensing science algorithms increases, the need to investigate new computing paradigms its justified. Field Programmable Gate Arrays enable the implementation of algorithms at the hardware gate level, leading to orders of m a,gnitude performance increase over microprocessor based systems. The automatic classification of spaceborne multispectral images is an example of a computation intensive application, that, can benefit from implementation on an FPGA - based custom computing machine (adaptive or reconfigurable computer). A probabilistic neural network is used here to classify pixels of of a multispectral LANDSAT-2 image. The implementation described utilizes Java client/server application programs to access the adaptive computer from a remote site. Results verify that a remote hardware version of the algorithm (implemented on an adaptive computer) is significantly faster than a local software version of the same algorithm implemented on a typical general - purpose computer).

  3. CometCIEF: A web-based image enhancement facility to digitally enhance images of cometary comae

    NASA Astrophysics Data System (ADS)

    Martin, M. Patrick; Samarasinha, Nalin; Larson, Stephen

    2015-12-01

    We present details of an online web facility for enhancing coma images of comets. This facility, the Cometary Coma Image Enhancement Facility (CometCIEF), allows a user to enhance FITS images using five advanced image enhancement techniques which were not previously available as an open source. The resultant enhanced image as well as intermediate images produced during the enhancement process can then be downloaded as FITS images. We provide additional documentation and source codes for the user to download at the Facility, available at http://www.psi.edu/research/cometimen.

  4. Digital Image Enhancement Techniques For Nondestructive Evaluation

    NASA Astrophysics Data System (ADS)

    Merenyi, Robert; Heller, Warren

    1986-11-01

    Computer image enhancement of digitized radiographic and conventional photographs have taken advantage of several unique state-of-the-art developments to reveal anomalies in aerospace hardware. Signal processing of such imagery at TASC includes multi-frame averaging to increase signal-to-noise levels, applying specially-developed filters to sharpen details without sacrificing image information, and performing local contrast stretch and histogram equalization to display structure in low-contrast areas. Edge detection, normally complicated in radiographic images by low-contrast, poor spatial resolution, and noise, is performed as a post-processing operation and utilizes a difference-of-Gaussians method and a least-squares fitting procedure. With these software tools, multi-image signal processing allows for the precise measurement (to within + 0.02 inches, rms) of structural motion within a rocket motor during a static test firing as well as identifying stress conditions in turbine blades and matrix anomalies in composite materials. These and other image enhancement examples of aerospace hardware analysis are detailed in the presentation.

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

    NASA Technical Reports Server (NTRS)

    Shlien, S.; Goodenough, D.

    1974-01-01

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

  6. An adaptive algorithm for motion compensated color image coding

    NASA Technical Reports Server (NTRS)

    Kwatra, Subhash C.; Whyte, Wayne A.; Lin, Chow-Ming

    1987-01-01

    This paper presents an adaptive algorithm for motion compensated color image coding. The algorithm can be used for video teleconferencing or broadcast signals. Activity segmentation is used to reduce the bit rate and a variable stage search is conducted to save computations. The adaptive algorithm is compared with the nonadaptive algorithm and it is shown that with approximately 60 percent savings in computing the motion vector and 33 percent additional compression, the performance of the adaptive algorithm is similar to the nonadaptive algorithm. The adaptive algorithm results also show improvement of up to 1 bit/pel over interframe DPCM coding with nonuniform quantization. The test pictures used for this study were recorded directly from broadcast video in color.

  7. [An adaptive threshloding segmentation method for urinary sediment image].

    PubMed

    Li, Yongming; Zeng, Xiaoping; Qin, Jian; Han, Liang

    2009-02-01

    In this paper is proposed a new method to solve the segmentation of the complicated defocusing urinary sediment image. The main points of the method are: (1) using wavelet transforms and morphology to erase the effect of defocusing and realize the first segmentation, (2) using adaptive threshold processing in accordance to the subimages after wavelet processing, and (3) using 'peel off' algorithm to deal with the overlapped cells' segmentations. The experimental results showed that this method was not affected by the defocusing, and it made good use of many kinds of characteristics of the images. So this new mehtod can get very precise segmentation; it is effective for defocusing urinary sediment image segmentation.

  8. Final Report: Deconvolution of Adaptive Optics Images of Titan, Neptune, and Uranus

    SciTech Connect

    Gibbard, S; Marchis, F

    2002-12-20

    This project involved images of Titan, Neptune, and Uranus obtained using the 10-meter W.M. Keck II Telescope and its adaptive optics system. An adaptive optics system corrects for turbulence in the Earth's atmosphere by sampling the wavefront and applying a correction based on the distortion measured for a known source within the same isoplanatic patch as the science target (for example, a point source such as a star). Adaptive optics can achieve a 10-fold increase in resolution over that obtained by images without adaptive optics (for example, Saturn's largest moon Titan is unresolved without adaptive optics but at least 10 resolution elements can be obtained across the disk in Keck adaptive optics images). The adaptive optics correction for atmospheric turbulence is not perfect; a point source is converted to a diffraction-limited core surrounded by a ''halo''. This halo is roughly the size and shape of the uncorrected point spread function one would observe without adaptive optics. In order to enhance the sharpness of the Keck images it is necessary to apply a deconvolution algorithm to the data. Many such deconvolution algorithms exist such as maximum likelihood and maximum entropy. These algorithms suffer to various degrees from noise amplification and creation of artifacts near sharp edges (''ringing''). In order to deconvolve the Keck images I have applied an algorithm specifically developed for observations of planetary bodies, the myopic deconvolution algorithm MISTRAL (''Myopic Iterative STep-preserving Restoration ALgorithm'') (Conan et al. 1998, 2000). MISTRAL was developed by ONERA (Office National d'Etudes et de Recherches Aerospatiales) and has been extensively tested on simulated and real AO observations, including observations of Titan (Coustenis et al.2001), Io (Marchis et al.2002, 2001), and asteroids (Hestroffer et al.2001, Rosenberg et al.2001, Makhoul et al.2001). Compared to more classical methods, MISTRAL avoids noise amplification and

  9. Digital adaptive optics line-scanning confocal imaging system.

    PubMed

    Liu, Changgeng; Kim, Myung K

    2015-01-01

    A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea.

  10. Adaptive optics with pupil tracking for high resolution retinal imaging.

    PubMed

    Sahin, Betul; Lamory, Barbara; Levecq, Xavier; Harms, Fabrice; Dainty, Chris

    2012-02-01

    Adaptive optics, when integrated into retinal imaging systems, compensates for rapidly changing ocular aberrations in real time and results in improved high resolution images that reveal the photoreceptor mosaic. Imaging the retina at high resolution has numerous potential medical applications, and yet for the development of commercial products that can be used in the clinic, the complexity and high cost of the present research systems have to be addressed. We present a new method to control the deformable mirror in real time based on pupil tracking measurements which uses the default camera for the alignment of the eye in the retinal imaging system and requires no extra cost or hardware. We also present the first experiments done with a compact adaptive optics flood illumination fundus camera where it was possible to compensate for the higher order aberrations of a moving model eye and in vivo in real time based on pupil tracking measurements, without the real time contribution of a wavefront sensor. As an outcome of this research, we showed that pupil tracking can be effectively used as a low cost and practical adaptive optics tool for high resolution retinal imaging because eye movements constitute an important part of the ocular wavefront dynamics.

  11. Digital adaptive optics line-scanning confocal imaging system

    PubMed Central

    Liu, Changgeng; Kim, Myung K.

    2015-01-01

    Abstract. A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea. PMID:26140334

  12. Digital adaptive optics line-scanning confocal imaging system.

    PubMed

    Liu, Changgeng; Kim, Myung K

    2015-01-01

    A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea. PMID:26140334

  13. Digital adaptive optics line-scanning confocal imaging system

    NASA Astrophysics Data System (ADS)

    Liu, Changgeng; Kim, Myung K.

    2015-11-01

    A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack-Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea.

  14. Precision Imaging with Adaptive Optics Aperture Masking Interferometry

    NASA Astrophysics Data System (ADS)

    Martinache, F.; Lloyd, J. P.; Tuthill, P.; Woodruff, H. C.; ten Brummelaar, T.; Turner, N.

    2005-12-01

    Adaptive Optics (AO) enables sensitive diffraction limited imaging from the ground on large telescopes. Much of the promise of AO has yet to be fully realised, due to the difficulties imposed by the complicated, unstable and unknown PSF. At the highest resolutions, (inside the PSF) AO has yet to demonstrate full potential for improvements over speckle techniques. The most precise astronomical speckle imaging observations have resulted from non-redundant pupil masking. We are developing a technique to solve the problem of PSF characterization in AO imaging by synthesizing the heritage of image reconstruction with sparse pupil sampling from astronomical interferometry with the long coherence times available after AO correction. Masking the output pupil of the AO system with a non-redundant array can provide self-calibrated imaging. Further calibration of the MTF can be provided with AO wavefront sensor telemetry data. With a precision calibrated PSF, reliable, well-posed deconvolution is possible. High SNR data and accurate MTF calibration provided by the combination of non-redundant masking and AO system telemetry, allow super-resolution. AEOS provides a unique capability to explore the dynamic range and imaging precision of this technique at visible wavelengths. The NSF/AFOSR program has funded an instrument to explore these new imaging techniques at AEOS. ZOR/AO (Zero Optical Redundance with Adaptive Optics) is presently under construction, to be deployed at AEOS in 2005.

  15. Image quality-based adaptive illumination normalisation for face recognition

    NASA Astrophysics Data System (ADS)

    Sellahewa, Harin; Jassim, Sabah A.

    2009-05-01

    Automatic face recognition is a challenging task due to intra-class variations. Changes in lighting conditions during enrolment and identification stages contribute significantly to these intra-class variations. A common approach to address the effects such of varying conditions is to pre-process the biometric samples in order normalise intra-class variations. Histogram equalisation is a widely used illumination normalisation technique in face recognition. However, a recent study has shown that applying histogram equalisation on well-lit face images could lead to a decrease in recognition accuracy. This paper presents a dynamic approach to illumination normalisation, based on face image quality. The quality of a given face image is measured in terms of its luminance distortion by comparing this image against a known reference face image. Histogram equalisation is applied to a probe image if its luminance distortion is higher than a predefined threshold. We tested the proposed adaptive illumination normalisation method on the widely used Extended Yale Face Database B. Identification results demonstrate that our adaptive normalisation produces better identification accuracy compared to the conventional approach where every image is normalised, irrespective of the lighting condition they were acquired.

  16. Intuitionistic fuzzy approach in enhancing image of flat EEG

    NASA Astrophysics Data System (ADS)

    Zenian, Suzelawati; Ahmad, Tahir; Idris, Amidora

    2014-07-01

    Image enhancement is a process to improve the quality of an image which mainly due to presence of noise. It is an initial step in medical imaging. Fuzzy approach has been used widely in the area of image processing. However, in this paper, image enhancement of Flat EEG (fEEG) during epileptic seizures using intuitionistic fuzzy set (IFS) is presented and compared.

  17. Objective assessment of image quality. IV. Application to adaptive optics

    PubMed Central

    Barrett, Harrison H.; Myers, Kyle J.; Devaney, Nicholas; Dainty, Christopher

    2008-01-01

    The methodology of objective assessment, which defines image quality in terms of the performance of specific observers on specific tasks of interest, is extended to temporal sequences of images with random point spread functions and applied to adaptive imaging in astronomy. The tasks considered include both detection and estimation, and the observers are the optimal linear discriminant (Hotelling observer) and the optimal linear estimator (Wiener). A general theory of first- and second-order spatiotemporal statistics in adaptive optics is developed. It is shown that the covariance matrix can be rigorously decomposed into three terms representing the effect of measurement noise, random point spread function, and random nature of the astronomical scene. Figures of merit are developed, and computational methods are discussed. PMID:17106464

  18. Objective assessment of image quality. IV. Application to adaptive optics.

    PubMed

    Barrett, Harrison H; Myers, Kyle J; Devaney, Nicholas; Dainty, Christopher

    2006-12-01

    The methodology of objective assessment, which defines image quality in terms of the performance of specific observers on specific tasks of interest, is extended to temporal sequences of images with random point spread functions and applied to adaptive imaging in astronomy. The tasks considered include both detection and estimation, and the observers are the optimal linear discriminant (Hotelling observer) and the optimal linear estimator (Wiener). A general theory of first- and second-order spatiotemporal statistics in adaptive optics is developed. It is shown that the covariance matrix can be rigorously decomposed into three terms representing the effect of measurement noise, random point spread function, and random nature of the astronomical scene. Figures of merit are developed, and computational methods are discussed.

  19. Objective assessment of image quality. IV. Application to adaptive optics.

    PubMed

    Barrett, Harrison H; Myers, Kyle J; Devaney, Nicholas; Dainty, Christopher

    2006-12-01

    The methodology of objective assessment, which defines image quality in terms of the performance of specific observers on specific tasks of interest, is extended to temporal sequences of images with random point spread functions and applied to adaptive imaging in astronomy. The tasks considered include both detection and estimation, and the observers are the optimal linear discriminant (Hotelling observer) and the optimal linear estimator (Wiener). A general theory of first- and second-order spatiotemporal statistics in adaptive optics is developed. It is shown that the covariance matrix can be rigorously decomposed into three terms representing the effect of measurement noise, random point spread function, and random nature of the astronomical scene. Figures of merit are developed, and computational methods are discussed. PMID:17106464

  20. Light sheet adaptive optics microscope for 3D live imaging

    NASA Astrophysics Data System (ADS)

    Bourgenot, C.; Taylor, J. M.; Saunter, C. D.; Girkin, J. M.; Love, G. D.

    2013-02-01

    We report on the incorporation of adaptive optics (AO) into the imaging arm of a selective plane illumination microscope (SPIM). SPIM has recently emerged as an important tool for life science research due to its ability to deliver high-speed, optically sectioned, time-lapse microscope images from deep within in vivo selected samples. SPIM provides a very interesting system for the incorporation of AO as the illumination and imaging paths are decoupled and AO may be useful in both paths. In this paper, we will report the use of AO applied to the imaging path of a SPIM, demonstrating significant improvement in image quality of a live GFP-labeled transgenic zebrafish embryo heart using a modal, wavefront sensorless approach and a heart synchronization method. These experimental results are linked to a computational model showing that significant aberrations are produced by the tube holding the sample in addition to the aberration from the biological sample itself.

  1. Imaging of retinal vasculature using adaptive optics SLO/OCT.

    PubMed

    Felberer, Franz; Rechenmacher, Matthias; Haindl, Richard; Baumann, Bernhard; Hitzenberger, Christoph K; Pircher, Michael

    2015-04-01

    We use our previously developed adaptive optics (AO) scanning laser ophthalmoscope (SLO)/ optical coherence tomography (OCT) instrument to investigate its capability for imaging retinal vasculature. The system records SLO and OCT images simultaneously with a pixel to pixel correspondence which allows a direct comparison between those imaging modalities. Different field of views ranging from 0.8°x0.8° up to 4°x4° are supported by the instrument. In addition a dynamic focus scheme was developed for the AO-SLO/OCT system in order to maintain the high transverse resolution throughout imaging depth. The active axial eye tracking that is implemented in the OCT channel allows time resolved measurements of the retinal vasculature in the en-face imaging plane. Vessel walls and structures that we believe correspond to individual erythrocytes could be visualized with the system.

  2. Adaptive texture filtering for defect inspection in ultrasound images

    NASA Astrophysics Data System (ADS)

    Zmola, Carl; Segal, Andrew C.; Lovewell, Brian; Nash, Charles

    1993-05-01

    The use of ultrasonic imaging to analyze defects and characterize materials is critical in the development of non-destructive testing and non-destructive evaluation (NDT/NDE) tools for manufacturing. To develop better quality control and reliability in the manufacturing environment advanced image processing techniques are useful. For example, through the use of texture filtering on ultrasound images, we have been able to filter characteristic textures from highly-textured C-scan images of materials. The materials have highly regular characteristic textures which are of the same resolution and dynamic range as other important features within the image. By applying texture filters and adaptively modifying their filter response, we have examined a family of filters for removing these textures.

  3. Enhanced high-speed coherent diffraction imaging

    NASA Astrophysics Data System (ADS)

    Potier, Jonathan; Fricker, Sebastien; Idir, Mourad

    2011-03-01

    Due to recent advances in X-ray microscopy, we are now able to image objects with nanometer resolution thanks to Synchrotron beam lines or Free Electron Lasers (FEL). The PCI (Phase Contrast Imaging) is a robust technique that can recover the wavefront from measurements of only few intensity pictures in the Fresnel diffraction region. With our fast straightforward calculus methods, we manage to provide the phase induced by a microscopic specimen in few seconds. We can therefore obtain high contrasted images from transparent materials at very small scales. To reach atomic resolution imaging and thus make a transition from the near to the far field, the Coherent Diffraction Imaging (CDI) technique finds its roots in the analysis of diffraction patterns to obtain the phase of the altered complex wave. Theoretical results about existence and uniqueness of this retrieved piece of information by both iterative and direct algorithms have already been released. However, performances of algorithms remain limited by the coherence of the X-ray beam, presence of random noise and the saturation threshold of the detector. We will present reconstructions of samples using an enhanced version of HIO algorithm improving the speed of convergence and its repeatability. As a first step toward a practical X-Ray CDI system, initial images for reconstructions are acquired with the laser-based CDI system working in the visible spectrum.

  4. Enhancing the Imaging Experience for Pediatric Patients.

    PubMed

    Baron, Molly; Joslin, Shannon; Kim, Jane S; Shet, Narendra S; Pocta, Brigitte; Olivi, Penny

    2016-01-01

    The University of Maryland Medical Center's goal was to improve the safety and comfort of pediatric imaging by enhancing the experience for children. Two pediatric radiologists and two child life specialists worked together to create a training program to help guide radiology technologists on how to approach and interact with children undergoing medical imaging. The results of surveys administered to technologists and parents or caregivers helped refine the strategy for both creating training sessions for technologists and reading materials for children and their parents to optimally prepare for the procedures. Training sessions included information on language choices, developmental considerations, comfort techniques, patient- and family-centered care practices, procedural support techniques, and coping styles. Through the implementation of learning sessions and distraction resources for technologists, and the development of preparation books, the imaging experience for pediatric patients at UMMC has improved. PMID:27514108

  5. Advanced enhancement techniques for digitized images

    NASA Astrophysics Data System (ADS)

    Tom, V. T.; Merenyi, R. C.; Carlotto, M. J.; Heller, W. G.

    Computer image enhancement of digitized X-ray and conventional photographs has been employed to reveal anomalies in aerospace hardware. Signal processing of these images included use of specially-developed filters to sharpen detail without sacrificing radiographic information, application of local contrast stretch and histogram equalization algorithms to display structure in low-contrast areas and employment of other unique digital processing methods. Edge detection, normally complicated by poor spatial resolution, limited contrast and recording media noise, was performed as a post-processing operation via a difference-of-Gaussians method and a least squares fitting procedures. In this manner, multi-image signal processing allowed for the precise measurement (to within 0.02 inches, rms) of the Inertial Upper Stage nozzle nosecap motion during a static test firing as well as identifying potential problems in the Solid Rocket Booster parachute deployment.

  6. Frequency adaptation for enhanced radiation force amplitude in dynamic elastography.

    PubMed

    Ouared, Abderrahmane; Montagnon, Emmanuel; Kazemirad, Siavash; Gaboury, Louis; Robidoux, André; Cloutier, Guy

    2015-08-01

    In remote dynamic elastography, the amplitude of the generated displacement field is directly related to the amplitude of the radiation force. Therefore, displacement improvement for better tissue characterization requires the optimization of the radiation force amplitude by increasing the push duration and/or the excitation amplitude applied on the transducer. The main problem of these approaches is that the Food and Drug Administration (FDA) thresholds for medical applications and transducer limitations may be easily exceeded. In the present study, the effect of the frequency used for the generation of the radiation force on the amplitude of the displacement field was investigated. We found that amplitudes of displacements generated by adapted radiation force sequences were greater than those generated by standard nonadapted ones (i.e., single push acoustic radiation force impulse and supersonic shear imaging). Gains in magnitude were between 20 to 158% for in vitro measurements on agar-gelatin phantoms, and 170 to 336% for ex vivo measurements on a human breast sample, depending on focus depths and attenuations of tested samples. The signal-to-noise ratio was also improved more than 4-fold with adapted sequences. We conclude that frequency adaptation is a complementary technique that is efficient for the optimization of displacement amplitudes. This technique can be used safely to optimize the deposited local acoustic energy without increasing the risk of damaging tissues and transducer elements.

  7. Teaching People and Machines to Enhance Images

    NASA Astrophysics Data System (ADS)

    Berthouzoz, Floraine Sara Martianne

    tutorials based on their command-level structure. Sites such as tutorialized.com or good-tutorials.com collect tens of thousands of photo manipulation tutorials. These collections typically contain many different tutorials for the same task. For example, there are many different tutorials that describe how to recolor the hair of a person in an image. Learners often want to compare these tutorials to understand the different ways a task can be done. They may also want to identify common strategies that are used across tutorials for a variety of tasks. However, the large number of tutorials in these collections and their inconsistent formats can make it difficult for users to systematically explore and compare them. Current tutorial collections do not exploit the underlying command-level structure of tutorials, and to explore the collection users have to either page through long lists of tutorial titles or perform keyword searches on the natural language tutorial text. We present a new browsing interface to help learners navigate, explore and compare collections of photo manipulation tutorials based on their command-level structure. Our browser indexes tutorials by their commands, identifies common strategies within the tutorial collection, and highlights the similarities and differences between sets of tutorials that execute the same task. User feedback suggests that our interface is easy to understand and use, and that users find command-level browsing to be useful for exploring large tutorial collections. They strongly preferred to explore tutorial collections with our browser over keyword search. Finally, we present a framework for generating content-adaptive macros (programs) that can transfer complex photo manipulation procedures to new target images. After learners master a photo manipulation procedure, they often repeatedly apply it to multiple images. For example, they might routinely apply the same vignetting effect to all their photographs. This process can be very

  8. Spatial structure enhanced cooperation in dissatisfied adaptive snowdrift game

    NASA Astrophysics Data System (ADS)

    Zhang, Wen; Xu, Chen; Hui, Pak Ming

    2013-05-01

    The dissatisfied adaptive snowdrift game (DASG) describes the adaptive actions driven by the level of dissatisfaction when two connected agents interact. We study the DASG in static networks both numerically and analytically. In a random network of uniform degree k, the system evolves into a homogeneous state consisting only of cooperators when the cost-to-benefit ratio r < r 0 and a mixed phase with the coexistence of cooperators and defectors when r > r 0, where r 0 is a threshold. For an infinite population, the large k limit corresponding to the well-mixed case is solved analytically. A theory is developed based on the pair approximation. It gives the frequency of cooperation f c and the densities of different pairs that are in good agreement with simulation results. The results revealed that f c is enhanced in networked populations with a finite k, when compared with the well-mixed case. The reasons that the theory works well for the present model are traced back to the weak spatial correlation implied by the random network and the fact that the adaptive actions in DASG are driven only by the strategy pairs. The results shed light on the class of models that the pair approximation is applicable.

  9. Image-adapted visually weighted quantization matrices for digital image compression

    NASA Technical Reports Server (NTRS)

    Watson, Andrew B. (Inventor)

    1994-01-01

    A method for performing image compression that eliminates redundant and invisible image components is presented. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

  10. Image Super-Resolution via Adaptive Regularization and Sparse Representation.

    PubMed

    Cao, Feilong; Cai, Miaomiao; Tan, Yuanpeng; Zhao, Jianwei

    2016-07-01

    Previous studies have shown that image patches can be well represented as a sparse linear combination of elements from an appropriately selected over-complete dictionary. Recently, single-image super-resolution (SISR) via sparse representation using blurred and downsampled low-resolution images has attracted increasing interest, where the aim is to obtain the coefficients for sparse representation by solving an l0 or l1 norm optimization problem. The l0 optimization is a nonconvex and NP-hard problem, while the l1 optimization usually requires many more measurements and presents new challenges even when the image is the usual size, so we propose a new approach for SISR recovery based on regularization nonconvex optimization. The proposed approach is potentially a powerful method for recovering SISR via sparse representations, and it can yield a sparser solution than the l1 regularization method. We also consider the best choice for lp regularization with all p in (0, 1), where we propose a scheme that adaptively selects the norm value for each image patch. In addition, we provide a method for estimating the best value of the regularization parameter λ adaptively, and we discuss an alternate iteration method for selecting p and λ . We perform experiments, which demonstrates that the proposed regularization nonconvex optimization method can outperform the convex optimization method and generate higher quality images.

  11. Adapting smartphones for low-cost optical medical imaging

    NASA Astrophysics Data System (ADS)

    Pratavieira, Sebastião.; Vollet-Filho, José D.; Carbinatto, Fernanda M.; Blanco, Kate; Inada, Natalia M.; Bagnato, Vanderlei S.; Kurachi, Cristina

    2015-06-01

    Optical images have been used in several medical situations to improve diagnosis of lesions or to monitor treatments. However, most systems employ expensive scientific (CCD or CMOS) cameras and need computers to display and save the images, usually resulting in a high final cost for the system. Additionally, this sort of apparatus operation usually becomes more complex, requiring more and more specialized technical knowledge from the operator. Currently, the number of people using smartphone-like devices with built-in high quality cameras is increasing, which might allow using such devices as an efficient, lower cost, portable imaging system for medical applications. Thus, we aim to develop methods of adaptation of those devices to optical medical imaging techniques, such as fluorescence. Particularly, smartphones covers were adapted to connect a smartphone-like device to widefield fluorescence imaging systems. These systems were used to detect lesions in different tissues, such as cervix and mouth/throat mucosa, and to monitor ALA-induced protoporphyrin-IX formation for photodynamic treatment of Cervical Intraepithelial Neoplasia. This approach may contribute significantly to low-cost, portable and simple clinical optical imaging collection.

  12. Optimal imaging with adaptive mesh refinement in electrical impedance tomography.

    PubMed

    Molinari, Marc; Blott, Barry H; Cox, Simon J; Daniell, Geoffrey J

    2002-02-01

    In non-linear electrical impedance tomography the goodness of fit of the trial images is assessed by the well-established statistical chi2 criterion applied to the measured and predicted datasets. Further selection from the range of images that fit the data is effected by imposing an explicit constraint on the form of the image, such as the minimization of the image gradients. In particular, the logarithm of the image gradients is chosen so that conductive and resistive deviations are treated in the same way. In this paper we introduce the idea of adaptive mesh refinement to the 2D problem so that the local scale of the mesh is always matched to the scale of the image structures. This improves the reconstruction resolution so that the image constraint adopted dominates and is not perturbed by the mesh discretization. The avoidance of unnecessary mesh elements optimizes the speed of reconstruction without degrading the resulting images. Starting with a mesh scale length of the order of the electrode separation it is shown that, for data obtained at presently achievable signal-to-noise ratios of 60 to 80 dB, one or two refinement stages are sufficient to generate high quality images.

  13. A wavelet packet adaptive filtering algorithm for enhancing manatee vocalizations.

    PubMed

    Gur, M Berke; Niezrecki, Christopher

    2011-04-01

    Approximately a quarter of all West Indian manatee (Trichechus manatus latirostris) mortalities are attributed to collisions with watercraft. A boater warning system based on the passive acoustic detection of manatee vocalizations is one possible solution to reduce manatee-watercraft collisions. The success of such a warning system depends on effective enhancement of the vocalization signals in the presence of high levels of background noise, in particular, noise emitted from watercraft. Recent research has indicated that wavelet domain pre-processing of the noisy vocalizations is capable of significantly improving the detection ranges of passive acoustic vocalization detectors. In this paper, an adaptive denoising procedure, implemented on the wavelet packet transform coefficients obtained from the noisy vocalization signals, is investigated. The proposed denoising algorithm is shown to improve the manatee detection ranges by a factor ranging from two (minimum) to sixteen (maximum) compared to high-pass filtering alone, when evaluated using real manatee vocalization and background noise signals of varying signal-to-noise ratios (SNR). Furthermore, the proposed method is also shown to outperform a previously suggested feedback adaptive line enhancer (FALE) filter on average 3.4 dB in terms of noise suppression and 0.6 dB in terms of waveform preservation.

  14. A wavelet packet adaptive filtering algorithm for enhancing manatee vocalizations.

    PubMed

    Gur, M Berke; Niezrecki, Christopher

    2011-04-01

    Approximately a quarter of all West Indian manatee (Trichechus manatus latirostris) mortalities are attributed to collisions with watercraft. A boater warning system based on the passive acoustic detection of manatee vocalizations is one possible solution to reduce manatee-watercraft collisions. The success of such a warning system depends on effective enhancement of the vocalization signals in the presence of high levels of background noise, in particular, noise emitted from watercraft. Recent research has indicated that wavelet domain pre-processing of the noisy vocalizations is capable of significantly improving the detection ranges of passive acoustic vocalization detectors. In this paper, an adaptive denoising procedure, implemented on the wavelet packet transform coefficients obtained from the noisy vocalization signals, is investigated. The proposed denoising algorithm is shown to improve the manatee detection ranges by a factor ranging from two (minimum) to sixteen (maximum) compared to high-pass filtering alone, when evaluated using real manatee vocalization and background noise signals of varying signal-to-noise ratios (SNR). Furthermore, the proposed method is also shown to outperform a previously suggested feedback adaptive line enhancer (FALE) filter on average 3.4 dB in terms of noise suppression and 0.6 dB in terms of waveform preservation. PMID:21476661

  15. Efficient text segmentation and adaptive color error diffusion for text enhancement

    NASA Astrophysics Data System (ADS)

    Kwon, Jae-Hyun; Park, Tae-Yong; Kim, Yun-Tae; Cho, Yang-Ho; Ha, Yeong-Ho

    2005-01-01

    This paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, then the MGD values are filled within a local window to merge text segments. If the value is above a threshold, the pixel is considered as potential text. Isolated segments are then eliminated in a non-text region filtering process. After the text segmentation, a conventional error diffusion method is applied to the background, while edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) then prevents the printing of successive dots around the text region boundaries. The method is extended to halftone color images to sharpen the text regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. However, edge enhancement unfortunately produces color distortion, as edge enhancement and color difference are trade-offs. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, an additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. In experiments, the text of a scanned image was sharper when using the proposed algorithm than with conventional error diffusion without changing the background.

  16. Efficient text segmentation and adaptive color error diffusion for text enhancement

    NASA Astrophysics Data System (ADS)

    Kwon, Jae-Hyun; Park, Tae-Yong; Kim, Yun-Tae; Cho, Yang-Ho; Ha, Yeong-Ho

    2004-12-01

    This paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, then the MGD values are filled within a local window to merge text segments. If the value is above a threshold, the pixel is considered as potential text. Isolated segments are then eliminated in a non-text region filtering process. After the text segmentation, a conventional error diffusion method is applied to the background, while edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) then prevents the printing of successive dots around the text region boundaries. The method is extended to halftone color images to sharpen the text regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. However, edge enhancement unfortunately produces color distortion, as edge enhancement and color difference are trade-offs. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, an additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. In experiments, the text of a scanned image was sharper when using the proposed algorithm than with conventional error diffusion without changing the background.

  17. Enhancing retinal images by nonlinear registration

    NASA Astrophysics Data System (ADS)

    Molodij, G.; Ribak, E. N.; Glanc, M.; Chenegros, G.

    2015-05-01

    Being able to image the human retina in high resolution opens a new era in many important fields, such as pharmacological research for retinal diseases, researches in human cognition, nervous system, metabolism and blood stream, to name a few. In this paper, we propose to share the knowledge acquired in the fields of optics and imaging in solar astrophysics in order to improve the retinal imaging in the perspective to perform a medical diagnosis. The main purpose would be to assist health care practitioners by enhancing the spatial resolution of the retinal images and increase the level of confidence of the abnormal feature detection. We apply a nonlinear registration method using local correlation tracking to increase the field of view and follow structure evolutions using correlation techniques borrowed from solar astronomy technique expertise. Another purpose is to define the tracer of movements after analyzing local correlations to follow the proper motions of an image from one moment to another, such as changes in optical flows that would be of high interest in a medical diagnosis.

  18. Enhancement and quality control of GOES images

    NASA Astrophysics Data System (ADS)

    Jentoft-Nilsen, Marit; Palaniappan, Kannappan; Hasler, A. Frederick; Chesters, Dennis

    1996-10-01

    The new generation of Geostationary Operational Environmental Satellites (GOES) have an imager instrument with five multispectral bands of high spatial resolution,and very high dynamic range radiance measurements with 10-bit precision. A wide variety of environmental processes can be observed at unprecedented time scales using the new imager instrument. Quality assurance and feedback to the GOES project office is performed using rapid animation at high magnification, examining differences between successive frames, and applying radiometric and geometric correction algorithms. Missing or corrupted scanline data occur unpredictably due to noise in the ground based receiving system. Smooth high resolution noise-free animations can be recovered using automatic techniques even from scanline scratches affecting more than 25 percent of the dataset. Radiometric correction using the local solar zenith angle was applied to the visible channel to compensate for time- of-day illumination variations to produce gain-compensated movies that appear well-lit from dawn to dusk and extend the interval of useful image observations by more than two hours. A time series of brightness histograms displays some subtle quality control problems in the GOES channels related to rebinning of the radiance measurements. The human visual system is sensitive to only about half of the measured 10- bit dynamic range in intensity variations, at a given point in a monochrome image. In order to effectively use the additional bits of precision and handle the high data rate, new enhancement techniques and visualization tools were developed. We have implemented interactive image enhancement techniques to selectively emphasize different subranges of the 10-bits of intensity levels. Improving navigational accuracy using registration techniques and geometric correction of scanline interleaving errors is a more difficult problem that is currently being investigated.

  19. An adaptive optics imaging system designed for clinical use.

    PubMed

    Zhang, Jie; Yang, Qiang; Saito, Kenichi; Nozato, Koji; Williams, David R; Rossi, Ethan A

    2015-06-01

    Here we demonstrate a new imaging system that addresses several major problems limiting the clinical utility of conventional adaptive optics scanning light ophthalmoscopy (AOSLO), including its small field of view (FOV), reliance on patient fixation for targeting imaging, and substantial post-processing time. We previously showed an efficient image based eye tracking method for real-time optical stabilization and image registration in AOSLO. However, in patients with poor fixation, eye motion causes the FOV to drift substantially, causing this approach to fail. We solve that problem here by tracking eye motion at multiple spatial scales simultaneously by optically and electronically integrating a wide FOV SLO (WFSLO) with an AOSLO. This multi-scale approach, implemented with fast tip/tilt mirrors, has a large stabilization range of ± 5.6°. Our method consists of three stages implemented in parallel: 1) coarse optical stabilization driven by a WFSLO image, 2) fine optical stabilization driven by an AOSLO image, and 3) sub-pixel digital registration of the AOSLO image. We evaluated system performance in normal eyes and diseased eyes with poor fixation. Residual image motion with incremental compensation after each stage was: 1) ~2-3 arc minutes, (arcmin) 2) ~0.5-0.8 arcmin and, 3) ~0.05-0.07 arcmin, for normal eyes. Performance in eyes with poor fixation was: 1) ~3-5 arcmin, 2) ~0.7-1.1 arcmin and 3) ~0.07-0.14 arcmin. We demonstrate that this system is capable of reducing image motion by a factor of ~400, on average. This new optical design provides additional benefits for clinical imaging, including a steering subsystem for AOSLO that can be guided by the WFSLO to target specific regions of interest such as retinal pathology and real-time averaging of registered images to eliminate image post-processing.

  20. An adaptive optics imaging system designed for clinical use.

    PubMed

    Zhang, Jie; Yang, Qiang; Saito, Kenichi; Nozato, Koji; Williams, David R; Rossi, Ethan A

    2015-06-01

    Here we demonstrate a new imaging system that addresses several major problems limiting the clinical utility of conventional adaptive optics scanning light ophthalmoscopy (AOSLO), including its small field of view (FOV), reliance on patient fixation for targeting imaging, and substantial post-processing time. We previously showed an efficient image based eye tracking method for real-time optical stabilization and image registration in AOSLO. However, in patients with poor fixation, eye motion causes the FOV to drift substantially, causing this approach to fail. We solve that problem here by tracking eye motion at multiple spatial scales simultaneously by optically and electronically integrating a wide FOV SLO (WFSLO) with an AOSLO. This multi-scale approach, implemented with fast tip/tilt mirrors, has a large stabilization range of ± 5.6°. Our method consists of three stages implemented in parallel: 1) coarse optical stabilization driven by a WFSLO image, 2) fine optical stabilization driven by an AOSLO image, and 3) sub-pixel digital registration of the AOSLO image. We evaluated system performance in normal eyes and diseased eyes with poor fixation. Residual image motion with incremental compensation after each stage was: 1) ~2-3 arc minutes, (arcmin) 2) ~0.5-0.8 arcmin and, 3) ~0.05-0.07 arcmin, for normal eyes. Performance in eyes with poor fixation was: 1) ~3-5 arcmin, 2) ~0.7-1.1 arcmin and 3) ~0.07-0.14 arcmin. We demonstrate that this system is capable of reducing image motion by a factor of ~400, on average. This new optical design provides additional benefits for clinical imaging, including a steering subsystem for AOSLO that can be guided by the WFSLO to target specific regions of interest such as retinal pathology and real-time averaging of registered images to eliminate image post-processing. PMID:26114033

  1. Modified Sigmoid Function Based Gray Scale Image Contrast Enhancement Using Particle Swarm Optimization

    NASA Astrophysics Data System (ADS)

    Verma, Harish Kumar; Pal, Sandeep

    2016-06-01

    The main objective of an image enhancement is to improve eminence by maximizing the information content in the test image. Conventional contrast enhancement techniques either often fails to produce reasonable results for a broad variety of low-contrast and high contrast images, or cannot be automatically applied to different images, because they are parameters dependent. Hence this paper introduces a novel hybrid image enhancement approach by taking both the local and global information of an image. In the present work, sigmoid function is being modified on the basis of contrast of the images. The gray image enhancement problem is treated as nonlinear optimization problem with several constraints and solved by particle swarm optimization. The entropy and edge information is included in the objective function as quality measure of an image. The effectiveness of modified sigmoid function based enhancement over conventional methods namely linear contrast stretching, histogram equalization, and adaptive histogram equalization are better revealed by the enhanced images and further validated by statistical analysis of these images.

  2. Robust image reconstruction enhancement based on Gaussian mixture model estimation

    NASA Astrophysics Data System (ADS)

    Zhao, Fan; Zhao, Jian; Han, Xizhen; Wang, He; Liu, Bochao

    2016-03-01

    The low quality of an image is often characterized by low contrast and blurred edge details. Gradients have a direct relationship with image edge details. More specifically, the larger the gradients, the clearer the image details become. Robust image reconstruction enhancement based on Gaussian mixture model estimation is proposed here. First, image is transformed to its gradient domain, obtaining the gradient histogram. Second, the gradient histogram is estimated and extended using a Gaussian mixture model, and the predetermined function is constructed. Then, using histogram specification technology, the gradient field is enhanced with the constraint of the predetermined function. Finally, a matrix sine transform-based method is applied to reconstruct the enhanced image from the enhanced gradient field. Experimental results show that the proposed algorithm can effectively enhance different types of images such as medical image, aerial image, and visible image, providing high-quality image information for high-level processing.

  3. Wideband enhancement of television images for people with visual impairments.

    PubMed

    Peli, Eli; Kim, Jeonghoon; Yitzhaky, Yitzhak; Goldstein, Robert B; Woods, Russell L

    2004-06-01

    Wideband enhancement was implemented by detecting visually relevant edge and bar features in an image to produce a bipolar contour map. The addition of these contours to the original image resulted in increased local contrast of these features and an increase in the spatial bandwidth of the image. Testing with static television images revealed that visually impaired patients (n = 35) could distinguish the enhanced images and preferred them over the original images (and degraded images). Most patients preferred a moderate level of wideband enhancement, since they preferred natural-looking images and rejected visible artifacts of the enhancement. Comparison of the enhanced images with the originals revealed that the improvement in the perceived image quality was significant for only 22% of the patients. Possible reasons for the limited increase in perceived image quality are discussed, and improvements are suggested. PMID:15191173

  4. Widefield multiphoton microscopy with image-based adaptive optics

    NASA Astrophysics Data System (ADS)

    Chang, C.-Y.; Cheng, L.-C.; Su, H.-W.; Yen, W.-C.; Chen, S.-J.

    2012-10-01

    Unlike conventional multiphoton microscopy according to pixel by pixel point scanning, a widefield multiphoton microscope based on spatiotemporal focusing has been developed to provide fast optical sectioning images at a frame rate over 100 Hz. In order to overcome the aberrations of the widefield multiphoton microscope and the wavefront distortion from turbid biospecimens, an image-based adaptive optics system (AOS) was integrated. The feedback control signal of the AOS was acquired according to locally maximize image intensity, which were provided by the widefield multiphoton excited microscope, by using a hill climbing algorithm. Then, the control signal was utilized to drive a deformable mirror in such a way as to eliminate the aberration and distortion. A R6G-doped PMMA thin film is also increased by 3.7-fold. Furthermore, the TPEF image quality of 1 μm fluorescent beads sealed in agarose gel at different depths is improved.

  5. Bio-inspired color image enhancement model

    NASA Astrophysics Data System (ADS)

    Zheng, Yufeng

    2009-05-01

    Human being can perceive natural scenes very well under various illumination conditions. Partial reasons are due to the contrast enhancement of center/surround networks and opponent analysis on the human retina. In this paper, we propose an image enhancement model to simulate the color processes in the human retina. Specifically, there are two center/surround layers, bipolar/horizontal and ganglion/amacrine; and four color opponents, red (R), green (G), blue (B), and yellow (Y). The central cell (bipolar or ganglion) takes the surrounding information from one or several horizontal or amacrine cells; and bipolar and ganglion both have ON and OFF sub-types. For example, a +R/-G bipolar (red-center- ON/green-surround-OFF) will be excited if only the center is illuminated, or inhibited if only the surroundings (bipolars) are illuminated, or stay neutral if both center and surroundings are illuminated. Likewise, other two color opponents with ON-center/OFF-surround, +G/-R and +B/-Y, follow the same rules. The yellow (Y) channel can be obtained by averaging red and green channels. On the other hand, OFF-center/ON-surround bipolars (i.e., -R/+G and -G/+R, but no - B/+Y) are inhibited when the center is illuminated. An ON-bipolar (or OFF-bipolar) only transfers signals to an ONganglion (or OFF-ganglion), where amacrines provide surrounding information. Ganglion cells have strong spatiotemporal responses to moving objects. In our proposed enhancement model, the surrounding information is obtained using weighted average of neighborhood; excited or inhibited can be implemented with pixel intensity increase or decrease according to a linear or nonlinear response; and center/surround excitations are decided by comparing their intensities. A difference of Gaussian (DOG) model is used to simulate the ganglion differential response. Experimental results using natural scenery pictures proved that, the proposed image enhancement model by simulating the two-layer center

  6. New CCD imagers for adaptive optics wavefront sensors

    NASA Astrophysics Data System (ADS)

    Schuette, Daniel R.; Reich, Robert K.; Prigozhin, Ilya; Burke, Barry E.; Johnson, Robert

    2014-08-01

    We report on two recently developed charge-coupled devices (CCDs) for adaptive optics wavefront sensing, both designed to provide exceptional sensitivity (low noise and high quantum efficiency) in high-frame-rate low-latency readout applications. The first imager, the CCID75, is a back-illuminated 16-port 160×160-pixel CCD that has been demonstrated to operate at frame rates above 1,300 fps with noise of < 3 e-. We will describe the architecture of this CCD that enables this level of performance, present and discuss characterization data, and review additional design features that enable unique operating modes for adaptive optics wavefront sensing. We will also present an architectural overview and initial characterization data of a recently designed variation on the CCID75 architecture, the CCID82, which incorporates an electronic shutter to support adaptive optics using Rayleigh beacons.

  7. Adaptive registration of diffusion tensor images on lie groups

    NASA Astrophysics Data System (ADS)

    Liu, Wei; Chen, LeiTing; Cai, HongBin; Qiu, Hang; Fei, Nanxi

    2016-08-01

    With diffusion tensor imaging (DTI), more exquisite information on tissue microstructure is provided for medical image processing. In this paper, we present a locally adaptive topology preserving method for DTI registration on Lie groups. The method aims to obtain more plausible diffeomorphisms for spatial transformations via accurate approximation for the local tangent space on the Lie group manifold. In order to capture an exact geometric structure of the Lie group, the local linear approximation is efficiently optimized by using the adaptive selection of the local neighborhood sizes on the given set of data points. Furthermore, numerical comparative experiments are conducted on both synthetic data and real DTI data to demonstrate that the proposed method yields a higher degree of topology preservation on a dense deformation tensor field while improving the registration accuracy.

  8. Haar wavelet processor for adaptive on-line image compression

    NASA Astrophysics Data System (ADS)

    Diaz, F. Javier; Buron, Angel M.; Solana, Jose M.

    2005-06-01

    An image coding processing scheme based on a variant of the Haar Wavelet Transform that uses only addition and subtraction is presented. After computing the transform, the selection and coding of the coefficients is performed using a methodology optimized to attain the lowest hardware implementation complexity. Coefficients are sorted in groups according to the number of pixels used in their computing. The idea behind it is to use a different threshold for each group of coefficients; these thresholds are obtained recurrently from an initial one. Parameter values used to achieve the desired compression level are established "on-line", adapting their values to each image, which leads to an improvement in the quality obtained for a preset compression level. Despite its adaptive characteristic, the coding scheme presented leads to a hardware implementation of markedly low circuit complexity. The compression reached for images of 512x512 pixels (256 grey levels) is over 22:1 (~0.4 bits/pixel) with a rmse of 8-10%. An image processor (excluding memory) prototype designed to compute the proposed transform has been implemented using FPGA chips. The processor for images of 256x256 pixels has been implemented using only one general-purpose low-cost FPGA chip, thus proving the design reliability and its relative simplicity.

  9. Tone reproduction for high-dynamic range imaging based on adaptive filtering

    NASA Astrophysics Data System (ADS)

    Ha, Changwoo; Lee, Joohyun; Jeong, Jechang

    2014-03-01

    A tone reproduction algorithm with enhanced contrast of high-dynamic range images on conventional low-dynamic range display devices is presented. The proposed algorithm consists mainly of block-based parameter estimation, a characteristic-based luminance adjustment, and an adaptive Gaussian filter using minimum description length. Instead of relying only on the reduction of the dynamic range, a characteristic-based luminance adjustment process modifies the luminance values. The Gaussian-filtered luminance value is obtained from appropriate value of variance, and the contrast is then enhanced through the use of a relation between the adjusted luminance and Gaussian-filtered luminance values. In the final tone-reproduction process, the proposed algorithm combines color and luminance components in order to preserve the color consistency. The experimental results demonstrate that the proposed algorithm achieves a good subjective quality while enhancing the contrast of the image details.

  10. Adaptive Tensor-Based Principal Component Analysis for Low-Dose CT Image Denoising

    PubMed Central

    Ai, Danni; Yang, Jian; Fan, Jingfan; Cong, Weijian; Wang, Yongtian

    2015-01-01

    Computed tomography (CT) has a revolutionized diagnostic radiology but involves large radiation doses that directly impact image quality. In this paper, we propose adaptive tensor-based principal component analysis (AT-PCA) algorithm for low-dose CT image denoising. Pixels in the image are presented by their nearby neighbors, and are modeled as a patch. Adaptive searching windows are calculated to find similar patches as training groups for further processing. Tensor-based PCA is used to obtain transformation matrices, and coefficients are sequentially shrunk by the linear minimum mean square error. Reconstructed patches are obtained, and a denoised image is finally achieved by aggregating all of these patches. The experimental results of the standard test image show that the best results are obtained with two denoising rounds according to six quantitative measures. For the experiment on the clinical images, the proposed AT-PCA method can suppress the noise, enhance the edge, and improve the image quality more effectively than NLM and KSVD denoising methods. PMID:25993566

  11. Resolution enhancement in nonlinear photoacoustic imaging

    SciTech Connect

    Goy, Alexandre S.; Fleischer, Jason W.

    2015-11-23

    Nonlinear processes can be exploited to gain access to more information than is possible in the linear regime. Nonlinearity modifies the spectra of the excitation signals through harmonic generation, frequency mixing, and spectral shifting, so that features originally outside the detector range can be detected. Here, we present an experimental study of resolution enhancement for photoacoustic imaging of thin metal layers immersed in water. In this case, there is a threshold in the excitation below which no acoustic signal is detected. Above threshold, the nonlinearity reduces the width of the active area of the excitation beam, resulting in a narrower absorption region and thus improved spatial resolution. This gain is limited only by noise, as the active area of the excitation can be arbitrarily reduced when the fluence becomes closer to the threshold. Here, we demonstrate a two-fold improvement in resolution and quantify the image quality as the excitation fluence goes through threshold.

  12. Resolution enhancement in nonlinear photoacoustic imaging

    NASA Astrophysics Data System (ADS)

    Goy, Alexandre S.; Fleischer, Jason W.

    2015-11-01

    Nonlinear processes can be exploited to gain access to more information than is possible in the linear regime. Nonlinearity modifies the spectra of the excitation signals through harmonic generation, frequency mixing, and spectral shifting, so that features originally outside the detector range can be detected. Here, we present an experimental study of resolution enhancement for photoacoustic imaging of thin metal layers immersed in water. In this case, there is a threshold in the excitation below which no acoustic signal is detected. Above threshold, the nonlinearity reduces the width of the active area of the excitation beam, resulting in a narrower absorption region and thus improved spatial resolution. This gain is limited only by noise, as the active area of the excitation can be arbitrarily reduced when the fluence becomes closer to the threshold. Here, we demonstrate a two-fold improvement in resolution and quantify the image quality as the excitation fluence goes through threshold.

  13. Enhanced flexural wave sensing by adaptive gradient-index metamaterials

    NASA Astrophysics Data System (ADS)

    Chen, Y. Y.; Zhu, R.; Barnhart, M. V.; Huang, G. L.

    2016-10-01

    Increasing sensitivity and signal to noise ratios of conventional wave sensors is an interesting topic in structural health monitoring, medical imaging, aerospace and nuclear instrumentation. Here, we report the concept of a gradient piezoelectric self-sensing system by integrating shunting circuitry into conventional sensors. By tuning circuit elements properly, both the quality and quantity of the flexural wave measurement data can be significantly increased for new adaptive sensing applications. Through analytical, numerical and experimental studies, we demonstrate that a metamaterial-based sensing system (MBSS) with gradient bending stiffness can be designed by connecting gradient negative capacitance circuits to an array of piezoelectric patches (sensors). Furthermore, we demonstrate that the proposed system can achieve more than two orders of magnitude amplification of flexural wave signals to overcome the detection limit. This research encompasses fundamental advancements in the MBSS with improved performance and functionalities, and will yield significant advances for a range of applications.

  14. Enhanced flexural wave sensing by adaptive gradient-index metamaterials

    PubMed Central

    Chen, Y. Y.; Zhu, R.; Barnhart, M. V.; Huang, G. L.

    2016-01-01

    Increasing sensitivity and signal to noise ratios of conventional wave sensors is an interesting topic in structural health monitoring, medical imaging, aerospace and nuclear instrumentation. Here, we report the concept of a gradient piezoelectric self-sensing system by integrating shunting circuitry into conventional sensors. By tuning circuit elements properly, both the quality and quantity of the flexural wave measurement data can be significantly increased for new adaptive sensing applications. Through analytical, numerical and experimental studies, we demonstrate that a metamaterial-based sensing system (MBSS) with gradient bending stiffness can be designed by connecting gradient negative capacitance circuits to an array of piezoelectric patches (sensors). Furthermore, we demonstrate that the proposed system can achieve more than two orders of magnitude amplification of flexural wave signals to overcome the detection limit. This research encompasses fundamental advancements in the MBSS with improved performance and functionalities, and will yield significant advances for a range of applications. PMID:27748379

  15. Multi-scale image enhancement using a second derivative-like measure of contrast

    NASA Astrophysics Data System (ADS)

    Nercessian, Shahan; Agaian, Sos S.; Panetta, Karen A.

    2012-03-01

    Image enhancement algorithms attempt to improve the visual quality of images for human or machine perception. Most direct multi-scale image enhancement methods are based on enhancing either absolute intensity changes or the Weber contrast at each scale, and have the advantage that the visual contrast is enhanced in a controlled manner. However, the human visual system is not adapted to absolute intensity changes, while the Weber contrast is unstable for small values of background luminance and potentially unsuitable for complex image patterns. The Michelson contrast measure is a bounded measure of contrast, but its expression does not allow a straightforward direct image enhancement formulation. Recently, a second derivative-like measure of contrast has been used to assess the performance of image enhancement algorithms. This measure is a Michelson-like contrast measure for which a direct image enhancement algorithm can be formulated. Accordingly, we propose a new direct multi-scale image enhancement algorithm based on the SDME in this paper. Experimental results illustrate the potential benefits of the proposed algorithm.

  16. Image enhancement with polymer grid triode arrays

    SciTech Connect

    Heeger, A.J.; Heeger, D.J.; Langan, J.

    1995-12-08

    An array of polymer grid triodes connected by a common grid functions as a {open_quotes}plastic retina,{close_quotes} providing local contrast gain control for image enhancement. This simple device, made from layers of conducting polymers, functions as an active resistive network that performs center-surround filtering. The polymer grid triode array with common grid is a continuous analog of the discrete approach of Mead, with a variety of fabrication advantages and significant savings in area within the unit cell of each pixel. 6 refs., 4 figs.

  17. Integration of AdaptiSPECT, a small-animal adaptive SPECT imaging system

    PubMed Central

    Chaix, Cécile; Kovalsky, Stephen; Kosmider, Matthew; Barrett, Harrison H.; Furenlid, Lars R.

    2015-01-01

    AdaptiSPECT is a pre-clinical adaptive SPECT imaging system under final development at the Center for Gamma-ray Imaging. The system incorporates multiple adaptive features: an adaptive aperture, 16 detectors mounted on translational stages, and the ability to switch between a non-multiplexed and a multiplexed imaging configuration. In this paper, we review the design of AdaptiSPECT and its adaptive features. We then describe the on-going integration of the imaging system. PMID:26347197

  18. Multimodal Medical Image Fusion by Adaptive Manifold Filter.

    PubMed

    Geng, Peng; Liu, Shuaiqi; Zhuang, Shanna

    2015-01-01

    Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. The modified local contrast information is proposed to fuse multimodal medical images. Firstly, the adaptive manifold filter is introduced into filtering source images as the low-frequency part in the modified local contrast. Secondly, the modified spatial frequency of the source images is adopted as the high-frequency part in the modified local contrast. Finally, the pixel with larger modified local contrast is selected into the fused image. The presented scheme outperforms the guided filter method in spatial domain, the dual-tree complex wavelet transform-based method, nonsubsampled contourlet transform-based method, and four classic fusion methods in terms of visual quality. Furthermore, the mutual information values by the presented method are averagely 55%, 41%, and 62% higher than the three methods and those values of edge based similarity measure by the presented method are averagely 13%, 33%, and 14% higher than the three methods for the six pairs of source images. PMID:26664494

  19. Adaptive SPECT imaging with crossed-slit apertures

    PubMed Central

    Durko, Heather L.; Furenlid, Lars R.

    2015-01-01

    Preclinical single-photon emission computed tomography (SPECT) is an essential tool for studying the progression, response to treatment, and physiological changes in small animal models of human disease. The wide range of imaging applications is often limited by the static design of many preclinical SPECT systems. We have developed a prototype imaging system that replaces the standard static pinhole aperture with two sets of movable, keel-edged copper-tungsten blades configured as crossed (skewed) slits. These apertures can be positioned independently between the object and detector, producing a continuum of imaging configurations in which the axial and transaxial magnifications are not constrained to be equal. We incorporated a megapixel silicon double-sided strip detector to permit ultrahigh-resolution imaging. We describe the configuration of the adjustable slit aperture imaging system and discuss its application toward adaptive imaging, and reconstruction techniques using an accurate imaging forward model, a novel geometric calibration technique, and a GPU-based ultra-high-resolution reconstruction code. PMID:26190884

  20. Radiological image presentation requires consideration of human adaptation characteristics

    NASA Astrophysics Data System (ADS)

    O'Connell, N. M.; Toomey, R. J.; McEntee, M.; Ryan, J.; Stowe, J.; Adams, A.; Brennan, P. C.

    2008-03-01

    Visualisation of anatomical or pathological image data is highly dependent on the eye's ability to discriminate between image brightnesses and this is best achieved when these data are presented to the viewer at luminance levels to which the eye is adapted. Current ambient light recommendations are often linked to overall monitor luminance but this relies on specific regions of interest matching overall monitor brightness. The current work investigates the luminances of specific regions of interest within three image-types: postero-anterior (PA) chest; PA wrist; computerised tomography (CT) of the head. Luminance levels were measured within the hilar region and peripheral lung distal radius and supra-ventricular grey matter. For each image type average monitor luminances were calculated with a calibrated photometer at ambient light levels of 0, 100 and 400 lux. Thirty samples of each image-type were employed, resulting in a total of over 6,000 measurements. Results demonstrate that average monitor luminances varied from clinically-significant values by up to a factor of 4, 2 and 6 for chest, wrist and CT head images respectively. Values for the thoracic hilum and wrist were higher and for the peripheral lung and CT brain lower than overall monitor levels. The ambient light level had no impact on the results. The results demonstrate that clinically important radiological information for common radiological examinations is not being presented to the viewer in a way that facilitates optimised visual adaptation and subsequent interpretation. The importance of image-processing algorithms focussing on clinically-significant anatomical regions instead of radiographic projections is highlighted.

  1. A new method for fusion, denoising and enhancement of x-ray images retrieved from Talbot-Lau grating interferometry

    NASA Astrophysics Data System (ADS)

    Scholkmann, Felix; Revol, Vincent; Kaufmann, Rolf; Baronowski, Heidrun; Kottler, Christian

    2014-03-01

    This paper introduces a new image denoising, fusion and enhancement framework for combining and optimal visualization of x-ray attenuation contrast (AC), differential phase contrast (DPC) and dark-field contrast (DFC) images retrieved from x-ray Talbot-Lau grating interferometry. The new image fusion framework comprises three steps: (i) denoising each input image (AC, DPC and DFC) through adaptive Wiener filtering, (ii) performing a two-step image fusion process based on the shift-invariant wavelet transform, i.e. first fusing the AC with the DPC image and then fusing the resulting image with the DFC image, and finally (iii) enhancing the fused image to obtain a final image using adaptive histogram equalization, adaptive sharpening and contrast optimization. Application examples are presented for two biological objects (a human tooth and a cherry) and the proposed method is compared to two recently published AC/DPC/DFC image processing techniques. In conclusion, the new framework for the processing of AC, DPC and DFC allows the most relevant features of all three images to be combined in one image while reducing the noise and enhancing adaptively the relevant image features. The newly developed framework may be used in technical and medical applications.

  2. Enhancing topology adaptation in information-sharing social networks

    NASA Astrophysics Data System (ADS)

    Cimini, Giulio; Chen, Duanbing; Medo, Matúš; Lü, Linyuan; Zhang, Yi-Cheng; Zhou, Tao

    2012-04-01

    The advent of the Internet and World Wide Web has led to unprecedent growth of the information available. People usually face the information overload by following a limited number of sources which best fit their interests. It has thus become important to address issues like who gets followed and how to allow people to discover new and better information sources. In this paper we conduct an empirical analysis of different online social networking sites and draw inspiration from its results to present different source selection strategies in an adaptive model for social recommendation. We show that local search rules which enhance the typical topological features of real social communities give rise to network configurations that are globally optimal. These rules create networks which are effective in information diffusion and resemble structures resulting from real social systems.

  3. The application of image enhancement techniques to remote manipulator operation

    NASA Technical Reports Server (NTRS)

    Gonzalez, R. C.

    1974-01-01

    Methods of image enhancement which can be used by an operator who is not experienced with the mechanisms of enhancement to obtain satisfactory results were designed and implemented. Investigation of transformations which operate directly on the image domain resulted in a new technique of contrast enhancement. Transformations on the Fourier transform of the original image, including such techniques as homomorphic filtering, were also investigated. The methods of communication between the enhancement system and the computer operator were analyzed, and a language was developed for use in image enhancement. A working enhancement system was then created, and is included.

  4. Dynamic experiment design regularization approach to adaptive imaging with array radar/SAR sensor systems.

    PubMed

    Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart

    2011-01-01

    We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the "model-free" variational analysis (VA)-based image enhancement approach and the "model-based" descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations.

  5. Dynamic Experiment Design Regularization Approach to Adaptive Imaging with Array Radar/SAR Sensor Systems

    PubMed Central

    Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart

    2011-01-01

    We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the “model-free” variational analysis (VA)-based image enhancement approach and the “model-based” descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations. PMID:22163859

  6. Ultrasound harmonic enhanced imaging using eigenspace-based coherence factor.

    PubMed

    Guo, Wei; Wang, Yuanyuan; Yu, Jinhua

    2016-12-01

    Tissue harmonic imaging (THI) utilizes harmonic signals generating within the tissue as the result of nonlinear acoustic wave propagation. With inadequate transmitting acoustic energy, THI is incapable to detect the small objects since poor harmonic signals have been generated. In most cases, high transmission energy cannot be guaranteed because of the imaging safety issue or specific imaging modality such as the plane wave imaging (PWI). Discrimination of small point targets such as calcification, however, is particularly important in the ultrasound diagnosis. Few efforts have been made to pursue the THI with high resolution and good small target visibility at the same time. In this paper, we proposed a new eigenspace-based coherence factor (ESBCF) beamformer to solve this problem. A new kind of coherence factor (CF), named as ESBCF, is firstly proposed to detect the point targets. The detected region-of-interest (ROI) is then enhanced adaptively by using a newly developed beamforming method. The ESBCF combines the information from signal eigenspace and coherence factor by expanding the CF to the covariance matrix of signal. Analogous to the image processing but in the radio frequency (RF) data domain, the proposed method fully utilizes the information from the fundamental and harmonic components. The performance of the proposed method is demonstrated by simulation and phantom experiments. The improvement of the point contrast ratio (PCR) is 7.6dB in the simulated data, and 6.0dB in the phantom experiment. Thanks to the improved small point detection ability of the ESBCF, the proposed beamforming algorithm can enhance the PCR considerably and maintain the high resolution of the THI at the same time. PMID:27513207

  7. Fast Source Camera Identification Using Content Adaptive Guided Image Filter.

    PubMed

    Zeng, Hui; Kang, Xiangui

    2016-03-01

    Source camera identification (SCI) is an important topic in image forensics. One of the most effective fingerprints for linking an image to its source camera is the sensor pattern noise, which is estimated as the difference between the content and its denoised version. It is widely believed that the performance of the sensor-based SCI heavily relies on the denoising filter used. This study proposes a novel sensor-based SCI method using content adaptive guided image filter (CAGIF). Thanks to the low complexity nature of the CAGIF, the proposed method is much faster than the state-of-the-art methods, which is a big advantage considering the potential real-time application of SCI. Despite the advantage of speed, experimental results also show that the proposed method can achieve comparable or better performance than the state-of-the-art methods in terms of accuracy. PMID:27404627

  8. Computer Based Melanocytic and Nevus Image Enhancement and Segmentation

    PubMed Central

    Jamil, Uzma; Khalid, Shehzad; Abbas, Sarmad; Saleem, Kashif

    2016-01-01

    Digital dermoscopy aids dermatologists in monitoring potentially cancerous skin lesions. Melanoma is the 5th common form of skin cancer that is rare but the most dangerous. Melanoma is curable if it is detected at an early stage. Automated segmentation of cancerous lesion from normal skin is the most critical yet tricky part in computerized lesion detection and classification. The effectiveness and accuracy of lesion classification are critically dependent on the quality of lesion segmentation. In this paper, we have proposed a novel approach that can automatically preprocess the image and then segment the lesion. The system filters unwanted artifacts including hairs, gel, bubbles, and specular reflection. A novel approach is presented using the concept of wavelets for detection and inpainting the hairs present in the cancer images. The contrast of lesion with the skin is enhanced using adaptive sigmoidal function that takes care of the localized intensity distribution within a given lesion's images. We then present a segmentation approach to precisely segment the lesion from the background. The proposed approach is tested on the European database of dermoscopic images. Results are compared with the competitors to demonstrate the superiority of the suggested approach. PMID:27774454

  9. Adaptive codebook selection schemes for image classification in correlated channels

    NASA Astrophysics Data System (ADS)

    Hu, Chia Chang; Liu, Xiang Lian; Liu, Kuan-Fu

    2015-09-01

    The multiple-input multiple-output (MIMO) system with the use of transmit and receive antenna arrays achieves diversity and array gains via transmit beamforming. Due to the absence of full channel state information (CSI) at the transmitter, the transmit beamforming vector can be quantized at the receiver and sent back to the transmitter by a low-rate feedback channel, called limited feedback beamforming. One of the key roles of Vector Quantization (VQ) is how to generate a good codebook such that the distortion between the original image and the reconstructed image is the minimized. In this paper, a novel adaptive codebook selection scheme for image classification is proposed with taking both spatial and temporal correlation inherent in the channel into consideration. The new codebook selection algorithm is developed to select two codebooks from the discrete Fourier transform (DFT) codebook, the generalized Lloyd algorithm (GLA) codebook and the Grassmannian codebook to be combined and used as candidates of the original image and the reconstructed image for image transmission. The channel is estimated and divided into four regions based on the spatial and temporal correlation of the channel and an appropriate codebook is assigned to each region. The proposed method can efficiently reduce the required information of feedback under the spatially and temporally correlated channels, where each region is adaptively. Simulation results show that in the case of temporally and spatially correlated channels, the bit-error-rate (BER) performance can be improved substantially by the proposed algorithm compared to the one with only single codebook.

  10. Breast image feature learning with adaptive deconvolutional networks

    NASA Astrophysics Data System (ADS)

    Jamieson, Andrew R.; Drukker, Karen; Giger, Maryellen L.

    2012-03-01

    Feature extraction is a critical component of medical image analysis. Many computer-aided diagnosis approaches employ hand-designed, heuristic lesion extracted features. An alternative approach is to learn features directly from images. In this preliminary study, we explored the use of Adaptive Deconvolutional Networks (ADN) for learning high-level features in diagnostic breast mass lesion images with potential application to computer-aided diagnosis (CADx) and content-based image retrieval (CBIR). ADNs (Zeiler, et. al., 2011), are recently-proposed unsupervised, generative hierarchical models that decompose images via convolution sparse coding and max pooling. We trained the ADNs to learn multiple layers of representation for two breast image data sets on two different modalities (739 full field digital mammography (FFDM) and 2393 ultrasound images). Feature map calculations were accelerated by use of GPUs. Following Zeiler et. al., we applied the Spatial Pyramid Matching (SPM) kernel (Lazebnik, et. al., 2006) on the inferred feature maps and combined this with a linear support vector machine (SVM) classifier for the task of binary classification between cancer and non-cancer breast mass lesions. Non-linear, local structure preserving dimension reduction, Elastic Embedding (Carreira-Perpiñán, 2010), was then used to visualize the SPM kernel output in 2D and qualitatively inspect image relationships learned. Performance was found to be competitive with current CADx schemes that use human-designed features, e.g., achieving a 0.632+ bootstrap AUC (by case) of 0.83 [0.78, 0.89] for an ultrasound image set (1125 cases).

  11. An adaptive filtered back-projection for photoacoustic image reconstruction

    SciTech Connect

    Huang, He; Bustamante, Gilbert; Peterson, Ralph; Ye, Jing Yong

    2015-05-15

    Purpose: The purpose of this study is to develop an improved filtered-back-projection (FBP) algorithm for photoacoustic tomography (PAT), which allows image reconstruction with higher quality compared to images reconstructed through traditional algorithms. Methods: A rigorous expression of a weighting function has been derived directly from a photoacoustic wave equation and used as a ramp filter in Fourier domain. The authors’ new algorithm utilizes this weighting function to precisely calculate each photoacoustic signal’s contribution and then reconstructs the image based on the retarded potential generated from the photoacoustic sources. In addition, an adaptive criterion has been derived for selecting the cutoff frequency of a low pass filter. Two computational phantoms were created to test the algorithm. The first phantom contained five spheres with each sphere having different absorbances. The phantom was used to test the capability for correctly representing both the geometry and the relative absorbed energy in a planar measurement system. The authors also used another phantom containing absorbers of different sizes with overlapping geometry to evaluate the performance of the new method for complicated geometry. In addition, random noise background was added to the simulated data, which were obtained by using an arc-shaped array of 50 evenly distributed transducers that spanned 160° over a circle with a radius of 65 mm. A normalized factor between the neighbored transducers was applied for correcting measurement signals in PAT simulations. The authors assumed that the scanned object was mounted on a holder that rotated over the full 360° and the scans were set to a sampling rate of 20.48 MHz. Results: The authors have obtained reconstructed images of the computerized phantoms by utilizing the new FBP algorithm. From the reconstructed image of the first phantom, one can see that this new approach allows not only obtaining a sharp image but also showing

  12. An adaptive filtered back-projection for photoacoustic image reconstruction

    PubMed Central

    Huang, He; Bustamante, Gilbert; Peterson, Ralph; Ye, Jing Yong

    2015-01-01

    Purpose: The purpose of this study is to develop an improved filtered-back-projection (FBP) algorithm for photoacoustic tomography (PAT), which allows image reconstruction with higher quality compared to images reconstructed through traditional algorithms. Methods: A rigorous expression of a weighting function has been derived directly from a photoacoustic wave equation and used as a ramp filter in Fourier domain. The authors’ new algorithm utilizes this weighting function to precisely calculate each photoacoustic signal’s contribution and then reconstructs the image based on the retarded potential generated from the photoacoustic sources. In addition, an adaptive criterion has been derived for selecting the cutoff frequency of a low pass filter. Two computational phantoms were created to test the algorithm. The first phantom contained five spheres with each sphere having different absorbances. The phantom was used to test the capability for correctly representing both the geometry and the relative absorbed energy in a planar measurement system. The authors also used another phantom containing absorbers of different sizes with overlapping geometry to evaluate the performance of the new method for complicated geometry. In addition, random noise background was added to the simulated data, which were obtained by using an arc-shaped array of 50 evenly distributed transducers that spanned 160° over a circle with a radius of 65 mm. A normalized factor between the neighbored transducers was applied for correcting measurement signals in PAT simulations. The authors assumed that the scanned object was mounted on a holder that rotated over the full 360° and the scans were set to a sampling rate of 20.48 MHz. Results: The authors have obtained reconstructed images of the computerized phantoms by utilizing the new FBP algorithm. From the reconstructed image of the first phantom, one can see that this new approach allows not only obtaining a sharp image but also showing

  13. Two-color ghost imaging with enhanced angular resolving power

    SciTech Connect

    Karmakar, Sanjit; Shih, Yanhua

    2010-03-15

    This article reports an experimental demonstration on nondegenerate, two-color, biphoton ghost imaging which reproduced a ghost image with enhanced angular resolving power by means of a greater field of view compared with that of classical imaging. With the same imaging magnification, the enhanced angular resolving power and field of view compared with those of classical imaging are 1.25:1 and 1.16:1, respectively. The enhancement of angular resolving power depends on the ratio between the idler and the signal photon frequencies, and the enhancement of the field of view depends mainly on the same ratio and also on the distances of the object plane and the imaging lens from the two-photon source. This article also reports the possibility of reproducing a ghost image with the enhancement of the angular resolving power by means of a greater imaging amplification compared with that of classical imaging.

  14. Image enhancement by non-linear extrapolation in frequency space

    NASA Technical Reports Server (NTRS)

    Anderson, Charles H. (Inventor); Greenspan, Hayit K. (Inventor)

    1998-01-01

    An input image is enhanced to include spatial frequency components having frequencies higher than those in an input image. To this end, an edge map is generated from the input image using a high band pass filtering technique. An enhancing map is subsequently generated from the edge map, with the enhanced map having spatial frequencies exceeding an initial maximum spatial frequency of the input image. The enhanced map is generated by applying a non-linear operator to the edge map in a manner which preserves the phase transitions of the edges of the input image. The enhanced map is added to the input image to achieve a resulting image having spatial frequencies greater than those in the input image. Simplicity of computations and ease of implementation allow for image sharpening after enlargement and for real-time applications such as videophones, advanced definition television, zooming, and restoration of old motion pictures.

  15. Image-quality metrics for characterizing adaptive optics system performance.

    PubMed

    Brigantic, R T; Roggemann, M C; Bauer, K W; Welsh, B M

    1997-09-10

    Adaptive optics system (AOS) performance is a function of the system design, seeing conditions, and light level of the wave-front beacon. It is desirable to optimize the controllable parameters in an AOS to maximize some measure of performance. For this optimization to be useful, it is necessary that a set of image-quality metrics be developed that vary monotonically with the AOS performance under a wide variety of imaging environments. Accordingly, as conditions change, one can be confident that the computed metrics dictate appropriate system settings that will optimize performance. Three such candidate metrics are presented. The first is the Strehl ratio; the second is a novel metric that modifies the Strehl ratio by integration of the modulus of the average system optical transfer function to a noise-effective cutoff frequency at which some specified image spectrum signal-to-noise ratio level is attained; and the third is simply the cutoff frequency just mentioned. It is shown that all three metrics are correlated with the rms error (RMSE) between the measured image and the associated diffraction-limited image. Of these, the Strehl ratio and the modified Strehl ratio exhibit consistently high correlations with the RMSE across a broad range of conditions and system settings. Furthermore, under conditions that yield a constant average system optical transfer function, the modified Strehl ratio can still be used to delineate image quality, whereas the Strehl ratio cannot.

  16. Teaching People and Machines to Enhance Images

    NASA Astrophysics Data System (ADS)

    Berthouzoz, Floraine Sara Martianne

    tutorials based on their command-level structure. Sites such as tutorialized.com or good-tutorials.com collect tens of thousands of photo manipulation tutorials. These collections typically contain many different tutorials for the same task. For example, there are many different tutorials that describe how to recolor the hair of a person in an image. Learners often want to compare these tutorials to understand the different ways a task can be done. They may also want to identify common strategies that are used across tutorials for a variety of tasks. However, the large number of tutorials in these collections and their inconsistent formats can make it difficult for users to systematically explore and compare them. Current tutorial collections do not exploit the underlying command-level structure of tutorials, and to explore the collection users have to either page through long lists of tutorial titles or perform keyword searches on the natural language tutorial text. We present a new browsing interface to help learners navigate, explore and compare collections of photo manipulation tutorials based on their command-level structure. Our browser indexes tutorials by their commands, identifies common strategies within the tutorial collection, and highlights the similarities and differences between sets of tutorials that execute the same task. User feedback suggests that our interface is easy to understand and use, and that users find command-level browsing to be useful for exploring large tutorial collections. They strongly preferred to explore tutorial collections with our browser over keyword search. Finally, we present a framework for generating content-adaptive macros (programs) that can transfer complex photo manipulation procedures to new target images. After learners master a photo manipulation procedure, they often repeatedly apply it to multiple images. For example, they might routinely apply the same vignetting effect to all their photographs. This process can be very

  17. Adaptive geodesic transform for segmentation of vertebrae on CT images

    NASA Astrophysics Data System (ADS)

    Gaonkar, Bilwaj; Shu, Liao; Hermosillo, Gerardo; Zhan, Yiqiang

    2014-03-01

    Vertebral segmentation is a critical first step in any quantitative evaluation of vertebral pathology using CT images. This is especially challenging because bone marrow tissue has the same intensity profile as the muscle surrounding the bone. Thus simple methods such as thresholding or adaptive k-means fail to accurately segment vertebrae. While several other algorithms such as level sets may be used for segmentation any algorithm that is clinically deployable has to work in under a few seconds. To address these dual challenges we present here, a new algorithm based on the geodesic distance transform that is capable of segmenting the spinal vertebrae in under one second. To achieve this we extend the theory of the geodesic distance transforms proposed in1 to incorporate high level anatomical knowledge through adaptive weighting of image gradients. Such knowledge may be provided by the user directly or may be automatically generated by another algorithm. We incorporate information 'learnt' using a previously published machine learning algorithm2 to segment the L1 to L5 vertebrae. While we present a particular application here, the adaptive geodesic transform is a generic concept which can be applied to segmentation of other organs as well.

  18. in vivo laser speckle imaging by adaptive contrast computation for microvasculature assessment

    NASA Astrophysics Data System (ADS)

    Basak, Kausik; Dey, Goutam; Mahadevappa, Manjunatha; Mandal, Mahitosh; Dutta, Pranab Kumar

    2014-11-01

    Interference of light backscattered from a diffused surface leads to speckle formation in laser speckle imaging. These time integrated speckle patterns can be statistically analyzed to study the flow profile of moving scatterers. Simple speckle contrast analysis techniques have limited ability to distinguish thin structures due to presence of corrupting speckles. This paper presents a high resolution imaging technique by adaptive computation of contrast for laser speckle contrast analysis (adLASCA). Speckle images of retinal microvasculature in mice model are acquired during normal and reduced blood flow conditions. Initially, the speckle images are registered to compensate for movements, associated with heart beating and respiration. Adaptive computation is performed using local image statistics, estimated within a spatially moving window over successive time frames. Experimental evidence suggests that adLASCA outperforms other contrast analysis methods, substantiating significant improvement in contrast resolution. Fine vessels can be distinguished more efficiently with reduced fluctuations in contrast level. Quantitative performance of adLASCA is evaluated by computing standard deviation, corresponding to speckle fluctuations due to unwanted speckles. There is a significant reduction in standard deviation compared to other methods. Therefore, adLASCA can be used for enhancing microvasculature in high resolution perfusion imaging with reduced effect of corrupting speckles for effective assessment.

  19. An adaptive-optics scanning laser ophthalmoscope for imaging murine retinal microstructure

    NASA Astrophysics Data System (ADS)

    Alt, Clemens; Biss, David P.; Tajouri, Nadja; Jakobs, Tatjana C.; Lin, Charles P.

    2010-02-01

    In vivo retinal imaging is an outstanding tool to observe biological processes unfold in real-time. The ability to image microstructure in vivo can greatly enhance our understanding of function in retinal microanatomy under normal conditions and in disease. Transgenic mice are frequently used for mouse models of retinal diseases. However, commercially available retinal imaging instruments lack the optical resolution and spectral flexibility necessary to visualize detail comprehensively. We developed an adaptive optics scanning laser ophthalmoscope (AO-SLO) specifically for mouse eyes. Our SLO is a sensor-less adaptive optics system (no Shack Hartmann sensor) that employs a stochastic parallel gradient descent algorithm to modulate a deformable mirror, ultimately aiming to correct wavefront aberrations by optimizing confocal image sharpness. The resulting resolution allows detailed observation of retinal microstructure. The AO-SLO can resolve retinal microglia and their moving processes, demonstrating that microglia processes are highly motile, constantly probing their immediate environment. Similarly, retinal ganglion cells are imaged along with their axons and sprouting dendrites. Retinal blood vessels are imaged both using evans blue fluorescence and backscattering contrast.

  20. Digitally enhanced GLORIA images for petroleum exploration

    SciTech Connect

    Prindle, R.O. ); Lanz, K )

    1990-05-01

    This poster presentation graphically depicts the geological and structural information that can be derived from digitally enhanced Geological Long Range Inclined Asdic (GLORIA) sonar images. This presentation illustrates the advantages of scale enlargement as an interpreter's tool in an offshore area within the Eel River Basin, Northern California. Sonographs were produced from digital tapes originally collected for the exclusive economic zone (EEZ)-SCAN 1984 survey, which was published in the Atlas of the Western Conterminous US at a scale of 1:500,000. This scale is suitable for displaying regional offshore tectonic features but does not have the resolution required for detailed geological mapping necessary for petroleum exploration. Applications of digital enhancing techniques which utilize contrast stretching and assign false colors to wide-swath sonar imagery (approximately 40 km) with 50-m resolution enables the acquisition and interpretation of significantly more geological and structural data. This, combined with a scale enlargement to 1:100,000 and high contrast contact prints vs. the offset prints of the atlas, increases the resolution and sharpness of bathymetric features so that many more subtle features may be mapped in detail. A tectonic interpretation of these digitally enhanced GLORIA sonographs from the Eel River basin is presented, displaying anticlines, lineaments, ridge axis, pathways of sediment flow, and subtle doming. Many of these features are not present on published bathymetric maps and have not been derived from seismic data because the plan view spatial resolution is much less than that available from the GLORIA imagery.

  1. Adaptive Fusion of Stochastic Information for Imaging Fractured Vadose Zones

    NASA Astrophysics Data System (ADS)

    Daniels, J.; Yeh, J.; Illman, W.; Harri, S.; Kruger, A.; Parashar, M.

    2004-12-01

    A stochastic information fusion methodology is developed to assimilate electrical resistivity tomography, high-frequency ground penetrating radar, mid-range-frequency radar, pneumatic/gas tracer tomography, and hydraulic/tracer tomography to image fractures, characterize hydrogeophysical properties, and monitor natural processes in the vadose zone. The information technology research will develop: 1) mechanisms and algorithms for fusion of large data volumes ; 2) parallel adaptive computational engines supporting parallel adaptive algorithms and multi-physics/multi-model computations; 3) adaptive runtime mechanisms for proactive and reactive runtime adaptation and optimization of geophysical and hydrological models of the subsurface; and 4) technologies and infrastructure for remote (pervasive) and collaborative access to computational capabilities for monitoring subsurface processes through interactive visualization tools. The combination of the stochastic fusion approach and information technology can lead to a new level of capability for both hydrologists and geophysicists enabling them to "see" into the earth at greater depths and resolutions than is possible today. Furthermore, the new computing strategies will make high resolution and large-scale hydrological and geophysical modeling feasible for the private sector, scientists, and engineers who are unable to access supercomputers, i.e., an effective paradigm for technology transfer.

  2. A comparative study on preprocessing techniques in diabetic retinopathy retinal images: illumination correction and contrast enhancement.

    PubMed

    Rasta, Seyed Hossein; Partovi, Mahsa Eisazadeh; Seyedarabi, Hadi; Javadzadeh, Alireza

    2015-01-01

    To investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal image quality, a comparative study was carried out. We studied and implemented a few illumination correction and contrast enhancement techniques on color retinal images to find out the best technique for optimum image enhancement. To compare and choose the best illumination correction technique we analyzed the corrected red and green components of color retinal images statistically and visually. The two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivity and specificity. The statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients of variation. The dividing method using the median filter to estimate background illumination showed the lowest Coefficients of variations in the red component. The quotient and homomorphic filtering methods after the dividing method presented good results based on their low Coefficients of variations. The contrast limited adaptive histogram equalization increased the sensitivity of the vessel segmentation algorithm up to 5% in the same amount of accuracy. The contrast limited adaptive histogram equalization technique has a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation. Three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphic filtering were found as the effective illumination correction techniques based on a statistical evaluation. Applying the local contrast enhancement technique, such as CLAHE, for fundus images presented good potentials in enhancing the vasculature segmentation.

  3. Fusion of infrared and visible images for night-vision context enhancement.

    PubMed

    Zhou, Zhiqiang; Dong, Mingjie; Xie, Xiaozhu; Gao, Zhifeng

    2016-08-10

    Because of the poor lighting conditions at night time, visible images are often fused with corresponding infrared (IR) images for context enhancement of the scenes in night vision. In this paper, we present a novel night-vision context enhancement algorithm through IR and visible image fusion with the guided filter. First, to enhance the visibility of poorly illuminated details in the visible image before the fusion, an adaptive enhancement method is developed by incorporating the processes of dynamic range compression and contrast restoration based on the guided filter. Then, a hybrid multi-scale decomposition based on the guided filter is introduced to inject the IR image information into the visible image through a multi-scale fusion approach. Moreover, a perceptual-based regularization parameter selection method is used to determine the relative amount of the injected IR spectral features by comparing the perceptual saliency of the IR and visible image information. This fusion method can successfully transfer the important IR image information into the fused image, and simultaneously preserve the details and background scenery in the input visible image. Experimental results show that the proposed algorithm is able to achieve better context enhancement results in night vision. PMID:27534499

  4. Fingerprint image enhancement via log-Gabor filtering

    NASA Astrophysics Data System (ADS)

    Lu, Zhen-kun; Yu, Zhen-ming

    2011-11-01

    In this paper, a method to enhance the fingerprint image by using Log-Gabor filters is proposed. Firstly, a filter for extracting fingerprint image texture feature is designed. Then, the high frequency components of fingerprint image are extracted by filtering. Finally, the fingerprint image details can be improved by enhancing high frequency components. Experimental results show that the proposed algorithm can effectively improve the quality of fingerprint image and the reliability of fingerprint identification.

  5. Frequency-shift low-pass filtering and least mean square adaptive filtering for ultrasound imaging

    NASA Astrophysics Data System (ADS)

    Wang, Shanshan; Li, Chunyu; Ding, Mingyue; Yuchi, Ming

    2016-04-01

    Ultrasound image quality enhancement is a problem of considerable interest in medical imaging modality and an ongoing challenge to date. This paper investigates a method based on frequency-shift low-pass filtering (FSLF) and least mean square adaptive filtering (LMSAF) for ultrasound image quality enhancement. FSLF is used for processing the ultrasound signal in the frequency domain, while LMSAPF in the time domain. Firstly, FSLF shifts the center frequency of the focused signal to zero. Then the real and imaginary part of the complex data are filtered respectively by finite impulse response (FIR) low-pass filter. Thus the information around the center frequency are retained while the undesired ones, especially background noises are filtered. Secondly, LMSAF multiplies the signals with an automatically adjusted weight vector to further eliminate the noises and artifacts. Through the combination of the two filters, the ultrasound image is expected to have less noises and artifacts and higher resolution, and contrast. The proposed method was verified with the RF data of the CIRS phantom 055A captured by SonixTouch DAQ system. Experimental results show that the background noises and artifacts can be efficiently restrained, the wire object has a higher resolution and the contrast ratio (CR) can be enhanced for about 12dB to 15dB at different image depth comparing to delay-and-sum (DAS).

  6. Adaptive downsampling to improve image compression at low bit rates.

    PubMed

    Lin, Weisi; Dong, Li

    2006-09-01

    At low bit rates, better coding quality can be achieved by downsampling the image prior to compression and estimating the missing portion after decompression. This paper presents a new algorithm in such a paradigm, based on the adaptive decision of appropriate downsampling directions/ratios and quantization steps, in order to achieve higher coding quality with low bit rates with the consideration of local visual significance. The full-resolution image can be restored from the DCT coefficients of the downsampled pixels so that the spatial interpolation required otherwise is avoided. The proposed algorithm significantly raises the critical bit rate to approximately 1.2 bpp, from 0.15-0.41 bpp in the existing downsample-prior-to-JPEG schemes and, therefore, outperforms the standard JPEG method in a much wider bit-rate scope. The experiments have demonstrated better PSNR improvement over the existing techniques before the critical bit rate. In addition, the adaptive mode decision not only makes the critical bit rate less image-independent, but also automates the switching coders in variable bit-rate applications, since the algorithm turns to the standard JPEG method whenever it is necessary at higher bit rates.

  7. Improved compressed sensing-based cone-beam CT reconstruction using adaptive prior image constraints

    NASA Astrophysics Data System (ADS)

    Lee, Ho; Xing, Lei; Davidi, Ran; Li, Ruijiang; Qian, Jianguo; Lee, Rena

    2012-04-01

    Volumetric cone-beam CT (CBCT) images are acquired repeatedly during a course of radiation therapy and a natural question to ask is whether CBCT images obtained earlier in the process can be utilized as prior knowledge to reduce patient imaging dose in subsequent scans. The purpose of this work is to develop an adaptive prior image constrained compressed sensing (APICCS) method to solve this problem. Reconstructed images using full projections are taken on the first day of radiation therapy treatment and are used as prior images. The subsequent scans are acquired using a protocol of sparse projections. In the proposed APICCS algorithm, the prior images are utilized as an initial guess and are incorporated into the objective function in the compressed sensing (CS)-based iterative reconstruction process. Furthermore, the prior information is employed to detect any possible mismatched regions between the prior and current images for improved reconstruction. For this purpose, the prior images and the reconstructed images are classified into three anatomical regions: air, soft tissue and bone. Mismatched regions are identified by local differences of the corresponding groups in the two classified sets of images. A distance transformation is then introduced to convert the information into an adaptive voxel-dependent relaxation map. In constructing the relaxation map, the matched regions (unchanged anatomy) between the prior and current images are assigned with smaller weight values, which are translated into less influence on the CS iterative reconstruction process. On the other hand, the mismatched regions (changed anatomy) are associated with larger values and the regions are updated more by the new projection data, thus avoiding any possible adverse effects of prior images. The APICCS approach was systematically assessed by using patient data acquired under standard and low-dose protocols for qualitative and quantitative comparisons. The APICCS method provides an

  8. Focusing a NIR adaptive optics imager; experience with GSAOI

    NASA Astrophysics Data System (ADS)

    Doolan, Matthew; Bloxham, Gabe; Conroy, Peter; Jones, Damien; McGregor, Peter; Stevanovic, Dejan; Van Harmelen, Jan; Waldron, Liam E.; Waterson, Mark; Zhelem, Ross

    2006-06-01

    The Gemini South Adaptive Optics Imager (GSAOI) to be used with the Multi-Conjugate Adaptive Optics (MCAO) system at Gemini South is currently in the final stages of assembly and testing. GSAOI uses a suite of 26 different filters, made from both BK7 and Fused Silica substrates. These filters, located in a non-collimated beam, work as active optical elements. The optical design was undertaken to ensure that both the filter substrates both focused longitudinally at the same point. During the testing of the instrument it was found that longitudinal focus was filter dependant. The methods used to investigate this are outlined in the paper. These investigations identified several possible causes for the focal shift including substrate material properties in cryogenic conditions and small amounts of residual filter power.

  9. Liquid-Crystal Light Valve Enhances Edges In Images

    NASA Technical Reports Server (NTRS)

    Chao, Tien-Hsin; Liu, Hua-Kuang

    1991-01-01

    Experiments show liquid-crystal light valve (LCLV) exhibits operating mode in which it enhances edges in images projected on it. Operates in edge-enhancing mode (or in combination of edge-enhancing and normal modes) by suitably adjusting bias voltage and frequency. Enhancement of edges one of most important preprocessing steps in optical pattern-recognition systems. Incorporated into image-processing system to enhance edges without introducing excessive optical noise.

  10. Comparison of enhanced flat EEG image via distinct fuzzification

    NASA Astrophysics Data System (ADS)

    Zenian, S.; Ahmad, T.; Idris, A.

    2015-12-01

    In medical imaging, image enhancement is an important step before further processing is being carried out. It aims to improve the quality of the images as uncertainties maybe inherited due to several factors. In this paper, the image of Flat EEG (fEEG) is enhanced (in terms of contrast enhancement) by using intuitionistic fuzzy set (IFS) approach. The enhanced images are compared through two different membership functions whereby it is implemented in the initial step of the enhancement process. It is observed that cluster centres with darker background appeared in the resultant images as compared to the input image. Moreover, the contrast comparison between the input and output images are being carried out.

  11. Robust image registration using adaptive coherent point drift method

    NASA Astrophysics Data System (ADS)

    Yang, Lijuan; Tian, Zheng; Zhao, Wei; Wen, Jinhuan; Yan, Weidong

    2016-04-01

    Coherent point drift (CPD) method is a powerful registration tool under the framework of the Gaussian mixture model (GMM). However, the global spatial structure of point sets is considered only without other forms of additional attribute information. The equivalent simplification of mixing parameters and the manual setting of the weight parameter in GMM make the CPD method less robust to outlier and have less flexibility. An adaptive CPD method is proposed to automatically determine the mixing parameters by embedding the local attribute information of features into the construction of GMM. In addition, the weight parameter is treated as an unknown parameter and automatically determined in the expectation-maximization algorithm. In image registration applications, the block-divided salient image disk extraction method is designed to detect sparse salient image features and local self-similarity is used as attribute information to describe the local neighborhood structure of each feature. The experimental results on optical images and remote sensing images show that the proposed method can significantly improve the matching performance.

  12. Enhanced polyaromatic hydrocarbon degradation by adapted cultures of actinomycete strains.

    PubMed

    Bourguignon, Natalia; Isaac, Paula; Alvarez, Héctor; Amoroso, María J; Ferrero, Marcela A

    2014-12-01

    Fifteen actinomycete strains were evaluated for their potential use in removal of polycyclic aromatic hydrocarbons (PAH). Their capability to degrade of naphthalene, phenanthrene, and pyrene was tested in minimal medium (MM) and MM with glucose as another substrate. Degradation of naphthalene in MM was observed in all isolates at different rates, reaching maximum values near to 76% in some strains of Streptomyces, Rhodococcus sp. 016 and Amycolatopsis tucumanensis DSM 45259. Maximum values of degradation of phenanthrene in MM occurred in cultures of A. tucumanensis DSM 45259 (36.2%) and Streptomyces sp. A12 (20%), while the degradation of pyrene in MM was poor and only significant with Streptomyces sp. A12 (4.3%). Because of the poor performance when growing on phenanthrene and pyrene alone, Rhodococcus sp. 20, Rhodococcus sp. 016, A. tucumanensis DSM 45259, Streptomyces sp. A2, and Streptomyces sp. A12 were challenged to an adaptation schedule of successive cultures on a fresh solid medium supplemented with PAHs, decreasing concentration of glucose in each step. As a result, an enhanced degradation of PAHs by adapted strains was observed in the presence of glucose as co-substrate, without degradation of phenanthrene and pyrene in MM while an increase to up to 50% of degradation was seen with these strains in glucose amended media. An internal fragment of the catA gene, which codes for catechol 1,2-dioxygenase, was amplified from both Rhodococcus strains, showing the potential for degradation of aromatic compounds via salycilate. These results allow us to propose the usefulness of these actinomycete strains for PAH bioremediation in the environment. PMID:25205070

  13. Adaptive regularized scheme for remote sensing image fusion

    NASA Astrophysics Data System (ADS)

    Tang, Sizhang; Shen, Chaomin; Zhang, Guixu

    2016-06-01

    We propose an adaptive regularized algorithm for remote sensing image fusion based on variational methods. In the algorithm, we integrate the inputs using a "grey world" assumption to achieve visual uniformity. We propose a fusion operator that can automatically select the total variation (TV)-L1 term for edges and L2-terms for non-edges. To implement our algorithm, we use the steepest descent method to solve the corresponding Euler-Lagrange equation. Experimental results show that the proposed algorithm achieves remarkable results.

  14. An adaptive fusion approach for infrared and visible images based on NSCT and compressed sensing

    NASA Astrophysics Data System (ADS)

    Zhang, Qiong; Maldague, Xavier

    2016-01-01

    A novel nonsubsampled contourlet transform (NSCT) based image fusion approach, implementing an adaptive-Gaussian (AG) fuzzy membership method, compressed sensing (CS) technique, total variation (TV) based gradient descent reconstruction algorithm, is proposed for the fusion computation of infrared and visible images. Compared with wavelet, contourlet, or any other multi-resolution analysis method, NSCT has many evident advantages, such as multi-scale, multi-direction, and translation invariance. As is known, a fuzzy set is characterized by its membership function (MF), while the commonly known Gaussian fuzzy membership degree can be introduced to establish an adaptive control of the fusion processing. The compressed sensing technique can sparsely sample the image information in a certain sampling rate, and the sparse signal can be recovered by solving a convex problem employing gradient descent based iterative algorithm(s). In the proposed fusion process, the pre-enhanced infrared image and the visible image are decomposed into low-frequency subbands and high-frequency subbands, respectively, via the NSCT method as a first step. The low-frequency coefficients are fused using the adaptive regional average energy rule; the highest-frequency coefficients are fused using the maximum absolute selection rule; the other high-frequency coefficients are sparsely sampled, fused using the adaptive-Gaussian regional standard deviation rule, and then recovered by employing the total variation based gradient descent recovery algorithm. Experimental results and human visual perception illustrate the effectiveness and advantages of the proposed fusion approach. The efficiency and robustness are also analyzed and discussed through different evaluation methods, such as the standard deviation, Shannon entropy, root-mean-square error, mutual information and edge-based similarity index.

  15. Adapted waveform analysis, wavelet packets, and local cosine libraries as a tool for image processing

    NASA Astrophysics Data System (ADS)

    Coifman, Ronald R.; Woog, Lionel J.

    1995-09-01

    Adapted wave form analysis, refers to a collection of FFT like adapted transform algorithms. Given an image these methods provide special matched collections of templates (orthonormal bases) enabling an efficient coding of the image. Perhaps the closest well known example of such coding method is provided by musical notation, where each segment of music is represented by a musical score made up of notes (templates) characterised by their duration, pitch, location and amplitude, our method corresponds to transcribing the music in as few notes as possible. The extension to images and video is straightforward we describe the image by collections of oscillatory patterns (paint brush strokes)of various sizes locations and amplitudes using a variety of orthogonal bases. These selected basis functions are chosen inside predefined libraries of oscillatory localized functions (trigonometric and wavelet-packets waveforms) so as to optimize the number of parameters needed to describe our object. These algorithms are of complexity N log N opening the door for a large range of applications in signal and image processing, such as compression, feature extraction denoising and enhancement. In particular we describe a class of special purpose compressions for fingerprint irnages, as well as denoising tools for texture and noise extraction. We start by relating traditional Fourier methods to wavelet, wavelet-packet based algorithms using a recent refinement of the windowed sine and cosine transforms. We will then derive an adapted local sine transform show it's relation to wavelet and wavelet-packet analysis and describe an analysis toolkit illustrating the merits of different adaptive and nonadaptive schemes.

  16. Adaptive stereo medical image watermarking using non-corresponding blocks.

    PubMed

    Mohaghegh, H; Karimi, N; Soroushmehr, S M R; Samavi, S; Najarian, K

    2015-08-01

    Today with the advent of technology in different medical imaging fields, the use of stereoscopic images has increased. Furthermore, with the rapid growth in telemedicine for remote diagnosis, treatment, and surgery, there is a need for watermarking. This is for copyright protection and tracking of digital media. Also, the efficient use of bandwidth for transmission of such data is another concern. In this paper an adaptive watermarking scheme is proposed that considers human visual system in depth perception. Our proposed scheme modifies maximum singular values of wavelet coefficients of stereo pair for embedding watermark bits. Experimental results show high 3D visual quality of watermarked video frames. Moreover, comparison with a compatible state of the art method shows that the proposed method is highly robust against attacks such as AWGN, salt and pepper noise, and JPEG compression. PMID:26737224

  17. Adaptive stereo medical image watermarking using non-corresponding blocks.

    PubMed

    Mohaghegh, H; Karimi, N; Soroushmehr, S M R; Samavi, S; Najarian, K

    2015-01-01

    Today with the advent of technology in different medical imaging fields, the use of stereoscopic images has increased. Furthermore, with the rapid growth in telemedicine for remote diagnosis, treatment, and surgery, there is a need for watermarking. This is for copyright protection and tracking of digital media. Also, the efficient use of bandwidth for transmission of such data is another concern. In this paper an adaptive watermarking scheme is proposed that considers human visual system in depth perception. Our proposed scheme modifies maximum singular values of wavelet coefficients of stereo pair for embedding watermark bits. Experimental results show high 3D visual quality of watermarked video frames. Moreover, comparison with a compatible state of the art method shows that the proposed method is highly robust against attacks such as AWGN, salt and pepper noise, and JPEG compression.

  18. Fourier transform digital holographic adaptive optics imaging system

    PubMed Central

    Liu, Changgeng; Yu, Xiao; Kim, Myung K.

    2013-01-01

    A Fourier transform digital holographic adaptive optics imaging system and its basic principles are proposed. The CCD is put at the exact Fourier transform plane of the pupil of the eye lens. The spherical curvature introduced by the optics except the eye lens itself is eliminated. The CCD is also at image plane of the target. The point-spread function of the system is directly recorded, making it easier to determine the correct guide-star hologram. Also, the light signal will be stronger at the CCD, especially for phase-aberration sensing. Numerical propagation is avoided. The sensor aperture has nothing to do with the resolution and the possibility of using low coherence or incoherent illumination is opened. The system becomes more efficient and flexible. Although it is intended for ophthalmic use, it also shows potential application in microscopy. The robustness and feasibility of this compact system are demonstrated by simulations and experiments using scattering objects. PMID:23262541

  19. Enhancement of brain tumor MR images based on intuitionistic fuzzy sets

    NASA Astrophysics Data System (ADS)

    Deng, Wankai; Deng, He; Cheng, Lifang

    2015-12-01

    Brain tumor is one of the most fatal cancers, especially high-grade gliomas are among the most deadly. However, brain tumor MR images usually have the disadvantages of low resolution and contrast when compared with the optical images. Consequently, we present a novel adaptive intuitionistic fuzzy enhancement scheme by combining a nonlinear fuzzy filtering operation with fusion operators, for the enhancement of brain tumor MR images in this paper. The presented scheme consists of the following six steps: Firstly, the image is divided into several sub-images. Secondly, for each sub-image, object and background areas are separated by a simple threshold. Thirdly, respective intuitionistic fuzzy generators of object and background areas are constructed based on the modified restricted equivalence function. Fourthly, different suitable operations are performed on respective membership functions of object and background areas. Fifthly, the membership plane is inversely transformed into the image plane. Finally, an enhanced image is obtained through fusion operators. The comparison and evaluation of enhancement performance demonstrate that the presented scheme is helpful to determine the abnormal functional areas, guide the operation, judge the prognosis, and plan the radiotherapy by enhancing the fine detail of MR images.

  20. Adaptive optics scanning laser ophthalmoscope imaging: technology update.

    PubMed

    Merino, David; Loza-Alvarez, Pablo

    2016-01-01

    Adaptive optics (AO) retinal imaging has become very popular in the past few years, especially within the ophthalmic research community. Several different retinal techniques, such as fundus imaging cameras or optical coherence tomography systems, have been coupled with AO in order to produce impressive images showing individual cell mosaics over different layers of the in vivo human retina. The combination of AO with scanning laser ophthalmoscopy has been extensively used to generate impressive images of the human retina with unprecedented resolution, showing individual photoreceptor cells, retinal pigment epithelium cells, as well as microscopic capillary vessels, or the nerve fiber layer. Over the past few years, the technique has evolved to develop several different applications not only in the clinic but also in different animal models, thanks to technological developments in the field. These developments have specific applications to different fields of investigation, which are not limited to the study of retinal diseases but also to the understanding of the retinal function and vision science. This review is an attempt to summarize these developments in an understandable and brief manner in order to guide the reader into the possibilities that AO scanning laser ophthalmoscopy offers, as well as its limitations, which should be taken into account when planning on using it.

  1. Adaptive optics scanning laser ophthalmoscope imaging: technology update

    PubMed Central

    Merino, David; Loza-Alvarez, Pablo

    2016-01-01

    Adaptive optics (AO) retinal imaging has become very popular in the past few years, especially within the ophthalmic research community. Several different retinal techniques, such as fundus imaging cameras or optical coherence tomography systems, have been coupled with AO in order to produce impressive images showing individual cell mosaics over different layers of the in vivo human retina. The combination of AO with scanning laser ophthalmoscopy has been extensively used to generate impressive images of the human retina with unprecedented resolution, showing individual photoreceptor cells, retinal pigment epithelium cells, as well as microscopic capillary vessels, or the nerve fiber layer. Over the past few years, the technique has evolved to develop several different applications not only in the clinic but also in different animal models, thanks to technological developments in the field. These developments have specific applications to different fields of investigation, which are not limited to the study of retinal diseases but also to the understanding of the retinal function and vision science. This review is an attempt to summarize these developments in an understandable and brief manner in order to guide the reader into the possibilities that AO scanning laser ophthalmoscopy offers, as well as its limitations, which should be taken into account when planning on using it. PMID:27175057

  2. Adaptive near-field beamforming techniques for sound source imaging.

    PubMed

    Cho, Yong Thung; Roan, Michael J

    2009-02-01

    Phased array signal processing techniques such as beamforming have a long history in applications such as sonar for detection and localization of far-field sound sources. Two sometimes competing challenges arise in any type of spatial processing; these are to minimize contributions from directions other than the look direction and minimize the width of the main lobe. To tackle this problem a large body of work has been devoted to the development of adaptive procedures that attempt to minimize side lobe contributions to the spatial processor output. In this paper, two adaptive beamforming procedures-minimum variance distorsionless response and weight optimization to minimize maximum side lobes--are modified for use in source visualization applications to estimate beamforming pressure and intensity using near-field pressure measurements. These adaptive techniques are compared to a fixed near-field focusing technique (both techniques use near-field beamforming weightings focusing at source locations estimated based on spherical wave array manifold vectors with spatial windows). Sound source resolution accuracies of near-field imaging procedures with different weighting strategies are compared using numerical simulations both in anechoic and reverberant environments with random measurement noise. Also, experimental results are given for near-field sound pressure measurements of an enclosed loudspeaker.

  3. Extended adaptive filtering for wide-angle SAR image formation

    NASA Astrophysics Data System (ADS)

    Wang, Yanwei; Roberts, William; Li, Jian

    2005-05-01

    For two-dimensional (2-D) spectral analysis, the adaptive filtering based technologies, such as CAPON and APES (Amplitude and Phase EStimation), are developed under the implicit assumption that the data sets are rectangular. However, in real SAR applications, especially for the wide-angle cases, the collected data sets are always non-rectangular. This raises the problem of how to extend the original adaptive filtering based algorithms for such kind of scenarios. In this paper, we propose an extended adaptive filtering (EAF) approach, which includes Extended APES (E-APES) and Extended CAPON (E-CAPON), for arbitrarily shaped 2-D data. The EAF algorithms adopt a missing-data approach where the unavailable data samples close to the collected data set are assumed missing. Using a group of filter-banks with varying sizes, these algorithms are non-iterative and do not require the estimation of the unavailable samples. The improved imaging results of the proposed algorithms are demonstrated by applying them to two different SAR data sets.

  4. Shape adaptive, robust iris feature extraction from noisy iris images.

    PubMed

    Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

    2013-10-01

    In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate. PMID:24696801

  5. Adaptive Optics and Lucky Imager (AOLI): presentation and first light

    NASA Astrophysics Data System (ADS)

    Velasco, S.; Rebolo, R.; Mackay, C.; Oscoz, A.; King, D. L.; Crass, J.; Díaz-Sánchez, A.; Femenía, B.; González-Escalera, V.; Labadie, L.; López, R. L.; Pérez Garrido, A.; Puga, M.; Rodríguez-Ramos, L. F.; Zuther, J.

    2015-05-01

    In this paper we present the Adaptive Optics Lucky Imager (AOLI), a state-of-the-art instrument which makes use of two well proved techniques for extremely high spatial resolution with ground-based telescopes: Lucky Imaging (LI) and Adaptive Optics (AO). AOLI comprises an AO system, including a low order non-linear curvature wavefront sensor together with a 241 actuators deformable mirror, a science array of four 1024x1024 EMCCDs, allowing a 120×120 down to 36×36" field of view, a calibration subsystem and a powerful LI software. Thanks to the revolutionary WFS, AOLI shall have the capability of using faint reference stars (I˜16.5-17.5), enabling it to be used over a much wider part of the sky than with common Shack-Hartmann AO systems. This instrument saw first light in September 2013 at William Herschel Telescope. Although the instrument was not complete, these commissioning demonstrated its feasibility, obtaining a FWHM for the best PSF of 0.151±0.005" and a plate scale of 55.0±0.3 {mas} {pix}^{-1}. Those observations served us to prove some characteristics of the interesting multiple T Tauri system LkHα 262-263, finding it to be gravitationally bounded. This interesting multiple system mixes the presence of proto-planetary discs, one proved to be double, and the first-time optically resolved pair LkHα 263AB (0.42" separation).

  6. Adaptation of commercial microscopes for advanced imaging applications

    NASA Astrophysics Data System (ADS)

    Brideau, Craig; Poon, Kelvin; Stys, Peter

    2015-03-01

    Today's commercially available microscopes offer a wide array of options to accommodate common imaging experiments. Occasionally, an experimental goal will require an unusual light source, filter, or even irregular sample that is not compatible with existing equipment. In these situations the ability to modify an existing microscopy platform with custom accessories can greatly extend its utility and allow for experiments not possible with stock equipment. Light source conditioning/manipulation such as polarization, beam diameter or even custom source filtering can easily be added with bulk components. Custom and after-market detectors can be added to external ports using optical construction hardware and adapters. This paper will present various examples of modifications carried out on commercial microscopes to address both atypical imaging modalities and research needs. Violet and near-ultraviolet source adaptation, custom detection filtering, and laser beam conditioning and control modifications will be demonstrated. The availability of basic `building block' parts will be discussed with respect to user safety, construction strategies, and ease of use.

  7. Adaptive Optics Imaging Survey of Luminous Infrared Galaxies

    SciTech Connect

    Laag, E A; Canalizo, G; van Breugel, W; Gates, E L; de Vries, W; Stanford, S A

    2006-03-13

    We present high resolution imaging observations of a sample of previously unidentified far-infrared galaxies at z < 0.3. The objects were selected by cross-correlating the IRAS Faint Source Catalog with the VLA FIRST catalog and the HST Guide Star Catalog to allow for adaptive optics observations. We found two new ULIGs (with L{sub FIR} {ge} 10{sup 12} L{sub {circle_dot}}) and 19 new LIGs (with L{sub FIR} {ge} 10{sup 11} L{sub {circle_dot}}). Twenty of the galaxies in the sample were imaged with either the Lick or Keck adaptive optics systems in H or K{prime}. Galaxy morphologies were determined using the two dimensional fitting program GALFIT and the residuals examined to look for interesting structure. The morphologies reveal that at least 30% are involved in tidal interactions, with 20% being clear mergers. An additional 50% show signs of possible interaction. Line ratios were used to determine powering mechanism; of the 17 objects in the sample showing clear emission lines--four are active galactic nuclei and seven are starburst galaxies. The rest exhibit a combination of both phenomena.

  8. Near-lossless image compression by adaptive prediction: new developments and comparison of algorithms

    NASA Astrophysics Data System (ADS)

    Aiazzi, Bruno; Alparone, Luciano; Baronti, Stefano

    2003-01-01

    This paper describes state-of-the-art approaches to near-lossless image compression by adaptive causal DPCM and presents two advanced schemes based on crisp and fuzzy switching of predictors, respectively. The former relies on a linear-regression prediction in which a different predictor is employed for each image block. Such block-representative predictors are calculated from the original data set through an iterative relaxation-labeling procedure. Coding time are affordable thanks to fast convergence of training. Decoding is always performed in real time. The latter is still based on adaptive MMSE prediction in which a different predictor at each pixel position is achieved by blending a number of prototype predictors through adaptive weights calculated from the past decoded samples. Quantization error feedback loops are introduced into the basic lossless encoders to enable user-defined upper-bounded reconstruction errors. Both schemes exploit context modeling of prediction errors followed by arithmetic coding to enhance entropy coding performances. A thorough performance comparison on a wide test image set show the superiority of the proposed schemes over both up-to-date encoders in the literature and new/upcoming standards.

  9. Image processing for flight crew enhanced situation awareness

    NASA Technical Reports Server (NTRS)

    Roberts, Barry

    1993-01-01

    This presentation describes the image processing work that is being performed for the Enhanced Situational Awareness System (ESAS) application. Specifically, the presented work supports the Enhanced Vision System (EVS) component of ESAS.

  10. Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C-Means Clustering.

    PubMed

    Elazab, Ahmed; Wang, Changmiao; Jia, Fucang; Wu, Jianhuang; Li, Guanglin; Hu, Qingmao

    2015-01-01

    An adaptively regularized kernel-based fuzzy C-means clustering framework is proposed for segmentation of brain magnetic resonance images. The framework can be in the form of three algorithms for the local average grayscale being replaced by the grayscale of the average filter, median filter, and devised weighted images, respectively. The algorithms employ the heterogeneity of grayscales in the neighborhood and exploit this measure for local contextual information and replace the standard Euclidean distance with Gaussian radial basis kernel functions. The main advantages are adaptiveness to local context, enhanced robustness to preserve image details, independence of clustering parameters, and decreased computational costs. The algorithms have been validated against both synthetic and clinical magnetic resonance images with different types and levels of noises and compared with 6 recent soft clustering algorithms. Experimental results show that the proposed algorithms are superior in preserving image details and segmentation accuracy while maintaining a low computational complexity. PMID:26793269

  11. Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C-Means Clustering.

    PubMed

    Elazab, Ahmed; Wang, Changmiao; Jia, Fucang; Wu, Jianhuang; Li, Guanglin; Hu, Qingmao

    2015-01-01

    An adaptively regularized kernel-based fuzzy C-means clustering framework is proposed for segmentation of brain magnetic resonance images. The framework can be in the form of three algorithms for the local average grayscale being replaced by the grayscale of the average filter, median filter, and devised weighted images, respectively. The algorithms employ the heterogeneity of grayscales in the neighborhood and exploit this measure for local contextual information and replace the standard Euclidean distance with Gaussian radial basis kernel functions. The main advantages are adaptiveness to local context, enhanced robustness to preserve image details, independence of clustering parameters, and decreased computational costs. The algorithms have been validated against both synthetic and clinical magnetic resonance images with different types and levels of noises and compared with 6 recent soft clustering algorithms. Experimental results show that the proposed algorithms are superior in preserving image details and segmentation accuracy while maintaining a low computational complexity.

  12. Enhancement of multispectral thermal infrared images - Decorrelation contrast stretching

    NASA Technical Reports Server (NTRS)

    Gillespie, Alan R.

    1992-01-01

    Decorrelation contrast stretching is an effective method for displaying information from multispectral thermal infrared (TIR) images. The technique involves transformation of the data to principle components ('decorrelation'), independent contrast 'stretching' of data from the new 'decorrelated' image bands, and retransformation of the stretched data back to the approximate original axes, based on the inverse of the principle component rotation. The enhancement is robust in that colors of the same scene components are similar in enhanced images of similar scenes, or the same scene imaged at different times. Decorrelation contrast stretching is reviewed in the context of other enhancements applied to TIR images.

  13. An improved visual enhancement method for color images

    NASA Astrophysics Data System (ADS)

    Wang, Wenhan; Zhang, Biao

    2013-07-01

    The paper presents an improved method for color image enhancement based on dynamic range compression and shadow compensation method proposed by Felix Albu et al. The improved method consists of not only the dynamic range compression and shadow compensation but also intensity contrast stretching implemented under the logarithmic image processing (LIP) model. The previous method enhance image while preserve image details and color information without generating visual artifacts. On the premise of remaining the advantages of the previous one, our improved method enhances the intensity of the whole image especially the low-light areas. The experimental results illustrate the effectiveness of our proposed method and the superiority over the previous one.

  14. Theory of Adaptive Acquisition Method for Image Reconstruction from Projections and Application to EPR Imaging

    NASA Astrophysics Data System (ADS)

    Placidi, G.; Alecci, M.; Sotgiu, A.

    1995-07-01

    An adaptive method for selecting the projections to be used for image reconstruction is presented. The method starts with the acquisition of four projections at angles of 0°, 45°, 90°, 135° and selects the new angles by computing a function of the previous projections. This makes it possible to adapt the selection of projections to the arbitrary shape of the sample, thus measuring a more informative set of projections. When the sample is smooth or has internal symmetries, this technique allows a reduction in the number of projections required to reconstruct the image without loss of information. The method has been tested on simulated data at different values of signal-to-noise ratio (S/N) and on experimental data recorded by an EPR imaging apparatus.

  15. 75 FR 34988 - Federal Advisory Committee; Defense Science Board 2010 Summer Study on Enhancing Adaptability of...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-21

    ... of the Secretary Federal Advisory Committee; Defense Science Board 2010 Summer Study on Enhancing... meeting. SUMMARY: The Defense Science Board 2010 Summer Study on Enhancing Adaptability of our Military... of adaptation, both commercial and non-commercial, and what made them successful and...

  16. High-speed adaptive contact-mode atomic force microscopy imaging with near-minimum-force

    SciTech Connect

    Ren, Juan; Zou, Qingze

    2014-07-15

    In this paper, an adaptive contact-mode imaging approach is proposed to replace the traditional contact-mode imaging by addressing the major concerns in both the speed and the force exerted to the sample. The speed of the traditional contact-mode imaging is largely limited by the need to maintain precision tracking of the sample topography over the entire imaged sample surface, while large image distortion and excessive probe-sample interaction force occur during high-speed imaging. In this work, first, the image distortion caused by the topography tracking error is accounted for in the topography quantification. Second, the quantified sample topography is utilized in a gradient-based optimization method to adjust the cantilever deflection set-point for each scanline closely around the minimal level needed for maintaining stable probe-sample contact, and a data-driven iterative feedforward control that utilizes a prediction of the next-line topography is integrated to the topography feeedback loop to enhance the sample topography tracking. The proposed approach is demonstrated and evaluated through imaging a calibration sample of square pitches at both high speeds (e.g., scan rate of 75 Hz and 130 Hz) and large sizes (e.g., scan size of 30 μm and 80 μm). The experimental results show that compared to the traditional constant-force contact-mode imaging, the imaging speed can be increased by over 30 folds (with the scanning speed at 13 mm/s), and the probe-sample interaction force can be reduced by more than 15% while maintaining the same image quality.

  17. Adaptive HIFU noise cancellation for simultaneous therapy and imaging using an integrated HIFU/imaging transducer

    PubMed Central

    Jeong, Jong Seob; Cannata, Jonathan Matthew; Shung, K Kirk

    2010-01-01

    It was previously demonstrated that it is feasible to simultaneously perform ultrasound therapy and imaging of a coagulated lesion during treatment with an integrated transducer that is capable of high intensity focused ultrasound (HIFU) and B-mode ultrasound imaging. It was found that coded excitation and fixed notch filtering upon reception could significantly reduce interference caused by the therapeutic transducer. During HIFU sonication, the imaging signal generated with coded excitation and fixed notch filtering had a range side-lobe level of less than −40 dB, while traditional short-pulse excitation and fixed notch filtering produced a range side-lobe level of −20 dB. The shortcoming is, however, that relatively complicated electronics may be needed to utilize coded excitation in an array imaging system. It is for this reason that in this paper an adaptive noise canceling technique is proposed to improve image quality by minimizing not only the therapeutic interference, but also the remnant side-lobe ‘ripples’ when using the traditional short-pulse excitation. The performance of this technique was verified through simulation and experiments using a prototype integrated HIFU/imaging transducer. Although it is known that the remnant ripples are related to the notch attenuation value of the fixed notch filter, in reality, it is difficult to find the optimal notch attenuation value due to the change in targets or the media resulted from motion or different acoustic properties even during one sonication pulse. In contrast, the proposed adaptive noise canceling technique is capable of optimally minimizing both the therapeutic interference and residual ripples without such constraints. The prototype integrated HIFU/imaging transducer is composed of three rectangular elements. The 6 MHz center element is used for imaging and the outer two identical 4 MHz elements work together to transmit the HIFU beam. Two HIFU elements of 14.4 mm × 20.0 mm dimensions

  18. EUV imaging experiment of an adaptive optics telescope

    NASA Astrophysics Data System (ADS)

    Kitamoto, S.; Shibata, T.; Takenaka, E.; Yoshida, M.; Murakami, H.; Shishido, Y.; Gotoh, N.; Nagasaki, K.; Takei, D.; Morii, M.

    2009-08-01

    We report an experimental result of our normal-incident EUV telescope tuned to a 13.5 nm band, with an adaptive optics. The optics consists of a spherical primary mirror and a secondary mirror. Both are coated by Mo/Si multilayer. The diameter of the primary and the secondary mirrors are 80 mm and 55mm, respectively. The secondary mirror is a deformable mirror with 31 bimorph-piezo electrodes. The EUV from a laser plasma source was exposed to a Ni mesh with 31 micro-m wires. The image of this mesh was obtained by a backilluminated CCD. The reference wave was made by an optical laser source with 1 μm pin-hole. We measure the wave form of this reference wave and control the secondary mirror to get a good EUV image. Since the paths of EUV and the optical light for the reference were different from each other, we modify the target wave from to control the deformable mirror, as the EUV image is best. The higher order Zernike components of the target wave form, as well as the tilts and focus components, were added to the reference wave form made by simply calculated. We confirmed the validity of this control and performed a 2.1 arc-sec resolution.

  19. Fast-adaptive near-lossless image compression

    NASA Astrophysics Data System (ADS)

    He, Kejing

    2016-05-01

    The purpose of image compression is to store or transmit image data efficiently. However, most compression methods emphasize the compression ratio rather than the throughput. We propose an encoding process and rules, and consequently a fast-adaptive near-lossless image compression method (FAIC) with good compression ratio. FAIC is a single-pass method, which removes bits from each codeword, then predicts the next pixel value through localized edge detection techniques, and finally uses Golomb-Rice codes to encode the residuals. FAIC uses only logical operations, bitwise operations, additions, and subtractions. Meanwhile, it eliminates the slow operations (e.g., multiplication, division, and logarithm) and the complex entropy coder, which can be a bottleneck in hardware implementations. Besides, FAIC does not depend on any precomputed tables or parameters. Experimental results demonstrate that FAIC achieves good balance between compression ratio and computational complexity in certain range (e.g., peak signal-to-noise ratio >35 dB, bits per pixel>2). It is suitable for applications in which the amount of data is huge or the computation power is limited.

  20. High performance 3D adaptive filtering for DSP based portable medical imaging systems

    NASA Astrophysics Data System (ADS)

    Bockenbach, Olivier; Ali, Murtaza; Wainwright, Ian; Nadeski, Mark

    2015-03-01

    Portable medical imaging devices have proven valuable for emergency medical services both in the field and hospital environments and are becoming more prevalent in clinical settings where the use of larger imaging machines is impractical. Despite their constraints on power, size and cost, portable imaging devices must still deliver high quality images. 3D adaptive filtering is one of the most advanced techniques aimed at noise reduction and feature enhancement, but is computationally very demanding and hence often cannot be run with sufficient performance on a portable platform. In recent years, advanced multicore digital signal processors (DSP) have been developed that attain high processing performance while maintaining low levels of power dissipation. These processors enable the implementation of complex algorithms on a portable platform. In this study, the performance of a 3D adaptive filtering algorithm on a DSP is investigated. The performance is assessed by filtering a volume of size 512x256x128 voxels sampled at a pace of 10 MVoxels/sec with an Ultrasound 3D probe. Relative performance and power is addressed between a reference PC (Quad Core CPU) and a TMS320C6678 DSP from Texas Instruments.

  1. Retinal Image Enhancement Using Robust Inverse Diffusion Equation and Self-Similarity Filtering

    PubMed Central

    Fu, Shujun; Xu, Lingzhong; Zhao, Kun; Zhang, Caiming

    2016-01-01

    As a common ocular complication for diabetic patients, diabetic retinopathy has become an important public health problem in the world. Early diagnosis and early treatment with the help of fundus imaging technology is an effective control method. In this paper, a robust inverse diffusion equation combining a self-similarity filtering is presented to detect and evaluate diabetic retinopathy using retinal image enhancement. A flux corrected transport technique is used to control diffusion flux adaptively, which eliminates overshoots inherent in the Laplacian operation. Feature preserving denoising by the self-similarity filtering ensures a robust enhancement of noisy and blurry retinal images. Experimental results demonstrate that this algorithm can enhance important details of retinal image data effectively, affording an opportunity for better medical interpretation and subsequent processing. PMID:27388503

  2. Retinal Image Enhancement Using Robust Inverse Diffusion Equation and Self-Similarity Filtering.

    PubMed

    Wang, Lu; Liu, Guohua; Fu, Shujun; Xu, Lingzhong; Zhao, Kun; Zhang, Caiming

    2016-01-01

    As a common ocular complication for diabetic patients, diabetic retinopathy has become an important public health problem in the world. Early diagnosis and early treatment with the help of fundus imaging technology is an effective control method. In this paper, a robust inverse diffusion equation combining a self-similarity filtering is presented to detect and evaluate diabetic retinopathy using retinal image enhancement. A flux corrected transport technique is used to control diffusion flux adaptively, which eliminates overshoots inherent in the Laplacian operation. Feature preserving denoising by the self-similarity filtering ensures a robust enhancement of noisy and blurry retinal images. Experimental results demonstrate that this algorithm can enhance important details of retinal image data effectively, affording an opportunity for better medical interpretation and subsequent processing.

  3. Retinal Image Enhancement Using Robust Inverse Diffusion Equation and Self-Similarity Filtering.

    PubMed

    Wang, Lu; Liu, Guohua; Fu, Shujun; Xu, Lingzhong; Zhao, Kun; Zhang, Caiming

    2016-01-01

    As a common ocular complication for diabetic patients, diabetic retinopathy has become an important public health problem in the world. Early diagnosis and early treatment with the help of fundus imaging technology is an effective control method. In this paper, a robust inverse diffusion equation combining a self-similarity filtering is presented to detect and evaluate diabetic retinopathy using retinal image enhancement. A flux corrected transport technique is used to control diffusion flux adaptively, which eliminates overshoots inherent in the Laplacian operation. Feature preserving denoising by the self-similarity filtering ensures a robust enhancement of noisy and blurry retinal images. Experimental results demonstrate that this algorithm can enhance important details of retinal image data effectively, affording an opportunity for better medical interpretation and subsequent processing. PMID:27388503

  4. High dynamic range infrared images detail enhancement based on local edge preserving filter

    NASA Astrophysics Data System (ADS)

    Song, Qiong; Wang, Yuehuan; Bai, Kun

    2016-07-01

    In the field of infrared (IR) image processing, displaying a high dynamic range (HDR) image on a low dynamic range display equipment with a natural visual effect, clear details on local areas and less artifacts is an important issue. In this paper, we present a new approach to display HDR IR images with contrast enhancement. First, the local edge-preserving filter (LEPF) is utilized to separate the image into a base layer and detail layer(s). After the filtering procedure, we use an adaptive Gamma transformation to adjust the gray distribution of the base layer, and stretch the detail layer based on a human visual effect principle. Then, we recombine the detail layer and base layer to obtain the enhance output. Finally, we adjust the luminance of output by applying multiple exposure fusion method. The experimental results demonstrate that our proposed method can provide a significant performance in terms of enhancing details and less artifacts than the state of the arts.

  5. Image enhancement circuit using nonlinear processing curve and constrained histogram range equalization

    NASA Astrophysics Data System (ADS)

    Cvetkovic, Sascha D.; de With, Peter H. N.

    2004-01-01

    For real-time imaging in surveillance applications, image fidelity is of primary importance to ensure customer confidence. The obtained image fidelity is a result from amongst others dynamic range expansion and video signal enhancement. The dynamic range of the signal needs adaptation, because the sensor signal has a much larger range than the standard CRT display. The signal enhancement should accommodate for the widely varying light and scene conditions and user scenarios of the equipment. This paper proposes a new system to combine dynamic range and enhancement processing, offering a strongly improved picture quality for surveillance applications. The key to our solution is that we use Non-Linear Processing (NLP) with a so-called Constrained Histogram Range Equalization (CHRE). The NLP transforms the digitized high-dynamic luminance sensor signal such that details of the low-luminance parts are enhanced, while avoiding detail losses in the high-luminance areas. The CHRE technique enhances visibility of the global contrast for the camera signal without significant information loss in the statistically less relevant areas. Evaluations of this proposal have shown clear improvements of the perceptual image quality. An additional advantage is that the new scheme is adaptable and allows the concatenation of further enhancement techniques without sacrificing the obtained picture quality improvement.

  6. CW-THz image contrast enhancement using wavelet transform and Retinex

    NASA Astrophysics Data System (ADS)

    Chen, Lin; Zhang, Min; Hu, Qi-fan; Huang, Ying-Xue; Liang, Hua-Wei

    2015-10-01

    To enhance continuous wave terahertz (CW-THz) scanning images contrast and denoising, a method based on wavelet transform and Retinex theory was proposed. In this paper, the factors affecting the quality of CW-THz images were analysed. Second, an approach of combination of the discrete wavelet transform (DWT) and a designed nonlinear function in wavelet domain for the purpose of contrast enhancing was applied. Then, we combine the Retinex algorithm for further contrast enhancement. To evaluate the effectiveness of the proposed method in qualitative and quantitative, it was compared with the adaptive histogram equalization method, the homomorphic filtering method and the SSR(Single-Scale-Retinex) method. Experimental results demonstrated that the presented algorithm can effectively enhance the contrast of CW-THZ image and obtain better visual effect.

  7. Enhancing Student Motivation and Learning within Adaptive Tutors

    ERIC Educational Resources Information Center

    Ostrow, Korinn S.

    2015-01-01

    My research is rooted in improving K-12 educational practice using motivational facets made possible through adaptive tutoring systems. In an attempt to isolate best practices within the science of learning, I conduct randomized controlled trials within ASSISTments, an online adaptive tutoring system that provides assistance and assessment to…

  8. Imaging microscopic structures in pathological retinas using a flood-illumination adaptive optics retinal camera

    NASA Astrophysics Data System (ADS)

    Viard, Clément; Nakashima, Kiyoko; Lamory, Barbara; Pâques, Michel; Levecq, Xavier; Château, Nicolas

    2011-03-01

    This research is aimed at characterizing in vivo differences between healthy and pathological retinal tissues at the microscopic scale using a compact adaptive optics (AO) retinal camera. Tests were performed in 120 healthy eyes and 180 eyes suffering from 19 different pathological conditions, including age-related maculopathy (ARM), glaucoma and rare diseases such as inherited retinal dystrophies. Each patient was first examined using SD-OCT and infrared SLO. Retinal areas of 4°x4° were imaged using an AO flood-illumination retinal camera based on a large-stroke deformable mirror. Contrast was finally enhanced by registering and averaging rough images using classical algorithms. Cellular-resolution images could be obtained in most cases. In ARM, AO images revealed granular contents in drusen, which were invisible in SLO or OCT images, and allowed the observation of the cone mosaic between drusen. In glaucoma cases, visual field was correlated to changes in cone visibility. In inherited retinal dystrophies, AO helped to evaluate cone loss across the retina. Other microstructures, slightly larger in size than cones, were also visible in several retinas. AO provided potentially useful diagnostic and prognostic information in various diseases. In addition to cones, other microscopic structures revealed by AO images may also be of interest in monitoring retinal diseases.

  9. An optimized adaptive optics experimental setup for in vivo retinal imaging

    NASA Astrophysics Data System (ADS)

    Balderas-Mata, S. E.; Valdivieso González, L. G.; Ramírez Zavaleta, G.; López Olazagasti, E.; Tepichin Rodriguez, E.

    2012-10-01

    The use of Adaptive Optics (AO) in ophthalmologic instruments to image human retinas has been probed to improve the imaging lateral resolution, by correcting both static and dynamic aberrations inherent in human eyes. Typically, the configuration of the AO arm uses an infrared beam from a superluminescent diode (SLD), which is focused on the retina, acting as a point source. The back reflected light emerges through the eye optical system bringing with it the aberrations of the cornea. The aberrated wavefront is measured with a Shack - Hartmann wavefront sensor (SHWFS). However, the aberrations in the optical imaging system can reduced the performance of the wave front correction. The aim of this work is to present an optimized first stage AO experimental setup for in vivo retinal imaging. In our proposal, the imaging optical system has been designed in order to reduce spherical aberrations due to the lenses. The ANSI Standard is followed assuring the safety power levels. The performance of the system will be compared with a commercial aberrometer. This system will be used as the AO arm of a flood-illuminated fundus camera system for retinal imaging. We present preliminary experimental results showing the enhancement.

  10. Image enhancement by adjusting the contrast of spatial frequencies

    NASA Astrophysics Data System (ADS)

    Yang, Ching-Chung

    2008-02-01

    We demonstrate a brand-new method for image enhancement by adjusting the contrast of different spatial frequencies. Fine characteristics of an image are well enhanced with negligible side effects. This method is easy to implement owing to its simple optical basis.

  11. Adaptive distance metric learning for diffusion tensor image segmentation.

    PubMed

    Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C N; Chu, Winnie C W

    2014-01-01

    High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.

  12. Adaptive Distance Metric Learning for Diffusion Tensor Image Segmentation

    PubMed Central

    Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C. N.; Chu, Winnie C. W.

    2014-01-01

    High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework. PMID:24651858

  13. Adaptive optics retinal imaging in the living mouse eye.

    PubMed

    Geng, Ying; Dubra, Alfredo; Yin, Lu; Merigan, William H; Sharma, Robin; Libby, Richard T; Williams, David R

    2012-04-01

    Correction of the eye's monochromatic aberrations using adaptive optics (AO) can improve the resolution of in vivo mouse retinal images [Biss et al., Opt. Lett. 32(6), 659 (2007) and Alt et al., Proc. SPIE 7550, 755019 (2010)], but previous attempts have been limited by poor spot quality in the Shack-Hartmann wavefront sensor (SHWS). Recent advances in mouse eye wavefront sensing using an adjustable focus beacon with an annular beam profile have improved the wavefront sensor spot quality [Geng et al., Biomed. Opt. Express 2(4), 717 (2011)], and we have incorporated them into a fluorescence adaptive optics scanning laser ophthalmoscope (AOSLO). The performance of the instrument was tested on the living mouse eye, and images of multiple retinal structures, including the photoreceptor mosaic, nerve fiber bundles, fine capillaries and fluorescently labeled ganglion cells were obtained. The in vivo transverse and axial resolutions of the fluorescence channel of the AOSLO were estimated from the full width half maximum (FWHM) of the line and point spread functions (LSF and PSF), and were found to be better than 0.79 μm ± 0.03 μm (STD)(45% wider than the diffraction limit) and 10.8 μm ± 0.7 μm (STD)(two times the diffraction limit), respectively. The axial positional accuracy was estimated to be 0.36 μm. This resolution and positional accuracy has allowed us to classify many ganglion cell types, such as bistratified ganglion cells, in vivo.

  14. Adaptive optics retinal imaging in the living mouse eye

    PubMed Central

    Geng, Ying; Dubra, Alfredo; Yin, Lu; Merigan, William H.; Sharma, Robin; Libby, Richard T.; Williams, David R.

    2012-01-01

    Correction of the eye’s monochromatic aberrations using adaptive optics (AO) can improve the resolution of in vivo mouse retinal images [Biss et al., Opt. Lett. 32(6), 659 (2007) and Alt et al., Proc. SPIE 7550, 755019 (2010)], but previous attempts have been limited by poor spot quality in the Shack-Hartmann wavefront sensor (SHWS). Recent advances in mouse eye wavefront sensing using an adjustable focus beacon with an annular beam profile have improved the wavefront sensor spot quality [Geng et al., Biomed. Opt. Express 2(4), 717 (2011)], and we have incorporated them into a fluorescence adaptive optics scanning laser ophthalmoscope (AOSLO). The performance of the instrument was tested on the living mouse eye, and images of multiple retinal structures, including the photoreceptor mosaic, nerve fiber bundles, fine capillaries and fluorescently labeled ganglion cells were obtained. The in vivo transverse and axial resolutions of the fluorescence channel of the AOSLO were estimated from the full width half maximum (FWHM) of the line and point spread functions (LSF and PSF), and were found to be better than 0.79 μm ± 0.03 μm (STD)(45% wider than the diffraction limit) and 10.8 μm ± 0.7 μm (STD)(two times the diffraction limit), respectively. The axial positional accuracy was estimated to be 0.36 μm. This resolution and positional accuracy has allowed us to classify many ganglion cell types, such as bistratified ganglion cells, in vivo. PMID:22574260

  15. Algorithms for contrast enhancement of electronic portal images

    NASA Astrophysics Data System (ADS)

    Díez, S.; Sánchez, S.

    2015-11-01

    An implementation of two new automatized image processing algorithms for contrast enhancement of portal images is presented as suitable tools which facilitate the setup verification and visualization of patients during radiotherapy treatments. In the first algorithm, called Automatic Segmentation and Histogram Stretching (ASHS), the portal image is automatically segmented in two sub-images delimited by the conformed treatment beam: one image consisting of the imaged patient obtained directly from the radiation treatment field, and the second one is composed of the imaged patient outside it. By segmenting the original image, a histogram stretching can be independently performed and improved in both regions. The second algorithm involves a two-step process. In the first step, a Normalization to Local Mean (NLM), an inverse restoration filter is applied by dividing pixel by pixel a portal image by its blurred version. In the second step, named Lineally Combined Local Histogram Equalization (LCLHE), the contrast of the original image is strongly improved by a Local Contrast Enhancement (LCE) algorithm, revealing the anatomical structures of patients. The output image is lineally combined with a portal image of the patient. Finally the output images of the previous algorithms (NLM and LCLHE) are lineally combined, once again, in order to obtain a contrast enhanced image. These two algorithms have been tested on several portal images with great results.

  16. Enhancing Functional Performance using Sensorimotor Adaptability Training Programs

    NASA Technical Reports Server (NTRS)

    Bloomberg, J. J.; Mulavara, A. P.; Peters, B. T.; Brady, R.; Audas, C.; Ruttley, T. M.; Cohen, H. S.

    2009-01-01

    During the acute phase of adaptation to novel gravitational environments, sensorimotor disturbances have the potential to disrupt the ability of astronauts to perform functional tasks. The goal of this project is to develop a sensorimotor adaptability (SA) training program designed to facilitate recovery of functional capabilities when astronauts transition to different gravitational environments. The project conducted a series of studies that investigated the efficacy of treadmill training combined with a variety of sensory challenges designed to increase adaptability including alterations in visual flow, body loading, and support surface stability.

  17. Thermally Enhanced Photoacoustic Radar Imaging of Biotissues

    NASA Astrophysics Data System (ADS)

    Wang, Wei; Mandelis, Andreas

    2015-06-01

    The signal-to-noise ratio (SNR) and imaging depth of photoacoustic (PA) imaging remain limited for clinical applications. The temperature can influence PA signals; the SNR of PA signals can be increased at higher temperatures. Therefore, the imaging quality and depth can be improved by the assistance of heating. Experimental results showed that the maximum imaging depth can be doubled by raising the temperature of the absorbers ( ex-vivo beef muscle) uniformly from to , and the SNR can be increased.

  18. Automatic segmentation of canine retinal OCT using adaptive gradient enhancement and region growing

    NASA Astrophysics Data System (ADS)

    He, Yufan; Sun, Yankui; Chen, Min; Zheng, Yuanjie; Liu, Hui; Leon, Cecilia; Beltran, William; Gee, James C.

    2016-03-01

    In recent years, several studies have shown that the canine retina model offers important insight for our understanding of human retinal diseases. Several therapies developed to treat blindness in such models have already moved onto human clinical trials, with more currently under development [1]. Optical coherence tomography (OCT) offers a high resolution imaging modality for performing in-vivo analysis of the retinal layers. However, existing algorithms for automatically segmenting and analyzing such data have been mostly focused on the human retina. As a result, canine retinal images are often still being analyzed using manual segmentations, which is a slow and laborious task. In this work, we propose a method for automatically segmenting 5 boundaries in canine retinal OCT. The algorithm employs the position relationships between different boundaries to adaptively enhance the gradient map. A region growing algorithm is then used on the enhanced gradient maps to find the five boundaries separately. The automatic segmentation was compared against manual segmentations showing an average absolute error of 5.82 +/- 4.02 microns.

  19. High-accuracy wavefront control for retinal imaging with Adaptive-Influence-Matrix Adaptive Optics

    PubMed Central

    Zou, Weiyao; Burns, Stephen A.

    2010-01-01

    We present an iterative technique for improving adaptive optics (AO) wavefront correction for retinal imaging, called the Adaptive-Influence-Matrix (AIM) method. This method is based on the fact that the deflection-to-voltage relation of common deformable mirrors used in AO are nonlinear, and the fact that in general the wavefront errors of the eye can be considered to be composed of a static, non-zero wavefront error (such as the defocus and astigmatism), and a time-varying wavefront error. The aberrated wavefront is first corrected with a generic influence matrix, providing a mirror compensation figure for the static wavefront error. Then a new influence matrix that is more accurate for the specific static wavefront error is calibrated based on the mirror compensation figure. Experimental results show that with the AIM method the AO wavefront correction accuracy can be improved significantly in comparison to the generic AO correction. The AIM method is most useful in AO modalities where there are large static contributions to the wavefront aberrations. PMID:19997241

  20. Aberration correction during real time in vivo imaging of bone marrow with sensorless adaptive optics confocal microscope

    NASA Astrophysics Data System (ADS)

    Wang, Zhibin; Wei, Dan; Wei, Ling; He, Yi; Shi, Guohua; Wei, Xunbin; Zhang, Yudong

    2014-08-01

    We have demonstrated adaptive correction of specimen-induced aberration during in vivo imaging of mouse bone marrow vasculature with confocal fluorescence microscopy. Adaptive optics system was completed with wavefront sensorless correction scheme based on stochastic parallel gradient descent algorithm. Using image sharpness as the optimization metric, aberration correction was performed based upon Zernike polynomial modes. The experimental results revealed the improved signal and resolution leading to a substantially enhanced image contrast with aberration correction. The image quality of vessels at 38- and 75-μm depth increased three times and two times, respectively. The corrections allowed us to detect clearer bone marrow vasculature structures at greater contrast and improve the signal-to-noise ratio.

  1. Resolution Enhancement of Spaceborne Radiometer Images

    NASA Technical Reports Server (NTRS)

    Krim, Hamid

    2001-01-01

    Our progress over the last year has been along several dimensions: 1. Exploration and understanding of Earth Observatory System (EOS) mission with available data from NASA. 2. Comprehensive review of state of the art techniques and uncovering of limitations to be investigated (e.g. computational, algorithmic ...). and 3. Preliminary development of resolution enhancement algorithms. With the advent of well-collaborated satellite microwave radiometers, it is now possible to obtain long time series of geophysical parameters that are important for studying the global hydrologic cycle and earth radiation budget. Over the world's ocean, these radiometers simultaneously measure profiles of air temperature and the three phases of atmospheric water (vapor, liquid, and ice). In addition, surface parameters such as the near surface wind speed, the sea surface temperature, and the sea ice type and concentration can be retrieved. The special sensor microwaves imager SSM/I has wide application in atmospheric remote sensing over the ocean and provide essential inputs to numerical weather-prediction models. SSM/I data has also been used for land and ice studies, including snow cover classification measurements of soil and plant moisture contents, atmospheric moisture over land, land surface temperature and mapping polar ice. The brightness temperature observed by SSM/I is function of the effective brightness temperature of the earth's surface and the emission scattering and attenuation of the atmosphere. Advanced Microwave Scanning Radiometer (AMSR) is a new instrument that will measure the earth radiation over the spectral range from 7 to 90 GHz. Over the world's ocean, it will be possible to retrieve the four important geographical parameters SST, wind speed, vertically integrated water vapor, vertically integrated cloud liquid water L.

  2. Multi-scale Morphological Image Enhancement of Chest Radiographs by a Hybrid Scheme

    PubMed Central

    Alavijeh, Fatemeh Shahsavari; Mahdavi-Nasab, Homayoun

    2015-01-01

    Chest radiography is a common diagnostic imaging test, which contains an enormous amount of information about a patient. However, its interpretation is highly challenging. The accuracy of the diagnostic process is greatly influenced by image processing algorithms; hence enhancement of the images is indispensable in order to improve visibility of the details. This paper aims at improving radiograph parameters such as contrast, sharpness, noise level, and brightness to enhance chest radiographs, making use of a triangulation method. Here, contrast limited adaptive histogram equalization technique and noise suppression are simultaneously performed in wavelet domain in a new scheme, followed by morphological top-hat and bottom-hat filtering. A unique implementation of morphological filters allows for adjustment of the image brightness and significant enhancement of the contrast. The proposed method is tested on chest radiographs from Japanese Society of Radiological Technology database. The results are compared with conventional enhancement techniques such as histogram equalization, contrast limited adaptive histogram equalization, Retinex, and some recently proposed methods to show its strengths. The experimental results reveal that the proposed method can remarkably improve the image contrast while keeping the sensitive chest tissue information so that radiologists might have a more precise interpretation. PMID:25709942

  3. Infrared image detail enhancement approach based on improved joint bilateral filter

    NASA Astrophysics Data System (ADS)

    Liu, Ning; Chen, Xiaohong

    2016-07-01

    In this paper, we proposed a new infrared image detail enhancement approach. This approach could not only achieve the goal of enhancing the digital detail, but also make the processed image much closer to the real situation. Inspired by the joint-bilateral filter, two adjacent images were utilized to calculate the kernel functions in order to distinguish the detail information from the raw image. We also designed a new kernel function to modify the joint-bilateral filter and to eliminate the gradient reversal artifacts caused by the non-linear filtering. The new kernel is based on an adaptive emerge coefficient to realize the detail layer determination. The detail information was modified by the adaptive emerge coefficient along with two key parameters to realize the detail enhancement. Finally, we combined the processed detail layer with the base layer and rearrange the high dynamic image into monitor-suited low dynamic range to achieve better visual effect. Numerical calculation showed that this new technology has the best value compare to the previous research in detail enhancement. Figures and data flowcharts were demonstrated in the paper.

  4. The adaptive FEM elastic model for medical image registration.

    PubMed

    Zhang, Jingya; Wang, Jiajun; Wang, Xiuying; Feng, Dagan

    2014-01-01

    This paper proposes an adaptive mesh refinement strategy for the finite element method (FEM) based elastic registration model. The signature matrix for mesh refinement takes into account the regional intensity variance and the local deformation displacement. The regional intensity variance reflects detailed information for improving registration accuracy and the deformation displacement fine-tunes the mesh refinement for a more efficient algorithm. The gradient flows of two different similarity metrics, the sum of the squared difference and the spatially encoded mutual information for the mono-modal and multi-modal registrations, are used to derive external forces to drive the model to the equilibrium state. We compared our approach to three other models: (1) the conventional multi-resolution FEM registration algorithm; (2) the FEM elastic method that uses variation information for mesh refinement; and (3) the robust block matching based registration. Comparisons among different methods in a dataset with 20 CT image pairs upon artificial deformation demonstrate that our registration method achieved significant improvement in accuracies. Experimental results in another dataset of 40 real medical image pairs for both mono-modal and multi-modal registrations also show that our model outperforms the other three models in its accuracy.

  5. IMAGE resolution enhancement by using discrete and stationary wavelet decomposition.

    PubMed

    Demirel, Hasan; Anbarjafari, Gholamreza

    2011-05-01

    In this correspondence, the authors propose an image resolution enhancement technique based on interpolation of the high frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The edges are enhanced by introducing an intermediate stage by using stationary wavelet transform (SWT). DWT is applied in order to decompose an input image into different subbands. Then the high frequency subbands as well as the input image are interpolated. The estimated high frequency subbands are being modified by using high frequency subband obtained through SWT. Then all these subbands are combined to generate a new high resolution image by using inverse DWT (IDWT). The quantitative and visual results are showing the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques.

  6. Naturalness preserved enhancement algorithm for non-uniform illumination images.

    PubMed

    Wang, Shuhang; Zheng, Jin; Hu, Hai-Miao; Li, Bo

    2013-09-01

    Image enhancement plays an important role in image processing and analysis. Among various enhancement algorithms, Retinex-based algorithms can efficiently enhance details and have been widely adopted. Since Retinex-based algorithms regard illumination removal as a default preference and fail to limit the range of reflectance, the naturalness of non-uniform illumination images cannot be effectively preserved. However, naturalness is essential for image enhancement to achieve pleasing perceptual quality. In order to preserve naturalness while enhancing details, we propose an enhancement algorithm for non-uniform illumination images. In general, this paper makes the following three major contributions. First, a lightness-order-error measure is proposed to access naturalness preservation objectively. Second, a bright-pass filter is proposed to decompose an image into reflectance and illumination, which, respectively, determine the details and the naturalness of the image. Third, we propose a bi-log transformation, which is utilized to map the illumination to make a balance between details and naturalness. Experimental results demonstrate that the proposed algorithm can not only enhance the details but also preserve the naturalness for non-uniform illumination images. PMID:23661319

  7. Adaptive Sensor Optimization and Cognitive Image Processing Using Autonomous Optical Neuroprocessors

    SciTech Connect

    CAMERON, STEWART M.

    2001-10-01

    Measurement and signal intelligence demands has created new requirements for information management and interoperability as they affect surveillance and situational awareness. Integration of on-board autonomous learning and adaptive control structures within a remote sensing platform architecture would substantially improve the utility of intelligence collection by facilitating real-time optimization of measurement parameters for variable field conditions. A problem faced by conventional digital implementations of intelligent systems is the conflict between a distributed parallel structure on a sequential serial interface functionally degrading bandwidth and response time. In contrast, optically designed networks exhibit the massive parallelism and interconnect density needed to perform complex cognitive functions within a dynamic asynchronous environment. Recently, all-optical self-organizing neural networks exhibiting emergent collective behavior which mimic perception, recognition, association, and contemplative learning have been realized using photorefractive holography in combination with sensory systems for feature maps, threshold decomposition, image enhancement, and nonlinear matched filters. Such hybrid information processors depart from the classical computational paradigm based on analytic rules-based algorithms and instead utilize unsupervised generalization and perceptron-like exploratory or improvisational behaviors to evolve toward optimized solutions. These systems are robust to instrumental systematics or corrupting noise and can enrich knowledge structures by allowing competition between multiple hypotheses. This property enables them to rapidly adapt or self-compensate for dynamic or imprecise conditions which would be unstable using conventional linear control models. By incorporating an intelligent optical neuroprocessor in the back plane of an imaging sensor, a broad class of high-level cognitive image analysis problems including geometric

  8. Bas-relief map using texture analysis with application to live enhancement of ultrasound images.

    PubMed

    Du, Huarui; Ma, Rui; Wang, Xiaoying; Zhang, Jue; Fang, Jing

    2015-05-01

    For ultrasound imaging, speckle is one of the most important factors in the degradation of contrast resolution because it masks meaningful texture and has the potential to interfere with diagnosis. It is expected that researchers would explore appropriate ways to reduce the speckle noise, to find the edges of structures and enhance weak borders between different organs in ultrasound imaging. Inspired by the principle of differential interference contrast microscopy, a "bas-relief map" is proposed that depicts the texture structure of ultrasound images. Based on a bas-relief map, an adaptive bas-relief filter was developed for ultrafast despeckling. Subsequently, an edge map was introduced to enhance the edges of images in real time. The holistic bas-relief map approach has been used experimentally with synthetic phantoms and digital ultrasound B-scan images of liver, kidney and gallbladder. Based on the visual inspection and the performance metrics of the despeckled images, it was found that the bas-relief map approach is capable of effectively reducing the speckle while significantly enhancing contrast and tissue boundaries for ultrasonic images, and its speckle reduction ability is comparable to that of Kuan, Lee and Frost filters. Meanwhile, the proposed technique could preserve more intra-region details compared with the popular speckle reducing anisotropic diffusion technique and more effectively enhance edges. In addition, the adaptive bas-relief filter was much less time consuming than the Kuan, Lee and Frost filter and speckle reducing anisotropic diffusion techniques. The bas-relief map strategy is effective for speckle reduction and live enhancement of ultrasound images, and can provide a valuable tool for clinical diagnosis.

  9. Infrared image enhancement based on atmospheric scattering model and histogram equalization

    NASA Astrophysics Data System (ADS)

    Li, Yi; Zhang, Yunfeng; Geng, Aihui; Cao, Lihua; Chen, Juan

    2016-09-01

    Infrared images are fuzzy due to the special imaging technology of infrared sensor. In order to achieve contrast enhancement and gain clear edge details from a fuzzy infrared image, we propose an efficient enhancement method based on atmospheric scattering model and histogram equalization. The novel algorithm optimizes and improves the visual image haze remove method which combines the characteristics of the fuzzy infrared images. Firstly, an average filtering operation is presented to get the estimation of coarse transmission rate. Then we get the fuzzy free image through self-adaptive transmission rate calculated with the statistics information of original infrared image. Finally, to deal with low lighting problem of fuzzy free image, we propose a sectional plateau histogram equalization method which is capable of background suppression. Experimental results show that the performance and efficiency of the proposed algorithm are pleased, compared to four other algorithms in both subjective observation and objective quantitative evaluation. In addition, the proposed algorithm is competent to enhance infrared image for different applications under different circumstances.

  10. ACTIVE-EYES: an adaptive pixel-by-pixel image-segmentation sensor architecture for high-dynamic-range hyperspectral imaging.

    PubMed

    Christensen, Marc P; Euliss, Gary W; McFadden, Michael J; Coyle, Kevin M; Milojkovic, Predrag; Haney, Michael W; van der Gracht, Joeseph; Athale, Ravindra A

    2002-10-10

    The ACTIVE-EYES (adaptive control for thermal imagers via electro-optic elements to yield an enhanced sensor) architecture, an adaptive image-segmentation and processing architecture, based on digital micromirror (DMD) array technology, is described. The concept provides efficient front-end processing of multispectral image data by adaptively segmenting and routing portions of the scene data concurrently to an imager and a spectrometer. The goal is to provide a large reduction in the amount of data required to be sensed in a multispectral imager by means of preprocessing the data to extract the most useful spatial and spectral information during detection. The DMD array provides the flexibility to perform a wide range of spatial and spectral analyses on the scene data. The spatial and spectral processing for different portions of the input scene can be tailored in real time to achieve a variety of preprocessing functions. Since the detected intensity of individual pixels may be controlled, the spatial image can be analyzed with gain varied on a pixel-by-pixel basis to enhance dynamic range. Coarse or fine spectral resolution can be achieved in the spectrometer by use of dynamically controllable or addressable dispersion elements. An experimental prototype, which demonstrated the segmentation between an imager and a grating spectrometer, was demonstrated and shown to achieve programmable pixelated intensity control. An information theoretic analysis of the dynamic-range control aspect was conducted to predict the performance enhancements that might be achieved with this architecture. The results indicate that, with a properly configured algorithm, the concept achieves the greatest relative information recovery from a detected image when the scene is made up of a relatively large area of moderate-dynamic-range pixels and a relatively smaller area of strong pixels that would tend to saturate a conventional sensor. PMID:12389978

  11. Adaptive femtosecond control using feedback from three-dimensional momentum images

    NASA Astrophysics Data System (ADS)

    Wells, E.

    2011-05-01

    Shaping ultrafast laser pulses using adaptive feedback is a proven technique for manipulating dynamics in molecular systems with no readily apparent control mechanism. Commonly employed feedback signals include fluorescence or ion yield, which may not uniquely identify the final state. Raw velocity map images, which contain a two-dimensional representation of the full three-dimensional photofragment momentum vector, are a more specific feedback source. The raw images, however, are limited by an azimuthal ambiguity which is usually removed in offline processing. By implementing a rapid inversion procedure based upon the onion-peeling technique, we are able to incorporate three-dimensional momentum information directly into the adaptive control loop. This method enables more targeted control experiments. Two examples are used to demonstrate the utility of this feedback. First, double ionization of CO produces C+ and O+ fragments ejected both perpendicular and parallel to the laser polarization with kinetic energy release of ~6 eV. Both suppression and enhancement of the perpendicular transitions relative to the parallel transitions are demonstrated. Second, double ionization of acetylene can lead to both HCCH2+ and HHCC2+ isomers. We select between these outcomes using the angular information contained in the CH+ and CH2+images. Supported by National Science Foundation award PHY-0969687 and the Chemical Sciences, Geosciences, and Biosciences Division, Office of Basic Energy Science, Office of Science, US Department of Energy.

  12. Adapting content-based image retrieval techniques for the semantic annotation of medical images.

    PubMed

    Kumar, Ashnil; Dyer, Shane; Kim, Jinman; Li, Changyang; Leong, Philip H W; Fulham, Michael; Feng, Dagan

    2016-04-01

    The automatic annotation of medical images is a prerequisite for building comprehensive semantic archives that can be used to enhance evidence-based diagnosis, physician education, and biomedical research. Annotation also has important applications in the automatic generation of structured radiology reports. Much of the prior research work has focused on annotating images with properties such as the modality of the image, or the biological system or body region being imaged. However, many challenges remain for the annotation of high-level semantic content in medical images (e.g., presence of calcification, vessel obstruction, etc.) due to the difficulty in discovering relationships and associations between low-level image features and high-level semantic concepts. This difficulty is further compounded by the lack of labelled training data. In this paper, we present a method for the automatic semantic annotation of medical images that leverages techniques from content-based image retrieval (CBIR). CBIR is a well-established image search technology that uses quantifiable low-level image features to represent the high-level semantic content depicted in those images. Our method extends CBIR techniques to identify or retrieve a collection of labelled images that have similar low-level features and then uses this collection to determine the best high-level semantic annotations. We demonstrate our annotation method using retrieval via weighted nearest-neighbour retrieval and multi-class classification to show that our approach is viable regardless of the underlying retrieval strategy. We experimentally compared our method with several well-established baseline techniques (classification and regression) and showed that our method achieved the highest accuracy in the annotation of liver computed tomography (CT) images.

  13. An approach to integrate the human vision psychology and perception knowledge into image enhancement

    NASA Astrophysics Data System (ADS)

    Wang, Hui; Huang, Xifeng; Ping, Jiang

    2009-07-01

    Image enhancement is very important image preprocessing technology especially when the image is captured in the poor imaging condition or dealing with the high bits image. The benefactor of image enhancement either may be a human observer or a computer vision process performing some kind of higher-level image analysis, such as target detection or scene understanding. One of the main objects of the image enhancement is getting a high dynamic range image and a high contrast degree image for human perception or interpretation. So, it is very necessary to integrate either empirical or statistical human vision psychology and perception knowledge into image enhancement. The human vision psychology and perception claims that humans' perception and response to the intensity fluctuation δu of visual signals are weighted by the background stimulus u, instead of being plainly uniform. There are three main laws: Weber's law, Weber- Fechner's law and Stevens's Law that describe this phenomenon in the psychology and psychophysics. This paper will integrate these three laws of the human vision psychology and perception into a very popular image enhancement algorithm named Adaptive Plateau Equalization (APE). The experiments were done on the high bits star image captured in night scene and the infrared-red image both the static image and the video stream. For the jitter problem in the video stream, this algorithm reduces this problem using the difference between the current frame's plateau value and the previous frame's plateau value to correct the current frame's plateau value. Considering the random noise impacts, the pixel value mapping process is not only depending on the current pixel but the pixels in the window surround the current pixel. The window size is usually 3×3. The process results of this improved algorithms is evaluated by the entropy analysis and visual perception analysis. The experiments' result showed the improved APE algorithms improved the quality of the

  14. Coherence gated wavefront sensorless adaptive optics for two photon excited fluorescence retinal imaging (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Jian, Yifan; Cua, Michelle; Bonora, Stefano; Pugh, Edward N.; Zawadzki, Robert J.; Sarunic, Marinko V.

    2016-03-01

    We present a novel system for adaptive optics two photon imaging. We utilize the bandwidth of the femtosecond excitation beam to perform coherence gated imaging (OCT) of the sample. The location of the focus is directly observable in the cross sectional OCT images, and adjusted to the desired depth plane. Next, using real time volumetric OCT, we perform Wavefront Sensorless Adaptive Optics (WSAO) aberration correction using a multi-element adaptive lens capable of correcting up to 4th order Zernike polynomials. The aberration correction is performed based on an image quality metric, for example intensity. The optimization time is limited only by the OCT acquisition rate, and takes ~30s. Following aberration correction, two photon fluorescence images are acquired, and compared to results without adaptive optics correction. This technique is promising for multiphoton imaging in multi-layered, scattering samples such as eye and brain, in which traditional wavefront sensing and guide-star sensorless adaptive optics approaches may not be suitable.

  15. Adaptive Optics for Satellite Imaging and Space Debris Ranging

    NASA Astrophysics Data System (ADS)

    Bennet, F.; D'Orgeville, C.; Price, I.; Rigaut, F.; Ritchie, I.; Smith, C.

    Earth's space environment is becoming crowded and at risk of a Kessler syndrome, and will require careful management for the future. Modern low noise high speed detectors allow for wavefront sensing and adaptive optics (AO) in extreme circumstances such as imaging small orbiting bodies in Low Earth Orbit (LEO). The Research School of Astronomy and Astrophysics (RSAA) at the Australian National University have been developing AO systems for telescopes between 1 and 2.5m diameter to image and range orbiting satellites and space debris. Strehl ratios in excess of 30% can be achieved for targets in LEO with an AO loop running at 2kHz, allowing the resolution of small features (<30cm) and the capability to determine object shape and spin characteristics. The AO system developed at RSAA consists of a high speed EMCCD Shack-Hartmann wavefront sensor, a deformable mirror (DM), and realtime computer (RTC), and an imaging camera. The system works best as a laser guide star system but will also function as a natural guide star AO system, with the target itself being the guide star. In both circumstances tip-tilt is provided by the target on the imaging camera. The fast tip-tilt modes are not corrected optically, and are instead removed by taking images at a moderate speed (>30Hz) and using a shift and add algorithm. This algorithm can also incorporate lucky imaging to further improve the final image quality. A similar AO system for space debris ranging is also in development in collaboration with Electro Optic Systems (EOS) and the Space Environment Management Cooperative Research Centre (SERC), at the Mount Stromlo Observatory in Canberra, Australia. The system is designed for an AO corrected upward propagated 1064nm pulsed laser beam, from which time of flight information is used to precisely range the target. A 1.8m telescope is used for both propagation and collection of laser light. A laser guide star, Shack-Hartmann wavefront sensor, and DM are used for high order

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

    USGS Publications Warehouse

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

    2002-01-01

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

  17. Curved-Region-Based Ridge Frequency Estimation and Curved Gabor Filters for Fingerprint Image Enhancement

    NASA Astrophysics Data System (ADS)

    Gottschlich, Carsten

    2012-04-01

    Gabor filters play an important role in many application areas for the enhancement of various types of images and the extraction of Gabor features. For the purpose of enhancing curved structures in noisy images, we introduce curved Gabor filters which locally adapt their shape to the direction of flow. These curved Gabor filters enable the choice of filter parameters which increase the smoothing power without creating artifacts in the enhanced image. In this paper, curved Gabor filters are applied to the curved ridge and valley structure of low-quality fingerprint images. First, we combine two orientation field estimation methods in order to obtain a more robust estimation for very noisy images. Next, curved regions are constructed by following the respective local orientation and they are used for estimating the local ridge frequency. Lastly, curved Gabor filters are defined based on curved regions and they are applied for the enhancement of low-quality fingerprint images. Experimental results on the FVC2004 databases show improvements of this approach in comparison to state-of-the-art enhancement methods.

  18. Curved-region-based ridge frequency estimation and curved Gabor filters for fingerprint image enhancement.

    PubMed

    Gottschlich, Carsten

    2012-04-01

    Gabor filters (GFs) play an important role in many application areas for the enhancement of various types of images and the extraction of Gabor features. For the purpose of enhancing curved structures in noisy images, we introduce curved GFs that locally adapt their shape to the direction of flow. These curved GFs enable the choice of filter parameters that increase the smoothing power without creating artifacts in the enhanced image. In this paper, curved GFs are applied to the curved ridge and valley structures of low-quality fingerprint images. First, we combine two orientation-field estimation methods in order to obtain a more robust estimation for very noisy images. Next, curved regions are constructed by following the respective local orientation. Subsequently, these curved regions are used for estimating the local ridge frequency. Finally, curved GFs are defined based on curved regions, and they apply the previously estimated orientations and ridge frequencies for the enhancement of low-quality fingerprint images. Experimental results on the FVC2004 databases show improvements of this approach in comparison with state-of-the-art enhancement methods.

  19. Non-linear Post Processing Image Enhancement

    NASA Technical Reports Server (NTRS)

    Hunt, Shawn; Lopez, Alex; Torres, Angel

    1997-01-01

    A non-linear filter for image post processing based on the feedforward Neural Network topology is presented. This study was undertaken to investigate the usefulness of "smart" filters in image post processing. The filter has shown to be useful in recovering high frequencies, such as those lost during the JPEG compression-decompression process. The filtered images have a higher signal to noise ratio, and a higher perceived image quality. Simulation studies comparing the proposed filter with the optimum mean square non-linear filter, showing examples of the high frequency recovery, and the statistical properties of the filter are given,

  20. The Past, Present, and Future of Image-Enhanced Endoscopy

    PubMed Central

    Jang, Jae-Young

    2015-01-01

    Despite the remarkable progress recently made to enhance the resolution of white-light endoscopy, detection, and diagnosis of premalignant lesions, such as adenomas and subtle early-stage cancers, remains a great challenge. As for example, although chromoendoscopy, such as endoscopy using indigo carmine, is useful for the early diagnosis of subtle lesions, the technique presents various disadvantages ranging from the time required for spray application of the dye and suctioning of excess dye to the increased difficulty in identifying lesions in the presence of severe inflammation and obstruction of visual field due to the pooling of solution in depressed-type lesions. To overcome these diagnostic problems associated with chromoendoscopy, research has focused on the development of endoscopes based on new optical technologies. Several types of image-enhanced endoscopy methods have recently been presented. In particular, image-enhanced endoscopy has emerged as a new paradigm for the diagnosis of gastrointestinal disorders. Image-enhanced endoscopes provide high-contrast images of lesions by means of optical or electronic technologies, including the contrast enhancement of the mucosal surface and of blood vessels. Chromoendoscopy, narrow-band imaging, i-SCAN, and flexible spectral imaging color enhancement are representative examples of image-enhanced endoscopy discussed in this paper. PMID:26668791

  1. Enhancement of coupled multichannel images using sparsity constraints.

    PubMed

    Ramakrishnan, Naveen; Ertin, Emre; Moses, Randolph L

    2010-08-01

    We consider the problem of joint enhancement of multichannel images with pixel based constraints on the multichannel data. Previous work by Cetin and Karl introduced nonquadratic regularization methods for SAR image enhancement using sparsity enforcing penalty terms. We formulate an optimization problem that jointly enhances complex-valued multichannel images while preserving the cross-channel information, which we include as constraints tying the multichannel images together. We pose this problem as a joint optimization problem with constraints. We first reformulate it as an equivalent (unconstrained) dual problem and develop a numerically-efficient method for solving it. We develop the Dual Descent method, which has low complexity, for solving the joint optimization problem. The algorithm is applied to both an interferometric synthetic aperture radar (IFSAR) problem, in which the relative phase between two complex-valued images indicate height, and to a synthetic multimodal medical image example. PMID:20236892

  2. High Resolution Near-Infrared Imaging with Tip - Adaptive Optics.

    NASA Astrophysics Data System (ADS)

    Close, Laird Miller

    1995-01-01

    The development and design of the first operational tip-tilt Cassegrain secondary mirror are presented. This system, FASTTRAC, samples image motion at up to 50 Hz by tracking either infrared (m_{k } <=q 11) or visible (mR <=q 16) guide stars up to 30" and 90" away from the science target respectively. The Steward Observatory 2.3m or 1.5m telescope secondaries act as rapid tip-tilt mirrors to stabilize image motion (<=q0.1" rms;~5 Hz -3 dB frequency) based on the motion of the guide star. FASTTRAC obtains nearly diffraction-limited resolutions in seeing conditions where D/r_circ < 4 in agreement with theoretical expectations. FASTTRAC's unique ability to guide on infrared stars has allowed the first adaptively corrected images of the heavily extincted Galactic Center to be obtained. Over a hundred excellent (0.28" < FWHM < 0.6") images have been obtained of this region. These images do not detect any long term variations in the massive black hole candidate Sgr A*'s luminosity from June 1993 to September 1995. The average infrared magnitudes observed are K = 12.1 +/- 0.3, H = 13.7 +/- 0.3 and J = 16.6 +/- 0.4 integrated over 0.5" at the position of Sgr A*. No significant rapid periodicities were observed from Sgr A* for amplitudes >=q50% of the mean flux in the period range of 3-30 minutes. It is confirmed in the latest 0.28" FWHM image that there is 0.5" "bar" of emission running East-West at the position of Sgr A* as was earlier seen by Eckart et al. 1993. The observed fluxes are consistent with an inclined accretion disk around a ~1 times 10^6 M _odot black hole. However, they are also explained by a line of hot luminous (integrated luminosity of ~10^{3.5 -4.6}L_odot) central cluster stars positionally coincident with Sgr A* naturally explaining the observed 0.5" "bar". High-resolution images with FASTTRAC guiding on a faint (R = 16) visible guide star, combined with spectra from the MMT, have shown that IRAS FSC 10214 + 4724 (z = 2.28) gains its uniquely large

  3. Enhanced Mental Image Mapping in Autism

    ERIC Educational Resources Information Center

    Soulieres, I.; Zeffiro, T. A.; Girard, M. L.; Mottron, L.

    2011-01-01

    The formation and manipulation of mental images represents a key ability for successfully solving visuospatial tasks like Wechsler's Block Design or visual reasoning problems, tasks where autistics perform at higher levels than predicted by their Wechsler IQ. Visual imagery can be used to compare two mental images, allowing judgment of their…

  4. Professional Image: Enhanced or Inhibited by Attire?

    ERIC Educational Resources Information Center

    Newton, Marguerite; Chaney, Judith

    1996-01-01

    A questionnaire about professional image and attire was completed by 56 nursing faculty (56%) and 191 students (33%). Older faculty and older students preferred more traditional attire for nurses. Faculty and students in the upper division preferred nontraditional attire. Faculty positively influenced student perceptions of professional image. (SK)

  5. Metric Learning to Enhance Hyperspectral Image Segmentation

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

    Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy.

  6. An adaptive technique to maximize lossless image data compression of satellite images

    NASA Technical Reports Server (NTRS)

    Stewart, Robert J.; Lure, Y. M. Fleming; Liou, C. S. Joe

    1994-01-01

    Data compression will pay an increasingly important role in the storage and transmission of image data within NASA science programs as the Earth Observing System comes into operation. It is important that the science data be preserved at the fidelity the instrument and the satellite communication systems were designed to produce. Lossless compression must therefore be applied, at least, to archive the processed instrument data. In this paper, we present an analysis of the performance of lossless compression techniques and develop an adaptive approach which applied image remapping, feature-based image segmentation to determine regions of similar entropy and high-order arithmetic coding to obtain significant improvements over the use of conventional compression techniques alone. Image remapping is used to transform the original image into a lower entropy state. Several techniques were tested on satellite images including differential pulse code modulation, bi-linear interpolation, and block-based linear predictive coding. The results of these experiments are discussed and trade-offs between computation requirements and entropy reductions are used to identify the optimum approach for a variety of satellite images. Further entropy reduction can be achieved by segmenting the image based on local entropy properties then applying a coding technique which maximizes compression for the region. Experimental results are presented showing the effect of different coding techniques for regions of different entropy. A rule-base is developed through which the technique giving the best compression is selected. The paper concludes that maximum compression can be achieved cost effectively and at acceptable performance rates with a combination of techniques which are selected based on image contextual information.

  7. Edge Detection on Images of Pseudoimpedance Section Supported by Context and Adaptive Transformation Model Images

    NASA Astrophysics Data System (ADS)

    Kawalec-Latała, Ewa

    2014-03-01

    Most of underground hydrocarbon storage are located in depleted natural gas reservoirs. Seismic survey is the most economical source of detailed subsurface information. The inversion of seismic section for obtaining pseudoacoustic impedance section gives the possibility to extract detailed subsurface information. The seismic wavelet parameters and noise briefly influence the resolution. Low signal parameters, especially long signal duration time and the presence of noise decrease pseudoimpedance resolution. Drawing out from measurement or modelled seismic data approximation of distribution of acoustic pseuoimpedance leads us to visualisation and images useful to stratum homogeneity identification goal. In this paper, the improvement of geologic section image resolution by use of minimum entropy deconvolution method before inversion is applied. The author proposes context and adaptive transformation of images and edge detection methods as a way to increase the effectiveness of correct interpretation of simulated images. In the paper, the edge detection algorithms using Sobel, Prewitt, Robert, Canny operators as well as Laplacian of Gaussian method are emphasised. Wiener filtering of image transformation improving rock section structure interpretation pseudoimpedance matrix on proper acoustic pseudoimpedance value, corresponding to selected geologic stratum. The goal of the study is to develop applications of image transformation tools to inhomogeneity detection in salt deposits.

  8. Construction and solution of an adaptive image-restoration model for removing blur and mixed noise

    NASA Astrophysics Data System (ADS)

    Wang, Youquan; Cui, Lihong; Cen, Yigang; Sun, Jianjun

    2016-03-01

    We establish a practical regularized least-squares model with adaptive regularization for dealing with blur and mixed noise in images. This model has some advantages, such as good adaptability for edge restoration and noise suppression due to the application of a priori spatial information obtained from a polluted image. We further focus on finding an important feature of image restoration using an adaptive restoration model with different regularization parameters in polluted images. A more important observation is that the gradient of an image varies regularly from one regularization parameter to another under certain conditions. Then, a modified graduated nonconvexity approach combined with a median filter version of a spatial information indicator is proposed to seek the solution of our adaptive image-restoration model by applying variable splitting and weighted penalty techniques. Numerical experiments show that the method is robust and effective for dealing with various blur and mixed noise levels in images.

  9. Simple Image Processing Techniques For The Contrast Enhancement Of Real-Time Digital Speckle Pattern Interferometry Fringes

    NASA Astrophysics Data System (ADS)

    Ganesan, A. R.; Kothiyal, M. P.; Sirohi, Rajpal S.

    1989-09-01

    Some simple image processing techniques are suggested that can be used for enhancing the contrast of real-time digital speckle pattern interferometry fringes. The techniques have been developed for the commercial Intellect 100 image processing system interfaced to a PDP-1 1 /23+ microcomputer, but they can be adapted to any commercial image processing system with slight modifications, if necessary, depending on the hardware configuration of the system.

  10. Towards an Adaptive Multimedia Learning Environment: Enhancing the Student Experience.

    ERIC Educational Resources Information Center

    Kurzel, Frank; Slay, Jill; Rath, Michelle; Chau, Yenha

    This paper describes the development of an adaptive multimedia learning environment that utilizes multimedia presentation techniques in its interface while still providing Internet connectivity for management and delivery purposes. The system supports the WWW as its addressing space but uses the local client areas to store media items expensive in…

  11. Adaptation Duration Dissociates Category-, Image-, and Person-Specific Processes on Face-Evoked Event-Related Potentials.

    PubMed

    Zimmer, Márta; Zbanţ, Adriana; Németh, Kornél; Kovács, Gyula

    2015-01-01

    Several studies demonstrated that face perception is biased by the prior presentation of another face, a phenomenon termed as face-related after-effect (FAE). FAE is linked to a neural signal-reduction at occipito-temporal areas and it can be observed in the amplitude modulation of the early event-related potential (ERP) components. Recently, macaque single-cell recording studies suggested that manipulating the duration of the adaptor makes the selective adaptation of different visual motion processing steps possible. To date, however, only a few studies tested the effects of adaptor duration on the electrophysiological correlates of human face processing directly. The goal of the current study was to test the effect of adaptor duration on the image-, identity-, and generic category-specific face processing steps. To this end, in a two-alternative forced choice familiarity decision task we used five adaptor durations (ranging from 200-5000 ms) and four adaptor categories: adaptor and test were identical images-Repetition Suppression (RS); adaptor and test were different images of the Same Identity (SameID); adaptor and test images depicted Different Identities (DiffID); the adaptor was a Fourier phase-randomized image (No). Behaviorally, a strong priming effect was observed in both accuracy and response times for RS compared with both DiffID and No. The electrophysiological results suggest that rapid adaptation leads to a category-specific modulation of P100, N170, and N250. In addition, both identity and image-specific processes affected the N250 component during rapid adaptation. On the other hand, prolonged (5000 ms) adaptation enhanced, and extended category-specific adaptation processes over all tested ERP components. Additionally, prolonged adaptation led to the emergence of image-, and identity-specific modulations on the N170 and P2 components as well. In other words, there was a clear dissociation among category, identity-, and image-specific processing

  12. Image enhancement methods for turbulence mitigation and the influence of different color spaces

    NASA Astrophysics Data System (ADS)

    Huebner, Claudia S.

    2015-10-01

    In mid- to long-range horizontal imaging applications it is quite often atmospheric turbulence which limits the performance of an electro-optical system rather than the design and quality of the system itself. Even weak or moderate turbulence conditions can suffice to cause significant image degradation, the predominant effects being image dancing and blurring. To mitigate these effects many different methods have been proposed, most of which use either a hardware approach, such as adaptive optics, or a software approach. A great number of these methods are highly specialized with regard to input data, e.g. aiming exclusively at very short exposure images or at infrared data. So far, only a very limited number of these methods are concerned specifically with the restoration of RGB colour video. Beside motion compensation and deblurring, contrast enhancement plays a vital part in many turbulence mitigation schemes. While most contrast enhancement techniques, such as Contrast Limited Adaptive Histogram Equalization (CLAHE) work quite well on monochrome data or single colour frames, they tend to amplify noise in a colour video stream disproportionately, especially in scenes with low contrast. Therefore, in this paper the impact of different colour spaces (RGB, LAB, HSV) on the application of such typical image enhancement techniques is discussed and evaluated with regard to suppressing temporal noise as well as to their suitability for use in software-based turbulence mitigation algorithms.

  13. Image fusion for enhanced visualization of brain imaging

    NASA Astrophysics Data System (ADS)

    Socolinsky, Diego A.; Wolff, Lawrence B.

    1999-05-01

    We present a new formalism for the treatment and understanding of multispectral imags and multisensor fusion based on first order contrast information. Although little attention has been paid to the utility of multispectral contrast, we develop a theory for multispectral contrast that enables us to produce an optimal grayscale visualization of the first order contrast of an image with an arbitrary number of bands. In particular, we consider multiple registered visualization of multi-modal medical imaging. We demonstrate how our methodology can reveal significantly more interpretive information to a radiologist or image analyst, who can use it in a number of image understanding algorithms. Existing grayscale visualization strategies are reviewed and a discussion is given as to why our algorithm performs better. A variety of experimental results from medical imagin and remotely sensed data are presented.

  14. Resolution enhancement phase-contrast imaging by microsphere digital holography

    NASA Astrophysics Data System (ADS)

    Wang, Yunxin; Guo, Sha; Wang, Dayong; Lin, Qiaowen; Rong, Lu; Zhao, Jie

    2016-05-01

    Microsphere has shown the superiority of super-resolution imaging in the traditional 2D intensity microscope. Here a microsphere digital holography approach is presented to realize the resolution enhancement phase-contrast imaging. The system is designed by combining the microsphere with the image-plane digital holography. A microsphere very close to the object can increase the resolution by transforming the object wave from the higher frequency to the lower one. The resolution enhancement amplitude and phase images can be retrieved from a single hologram. The experiments are carried on the 1D and 2D gratings, and the results demonstrate that the observed resolution has been improved, meanwhile, the phase-contrast image is obtained. The proposed method can improve the transverse resolution in all directions based on a single exposure. Furthermore, this system has extended the application of the microsphere from the conventional 2D microscopic imaging to 3D phase-contrast microscopic imaging.

  15. Optimization of background subtraction for image enhancement

    NASA Astrophysics Data System (ADS)

    Venetsky, Larry; Boczar, Ross; Lee-Own, Robert

    2013-05-01

    Analysis of foreground objects in scenery via image processing often involves a background subtraction process. This process aims to improve blob (connected component) content in the image. Quality blob content is often needed for defining regions of interest for object recognition and tracking. Three techniques are examined which optimize the background to be subtracted - genetic algorithm, an analytic solution based on convex optimization, and a related application of the CVX solver toolbox. These techniques are applied to a set of images and the results are compared. Additionally, a possible implementation architecture that uses multiple optimization techniques with subsequent arbitration to produce the best background subtraction is considered.

  16. Body Image Distortion and Exposure to Extreme Body Types: Contingent Adaptation and Cross Adaptation for Self and Other.

    PubMed

    Brooks, Kevin R; Mond, Jonathan M; Stevenson, Richard J; Stephen, Ian D

    2016-01-01

    Body size misperception is common amongst the general public and is a core component of eating disorders and related conditions. While perennial media exposure to the "thin ideal" has been blamed for this misperception, relatively little research has examined visual adaptation as a potential mechanism. We examined the extent to which the bodies of "self" and "other" are processed by common or separate mechanisms in young women. Using a contingent adaptation paradigm, experiment 1 gave participants prolonged exposure to images both of the self and of another female that had been distorted in opposite directions (e.g., expanded other/contracted self), and assessed the aftereffects using test images both of the self and other. The directions of the resulting perceptual biases were contingent on the test stimulus, establishing at least some separation between the mechanisms encoding these body types. Experiment 2 used a cross adaptation paradigm to further investigate the extent to which these mechanisms are independent. Participants were adapted either to expanded or to contracted images of their own body or that of another female. While adaptation effects were largest when adapting and testing with the same body type, confirming the separation of mechanisms reported in experiment 1, substantial misperceptions were also demonstrated for cross adaptation conditions, demonstrating a degree of overlap in the encoding of self and other. In addition, the evidence of misperception of one's own body following exposure to "thin" and to "fat" others demonstrates the viability of visual adaptation as a model of body image disturbance both for those who underestimate and those who overestimate their own size. PMID:27471447

  17. Body Image Distortion and Exposure to Extreme Body Types: Contingent Adaptation and Cross Adaptation for Self and Other

    PubMed Central

    Brooks, Kevin R.; Mond, Jonathan M.; Stevenson, Richard J.; Stephen, Ian D.

    2016-01-01

    Body size misperception is common amongst the general public and is a core component of eating disorders and related conditions. While perennial media exposure to the “thin ideal” has been blamed for this misperception, relatively little research has examined visual adaptation as a potential mechanism. We examined the extent to which the bodies of “self” and “other” are processed by common or separate mechanisms in young women. Using a contingent adaptation paradigm, experiment 1 gave participants prolonged exposure to images both of the self and of another female that had been distorted in opposite directions (e.g., expanded other/contracted self), and assessed the aftereffects using test images both of the self and other. The directions of the resulting perceptual biases were contingent on the test stimulus, establishing at least some separation between the mechanisms encoding these body types. Experiment 2 used a cross adaptation paradigm to further investigate the extent to which these mechanisms are independent. Participants were adapted either to expanded or to contracted images of their own body or that of another female. While adaptation effects were largest when adapting and testing with the same body type, confirming the separation of mechanisms reported in experiment 1, substantial misperceptions were also demonstrated for cross adaptation conditions, demonstrating a degree of overlap in the encoding of self and other. In addition, the evidence of misperception of one's own body following exposure to “thin” and to “fat” others demonstrates the viability of visual adaptation as a model of body image disturbance both for those who underestimate and those who overestimate their own size. PMID:27471447

  18. Body Image Distortion and Exposure to Extreme Body Types: Contingent Adaptation and Cross Adaptation for Self and Other.

    PubMed

    Brooks, Kevin R; Mond, Jonathan M; Stevenson, Richard J; Stephen, Ian D

    2016-01-01

    Body size misperception is common amongst the general public and is a core component of eating disorders and related conditions. While perennial media exposure to the "thin ideal" has been blamed for this misperception, relatively little research has examined visual adaptation as a potential mechanism. We examined the extent to which the bodies of "self" and "other" are processed by common or separate mechanisms in young women. Using a contingent adaptation paradigm, experiment 1 gave participants prolonged exposure to images both of the self and of another female that had been distorted in opposite directions (e.g., expanded other/contracted self), and assessed the aftereffects using test images both of the self and other. The directions of the resulting perceptual biases were contingent on the test stimulus, establishing at least some separation between the mechanisms encoding these body types. Experiment 2 used a cross adaptation paradigm to further investigate the extent to which these mechanisms are independent. Participants were adapted either to expanded or to contracted images of their own body or that of another female. While adaptation effects were largest when adapting and testing with the same body type, confirming the separation of mechanisms reported in experiment 1, substantial misperceptions were also demonstrated for cross adaptation conditions, demonstrating a degree of overlap in the encoding of self and other. In addition, the evidence of misperception of one's own body following exposure to "thin" and to "fat" others demonstrates the viability of visual adaptation as a model of body image disturbance both for those who underestimate and those who overestimate their own size.

  19. Adaptive optics images. III. 87 Kepler objects of interest

    SciTech Connect

    Dressing, Courtney D.; Dupree, Andrea K.; Adams, Elisabeth R.; Kulesa, Craig; McCarthy, Don

    2014-11-01

    The Kepler mission has revolutionized our understanding of exoplanets, but some of the planet candidates identified by Kepler may actually be astrophysical false positives or planets whose transit depths are diluted by the presence of another star. Adaptive optics images made with ARIES at the MMT of 87 Kepler Objects of Interest place limits on the presence of fainter stars in or near the Kepler aperture. We detected visual companions within 1'' for 5 stars, between 1'' and 2'' for 7 stars, and between 2'' and 4'' for 15 stars. For those systems, we estimate the brightness of companion stars in the Kepler bandpass and provide approximate corrections to the radii of associated planet candidates due to the extra light in the aperture. For all stars observed, we report detection limits on the presence of nearby stars. ARIES is typically sensitive to stars approximately 5.3 Ks magnitudes fainter than the target star within 1'' and approximately 5.7 Ks magnitudes fainter within 2'', but can detect stars as faint as ΔKs = 7.5 under ideal conditions.

  20. Patient-adaptive lesion metabolism analysis by dynamic PET images.

    PubMed

    Gao, Fei; Liu, Huafeng; Shi, Pengcheng

    2012-01-01

    Dynamic PET imaging provides important spatial-temporal information for metabolism analysis of organs and tissues, and generates a great reference for clinical diagnosis and pharmacokinetic analysis. Due to poor statistical properties of the measurement data in low count dynamic PET acquisition and disturbances from surrounding tissues, identifying small lesions inside the human body is still a challenging issue. The uncertainties in estimating the arterial input function will also limit the accuracy and reliability of the metabolism analysis of lesions. Furthermore, the sizes of the patients and the motions during PET acquisition will yield mismatch against general purpose reconstruction system matrix, this will also affect the quantitative accuracy of metabolism analyses of lesions. In this paper, we present a dynamic PET metabolism analysis framework by defining a patient adaptive system matrix to improve the lesion metabolism analysis. Both patient size information and potential small lesions are incorporated by simulations of phantoms of different sizes and individual point source responses. The new framework improves the quantitative accuracy of lesion metabolism analysis, and makes the lesion identification more precisely. The requirement of accurate input functions is also reduced. Experiments are conducted on Monte Carlo simulated data set for quantitative analysis and validation, and on real patient scans for assessment of clinical potential. PMID:23286175

  1. IR CMOS: near infrared enhanced digital imaging (Presentation Recording)

    NASA Astrophysics Data System (ADS)

    Pralle, Martin U.; Carey, James E.; Joy, Thomas; Vineis, Chris J.; Palsule, Chintamani

    2015-08-01

    SiOnyx has demonstrated imaging at light levels below 1 mLux (moonless starlight) at video frame rates with a 720P CMOS image sensor in a compact, low latency camera. Low light imaging is enabled by the combination of enhanced quantum efficiency in the near infrared together with state of the art low noise image sensor design. The quantum efficiency enhancements are achieved by applying Black Silicon, SiOnyx's proprietary ultrafast laser semiconductor processing technology. In the near infrared, silicon's native indirect bandgap results in low absorption coefficients and long absorption lengths. The Black Silicon nanostructured layer fundamentally disrupts this paradigm by enhancing the absorption of light within a thin pixel layer making 5 microns of silicon equivalent to over 300 microns of standard silicon. This results in a demonstrate 10 fold improvements in near infrared sensitivity over incumbent imaging technology while maintaining complete compatibility with standard CMOS image sensor process flows. Applications include surveillance, nightvision, and 1064nm laser see spot. Imaging performance metrics will be discussed. Demonstrated performance characteristics: Pixel size : 5.6 and 10 um Array size: 720P/1.3Mpix Frame rate: 60 Hz Read noise: 2 ele/pixel Spectral sensitivity: 400 to 1200 nm (with 10x QE at 1064nm) Daytime imaging: color (Bayer pattern) Nighttime imaging: moonless starlight conditions 1064nm laser imaging: daytime imaging out to 2Km

  2. Multi-image registration for an enhanced vision system

    NASA Astrophysics Data System (ADS)

    Hines, Glenn D.; Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

    2003-08-01

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

  3. Multi-Image Registration for an Enhanced Vision System

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  4. "Relative CIR": an image enhancement and visualization technique

    USGS Publications Warehouse

    Fleming, Michael D.

    1993-01-01

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

  5. Anomalous diffusion process applied to magnetic resonance image enhancement.

    PubMed

    Senra Filho, A C da S; Salmon, C E Garrido; Murta Junior, L O

    2015-03-21

    Diffusion process is widely applied to digital image enhancement both directly introducing diffusion equation as in anisotropic diffusion (AD) filter, and indirectly by convolution as in Gaussian filter. Anomalous diffusion process (ADP), given by a nonlinear relationship in diffusion equation and characterized by an anomalous parameters q, is supposed to be consistent with inhomogeneous media. Although classic diffusion process is widely studied and effective in various image settings, the effectiveness of ADP as an image enhancement is still unknown. In this paper we proposed the anomalous diffusion filters in both isotropic (IAD) and anisotropic (AAD) forms for magnetic resonance imaging (MRI) enhancement. Filters based on discrete implementation of anomalous diffusion were applied to noisy MRI T2w images (brain, chest and abdominal) in order to quantify SNR gains estimating the performance for the proposed anomalous filter when realistic noise is added to those images. Results show that for images containing complex structures, e.g. brain structures, anomalous diffusion presents the highest enhancements when compared to classical diffusion approach. Furthermore, ADP presented a more effective enhancement for images containing Rayleigh and Gaussian noise. Anomalous filters showed an ability to preserve anatomic edges and a SNR improvement of 26% for brain images, compared to classical filter. In addition, AAD and IAD filters showed optimum results for noise distributions that appear on extreme situations on MRI, i.e. in low SNR images with approximate Rayleigh noise distribution, and for high SNR images with Gaussian or non central χ noise distributions. AAD and IAD filter showed the best results for the parametric range 1.2 < q < 1.6, suggesting that the anomalous diffusion regime is more suitable for MRI. This study indicates the proposed anomalous filters as promising approaches in qualitative and quantitative MRI enhancement.

  6. Enhanced neutron imaging detector using optical processing

    SciTech Connect

    Hutchinson, D.P.; McElhaney, S.A.

    1992-08-01

    Existing neutron imaging detectors have limited count rates due to inherent property and electronic limitations. The popular multiwire proportional counter is qualified by gas recombination to a count rate of less than 10{sup 5} n/s over the entire array and the neutron Anger camera, even though improved with new fiber optic encoding methods, can only achieve 10{sup 6} cps over a limited array. We present a preliminary design for a new type of neutron imaging detector with a resolution of 2--5 mm and a count rate capability of 10{sup 6} cps pixel element. We propose to combine optical and electronic processing to economically increase the throughput of advanced detector systems while simplifying computing requirements. By placing a scintillator screen ahead of an optical image processor followed by a detector array, a high throughput imaging detector may be constructed.

  7. Film adhesive enhances neutron radiographic images

    NASA Technical Reports Server (NTRS)

    Reed, M. W.

    1978-01-01

    Resolution of neutron radiographic images of thermally conductive film is increased by replacing approximately 5 percent of aluminum powder, which provides thermal conductivity, with gadolinium oxide. Oxide is also chemically stable.

  8. Functional magnetic resonance imaging adaptation reveals a noncategorical representation of hue in early visual cortex.

    PubMed

    Persichetti, Andrew S; Thompson-Schill, Sharon L; Butt, Omar H; Brainard, David H; Aguirre, Geoffrey K

    2015-01-01

    Color names divide the fine-grained gamut of color percepts into discrete categories. A categorical transition must occur somewhere between the initial encoding of the continuous spectrum of light by the cones and the verbal report of the name of a color stimulus. Here, we used a functional magnetic resonance imaging (fMRI) adaptation experiment to examine the representation of hue in the early visual cortex. Our stimuli varied in hue between blue and green. We found in the early visual areas (V1, V2/3, and hV4) a smoothly increasing recovery from adaptation with increasing hue distance between adjacent stimuli during both passive viewing (Experiment 1) and active categorization (Experiment 2). We examined the form of the adaptation effect and found no evidence that a categorical representation mediates the release from adaptation for stimuli that cross the blue-green color boundary. Examination of the direct effect of stimulus hue on the fMRI response did, however, reveal an enhanced response to stimuli near the blue-green category border. This was largest in hV4 and when subjects were engaged in active categorization of the stimulus hue. In contrast with a recent report from another laboratory (Bird, Berens, Horner, & Franklin, 2014), we found no evidence for a categorical representation of color in the middle frontal gyrus. A post hoc whole-brain analysis, however, revealed several regions in the frontal cortex with a categorical effect in the adaptation response. Overall, our results support the idea that the representation of color in the early visual cortex is primarily fine grained and does not reflect color categories. PMID:26024465

  9. Microwave Imaging of Human Forearms: Pilot Study and Image Enhancement

    PubMed Central

    Gilmore, Colin; Zakaria, Amer; Pistorius, Stephen; LoVetri, Joe

    2013-01-01

    We present a pilot study using a microwave tomography system in which we image the forearms of 5 adult male and female volunteers between the ages of 30 and 48. Microwave scattering data were collected at 0.8 to 1.2 GHz with 24 transmitting and receiving antennas located in a matching fluid of deionized water and table salt. Inversion of the microwave data was performed with a balanced version of the multiplicative-regularized contrast source inversion algorithm formulated using the finite-element method (FEM-CSI). T1-weighted MRI images of each volunteer's forearm were also collected in the same plane as the microwave scattering experiment. Initial “blind” imaging results from the utilized inversion algorithm show that the image quality is dependent on the thickness of the arm's peripheral adipose tissue layer; thicker layers of adipose tissue lead to poorer overall image quality. Due to the exible nature of the FEM-CSI algorithm used, prior information can be readily incorporated into the microwave imaging inversion process. We show that by introducing prior information into the FEM-CSI algorithm the internal anatomical features of all the arms are resolved, significantly improving the images. The prior information was estimated manually from the blind inversions using an ad hoc procedure. PMID:24023539

  10. Image subband coding using context-based classification and adaptive quantization.

    PubMed

    Yoo, Y; Ortega, A; Yu, B

    1999-01-01

    Adaptive compression methods have been a key component of many proposed subband (or wavelet) image coding techniques. This paper deals with a particular type of adaptive subband image coding where we focus on the image coder's ability to adjust itself "on the fly" to the spatially varying statistical nature of image contents. This backward adaptation is distinguished from more frequently used forward adaptation in that forward adaptation selects the best operating parameters from a predesigned set and thus uses considerable amount of side information in order for the encoder and the decoder to operate with the same parameters. Specifically, we present backward adaptive quantization using a new context-based classification technique which classifies each subband coefficient based on the surrounding quantized coefficients. We couple this classification with online parametric adaptation of the quantizer applied to each class. A simple uniform threshold quantizer is employed as the baseline quantizer for which adaptation is achieved. Our subband image coder based on the proposed adaptive classification quantization idea exhibits excellent rate-distortion performance, in particular at very low rates. For popular test images, it is comparable or superior to most of the state-of-the-art coders in the literature.

  11. Digital enhancement of multispectral MSS data for maximum image visibility

    NASA Technical Reports Server (NTRS)

    Algazi, V. R.

    1973-01-01

    A systematic approach to the enhancement of images has been developed. This approach exploits two principal features involved in the observation of images: the properties of human vision and the statistics of the images being observed. The rationale of the enhancement procedure is as follows: in the observation of some features of interest in an image, the range of objective luminance-chrominance values being displayed is generally limited and does not use the whole perceptual range of vision of the observer. The purpose of the enhancement technique is to expand and distort in a systematic way the grey scale values of each of the multispectral bands making up a color composite, to enhance the average visibility of the features being observed.

  12. Offset-sparsity decomposition for automated enhancement of color microscopic image of stained specimen in histopathology

    NASA Astrophysics Data System (ADS)

    Kopriva, Ivica; Hadžija, Marijana Popović; Hadžija, Mirko; Aralica, Gorana

    2015-07-01

    We propose an offset-sparsity decomposition method for the enhancement of a color microscopic image of a stained specimen. The method decomposes vectorized spectral images into offset terms and sparse terms. A sparse term represents an enhanced image, and an offset term represents a "shadow." The related optimization problem is solved by computational improvement of the accelerated proximal gradient method used initially to solve the related rank-sparsity decomposition problem. Removal of an image-adapted color offset yields an enhanced image with improved colorimetric differences among the histological structures. This is verified by a no-reference colorfulness measure estimated from 35 specimens of the human liver, 1 specimen of the mouse liver stained with hematoxylin and eosin, 6 specimens of the mouse liver stained with Sudan III, and 3 specimens of the human liver stained with the anti-CD34 monoclonal antibody. The colorimetric difference improves on average by 43.86% with a 99% confidence interval (CI) of [35.35%, 51.62%]. Furthermore, according to the mean opinion score, estimated on the basis of the evaluations of five pathologists, images enhanced by the proposed method exhibit an average quality improvement of 16.60% with a 99% CI of [10.46%, 22.73%].

  13. New technique for enhancement of high dynamic range infrared images

    NASA Astrophysics Data System (ADS)

    Liu, Yu; Wang, Xin-sai; Xu, Hualiang; He, Ming; Li, Mingming

    2012-10-01

    A Bilateral Filter (BF) and Multi-scale Retinex (MSR) based infrared image enhancement algorithm is proposed in this paper. It's known that the MSR algorithm derived from vision theory can achieve dynamic range compression and tonal rendition effectively but suffers from `halo' phenomena caused by the existence of "sharp" edges in infrared images. Research shows that bilateral filter has the property of separating image details from strong edges. Therefore, we process detail components containing strong edges in MSR algorithm with bilateral filter to achieve dynamic range compression, detail enhancement and avoid `halo' artifacts at the same time. The performance of proposed algorithm is then validated by experiments with three real infrared images and compared with other two infrared images enhancement algorithms.

  14. Adaptive local backlight dimming algorithm based on local histogram and image characteristics

    NASA Astrophysics Data System (ADS)

    Nadernejad, Ehsan; Burini, Nino; Korhonen, Jari; Forchhammer, Søren; Mantel, Claire

    2013-02-01

    Liquid Crystal Display (LCDs) with Light Emitting Diode (LED) backlight is a very popular display technology, used for instance in television sets, monitors and mobile phones. This paper presents a new backlight dimming algorithm that exploits the characteristics of the target image, such as the local histograms and the average pixel intensity of each backlight segment, to reduce the power consumption of the backlight and enhance image quality. The local histogram of the pixels within each backlight segment is calculated and, based on this average, an adaptive quantile value is extracted. A classification into three classes based on the average luminance value is performed and, depending on the image luminance class, the extracted information on the local histogram determines the corresponding backlight value. The proposed method has been applied on two modeled screens: one with a high resolution direct-lit backlight, and the other screen with 16 edge-lit backlight segments placed in two columns and eight rows. We have compared the proposed algorithm against several known backlight dimming algorithms by simulations; and the results show that the proposed algorithm provides better trade-off between power consumption and image quality preservation than the other algorithms representing the state of the art among feature based backlight algorithms.

  15. Photographic copy of computer enhanced color photographic image. Photographer and ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photographic copy of computer enhanced color photographic image. Photographer and computer draftsman unknown. Original photographic image located in the office of Modjeski and Masters, Consulting Engineers at 1055 St. Charles Avenue, New Orleans, LA 70130. COMPUTER ENHANCED COLOR PHOTOGRAPH SHOWING THE PROPOSED HUEY P. LONG BRIDGE WIDENING LOOKING FROM THE WEST BANK TOWARD THE EAST BANK. - Huey P. Long Bridge, Spanning Mississippi River approximately midway between nine & twelve mile points upstream from & west of New Orleans, Jefferson, Jefferson Parish, LA

  16. Closed-loop adaptive optics using a CMOS image quality metric sensor

    NASA Astrophysics Data System (ADS)

    Ting, Chueh; Rayankula, Aditya; Giles, Michael K.; Furth, Paul M.

    2006-08-01

    When compared to a Shack-Hartmann sensor, a CMOS image sharpness sensor has the advantage of reduced complexity in a closed-loop adaptive optics system. It also has the potential to be implemented as a smart sensor using VLSI technology. In this paper, we present a novel adaptive optics testbed that uses a CMOS sharpness imager built in the New Mexico State University (NMSU) Electro-Optics Research Laboratory (EORL). The adaptive optics testbed, which includes a CMOS image quality metric sensor and a 37-channel deformable mirror, has the capability to rapidly compensate higher-order phase aberrations. An experimental performance comparison of the pinhole image sharpness feedback method and the CMOS imager is presented. The experimental data shows that the CMOS sharpness imager works well in a closed-loop adaptive optics system. Its overall performance is better than that of the pinhole method, and it has a fast response time.

  17. NEQR: a novel enhanced quantum representation of digital images

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Lu, Kai; Gao, Yinghui; Wang, Mo

    2013-08-01

    Quantum computation is becoming an important and effective tool to overcome the high real-time computational requirements of classical digital image processing. In this paper, based on analysis of existing quantum image representations, a novel enhanced quantum representation (NEQR) for digital images is proposed, which improves the latest flexible representation of quantum images (FRQI). The newly proposed quantum image representation uses the basis state of a qubit sequence to store the gray-scale value of each pixel in the image for the first time, instead of the probability amplitude of a qubit, as in FRQI. Because different basis states of qubit sequence are orthogonal, different gray scales in the NEQR quantum image can be distinguished. Performance comparisons with FRQI reveal that NEQR can achieve a quadratic speedup in quantum image preparation, increase the compression ratio of quantum images by approximately 1.5X, and retrieve digital images from quantum images accurately. Meanwhile, more quantum image operations related to gray-scale information in the image can be performed conveniently based on NEQR, for example partial color operations and statistical color operations. Therefore, the proposed NEQR quantum image model is more flexible and better suited for quantum image representation than other models in the literature.

  18. Adaptation Duration Dissociates Category-, Image-, and Person-Specific Processes on Face-Evoked Event-Related Potentials

    PubMed Central

    Zimmer, Márta; Zbanţ, Adriana; Németh, Kornél; Kovács, Gyula

    2015-01-01

    Several studies demonstrated that face perception is biased by the prior presentation of another face, a phenomenon termed as face-related after-effect (FAE). FAE is linked to a neural signal-reduction at occipito-temporal areas and it can be observed in the amplitude modulation of the early event-related potential (ERP) components. Recently, macaque single-cell recording studies suggested that manipulating the duration of the adaptor makes the selective adaptation of different visual motion processing steps possible. To date, however, only a few studies tested the effects of adaptor duration on the electrophysiological correlates of human face processing directly. The goal of the current study was to test the effect of adaptor duration on the image-, identity-, and generic category-specific face processing steps. To this end, in a two-alternative forced choice familiarity decision task we used five adaptor durations (ranging from 200–5000 ms) and four adaptor categories: adaptor and test were identical images—Repetition Suppression (RS); adaptor and test were different images of the Same Identity (SameID); adaptor and test images depicted Different Identities (DiffID); the adaptor was a Fourier phase-randomized image (No). Behaviorally, a strong priming effect was observed in both accuracy and response times for RS compared with both DiffID and No. The electrophysiological results suggest that rapid adaptation leads to a category-specific modulation of P100, N170, and N250. In addition, both identity and image-specific processes affected the N250 component during rapid adaptation. On the other hand, prolonged (5000 ms) adaptation enhanced, and extended category-specific adaptation processes over all tested ERP components. Additionally, prolonged adaptation led to the emergence of image-, and identity-specific modulations on the N170 and P2 components as well. In other words, there was a clear dissociation among category, identity-, and image

  19. Enhanced Infrared Surveillance Imaging Report for NA-22

    SciTech Connect

    Carrano, C J

    2005-10-04

    The purpose of this report is to describe our work on enhanced infrared (IR) surveillance using speckle imaging for NA-22. Speckle imaging in this context is an image post-processing algorithm that aims to solve the atmospheric blurring problem of imaging through horizontal or slant path turbulence. We will describe the IR imaging systems used in our data collections and show imagery before and after speckle processing. We will also compare IR imagery with visible wavelength imagery of the same target in the same conditions and demonstrate how going to longer wavelengths can be beneficial in the presence of strong turbulence.

  20. Adaptive box filters for removal of random noise from digital images

    USGS Publications Warehouse

    Eliason, E.M.; McEwen, A.S.

    1990-01-01

    We have developed adaptive box-filtering algorithms to (1) remove random bit errors (pixel values with no relation to the image scene) and (2) smooth noisy data (pixels related to the image scene but with an additive or multiplicative component of noise). For both procedures, we use the standard deviation (??) of those pixels within a local box surrounding each pixel, hence they are adaptive filters. This technique effectively reduces speckle in radar images without eliminating fine details. -from Authors

  1. Image Processing for Binarization Enhancement via Fuzzy Reasoning

    NASA Technical Reports Server (NTRS)

    Dominguez, Jesus A. (Inventor)

    2009-01-01

    A technique for enhancing a gray-scale image to improve conversions of the image to binary employs fuzzy reasoning. In the technique, pixels in the image are analyzed by comparing the pixel's gray scale value, which is indicative of its relative brightness, to the values of pixels immediately surrounding the selected pixel. The degree to which each pixel in the image differs in value from the values of surrounding pixels is employed as the variable in a fuzzy reasoning-based analysis that determines an appropriate amount by which the selected pixel's value should be adjusted to reduce vagueness and ambiguity in the image and improve retention of information during binarization of the enhanced gray-scale image.

  2. Noise suppressed, multifocus image fusion for enhanced intraoperative navigation.

    PubMed

    Feruglio, Paolo Fumene; Vinegoni, Claudio; Fexon, Lioubov; Thurber, Greg; Sbarbati, Andrea; Weissleder, Ralph

    2013-04-01

    Current intraoperative imaging systems are typically not able to provide 'sharp' images over entire large areas or entire organs. Distinct structures such as tissue margins or groups of malignant cells are therefore often difficult to detect, especially under low signal-to-noise-ratio conditions. In this report, we introduce a noise suppressed multifocus image fusion algorithm, that provides detailed reconstructions even when images are acquired under sub-optimal conditions, such is the case for real time fluorescence intraoperative surgery. The algorithm makes use of the Anscombe transform combined with a multi-level stationary wavelet transform with individual threshold-based shrinkage. While the imaging system is integrated with a respiratory monitor triggering system, it can be easily adapted to any commercial imaging system. The developed algorithm is made available as a plugin for Osirix. PMID:22887724

  3. Tumor detection from enhanced magnetic resonance imaging using fuzzy curvelet.

    PubMed

    Jaffar, M Arfan; Ain, Quratul; Choi, Tae Sun

    2012-04-01

    Effective medical image analysis is possible by the use of technique known as segmentation. Segmentation is a very challenging task because there is not any standard segmentation method is available for any medical application. In this article, we have proposed an automatic brain MR image segmentation method. Fast discrete curvelet transform and spatial fuzzy C-mean algorithm is used for noise removal and segmentation of brain MR image. Fuzzy entropy has been used for calculating adaptive and optimal threshold to separate out the image segments. Our proposed system is exclusively based on the information contained by the image itself. No extra information and no human intervention are required in our proposed system. We have tested our proposed system on different T1, T2 and PD brain MR images. PMID:21960292

  4. Noise suppressed, multifocus image fusion for enhanced intraoperative navigation.

    PubMed

    Feruglio, Paolo Fumene; Vinegoni, Claudio; Fexon, Lioubov; Thurber, Greg; Sbarbati, Andrea; Weissleder, Ralph

    2013-04-01

    Current intraoperative imaging systems are typically not able to provide 'sharp' images over entire large areas or entire organs. Distinct structures such as tissue margins or groups of malignant cells are therefore often difficult to detect, especially under low signal-to-noise-ratio conditions. In this report, we introduce a noise suppressed multifocus image fusion algorithm, that provides detailed reconstructions even when images are acquired under sub-optimal conditions, such is the case for real time fluorescence intraoperative surgery. The algorithm makes use of the Anscombe transform combined with a multi-level stationary wavelet transform with individual threshold-based shrinkage. While the imaging system is integrated with a respiratory monitor triggering system, it can be easily adapted to any commercial imaging system. The developed algorithm is made available as a plugin for Osirix.

  5. Embedded image enhancement for high-throughput cameras

    NASA Astrophysics Data System (ADS)

    Geerts, Stan J. C.; Cornelissen, Dion; de With, Peter H. N.

    2014-03-01

    This paper presents image enhancement for a novel Ultra-High-Definition (UHD) video camera offering 4K images and higher. Conventional image enhancement techniques need to be reconsidered for the high-resolution images and the low-light sensitivity of the new sensor. We study two image enhancement functions and evaluate and optimize the algorithms for embedded implementation in programmable logic (FPGA). The enhancement study involves high-quality Auto White Balancing (AWB) and Local Contrast Enhancement (LCE). We have compared multiple algorithms from literature, both with objective and subjective metrics. In order to objectively compare Local Contrast (LC), an existing LC metric is modified for LC measurement in UHD images. For AWB, we have found that color histogram stretching offers a subjective high image quality and it is among the algorithms with the lowest complexity, while giving only a small balancing error. We impose a color-to-color gain constraint, which improves robustness of low-light images. For local contrast enhancement, a combination of contrast preserving gamma and single-scale Retinex is selected. A modified bilateral filter is designed to prevent halo artifacts, while significantly reducing the complexity and simultaneously preserving quality. We show that by cascading contrast preserving gamma and single-scale Retinex, the visibility of details is improved towards the level appropriate for high-quality surveillance applications. The user is offered control over the amount of enhancement. Also, we discuss the mapping of those functions on a heterogeneous platform to come to an effective implementation while preserving quality and robustness.

  6. Retroreflective imaging systems for enhanced optical biosensing

    NASA Astrophysics Data System (ADS)

    Bergen, Mark H.; Nichols, Jacqueline; Collier, Christopher M.; Jin, Xian; Holzman, Jonathan F.

    2014-05-01

    Biosensing is important for detection and characterization of microorganisms. When the detection and characterization of targeted microorganisms require micron-scale resolutions, optical biosensing techniques are especially beneficial. Optical biosensing can be applied through direct or indirect optical sensing techniques. The latter have demonstrated especially high sensitivities for the detection of targeted microorganisms with labeling. Unfortunately, such systems rely on high-resolution microscopy with microscopic sampling areas to image the labeled target microorganisms. This leads to long characterization times for applications such as pathogen detection in water quality monitoring where users must scan the micron-scale sampling areas across millimeter- or even centimeter-scale samples. This work introduces retroreflector labels for the detection and characterization of microorganisms for macroscopic sample sizes. The demonstrated retroreflective imaging system uses a laser source to illuminate the sample, in lieu of the fluorescent excitation source, and micron-scale retroreflector labels, in lieu of fluorescent stains/proteins. Antibodies are used to bind retroreflectors to targeted microorganisms. The presence of these microscopic retroreflector-microorganism pairs is monitored in a retroreflected image that is captured by a distant image sensor which shows a well-localized retroreflected beamspot for each pair. Characteristics of an appropriately-designed retroreflective imaging system which provide a quantifiable record of microorganism-coupled retroreflectors across macroscopic sample sizes are presented. Retroreflection directionality, collimation, and contrast are investigated for both corner-cube retroreflectors and spherical retroreflectors (of varying refractive indices). It is ultimately found that such a system is an effective tool for the detection and characterization of microorganism targets, down to a single-target detection limit.

  7. Adaptative Peer to Peer Data Sharing for Technology Enhanced Learning

    NASA Astrophysics Data System (ADS)

    Angelaccio, Michele; Buttarazzi, Berta

    Starting from the hypothesis that P2P Data Sharing in a direct teaching scenario (e.g.: a classroom lesson) may lead to relevant benefits, this paper explores the features of EduSHARE a Collaborative Learning System useful for Enhanced Learning Process.

  8. Enhanced adaptive focusing through semi-transparent media

    NASA Astrophysics Data System (ADS)

    di Battista, Diego; Zacharakis, Giannis; Leonetti, Marco

    2015-12-01

    Adaptive optics can focus light through opaque media by compensating the random phase delay acquired while crossing a scattering curtain. The technique is commonly exploited in many fields, including astrophysics, microscopy, biomedicine and biology. A turbid lens has the capability of producing foci with a resolution higher than conventional optics, however it has a fundamental limit: to obtain a sharp focus one has to introduce a strongly scattering medium in the optical path. Indeed a tight focusing needs strong scattering and, as a consequence, high resolution focusing is obtained only for weakly transmitting samples. Here we describe a novel method allowing to obtain highly concentrated optical spots even by introducing a minimum amount of scattering in the beam path with semi-transparent materials. By filtering the pseudo-ballistic components of the transmitted beam we are able to experimentally overcome the limits of the adaptive focus resolution, gathering light on a spot with a diameter which is one third of the original speckle correlation function.

  9. Enhanced adaptive focusing through semi-transparent media

    PubMed Central

    Di Battista, Diego; Zacharakis, Giannis; Leonetti, Marco

    2015-01-01

    Adaptive optics can focus light through opaque media by compensating the random phase delay acquired while crossing a scattering curtain. The technique is commonly exploited in many fields, including astrophysics, microscopy, biomedicine and biology. A turbid lens has the capability of producing foci with a resolution higher than conventional optics, however it has a fundamental limit: to obtain a sharp focus one has to introduce a strongly scattering medium in the optical path. Indeed a tight focusing needs strong scattering and, as a consequence, high resolution focusing is obtained only for weakly transmitting samples. Here we describe a novel method allowing to obtain highly concentrated optical spots even by introducing a minimum amount of scattering in the beam path with semi-transparent materials. By filtering the pseudo-ballistic components of the transmitted beam we are able to experimentally overcome the limits of the adaptive focus resolution, gathering light on a spot with a diameter which is one third of the original speckle correlation function. PMID:26620906

  10. Enhanced adaptive focusing through semi-transparent media.

    PubMed

    Di Battista, Diego; Zacharakis, Giannis; Leonetti, Marco

    2015-01-01

    Adaptive optics can focus light through opaque media by compensating the random phase delay acquired while crossing a scattering curtain. The technique is commonly exploited in many fields, including astrophysics, microscopy, biomedicine and biology. A turbid lens has the capability of producing foci with a resolution higher than conventional optics, however it has a fundamental limit: to obtain a sharp focus one has to introduce a strongly scattering medium in the optical path. Indeed a tight focusing needs strong scattering and, as a consequence, high resolution focusing is obtained only for weakly transmitting samples. Here we describe a novel method allowing to obtain highly concentrated optical spots even by introducing a minimum amount of scattering in the beam path with semi-transparent materials. By filtering the pseudo-ballistic components of the transmitted beam we are able to experimentally overcome the limits of the adaptive focus resolution, gathering light on a spot with a diameter which is one third of the original speckle correlation function. PMID:26620906

  11. Enhancing images with Intensity-Dependent Spread functions

    NASA Technical Reports Server (NTRS)

    Reese, Greg

    1992-01-01

    The theory of Intensity-Dependent Spread functions (IDS), a model of the human visual system proposed by Cornsweet (1985), is applied to image enhancement. An artificial image is examined which illustrates the characteristics of IDS processing and shows how the theoretical results translate into visual effects. Examples of realistic scenes that have been enhanced by IDS are presented. The system is shown to be particularly useful for bringing out detail in regions of low-contrast images. IDS can be readily implemented on a parallel computer.

  12. An efficient implementation of Forward-Backward Least-Mean-Square Adaptive Line Enhancers

    NASA Technical Reports Server (NTRS)

    Yeh, H.-G.; Nguyen, T. M.

    1995-01-01

    An efficient implementation of the forward-backward least-mean-square (FBLMS) adaptive line enhancer is presented in this article. Without changing the characteristics of the FBLMS adaptive line enhancer, the proposed implementation technique reduces multiplications by 25% and additions by 12.5% in two successive time samples in comparison with those operations of direct implementation in both prediction and weight control. The proposed FBLMS architecture and algorithm can be applied to digital receivers for enhancing signal-to-noise ratio to allow fast carrier acquisition and tracking in both stationary and nonstationary environments.

  13. Dual-dictionary learning based MR image reconstruction with self-adaptive dictionaries.

    PubMed

    Jiansen Li; Ying Song; Jun Zhao

    2015-01-01

    Dual-dictionary learning method utilizes two dictionaries at two different resolution levels, a high resolution dictionary trained with full-data training set, and a low resolution dictionary co-trained with corresponding undersampled dataset. This method effectively incorporates a priori knowledge of typical structures, specific features and local details, leading to its success in magnetic resonance (MR) image reconstruction from highly undersampled k-space data. In this paper, we improve this dual-dictionary learning method by using self-adaptive dictionaries. The two level dictionaries are updated correspondingly in the inner iteration after updating the reconstruction result to maintain their matching accuracy. Experimental results show that the proposed method can improve the reconstruction quality efficiently and enhance the robustness significantly.

  14. Enhancement dark channel algorithm of color fog image based on the local segmentation

    NASA Astrophysics Data System (ADS)

    Yun, Lijun; Gao, Yin; Shi, Jun-sheng; Xu, Ling-zhang

    2015-04-01

    The classical dark channel theory algorithm has yielded good results in the processing of single fog image, but in some larger contrast regions, it appears image hue, brightness and saturation distortion problems to a certain degree, and also produces halo phenomenon. In the view of the above situation, through a lot of experiments, this paper has found some factors causing the halo phenomenon. The enhancement dark channel algorithm of color fog image based on the local segmentation is proposed. On the basis of the dark channel theory, first of all, the classic dark channel theory of mathematical model is modified, which is mainly to correct the brightness and saturation of image. Then, according to the local adaptive segmentation theory, it process the block of image, and overlap the local image. On the basis of the statistical rules, it obtains each pixel value from the segmentation processing, so as to obtain the local image. At last, using the dark channel theory, it achieves the enhanced fog image. Through the subjective observation and objective evaluation, the algorithm is better than the classic dark channel algorithm in the overall and details.

  15. Quality evaluation of adaptive optical image based on DCT and Rényi entropy

    NASA Astrophysics Data System (ADS)

    Xu, Yuannan; Li, Junwei; Wang, Jing; Deng, Rong; Dong, Yanbing

    2015-04-01

    The adaptive optical telescopes play a more and more important role in the detection system on the ground, and the adaptive optical images are so many that we need find a suitable method of quality evaluation to choose good quality images automatically in order to save human power. It is well known that the adaptive optical images are no-reference images. In this paper, a new logarithmic evaluation method based on the use of the discrete cosine transform(DCT) and Rényi entropy for the adaptive optical images is proposed. Through the DCT using one or two dimension window, the statistical property of Rényi entropy for images is studied. The different directional Rényi entropy maps of an input image containing different information content are obtained. The mean values of different directional Rényi entropy maps are calculated. For image quality evaluation, the different directional Rényi entropy and its standard deviation corresponding to region of interest is selected as an indicator for the anisotropy of the images. The standard deviation of different directional Rényi entropy is obtained as the quality evaluation value for adaptive optical image. Experimental results show the proposed method that the sorting quality matches well with the visual inspection.

  16. Color Histogram Diffusion for Image Enhancement

    NASA Technical Reports Server (NTRS)

    Kim, Taemin

    2011-01-01

    Various color histogram equalization (CHE) methods have been proposed to extend grayscale histogram equalization (GHE) for color images. In this paper a new method called histogram diffusion that extends the GHE method to arbitrary dimensions is proposed. Ranges in a histogram are specified as overlapping bars of uniform heights and variable widths which are proportional to their frequencies. This diagram is called the vistogram. As an alternative approach to GHE, the squared error of the vistogram from the uniform distribution is minimized. Each bar in the vistogram is approximated by a Gaussian function. Gaussian particles in the vistoram diffuse as a nonlinear autonomous system of ordinary differential equations. CHE results of color images showed that the approach is effective.

  17. Enhancing psychosocial adaptation to gastric partitioning for morbid obesity.

    PubMed Central

    Randolph, J

    1986-01-01

    Gastric partitioning, a surgical treatment for morbid obesity, challenges patients to drastically change their eating habits and self-image. Preoperative psychiatric assessment should not be aimed simply at selecting patients in whom there are no psychiatric contraindications. Many patients have some degree of risk for postoperative problems. If the risk factors can be identified before surgery, appropriate pre- and postoperative psychologic intervention may help minimize maladaptation. PMID:3708487

  18. CometCIEF: A Web-based Image Enhancement Facility to digitally enhance images of cometary comae

    NASA Astrophysics Data System (ADS)

    Samarasinha, N.; Martin, P.; Larson, S.

    2014-07-01

    The detailed analysis of cometary comae provides an observational basis to investigate both the nucleus as well as the coma of comets. The structures in the coma are indicative of the anisotropic emission of gas and dust from the nucleus. Therefore, accurate identifications and measurements of spatial information related to coma structures are needed for realistic quantitative interpretation of coma observations. In many instances, the coma features are only a few percent above the ambient background coma and require enhancement of such features to unambiguously identify them, to make measurements on them, and to carry out subsequent detailed analyses. There is a number of image enhancement techniques used by cometary scientists. Despite this, the wider applicability of many advanced enhancement techniques is limited due to the non-availability of relevant software as open source. To alleviate this, we are making available a number of such techniques using a user-friendly web interface. In this image enhancement facility available at http://www.psi.edu/research/cometimen one can upload a fits format image of a cometary coma and digitally enhance it using an image enhancement technique of the user's choice. The user can then easily download the enhanced image as well as any associated images generated during the enhancement as fits files for detailed analysis later at the user's institution. The available image enhancement techniques at the facility are: (a) division by azimuthal average; (b) division by azimuthal median; (c) azimuthal renormalization; (d) division by 1/ρ profile, where ρ is the sky-plane projected distance from the nucleus; and (e) radially variable spatial filtering. The site provides documentation describing the above enhancement techniques as well as a tutorial showing the application of the enhancement techniques to actual cometary images and how the results may vary with different input parameters. In addition, the source codes as well as

  19. Transfer of perceptual adaptation to space sickness: What enhances an individual's ability to adapt?

    NASA Technical Reports Server (NTRS)

    1993-01-01

    The objectives of this project were to explore systematically the determiners of transfer of perceptual adaptation as these principles might apply to the space adaptation syndrome. The perceptual experience of an astronaut exposed to the altered gravitational forces involved in spaceflight shares much with that of the subject exposed in laboratory experiments to optically induced visual rearrangement with tilt and dynamic motion illusions such as vection; and experiences and symptoms reported by the trainee who is exposed to the compellingly realistic visual imagery of flight simulators and virtual reality systems. In both of these cases the observer is confronted with a variety of inter- and intrasensory conflicts that initially disrupt perception, as well as behavior, and also produce symptoms of motion sickness.

  20. Embedded Bone Fragment Detection in Chicken Fillets using Transmittance Image Enhancement and Hyperspectral Reflectance Imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper is concerned with the detection of bone fragments embedded in compressed de-boned skinless chicken breast fillets by enhancing single-band transmittance images generated by back-lighting and exploiting spectral information from hyperspectral reflectance images. Optical imaging of chicken ...

  1. Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform

    NASA Astrophysics Data System (ADS)

    Wu, Zhi-guo; Wang, Ming-jia; Han, Guang-liang

    2011-08-01

    Being an efficient method of information fusion, image fusion has been used in many fields such as machine vision, medical diagnosis, military applications and remote sensing. In this paper, Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing, including segmentation, target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First, the two original images are decomposed by wavelet transform. Then, based on the PCNN, a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength, so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So, the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment, the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range, which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore, by this algorithm, the threshold adjusting constant is estimated by appointed iteration number. Furthermore, In order to sufficient reflect order of the firing time, the threshold adjusting constant αΘ is estimated by appointed iteration number. So after the iteration achieved, each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules, the experiments upon Multi-focus image are done. Moreover

  2. Hybridization can facilitate species invasions, even without enhancing local adaptation.

    PubMed

    Mesgaran, Mohsen B; Lewis, Mark A; Ades, Peter K; Donohue, Kathleen; Ohadi, Sara; Li, Chengjun; Cousens, Roger D

    2016-09-01

    The founding population in most new species introductions, or at the leading edge of an ongoing invasion, is likely to be small. Severe Allee effects-reductions in individual fitness at low population density-may then result in a failure of the species to colonize, even if the habitat could support a much larger population. Using a simulation model for plant populations that incorporates demography, mating systems, quantitative genetics, and pollinators, we show that Allee effects can potentially be overcome by transient hybridization with a resident species or an earlier colonizer. This mechanism does not require the invocation of adaptive changes usually attributed to invasions following hybridization. We verify our result in a case study of sequential invasions by two plant species where the outcrosser Cakile maritima has replaced an earlier, inbreeding, colonizer Cakile edentula (Brassicaceae). Observed historical rates of replacement are consistent with model predictions from hybrid-alleviated Allee effects in outcrossers, although other causes cannot be ruled out.

  3. NOTE Contrast enhancement of EPID images via difference imaging: a feasibility study

    NASA Astrophysics Data System (ADS)

    Kairn, T.; Khoei, S.; Markwell, T. S.; Fielding, A. L.; Trapp, J. V.

    2010-11-01

    In this study, the feasibility of difference imaging for improving the contrast of electronic portal imaging device (EPID) images is investigated. The difference imaging technique consists of the acquisition of two EPID images (with and without the placement of an additional layer of attenuating medium on the surface of the EPID) and the subtraction of one of these images from the other. The resulting difference image shows improved contrast, compared to a standard EPID image, since it is generated by lower-energy photons. Results of this study show that, firstly, this method can produce images exhibiting greater contrast than is seen in standard megavoltage EPID images and secondly, the optimal thickness of attenuating material for producing a maximum contrast enhancement may vary with phantom thickness and composition. Further studies of the possibilities and limitations of the difference imaging technique, and the physics behind it, are therefore recommended.

  4. Spatially adaptive migration tomography for multistatic GPR imaging

    DOEpatents

    Paglieroni, David W; Beer, N. Reginald

    2013-08-13

    A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

  5. Research on an Improved Medical Image Enhancement Algorithm Based on P-M Model.

    PubMed

    Dong, Beibei; Yang, Jingjing; Hao, Shangfu; Zhang, Xiao

    2015-01-01

    Image enhancement can improve the detail of the image and so as to achieve the purpose of the identification of the image. At present, the image enhancement is widely used in medical images, which can help doctor's diagnosis. IEABPM (Image Enhancement Algorithm Based on P-M Model) is one of the most common image enhancement algorithms. However, it may cause the lost of the texture details and other features. To solve the problems, this paper proposes an IIEABPM (Improved Image Enhancement Algorithm Based on P-M Model). Simulation demonstrates that IIEABPM can effectively solve the problems of IEABPM, and improve image clarity, image contrast, and image brightness. PMID:26628929

  6. Contrast-enhanced imaging of cerebral vasculature with laser speckle

    NASA Astrophysics Data System (ADS)

    Murari, K.; Li, N.; Rege, A.; Jia, X.; All, A.; Thakor, N.

    2007-08-01

    High-resolution cerebral vasculature imaging has applications ranging from intraoperative procedures to basic neuroscience research. Laser speckle, with spatial contrast processing, has recently been used to map cerebral blood flow. We present an application of the technique using temporal contrast processing to image cerebral vascular structures with a field of view a few millimeters across and approximately 20 μm resolution through a thinned skull. We validate the images using fluorescent imaging and demonstrate a factor of 2-4 enhancement in contrast-to-noise ratios over reflectance imaging using white or spectrally filtered green light. The contrast enhancement enables the perception of approximately 10%-30% more vascular structures without the introduction of any contrast agent.

  7. Reversibly switchable fluorescence microscopy with enhanced resolution and image contrast.

    PubMed

    Yao, Junjie; Shcherbakova, Daria M; Li, Chiye; Krumholz, Arie; Lorca, Ramon A; Reinl, Erin; England, Sarah K; Verkhusha, Vladislav V; Wang, Lihong V

    2014-08-01

    Confocal microscopy with optical sectioning has revolutionized biological studies by providing sharper images than conventional optical microscopy. Here, we introduce a fluorescence imaging method with enhanced resolution and imaging contrast, which can be implemented using a commercial confocal microscope setup. This approach, called the reversibly switchable photo-imprint microscopy (rsPIM), is based on the switching dynamics of reversibly switchable fluorophores. When the fluorophores are switched from the bright (ON) state to the dark (OFF) state, their switching rate carries the information about the local excitation light intensity. In rsPIM, a polynomial function is used to fit the fluorescence signal decay during the transition. The extracted high-order coefficient highlights the signal contribution from the center of the excitation volume, and thus sharpens the resolution in all dimensions. In particular, out-of-focus signals are greatly blocked for large targets, and thus the image contrast is considerably enhanced. Notably, since the fluorophores can be cycled between the ON and OFF states, the whole imaging process can be repeated. RsPIM imaging with enhanced image contrast was demonstrated in both fixed and live cells using a reversibly switchable synthetic dye and a genetically encoded red fluorescent protein. Since rsPIM does not require the modification of commercial microscope systems, it may provide a simple and cost-effective solution for subdiffraction imaging of live cells. PMID:25144452

  8. Dynamic contrast-enhanced 3D photoacoustic imaging

    NASA Astrophysics Data System (ADS)

    Wong, Philip; Kosik, Ivan; Carson, Jeffrey J. L.

    2013-03-01

    Photoacoustic imaging (PAI) is a hybrid imaging modality that integrates the strengths from both optical imaging and acoustic imaging while simultaneously overcoming many of their respective weaknesses. In previous work, we reported on a real-time 3D PAI system comprised of a 32-element hemispherical array of transducers. Using the system, we demonstrated the ability to capture photoacoustic data, reconstruct a 3D photoacoustic image, and display select slices of the 3D image every 1.4 s, where each 3D image resulted from a single laser pulse. The present study aimed to exploit the rapid imaging speed of an upgraded 3D PAI system by evaluating its ability to perform dynamic contrast-enhanced imaging. The contrast dynamics can provide rich datasets that contain insight into perfusion, pharmacokinetics and physiology. We captured a series of 3D PA images of a flow phantom before and during injection of piglet and rabbit blood. Principal component analysis was utilized to classify the data according to its spatiotemporal information. The results suggested that this technique can be used to separate a sequence of 3D PA images into a series of images representative of main features according to spatiotemporal flow dynamics.

  9. Enhancing Tabletop X-Ray Phase Contrast Imaging with Nano-Fabrication.

    PubMed

    Miao, Houxun; Gomella, Andrew A; Harmon, Katherine J; Bennett, Eric E; Chedid, Nicholas; Znati, Sami; Panna, Alireza; Foster, Barbara A; Bhandarkar, Priya; Wen, Han

    2015-01-01

    X-ray phase-contrast imaging is a promising approach for improving soft-tissue contrast and lowering radiation dose in biomedical applications. While current tabletop imaging systems adapt to common x-ray tubes and large-area detectors by employing absorptive elements such as absorption gratings or monolithic crystals to filter the beam, we developed nanometric phase gratings which enable tabletop x-ray far-field interferometry with only phase-shifting elements, leading to a substantial enhancement in the performance of phase contrast imaging. In a general sense the method transfers the demands on the spatial coherence of the x-ray source and the detector resolution to the feature size of x-ray phase masks. We demonstrate its capabilities in hard x-ray imaging experiments at a fraction of clinical dose levels and present comparisons with the existing Talbot-Lau interferometer and with conventional digital radiography.

  10. Enhancing Tabletop X-Ray Phase Contrast Imaging with Nano-Fabrication

    PubMed Central

    Miao, Houxun; Gomella, Andrew A.; Harmon, Katherine J.; Bennett, Eric E.; Chedid, Nicholas; Znati, Sami; Panna, Alireza; Foster, Barbara A.; Bhandarkar, Priya; Wen, Han

    2015-01-01

    X-ray phase-contrast imaging is a promising approach for improving soft-tissue contrast and lowering radiation dose in biomedical applications. While current tabletop imaging systems adapt to common x-ray tubes and large-area detectors by employing absorptive elements such as absorption gratings or monolithic crystals to filter the beam, we developed nanometric phase gratings which enable tabletop x-ray far-field interferometry with only phase-shifting elements, leading to a substantial enhancement in the performance of phase contrast imaging. In a general sense the method transfers the demands on the spatial coherence of the x-ray source and the detector resolution to the feature size of x-ray phase masks. We demonstrate its capabilities in hard x-ray imaging experiments at a fraction of clinical dose levels and present comparisons with the existing Talbot-Lau interferometer and with conventional digital radiography. PMID:26315891

  11. Manganese-Enhanced Magnetic Resonance Imaging (MEMRI)

    PubMed Central

    Massaad, Cynthia A.; Pautler, Robia G.

    2012-01-01

    The use of manganese ions (Mn2+) as an MRI contrast agent was introduced over 20 years ago in studies of Mn2+ toxicity in anesthetized rats (1). Manganese-enhanced MRI (MEMRI) evolved in the late nineties when Koretsky and associates pioneered the use of MEMRI for brain activity measurements (2) as well as neuronal tract tracing (3). Currently, MEMRI has three primary applications in biological systems: (1) contrast enhancement for anatomical detail, (2) activity-dependent assessment and (3) tracing of neuronal connections or tract tracing. MEMRI relies upon the following three main properties of Mn2+: (1) it is a paramagnetic ion that shortens the spin lattice relaxation time constant (T1) of tissues, where it accumulates and hence functions as an excellent T1 contrast agent; (2) it is a calcium (Ca2+) analog that can enter excitable cells, such as neurons and cardiac cells via voltage-gated Ca2+ channels; and (3) once in the cells Mn2+ can be transported along axons by microtubule-dependent axonal transport and can also cross synapses trans-synaptically to neighboring neurons. This chapter will emphasize the methodological approaches towards the use of MEMRI in biological systems. PMID:21279601

  12. Hybridization can facilitate species invasions, even without enhancing local adaptation.

    PubMed

    Mesgaran, Mohsen B; Lewis, Mark A; Ades, Peter K; Donohue, Kathleen; Ohadi, Sara; Li, Chengjun; Cousens, Roger D

    2016-09-01

    The founding population in most new species introductions, or at the leading edge of an ongoing invasion, is likely to be small. Severe Allee effects-reductions in individual fitness at low population density-may then result in a failure of the species to colonize, even if the habitat could support a much larger population. Using a simulation model for plant populations that incorporates demography, mating systems, quantitative genetics, and pollinators, we show that Allee effects can potentially be overcome by transient hybridization with a resident species or an earlier colonizer. This mechanism does not require the invocation of adaptive changes usually attributed to invasions following hybridization. We verify our result in a case study of sequential invasions by two plant species where the outcrosser Cakile maritima has replaced an earlier, inbreeding, colonizer Cakile edentula (Brassicaceae). Observed historical rates of replacement are consistent with model predictions from hybrid-alleviated Allee effects in outcrossers, although other causes cannot be ruled out. PMID:27601582

  13. Stokes vector analysis of adaptive optics images of the retina.

    PubMed

    Song, Hongxin; Zhao, Yanming; Qi, Xiaofeng; Chui, Yuenping Toco; Burns, Stephen A

    2008-01-15

    A high-resolution Stokes vector imaging polarimeter was developed to measure the polarization properties at the cellular level in living human eyes. The application of this cellular level polarimetric technique to in vivo retinal imaging has allowed us to measure depolarization in the retina and to improve the retinal image contrast of retinal structures based on their polarization properties. PMID:18197217

  14. Cytopathology whole slide images and adaptive tutorials for postgraduate pathology trainees: a randomized crossover trial.

    PubMed

    Van Es, Simone L; Kumar, Rakesh K; Pryor, Wendy M; Salisbury, Elizabeth L; Velan, Gary M

    2015-09-01

    To determine whether cytopathology whole slide images and virtual microscopy adaptive tutorials aid learning by postgraduate trainees, we designed a randomized crossover trial to evaluate the quantitative and qualitative impact of whole slide images and virtual microscopy adaptive tutorials compared with traditional glass slide and textbook methods of learning cytopathology. Forty-three anatomical pathology registrars were recruited from Australia, New Zealand, and Malaysia. Online assessments were used to determine efficacy, whereas user experience and perceptions of efficiency were evaluated using online Likert scales and open-ended questions. Outcomes of online assessments indicated that, with respect to performance, learning with whole slide images and virtual microscopy adaptive tutorials was equivalent to using traditional methods. High-impact learning, efficiency, and equity of learning from virtual microscopy adaptive tutorials were strong themes identified in open-ended responses. Participants raised concern about the lack of z-axis capability in the cytopathology whole slide images, suggesting that delivery of z-stacked whole slide images online may be important for future educational development. In this trial, learning cytopathology with whole slide images and virtual microscopy adaptive tutorials was found to be as effective as and perceived as more efficient than learning from glass slides and textbooks. The use of whole slide images and virtual microscopy adaptive tutorials has the potential to provide equitable access to effective learning from teaching material of consistently high quality. It also has broader implications for continuing professional development and maintenance of competence and quality assurance in specialist practice.

  15. Word Imageability Enhances Association-memory by Increasing Hippocampal Engagement.

    PubMed

    Caplan, Jeremy B; Madan, Christopher R

    2016-10-01

    The hippocampus is thought to support association-memory, particularly when tested with cued recall. One of the most well-known and studied factors that influences accuracy of verbal association-memory is imageability; participants remember pairs of high-imageability words better than pairs of low-imageability words. High-imageability words are also remembered better in tests of item-memory. However, we previously found that item-memory effects could not explain the enhancement in cued recall, suggesting that imageability enhances association-memory strength. Here we report an fMRI study designed to ask, what is the role of the hippocampus in the memory advantage for associations due to imageability? We tested two alternative hypotheses: (1) Recruitment Hypothesis: High-imageability pairs are remembered better because they recruit the underlying hippocampal association-memory function more effectively. Alternatively, (2) Bypassing Hypothesis: Imageability functions by making the association-forming process easier, enhancing memory in a way that bypasses the hippocampus, as has been found, for example, with explicit unitization imagery strategies. Results found, first, hippocampal BOLD signal was greater during study and recall of high- than low-imageability word pairs. Second, the difference in activity between recalled and forgotten pairs showed a main effect, but no significant interaction with imageability, challenging the bypassing hypothesis, but consistent with the predictions derived from the recruitment hypothesis. Our findings suggest that certain stimulus properties, like imageability, may leverage, rather than avoid, the associative function of the hippocampus to support superior association-memory. PMID:27315268

  16. Word Imageability Enhances Association-memory by Increasing Hippocampal Engagement.

    PubMed

    Caplan, Jeremy B; Madan, Christopher R

    2016-10-01

    The hippocampus is thought to support association-memory, particularly when tested with cued recall. One of the most well-known and studied factors that influences accuracy of verbal association-memory is imageability; participants remember pairs of high-imageability words better than pairs of low-imageability words. High-imageability words are also remembered better in tests of item-memory. However, we previously found that item-memory effects could not explain the enhancement in cued recall, suggesting that imageability enhances association-memory strength. Here we report an fMRI study designed to ask, what is the role of the hippocampus in the memory advantage for associations due to imageability? We tested two alternative hypotheses: (1) Recruitment Hypothesis: High-imageability pairs are remembered better because they recruit the underlying hippocampal association-memory function more effectively. Alternatively, (2) Bypassing Hypothesis: Imageability functions by making the association-forming process easier, enhancing memory in a way that bypasses the hippocampus, as has been found, for example, with explicit unitization imagery strategies. Results found, first, hippocampal BOLD signal was greater during study and recall of high- than low-imageability word pairs. Second, the difference in activity between recalled and forgotten pairs showed a main effect, but no significant interaction with imageability, challenging the bypassing hypothesis, but consistent with the predictions derived from the recruitment hypothesis. Our findings suggest that certain stimulus properties, like imageability, may leverage, rather than avoid, the associative function of the hippocampus to support superior association-memory.

  17. Adaptive diffusion regularization for enhancement of microcalcifications in digital breast tomosynthesis (DBT) reconstruction

    NASA Astrophysics Data System (ADS)

    Lu, Yao; Chan, Heang-Ping; Fessler, Jeffrey A.; Hadjiiski, Lubomir; Wei, Jun; Goodsitt, Mitchell M.

    2011-03-01

    Digital breast tomosynthesis (DBT) has been shown to increase mass detection. Detection of microcalcifications in DBT is challenging because of the small, subtle signals to be searched in the large breast volume and the noise in the reconstructed volume. We developed an adaptive diffusion (AD) regularization method that can differentially regularize noise and potential signal regions during reconstruction based on local contrast-to-noise ratio (CNR) information. This method adaptively applies different degrees of regularity to signal and noise regions, as guided by a CNR map for each DBT slice within the image volume, such that potential signals will be preserved while noise is suppressed. DBT scans of an American College of Radiology phantom and the breast of a subject with biopsy-proven calcifications were acquired with a GE prototype DBT system at 21 angles in 3° increments over a +/-30° range. Simultaneous algebraic reconstruction technique (SART) was used for DBT reconstruction. The AD regularization method was compared to the non-convex total p-variation (TpV) method and SART with no regularization (NR) in terms of the CNR and the full width at half maximum (FWHM) of the central gray-level line profile in the focal plane of a calcification. The results demonstrated that the SART regularized by the AD method enhanced the CNR and preserved the sharpness of microcalcifications compared to reconstruction without regularization. The AD regularization was superior to the TpV method for subtle microcalcifications in terms of the CNR while the FWHM was comparable. The AD regularized reconstruction has the potential to improve the CNR of microcalcifications in DBT for human or machine detection.

  18. Adaptive Wavefront Calibration and Control for the Gemini Planet Imager

    SciTech Connect

    Poyneer, L A; Veran, J

    2007-02-02

    Quasi-static errors in the science leg and internal AO flexure will be corrected. Wavefront control will adapt to current atmospheric conditions through Fourier modal gain optimization, or the prediction of atmospheric layers with Kalman filtering.

  19. Enhancement of Corneal Visibility in Optical Coherence Tomography Images with Corneal Opacification

    PubMed Central

    Chung, Cheuk Wang; Ang, Marcus; Farook, Mohamed; Strouthidis, Nicholas G.; Mehta, Joddhbir S.; Mari, Jean Martial; Girard, Michaël J. A.

    2016-01-01

    Purpose To establish and to rank the performance of a corneal adaptive compensation (CAC) algorithm in enhancing corneal images with scars acquired from three commercially available anterior segment optical coherence tomography (ASOCT) devices. Methods Horizontal B-scans of the cornea were acquired from 10 patients using three ASOCT devices (Spectralis, RTVue, and Cirrus). We compared ASOCT image quality (with and without CAC) by computing the intralayer contrast (a measure of shadow removal), the interlayer contrast (a measure of tissue boundary visibility), and the tissue/background contrast (a measure of overall corneal visibility). All six groups (Spectralis, RTVue, Cirrus, Spectralis+CAC, RTVue+CAC, and Cirrus+CAC) were ranked according to a global performance index that averaged all contrast quantities. Results CAC provided mean intralayer contrasts improvement for all devices (all P < 0.05). Mean tissue/boundary contrasts were also improved for Spectralis and Cirrus (both P < 0.001). Mean interlayer contrasts were increased for Spectralis (P = 0.011) only. When comparing global performance indices, all CAC groups outperformed their corresponding baseline groups significantly. RTVue performed best without CAC, but Spectralis+CAC was ranked first. Conclusions ASOCT images of corneal scars may be enhanced by CAC through shadow removal, improved tissue boundary visibility, and enhanced corneal visibility against the image background. RTVue produces the finest baseline images but the best image quality can be achieved by applying CAC to Spectralis images. Translational Relevance CAC could enhance visibility of corneal images with scars acquired from commercially available ASOCT devices and could aid preoperative planning of patients for ophthalmic procedures.

  20. Enhancement of Corneal Visibility in Optical Coherence Tomography Images with Corneal Opacification

    PubMed Central

    Chung, Cheuk Wang; Ang, Marcus; Farook, Mohamed; Strouthidis, Nicholas G.; Mehta, Joddhbir S.; Mari, Jean Martial; Girard, Michaël J. A.

    2016-01-01

    Purpose To establish and to rank the performance of a corneal adaptive compensation (CAC) algorithm in enhancing corneal images with scars acquired from three commercially available anterior segment optical coherence tomography (ASOCT) devices. Methods Horizontal B-scans of the cornea were acquired from 10 patients using three ASOCT devices (Spectralis, RTVue, and Cirrus). We compared ASOCT image quality (with and without CAC) by computing the intralayer contrast (a measure of shadow removal), the interlayer contrast (a measure of tissue boundary visibility), and the tissue/background contrast (a measure of overall corneal visibility). All six groups (Spectralis, RTVue, Cirrus, Spectralis+CAC, RTVue+CAC, and Cirrus+CAC) were ranked according to a global performance index that averaged all contrast quantities. Results CAC provided mean intralayer contrasts improvement for all devices (all P < 0.05). Mean tissue/boundary contrasts were also improved for Spectralis and Cirrus (both P < 0.001). Mean interlayer contrasts were increased for Spectralis (P = 0.011) only. When comparing global performance indices, all CAC groups outperformed their corresponding baseline groups significantly. RTVue performed best without CAC, but Spectralis+CAC was ranked first. Conclusions ASOCT images of corneal scars may be enhanced by CAC through shadow removal, improved tissue boundary visibility, and enhanced corneal visibility against the image background. RTVue produces the finest baseline images but the best image quality can be achieved by applying CAC to Spectralis images. Translational Relevance CAC could enhance visibility of corneal images with scars acquired from commercially available ASOCT devices and could aid preoperative planning of patients for ophthalmic procedures. PMID:27642539

  1. Resolution-enhancement for an orthographic-view image display in an integral imaging microscope system

    PubMed Central

    Kwon, Ki-Chul; Jeong, Ji-Seong; Erdenebat, Munkh-Uchral; Piao, Yan-Ling; Yoo, Kwan-Hee; Kim, Nam

    2015-01-01

    Due to the limitations of micro lens arrays and camera sensors, images on display devices through the integral imaging microscope systems have been suffering for a low-resolution. In this paper, a resolution-enhanced orthographic-view image display method for integral imaging microscopy is proposed and demonstrated. Iterative intermediate-view reconstructions are performed based on bilinear interpolation using neighborhood elemental image information, and a graphics processing unit parallel processing algorithm is applied for fast image processing. The proposed method is verified experimentally and the effective results are presented in this paper. PMID:25798299

  2. Adapting hypertension self-management interventions to enhance their sustained effectiveness among urban African Americans.

    PubMed

    Ameling, Jessica M; Ephraim, Patti L; Bone, Lee R; Levine, David M; Roter, Debra L; Wolff, Jennifer L; Hill-Briggs, Felicia; Fitzpatrick, Stephanie L; Noronha, Gary J; Fagan, Peter J; Lewis-Boyer, LaPricia; Hickman, Debra; Simmons, Michelle; Purnell, Leon; Fisher, Annette; Cooper, Lisa A; Aboumatar, Hanan J; Albert, Michael C; Flynn, Sarah J; Boulware, L Ebony

    2014-01-01

    African Americans suffer disproportionately poor hypertension control despite the availability of efficacious interventions. Using principles of community-based participatory research and implementation science, we adapted established hypertension self-management interventions to enhance interventions' cultural relevance and potential for sustained effectiveness among urban African Americans. We obtained input from patients and their family members, their health care providers, and community members. The process required substantial time and resources, and the adapted interventions will be tested in a randomized controlled trial.

  3. An Adaptive Digital Image Watermarking Algorithm Based on Morphological Haar Wavelet Transform

    NASA Astrophysics Data System (ADS)

    Huang, Xiaosheng; Zhao, Sujuan

    At present, much more of the wavelet-based digital watermarking algorithms are based on linear wavelet transform and fewer on non-linear wavelet transform. In this paper, we propose an adaptive digital image watermarking algorithm based on non-linear wavelet transform--Morphological Haar Wavelet Transform. In the algorithm, the original image and the watermark image are decomposed with multi-scale morphological wavelet transform respectively. Then the watermark information is adaptively embedded into the original image in different resolutions, combining the features of Human Visual System (HVS). The experimental results show that our method is more robust and effective than the ordinary wavelet transform algorithms.

  4. Research on adaptive segmentation and activity classification method of filamentous fungi image in microbe fermentation

    NASA Astrophysics Data System (ADS)

    Cai, Xiaochun; Hu, Yihua; Wang, Peng; Sun, Dujuan; Hu, Guilan

    2009-10-01

    The paper presents an adaptive segmentation and activity classification method for filamentous fungi image. Firstly, an adaptive structuring element (SE) construction algorithm is proposed for image background suppression. Based on watershed transform method, the color labeled segmentation of fungi image is taken. Secondly, the fungi elements feature space is described and the feature set for fungi hyphae activity classification is extracted. The growth rate evaluation of fungi hyphae is achieved by using SVM classifier. Some experimental results demonstrate that the proposed method is effective for filamentous fungi image processing.

  5. AVES-IMCO: an adaptive optics visible spectrograph and imager/coronograph for NAOS

    NASA Astrophysics Data System (ADS)

    Beuzit, Jean-Luc; Lagrange, A.-M.; Mouillet, D.; Chauvin, G.; Stadler, E.; Charton, J.; Lacombe, F.; AVES-IMCO Team

    2001-05-01

    The NAOS adaptive optics system will very soon provide diffraction-limited images on the VLT, down to the visible wavelengths (0.020 arcseconds at 0.83 micron for instance). At the moment, the only instrument dedicated to NAOS is the CONICA spectro-imager, operating in the near-infrared from 1 to 5 microns. We are now proposing to ESO, in collaboration with an Italian group, the development of a visible spectrograph/imager/coronograph, AVES-IMCO (Adaptive Optics Visual Echelle Spectrograph and IMager/COronograph). We present here the general concept of the new instrument as well as its expected performances in the different modes.

  6. In vivo fluorescent imaging of the mouse retina using adaptive optics

    PubMed Central

    Biss, David P.; Sumorok, Daniel; Burns, Stephen A.; Webb, Robert H.; Zhou, Yaopeng; Bifano, Thomas G.; Côté, Daniel; Veilleux, Israel; Zamiri, Parisa; Lin, Charles P.

    2009-01-01

    In vivo imaging of the mouse retina using visible and near infrared wavelengths does not achieve diffraction-limited resolution due to wavefront aberrations induced by the eye. Considering the pupil size and axial dimension of the eye, it is expected that unaberrated imaging of the retina would have a transverse resolution of 2 μm. Higher-order aberrations in retinal imaging of human can be compensated for by using adaptive optics. We demonstrate an adaptive optics system for in vivo imaging of fluorescent structures in the retina of a mouse, using a microelectromechanical system membrane mirror and a Shack–Hartmann wavefront sensor that detects fluorescent wavefront. PMID:17308593

  7. Application of Image Enhancement Techniques to Comets: A Critical Analysis

    NASA Astrophysics Data System (ADS)

    Samarasinha, Nalin H.; Larson, S.; Beshore, E.

    2006-09-01

    Investigation and accurate interpretation of many cometary coma phenomena depend on identification of coma features and their spatial and temporal variations. In many cases, the coma features are only few percent above the ambient coma, requiring the application of image enhancement techniques for easy identification and analysis. In the literature, there are a range of enhancement techniques used for the analysis of coma structures (e.g., Larson and Slaughter 1992, Schleicher and Farnham 2004). We use numerically simulated images to characterize pros and cons of a number of widely used enhancement techniques. In particular, we will identify techniques which are suitable for making measurements post-enhancement as well as the nature of the measurements which are unaffected by the enhancements. An effort will be made to present the results in a quantifiable format rather than with qualitative statements. Finally these enhancements techniques will be used to enhance and analyze the coma morphologies present in actual images of comet Hale-Bopp (C/1995 O1). NHS was supported by NASA Planetary Atmospheres Program.

  8. Application of adaptive optics in retinal imaging: a quantitative and clinical comparison with standard cameras

    NASA Astrophysics Data System (ADS)

    Barriga, E. S.; Erry, G.; Yang, S.; Russell, S.; Raman, B.; Soliz, P.

    2005-04-01

    Aim: The objective of this project was to evaluate high resolution images from an adaptive optics retinal imager through comparisons with standard film-based and standard digital fundus imagers. Methods: A clinical prototype adaptive optics fundus imager (AOFI) was used to collect retinal images from subjects with various forms of retinopathy to determine whether improved visibility into the disease could be provided to the clinician. The AOFI achieves low-order correction of aberrations through a closed-loop wavefront sensor and an adaptive optics system. The remaining high-order aberrations are removed by direct deconvolution using the point spread function (PSF) or by blind deconvolution when the PSF is not available. An ophthalmologist compared the AOFI images with standard fundus images and provided a clinical evaluation of all the modalities and processing techniques. All images were also analyzed using a quantitative image quality index. Results: This system has been tested on three human subjects (one normal and two with retinopathy). In the diabetic patient vascular abnormalities were detected with the AOFI that cannot be resolved with the standard fundus camera. Very small features, such as the fine vascular structures on the optic disc and the individual nerve fiber bundles are easily resolved by the AOFI. Conclusion: This project demonstrated that adaptive optic images have great potential in providing clinically significant detail of anatomical and pathological structures to the ophthalmologist.

  9. Adaptive optics OCT using 1060nm swept source and dual deformable lenses for human retinal imaging

    NASA Astrophysics Data System (ADS)

    Jian, Yifan; Lee, Sujin; Cua, Michelle; Miao, Dongkai; Bonora, Stefano; Zawadzki, Robert J.; Sarunic, Marinko V.

    2016-03-01

    Adaptive optics concepts have been applied to the advancement of biological imaging and microscopy. In particular, AO has also been very successfully applied to cellular resolution imaging of the retina, enabling visualization of the characteristic mosaic patterns of the outer retinal layers using flood illumination fundus photography, Scanning Laser Ophthalmoscopy (SLO), and Optical Coherence Tomography (OCT). Despite the high quality of the in vivo images, there has been a limited uptake of AO imaging into the clinical environment. The high resolution afforded by AO comes at the price of limited field of view and specialized equipment. The implementation of a typical adaptive optics imaging system results in a relatively large and complex optical setup. The wavefront measurement is commonly performed using a Hartmann-Shack Wavefront Sensor (HS-WFS) placed at an image plane that is optically conjugated to the eye's pupil. The deformable mirror is also placed at a conjugate plane, relaying the wavefront corrections to the pupil. Due to the sensitivity of the HS-WFS to back-reflections, the imaging system is commonly constructed from spherical mirrors. In this project, we present a novel adaptive optics OCT retinal imaging system with significant potential to overcome many of the barriers to integration with a clinical environment. We describe in detail the implementation of a compact lens based wavefront sensorless adaptive optics (WSAO) 1060nm swept source OCT human retinal imaging system with dual deformable lenses, and present retinal images acquired in vivo from research volunteers.

  10. Enhanced Adaptive Management: Integrating Decision Analysis, Scenario Analysis and Environmental Modeling for the Everglades

    NASA Astrophysics Data System (ADS)

    Convertino, Matteo; Foran, Christy M.; Keisler, Jeffrey M.; Scarlett, Lynn; Loschiavo, Andy; Kiker, Gregory A.; Linkov, Igor

    2013-10-01

    We propose to enhance existing adaptive management efforts with a decision-analytical approach that can guide the initial selection of robust restoration alternative plans and inform the need to adjust these alternatives in the course of action based on continuously acquired monitoring information and changing stakeholder values. We demonstrate an application of enhanced adaptive management for a wetland restoration case study inspired by the Florida Everglades restoration effort. We find that alternatives designed to reconstruct the pre-drainage flow may have a positive ecological impact, but may also have high operational costs and only marginally contribute to meeting other objectives such as reduction of flooding. Enhanced adaptive management allows managers to guide investment in ecosystem modeling and monitoring efforts through scenario and value of information analyses to support optimal restoration strategies in the face of uncertain and changing information.

  11. Content dependent selection of image enhancement parameters for mobile displays

    NASA Astrophysics Data System (ADS)

    Lee, Yoon-Gyoo; Kang, Yoo-Jin; Kim, Han-Eol; Kim, Ka-Hee; Kim, Choon-Woo

    2011-01-01

    Mobile devices such as cellular phones and portable multimedia player with capability of playing terrestrial digital multimedia broadcasting (T-DMB) contents have been introduced into consumer market. In this paper, content dependent image quality enhancement method for sharpness and colorfulness and noise reduction is presented to improve perceived image quality on mobile displays. Human visual experiments are performed to analyze viewers' preference. Relationship between the objective measures and the optimal values of image control parameters are modeled by simple lookup tables based on the results of human visual experiments. Content dependent values of image control parameters are determined based on the calculated measures and predetermined lookup tables. Experimental results indicate that dynamic selection of image control parameters yields better image quality.

  12. Facial nerve image enhancement from CBCT using supervised learning technique.

    PubMed

    Ping Lu; Barazzetti, Livia; Chandran, Vimal; Gavaghan, Kate; Weber, Stefan; Gerber, Nicolas; Reyes, Mauricio

    2015-08-01

    Facial nerve segmentation plays an important role in surgical planning of cochlear implantation. Clinically available CBCT images are used for surgical planning. However, its relatively low resolution renders the identification of the facial nerve difficult. In this work, we present a supervised learning approach to enhance facial nerve image information from CBCT. A supervised learning approach based on multi-output random forest was employed to learn the mapping between CBCT and micro-CT images. Evaluation was performed qualitatively and quantitatively by using the predicted image as input for a previously published dedicated facial nerve segmentation, and cochlear implantation surgical planning software, OtoPlan. Results show the potential of the proposed approach to improve facial nerve image quality as imaged by CBCT and to leverage its segmentation using OtoPlan. PMID:26736914

  13. Instrumentation For Diffraction Enhanced Imaging Experiments At HASYLAB

    NASA Astrophysics Data System (ADS)

    Lohmann, M.; Dix, W.-R.; Metge, J.; Reime, B.

    2004-05-01

    The new X-ray radiography imaging technique, named diffraction enhanced imaging (DEI), enables almost scatter free absorption imaging, the production of the so-called refraction images of a sample. The images show improved contrast compared to standard imaging applications. At the HASYLAB wiggler beamline W2 at the 2nd-generation storage ring DORIS a 5cm wide beam with an adjustable energy between 10 and 70keV is available. A Si [111] pre-monochromator is used followed by the main monochromator using the (111) or the (333)-reflection. Visualization of fossils, detecting internal pearl structures, monitoring of bone and cartilage and documentation of implant healing in bone are application examples at HASYLAB.

  14. IGF-2 is necessary for retinoblastoma-mediated enhanced adaptation after small-bowel resection.

    PubMed

    Choi, Pamela M; Sun, Raphael C; Sommovilla, Josh; Diaz-Miron, Jose; Guo, Jun; Erwin, Christopher R; Warner, Brad W

    2014-11-01

    Previously, we have demonstrated that genetically disrupting retinoblastoma protein (Rb) expression in enterocytes results in taller villi, mimicking resection-induced adaption responses. Rb deficiency also results in elevated insulin-like growth factor-2 (IGF-2) expression in villus enterocytes. We propose that postoperative disruption of Rb results in enhanced adaptation which is driven by IGF-2. Inducible, intestine-specific Rb-null mice (iRbIKO) and wild-type (WT) littermates underwent a 50% proximal small-bowel resection (SBR) at 7-9 weeks of age. They were then given tamoxifen on postoperative days (PODs) 4-6 and harvested on POD 28. The experiment was then repeated on double knockouts of both IGF-2 and Rb (IGF-2 null/iRbIKO). iRbIKO mice demonstrated enhanced resection-induced adaptive villus growth after SBR and increased IGF-2 messenger RNA (mRNA) in ileal villus enterocytes compared to their WT littermates. In the IGF-2 null/iRbIKO double-knockout mice, there was no additional villus growth beyond what was expected of normal resection-induced adaptation. Adult mice in which Rb is inducibly deleted from the intestinal epithelium following SBR have augmented adaptive growth. IGF-2 expression is necessary for enhanced adaptation associated with acute intestinal Rb deficiency.

  15. A Comparison of Visual Statistics for the Image Enhancement of FORESITE Aerial Images with Those of Major Image Classes

    NASA Technical Reports Server (NTRS)

    Johnson, Daniel J.; Rahman, Zia-ur; Woodell, Glenn A.; Hines, Glenn D.

    2006-01-01

    Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally with the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging--terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

  16. A comparison of visual statistics for the image enhancement of FORESITE aerial images with those of major image classes

    NASA Astrophysics Data System (ADS)

    Jobson, Daniel J.; Rahman, Zia-ur; Woodell, Glenn A.; Hines, Glenn D.

    2006-05-01

    Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally within the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging-terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on the limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

  17. MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods

    PubMed Central

    Schmidt, Johannes F. M.; Santelli, Claudio; Kozerke, Sebastian

    2016-01-01

    An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods. PMID:27116675

  18. The New England Climate Adaptation Project: Enhancing Local Readiness to Adapt to Climate Change through Role-Play Simulations

    NASA Astrophysics Data System (ADS)

    Rumore, D.; Kirshen, P. H.; Susskind, L.

    2014-12-01

    Despite scientific consensus that the climate is changing, local efforts to prepare for and manage climate change risks remain limited. How we can raise concern about climate change risks and enhance local readiness to adapt to climate change's effects? In this presentation, we will share the lessons learned from the New England Climate Adaptation Project (NECAP), a participatory action research project that tested science-based role-play simulations as a tool for educating the public about climate change risks and simulating collective risk management efforts. NECAP was a 2-year effort involving the Massachusetts Institute of Technology, the Consensus Building Institute, the National Estuarine Research Reserve System, and four coastal New England municipalities. During 2012-2013, the NECAP team produced downscaled climate change projections, a summary risk assessment, and a stakeholder assessment for each partner community. Working with local partners, we used these assessments to create a tailored, science-based role-play simulation for each site. Through a series of workshops in 2013, NECAP engaged between 115-170 diverse stakeholders and members of the public in each partner municipality in playing the simulation and a follow up conversation about local climate change risks and possible adaptation strategies. Data were collected through before-and-after surveys administered to all workshop participants, follow-up interviews with 25 percent of workshop participants, public opinion polls conducted before and after our intervention, and meetings with public officials. This presentation will report our research findings and explain how science-based role-play simulations can be used to help communicate local climate change risks and enhance local readiness to adapt.

  19. Molecular Optical Coherence Tomography Contrast Enhancement and Imaging

    NASA Astrophysics Data System (ADS)

    Oldenburg, Amy L.; Applegate, Brian E.; Tucker-Schwartz, Jason M.; Skala, Melissa C.; Kim, Jongsik; Boppart, Stephen A.

    Histochemistry began as early as the nineteenth century, with the development of synthetic dyes that provided spatially mapped chemical contrast in tissue [1]. Stains such as hematoxylin and eosin, which contrast cellular nuclei and cytoplasm, greatly aid in the interpretation of microscopy images. An analogous development is currently taking place in biomedical imaging, whereby techniques adapted for MRI, CT, and PET now provide in vivo molecular imaging over the entire human body, aiding in both fundamental research discovery and in clinical diagnosis and treatment monitoring. Because OCT offers a unique spatial scale that is intermediate between microscopy and whole-body biomedical imaging, molecular contrast OCT (MCOCT) also has great potential for providing new insight into in vivo molecular processes. The strength of MCOCT lies in its ability to isolate signals from a molecule or contrast agent from the tissue scattering background over large scan areas at depths greater than traditional microscopy techniques while maintaining high resolution.

  20. Adaptive memory: Animacy enhances free recall but impairs cued recall.

    PubMed

    Popp, Earl Y; Serra, Michael J

    2016-02-01

    Recent research suggests that human memory systems evolved to remember animate things better than inanimate things. In the present experiments, we examined whether these effects occur for both free recall and cued recall. In Experiment 1, we directly compared the effect of animacy on free recall and cued recall. Participants studied lists of objects and lists of animals for free-recall tests, and studied sets of animal-animal pairs and object-object pairs for cued-recall tests. In Experiment 2, we compared participants' cued recall for English-English, Swahili-English, and English-Swahili word pairs involving either animal or object English words. In Experiment 3, we compared participants' cued recall for animal-animal, object-object, animal-object, and object-animal pairs. Although we were able to replicate past effects of animacy aiding free recall, animacy typically impaired cued recall in the present experiments. More importantly, given the interactions found in the present experiments, we conclude that some factor associated with animacy (e.g., attention capture or mental arousal) is responsible for the present patterns of results. This factor seems to moderate the relationship between animacy and memory, producing a memory advantage for animate stimuli in scenarios where the moderator leads to enhanced target retrievability but a memory disadvantage for animate stimuli in scenarios where the moderator leads to impaired association memory. PMID:26375781

  1. Manganese-enhanced magnetic resonance imaging (MEMRI).

    PubMed

    Koretsky, Alan P; Silva, Afonso C

    2004-12-01

    Manganese ion (Mn2+) is an essential metal that participates as a cofactor in a number of critical biological functions, such as electron transport, detoxification of free radicals and synthesis of neurotransmitters. Mn2+ can enter excitable cells using some of the same transport systems as Ca2+ and it can bind to a number of intracellular sites because it has high affinity for Ca2+ and Mg2+ binding sites on proteins and nucleic acids. Paramagnetic forms of manganese ions are potent MRI relaxation agents. Indeed, Mn2+ was the first contrast agent proposed for use in MRI. Recently, there has been renewed interest in combining the strong MRI relaxation effects of Mn2+ with its unique biology, in order to further expand the already broad assortment of useful information that can be measured by MRI. Such an approach has been continuously developed in the past several years to provide unique tissue contrast, to assess tissue viability, to act as a surrogate marker of calcium influx into cells and to trace neuronal connections. This special issue of NMR in Biomedicine on manganese-enhanced MRI (MEMRI) is aimed at providing the readers of this journal with an extensive review of some of the most prominent applications of MEMRI in biological systems. Written by several of the leaders in the field, the reviews and original research articles featured in this special issue are likely to offer an exciting and inspiring view of the broad range of applications of MEMRI.

  2. Computer image processing - The Viking experience. [digital enhancement techniques

    NASA Technical Reports Server (NTRS)

    Green, W. B.

    1977-01-01

    Computer processing of digital imagery from the Viking mission to Mars is discussed, with attention given to subjective enhancement and quantitative processing. Contrast stretching and high-pass filtering techniques of subjective enhancement are described; algorithms developed to determine optimal stretch and filtering parameters are also mentioned. In addition, geometric transformations to rectify the distortion of shapes in the field of view and to alter the apparent viewpoint of the image are considered. Perhaps the most difficult problem in quantitative processing of Viking imagery was the production of accurate color representations of Orbiter and Lander camera images.

  3. Interior point methods for sea-bottom image enhancement

    NASA Astrophysics Data System (ADS)

    Carmona, Rene A.; Zhong, Sifen

    1997-07-01

    The purpose of this paper is to present an application of global optimization techniques to the problem of the enhancement of images. After reviewing the general strategy which is common to most modern enhancement method based on the solution of a variational problem, we explain the rationale behind the choice of our penalization formulation and we give the details of the practical implementation. Finally, we illustrate the efficiency of our approach by presenting the results obtained in preprocessing side-scan sonar images of the sea-bottom for the purpose of mine detection.

  4. Image analysis and classification by spectrum enhancement: new developments

    NASA Astrophysics Data System (ADS)

    Crosta, Giovanni F.

    2010-01-01

    The "enhanced spectrum" of an image g[.] is a function h[.] of wave-number u obtained by a sequence of operations on the power spectral density of g[.]. The main properties and the available theorems on the correspondence between spectrum enhancement and spatial differentiation, of either integer or fractional order, are stated. In order to apply the enhanced spectrum to image classification, one has to go, by interpolation, from h[.] to a polynomial q[.]. The graph of q[.] provides the set of morphological descriptors of the original image, suitable for submission to a multivariate statistical classifier. Since q[.] depends on an n-tuple, Ψ, of parameters which control image pre-processing, spectrum enhancement and interpolation, then one can train the classifier by tuning Ψ. In fact, classifier training is more articulated and relies on a "design", whereby different training sets are processed. The best performing n-tuple, Ψ*, is selected by maximizing a "design-wide" figure of merit. Next one can apply the trained classifier to recognize new images. A recent application to materials science is summarized.

  5. Detecting content adaptive scaling of images for forensic applications

    NASA Astrophysics Data System (ADS)

    Fillion, Claude; Sharma, Gaurav

    2010-01-01

    Content-aware resizing methods have recently been developed, among which, seam-carving has achieved the most widespread use. Seam-carving's versatility enables deliberate object removal and benign image resizing, in which perceptually important content is preserved. Both types of modifications compromise the utility and validity of the modified images as evidence in legal and journalistic applications. It is therefore desirable that image forensic techniques detect the presence of seam-carving. In this paper we address detection of seam-carving for forensic purposes. As in other forensic applications, we pose the problem of seam-carving detection as the problem of classifying a test image in either of two classes: a) seam-carved or b) non-seam-carved. We adopt a pattern recognition approach in which a set of features is extracted from the test image and then a Support Vector Machine based classifier, trained over a set of images, is utilized to estimate which of the two classes the test image lies in. Based on our study of the seam-carving algorithm, we propose a set of intuitively motivated features for the detection of seam-carving. Our methodology for detection of seam-carving is then evaluated over a test database of images. We demonstrate that the proposed method provides the capability for detecting seam-carving with high accuracy. For images which have been reduced 30% by benign seam-carving, our method provides a classification accuracy of 91%.

  6. Delayed Myocardial Enhancement in Cardiac Magnetic Resonance Imaging

    PubMed Central

    Franco, Arie; Javidi, Saeed; Ruehm, Stefan G

    2015-01-01

    Delayed myocardial enhancement MRI is a highly valuable but non-specific imaging technique that is ancillary in the diagnosis of a variety of diseases including myocardial viability, cardiomyopathy, myocarditis and other infiltrative myocardial processes. The lack of specificity stems from the wide variety of differential diagnoses that may present with overlapping patterns of delayed enhancement. Many of these differential diagnoses have been presented and discussed in this article. PMID:26622933

  7. Enhancing thermal video using a public database of images

    NASA Astrophysics Data System (ADS)

    Qadir, Hemin; Kozaitis, S. P.; Ali, Ehsan

    2014-05-01

    We presented a system to display nightime imagery with natural colors using a public database of images. We initially combined two spectral bands of images, thermal and visible, to enhance night vision imagery, however the fused image gave an unnatural color appearance. Therefore, a color transfer based on look-up table (LUT) was used to replace the false color appearance with a colormap derived from a daytime reference image obtained from a public database using the GPS coordinates of the vehicle. Because of the computational demand in deriving the colormap from the reference image, we created an additional local database of colormaps. Reference images from the public database were compared to a compact local database to retrieve one of a limited number of colormaps that represented several driving environments. Each colormap in the local database was stored with an image from which it was derived. To retrieve a colormap, we compared the histogram of the fused image with histograms of images in the local database. The colormaps of the best match was then used for the fused image. Continuously selecting and applying colormaps using this approach offered a convenient way to color night vision imagery.

  8. A Retina Inspired Model for Enhancing Visibility of Hazy Images

    PubMed Central

    Zhang, Xian-Shi; Gao, Shao-Bing; Li, Chao-Yi; Li, Yong-Jie

    2015-01-01

    The mammalian retina seems far smarter than scientists have believed so far. Inspired by the visual processing mechanisms in the retina, from the layer of photoreceptors to the layer of retinal ganglion cells (RGCs), we propose a computational model for haze removal from a single input image, which is an important issue in the field of image enhancement. In particular, the bipolar cells serve to roughly remove the low-frequency of haze, and the amacrine cells modulate the output of cone bipolar cells to compensate the loss of details by increasing the image contrast. Then the RGCs with disinhibitory receptive field surround refine the local haze removal as well as the image detail enhancement. Results on a variety of real-world and synthetic hazy images show that the proposed model yields results comparative to or even better than the state-of-the-art methods, having the advantage of simultaneous dehazing and enhancing of single hazy image with simple and straightforward implementation. PMID:26733857

  9. Patient-adaptive reconstruction and acquisition in dynamic imaging with sensitivity encoding (PARADISE).

    PubMed

    Sharif, Behzad; Derbyshire, J Andrew; Faranesh, Anthony Z; Bresler, Yoram

    2010-08-01

    MRI of the human heart without explicit cardiac synchronization promises to extend the applicability of cardiac MR to a larger patient population and potentially expand its diagnostic capabilities. However, conventional nongated imaging techniques typically suffer from low image quality or inadequate spatio-temporal resolution and fidelity. Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE) is a highly accelerated nongated dynamic imaging method that enables artifact-free imaging with high spatio-temporal resolutions by utilizing novel computational techniques to optimize the imaging process. In addition to using parallel imaging, the method gains acceleration from a physiologically driven spatio-temporal support model; hence, it is doubly accelerated. The support model is patient adaptive, i.e., its geometry depends on dynamics of the imaged slice, e.g., subject's heart rate and heart location within the slice. The proposed method is also doubly adaptive as it adapts both the acquisition and reconstruction schemes. Based on the theory of time-sequential sampling, the proposed framework explicitly accounts for speed limitations of gradient encoding and provides performance guarantees on achievable image quality. The presented in-vivo results demonstrate the effectiveness and feasibility of the PARADISE method for high-resolution nongated cardiac MRI during short breath-hold. PMID:20665794

  10. Fast microcalcification detection in ultrasound images using image enhancement and threshold adjacency statistics

    NASA Astrophysics Data System (ADS)

    Cho, Baek Hwan; Chang, Chuho; Lee, Jong-Ha; Ko, Eun Young; Seong, Yeong Kyeong; Woo, Kyoung-Gu

    2013-02-01

    The existence of microcalcifications (MCs) is an important marker of malignancy in breast cancer. In spite of the benefits in mass detection for dense breasts, ultrasonography is believed that it might not reliably detect MCs. For computer aided diagnosis systems, however, accurate detection of MCs has the possibility of improving the performance in both Breast Imaging-Reporting and Data System (BI-RADS) lexicon description for calcifications and malignancy classification. We propose a new efficient and effective method for MC detection using image enhancement and threshold adjacency statistics (TAS). The main idea of TAS is to threshold an image and to count the number of white pixels with a given number of adjacent white pixels. Our contribution is to adopt TAS features and apply image enhancement to facilitate MC detection in ultrasound images. We employed fuzzy logic, tophat filter, and texture filter to enhance images for MCs. Using a total of 591 images, the classification accuracy of the proposed method in MC detection showed 82.75%, which is comparable to that of Haralick texture features (81.38%). When combined, the performance was as high as 85.11%. In addition, our method also showed the ability in mass classification when combined with existing features. In conclusion, the proposed method exploiting image enhancement and TAS features has the potential to deal with MC detection in ultrasound images efficiently and extend to the real-time localization and visualization of MCs.

  11. The effect of retinal image error update rate on human vestibulo-ocular reflex gain adaptation.

    PubMed

    Fadaee, Shannon B; Migliaccio, Americo A

    2016-04-01

    The primary function of the angular vestibulo-ocular reflex (VOR) is to stabilise images on the retina during head movements. Retinal image movement is the likely feedback signal that drives VOR modification/adaptation for different viewing contexts. However, it is not clear whether a retinal image position or velocity error is used primarily as the feedback signal. Recent studies examining this signal are limited because they used near viewing to modify the VOR. However, it is not known whether near viewing drives VOR adaptation or is a pre-programmed contextual cue that modifies the VOR. Our study is based on analysis of the VOR evoked by horizontal head impulses during an established adaptation task. Fourteen human subjects underwent incremental unilateral VOR adaptation training and were tested using the scleral search coil technique over three separate sessions. The update rate of the laser target position (source of the retinal image error signal) used to drive VOR adaptation was different for each session [50 (once every 20 ms), 20 and 15/35 Hz]. Our results show unilateral VOR adaptation occurred at 50 and 20 Hz for both the active (23.0 ± 9.6 and 11.9 ± 9.1% increase on adapting side, respectively) and passive VOR (13.5 ± 14.9, 10.4 ± 12.2%). At 15 Hz, unilateral adaptation no longer occurred in the subject group for both the active and passive VOR, whereas individually, 4/9 subjects tested at 15 Hz had significant adaptation. Our findings suggest that 1-2 retinal image position error signals every 100 ms (i.e. target position update rate 15-20 Hz) are sufficient to drive VOR adaptation.

  12. The effect of retinal image error update rate on human vestibulo-ocular reflex gain adaptation.

    PubMed

    Fadaee, Shannon B; Migliaccio, Americo A

    2016-04-01

    The primary function of the angular vestibulo-ocular reflex (VOR) is to stabilise images on the retina during head movements. Retinal image movement is the likely feedback signal that drives VOR modification/adaptation for different viewing contexts. However, it is not clear whether a retinal image position or velocity error is used primarily as the feedback signal. Recent studies examining this signal are limited because they used near viewing to modify the VOR. However, it is not known whether near viewing drives VOR adaptation or is a pre-programmed contextual cue that modifies the VOR. Our study is based on analysis of the VOR evoked by horizontal head impulses during an established adaptation task. Fourteen human subjects underwent incremental unilateral VOR adaptation training and were tested using the scleral search coil technique over three separate sessions. The update rate of the laser target position (source of the retinal image error signal) used to drive VOR adaptation was different for each session [50 (once every 20 ms), 20 and 15/35 Hz]. Our results show unilateral VOR adaptation occurred at 50 and 20 Hz for both the active (23.0 ± 9.6 and 11.9 ± 9.1% increase on adapting side, respectively) and passive VOR (13.5 ± 14.9, 10.4 ± 12.2%). At 15 Hz, unilateral adaptation no longer occurred in the subject group for both the active and passive VOR, whereas individually, 4/9 subjects tested at 15 Hz had significant adaptation. Our findings suggest that 1-2 retinal image position error signals every 100 ms (i.e. target position update rate 15-20 Hz) are sufficient to drive VOR adaptation. PMID:26715411

  13. Hybrid Image Fusion for Sharpness Enhancement of Multi-Spectral Lunar Images

    NASA Astrophysics Data System (ADS)

    Awumah, Anna; Mahanti, Prasun; Robinson, Mark

    2016-10-01

    Image fusion enhances the sharpness of a multi-spectral (MS) image by incorporating spatial details from a higher-resolution panchromatic (Pan) image [1,2]. Known applications of image fusion for planetary images are rare, although image fusion is well-known for its applications to Earth-based remote sensing. In a recent work [3], six different image fusion algorithms were implemented and their performances were verified with images from the Lunar Reconnaissance Orbiter (LRO) Camera. The image fusion procedure obtained a high-resolution multi-spectral (HRMS) product from the LRO Narrow Angle Camera (used as Pan) and LRO Wide Angle Camera (used as MS) images. The results showed that the Intensity-Hue-Saturation (IHS) algorithm results in a high-spatial quality product while the Wavelet-based image fusion algorithm best preserves spectral quality among all the algorithms. In this work we show the results of a hybrid IHS-Wavelet image fusion algorithm when applied to LROC MS images. The hybrid method provides the best HRMS product - both in terms of spatial resolution and preservation of spectral details. Results from hybrid image fusion can enable new science and increase the science return from existing LROC images.[1] Pohl, Cle, and John L. Van Genderen. "Review article multisensor image fusion in remote sensing: concepts, methods and applications." International journal of remote sensing 19.5 (1998): 823-854.[2] Zhang, Yun. "Understanding image fusion." Photogramm. Eng. Remote Sens 70.6 (2004): 657-661.[3] Mahanti, Prasun et al. "Enhancement of spatial resolution of the LROC Wide Angle Camera images." Archives, XXIII ISPRS Congress Archives (2016).

  14. 3D segmentation of masses in DCE-MRI images using FCM and adaptive MRF

    NASA Astrophysics Data System (ADS)

    Zhang, Chengjie; Li, Lihua

    2014-03-01

    Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a sensitive imaging modality for the detection of breast cancer. Automated segmentation of breast lesions in DCE-MRI images is challenging due to inherent signal-to-noise ratios and high inter-patient variability. A novel 3D segmentation method based on FCM and MRF is proposed in this study. In this method, a MRI image is segmented by spatial FCM, firstly. And then MRF segmentation is conducted to refine the result. We combined with the 3D information of lesion in the MRF segmentation process by using segmentation result of contiguous slices to constraint the slice segmentation. At the same time, a membership matrix of FCM segmentation result is used for adaptive adjustment of Markov parameters in MRF segmentation process. The proposed method was applied for lesion segmentation on 145 breast DCE-MRI examinations (86 malignant and 59 benign cases). An evaluation of segmentation was taken using the traditional overlap rate method between the segmented region and hand-drawing ground truth. The average overlap rates for benign and malignant lesions are 0.764 and 0.755 respectively. Then we extracted five features based on the segmentation region, and used an artificial neural network (ANN) to classify between malignant and benign cases. The ANN had a classification performance measured by the area under the ROC curve of AUC=0.73. The positive and negative predictive values were 0.86 and 0.58, respectively. The results demonstrate the proposed method not only achieves a better segmentation performance in accuracy also has a reasonable classification performance.

  15. Image enhancement based on in vivo hyperspectral gastroscopic images: a case study.

    PubMed

    Gu, Xiaozhou; Han, Zhimin; Yao, Liqing; Zhong, Yunshi; Shi, Qiang; Fu, Ye; Liu, Changsheng; Wang, Xiguang; Xie, Tianyu

    2016-10-01

    Hyperspectral imaging (HSI) has been recognized as a powerful tool for noninvasive disease detection in the gastrointestinal field. However, most of the studies on HSI in this field have involved ex vivo biopsies or resected tissues. We proposed an image enhancement method based on in vivo hyperspectral gastroscopic images. First, we developed a flexible gastroscopy system capable of obtaining in vivo hyperspectral images of different types of stomach disease mucosa. Then, depending on a specific object, an appropriate band selection algorithm based on dependence of information was employed to determine a subset of spectral bands that would yield useful spatial information. Finally, these bands were assigned to be the color components of an enhanced image of the object. A gastric ulcer case study demonstrated that our method yields higher color tone contrast, which enhanced the displays of the gastric ulcer regions, and that it will be valuable in clinical applications. PMID:27206742

  16. The evolving role of response-adapted PET imaging in Hodgkin lymphoma

    PubMed Central

    Coyle, Michael; Kostakoglu, Lale; Evens, Andrew M.

    2016-01-01

    18F-fluorodeoxyglucose positron emission tomography with (FDG-PET) has a well-established role in the pre- and post-treatment staging of Hodgkin lymphoma (HL), however its use as a predictive therapeutic tool via responded-adapted therapy continues to evolve. There have been a multitude of retrospective and noncontrolled clinical studies showing that early (or interim) FDG-PET is highly prognostic in HL, particularly in the advanced-stage setting. Response-adapted treatment approaches in HL are attempting to diminish toxicity for low-risk patients by minimizing therapy, and conversely, intensify treatment for high-risk patients. Results from phase III noninferiority studies in early-stage HL with negative interim FDG-PET that randomized patients to chemotherapy alone versus combined modality therapy showed a continued small improvement in progression-free survival for patients who did not receive radiation. Preliminary reports of data escalating therapy for positive interim FDG-PET in early-stage HL and for de-escalation of therapy [i.e. bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine and prednisone (BEACOPP)] for negative interim FDG-PET in advanced stage HL (i.e. deletion of bleomycin) have demonstrated improved outcomes. Maturation of these studies and continued follow up of all response-adapted studies are needed. Altogether, the treatment of HL remains an individualized clinical management choice for physicians and patients. Continued refinement and optimization of FDG-PET is needed, including within the context of targeted therapeutic agents. In addition, a number of new and novel techniques of functional imaging, including metabolic tumor volume and tumor proliferation, are being explored in order to enhance staging, characterization, prognostication and ultimately patient outcome. PMID:27054026

  17. Assessment of brain perfusion using parametric and factor images extracted from dynamic contrast-enhanced MRI images

    NASA Astrophysics Data System (ADS)

    Martel, Anne L.; Moody, Alan R.

    1998-07-01

    Contrast-enhanced magnetic resonance (MR) imaging offers a minimally invasive method of investigating brain blood flow. This paper describes two different methods of extracting quantitative and qualitative information from this data. The first approach is to generate parametric images showing blood flow, blood volume and time-to-peak activity on a pixel by pixel basis. The second approach uses factor analysis. Principal components are extracted from the data and these orthogonal factors are then rotated to give a set of oblique factors, which satisfy certain simple constraints. In most cases three factors can be identified: a background or non- enhancing factor, an early vascular factor which is strongly correlated to arterial flow, and a late vascular factor which is strongly correlated to venous flow. The parametric and factor images are complimentary in nature: the former provides quantitative information that is readily understood by the clinician, while the latter makes no a priori assumptions about the underlying physiology and also allows more subtle changes in cerebral blood flow to be assessed. The factor images may also be of great value in defining regions of interest over which to carry out a more detailed quantitative analysis. This dual approach can be readily adapted to assess perfusion in other organs such as the heart or kidneys.

  18. High-resolution adaptive imaging of a single atom

    NASA Astrophysics Data System (ADS)

    Wong-Campos, J. D.; Johnson, K. G.; Neyenhuis, B.; Mizrahi, J.; Monroe, C.

    2016-09-01

    Optical imaging systems are used extensively in the life and physical sciences because of their ability to non-invasively capture details on the microscopic and nanoscopic scales. Such systems are often limited by source or detector noise, image distortions and human operator misjudgement. Here, we report a general, quantitative method to analyse and correct these errors. We use this method to identify and correct optical aberrations in an imaging system for single atoms and realize an atomic position sensitivity of ∼0.5 nm Hz‑1/2 with a minimum uncertainty of 1.7 nm, allowing the direct imaging of atomic motion. This is the highest position sensitivity ever measured for an isolated atom and opens up the possibility of performing out-of-focus three-dimensional particle tracking, imaging of atoms in three-dimensional optical lattices or sensing forces at the yoctonewton (10‑24 N) scale.

  19. High-resolution adaptive imaging of a single atom

    NASA Astrophysics Data System (ADS)

    Wong-Campos, J. D.; Johnson, K. G.; Neyenhuis, B.; Mizrahi, J.; Monroe, C.

    2016-09-01

    Optical imaging systems are used extensively in the life and physical sciences because of their ability to non-invasively capture details on the microscopic and nanoscopic scales. Such systems are often limited by source or detector noise, image distortions and human operator misjudgement. Here, we report a general, quantitative method to analyse and correct these errors. We use this method to identify and correct optical aberrations in an imaging system for single atoms and realize an atomic position sensitivity of ˜0.5 nm Hz-1/2 with a minimum uncertainty of 1.7 nm, allowing the direct imaging of atomic motion. This is the highest position sensitivity ever measured for an isolated atom and opens up the possibility of performing out-of-focus three-dimensional particle tracking, imaging of atoms in three-dimensional optical lattices or sensing forces at the yoctonewton (10-24 N) scale.

  20. Diffraction enhanced imaging contrast mechanisms and applications to medicine

    NASA Astrophysics Data System (ADS)

    Hasnah, Moumen Omar

    X-rays are one of the most commonly used forms of radiation in medical diagnostic imaging because of their ability to penetrate the body and give morphological information. Although several interactions may occur, as the x-ray photons traverse the object being radiographed, all of the common x-ray imaging techniques are based on absorption contrast. The fact that the density variations of these tissues are small makes soft tissue imaging difficult with x-rays. A number of imaging modalities have been developed to address the problem of soft tissue imaging that are of clinical relevance. These modalities typically use alternate methods of visualization based on sound propagation (ultrasound), proton density (Magnetic Resonance Imaging-MRI), and others. In addition, enhancements to the x-ray technique include computed tomography (Computed Axial Tomography---CAT) that has more sensitivity to tissue density, phase contrast methods relying on the phase of the traversing x-rays, and refraction methods such as Diffraction Enhanced Imaging (DEI). Of these techniques, ultrasound, MRI and CAT scans are presently common clinical techniques that are used to assist in the diagnosis and isolation of lesions in tissue. DEI is experimental technique that may someday be clinical used due to the high soft tissue contrast.

  1. Contrast-enhancement techniques for particle-image velocimetry.

    PubMed

    Dellenback, P A; Macharivilakathu, J; Pierce, S R

    2000-11-10

    In video-based particle-image velocimetry (PIV) systems for fluid mechanics research, it is sometimes desirable to image seed particles to be smaller than a camera pixel. However, imaging to this size can lead to marginal image contrast such that significant numbers of erroneous velocity vectors can be computed, even for simple flow fields. A variety of image-enhancement techniques suitable for a low-cost PIV system that uses video cameras are examined and tested on three representative flows. Techniques such as linear contrast enhancement and histogram hyperbolization are shown to have good potential for improving the image contrast and hence the accuracy of the data-reduction process with only a 15% increase in the computational time. Some other schemes that were examined appear to be of little practical value in PIV applications. An automated shifting algorithm based on mass conservation is shown to be useful for displacing the second interrogation region in the direction of flow, which minimizes the number of uncorrelated particle images that contribute noise to the data-reduction process. PMID:18354603

  2. Multiscale image fusion using an adaptive similarity-based sensor weighting scheme and human visual system-inspired contrast measure

    NASA Astrophysics Data System (ADS)

    Nercessian, Shahan C.; Panetta, Karen A.; Agaian, Sos S.

    2012-04-01

    The goal of image fusion is to combine multiple source images obtained using different capture techniques into a single image to provide an effective contextual enhancement of a scene for human or machine perception. In practice, considerable value can be gained in the fusion of images that are dissimilar or complementary in nature. However, in such cases, global weighting schemes may not sufficiently weigh the contribution of the pertinent information of the source images, while existing adaptive schemes calculate weights based on the relative amounts of salient features, which can cause severe artifacting or inadequate local luminance in the fusion result. Accordingly, a new multiscale image fusion algorithm is proposed. The approximation coefficient fusion rule of the algorithm is based on a novel similarity based weighting scheme capable of providing improved fusion results when the input source images are either similar or dissimilar to each other. Moreover, the algorithm employs a new detail coefficient fusion rule integrating a parametric multiscale contrast measure. The parametric nature of the contrast measure allows the degree to which psychophysical laws of human vision hold to be tuned based on image-dependent characteristics. Experimental results illustrate the superior performance of the proposed algorithm qualitatively and quantitatively.

  3. Noise suppressed, multifocus image fusion for enhanced intraoperative navigation

    PubMed Central

    Feruglio, Paolo Fumene; Vinegoni, Claudio; Fexon, Lyuba; Thurber, Greg; Sbarbati, Andrea; Weissleder, Ralph

    2013-01-01

    Current intraoperative imaging systems are typically not able to provide ‘sharp’ images over entire large areas or entire organs. Distinct structures such as tissue margins or groups of malignant cells are therefore often difficult to detect, especially under low signal-to-noise-ratio conditions. In this report, we introduce a noise suppressed multifocus image fusion algorithm, that provides detailed reconstructions even when images are acquired under sub-optimal conditions, such is the case for real time fluorescence intraoperative surgery. The algorithm makes use of the Anscombe transform combined with a multi-level stationary wavelet transform with individual threshold-based shrinkage. While the imaging system is integrated with a respiratory monitor triggering system, it can be easily adapted to any commercial imaging system. The developed algorithm is made available as a plugin for Osirix. Intraoperative detection of small malignant fluorescent cells using the proposed noise suppressed multifocus image fusion system. Red/Yellow circles indicate small groups of malignant cells. PMID:22887724

  4. Adaptation to Leftward-shifting Prisms Enhances Local Processing in Healthy Individuals

    PubMed Central

    Reed, Scott A.; Dassonville, Paul

    2014-01-01

    In healthy individuals, adaptation to left-shifting prisms has been shown to simulate the symptoms of hemispatial neglect, including a reduction in global processing that approximates the local bias observed in neglect patients. The current study tested whether leftward prism adaptation can more specifically enhance local processing abilities. In three experiments, the impact of local and global processing was assessed through tasks that measure susceptibility to illusions that are known to be driven by local or global contextual effects. Susceptibility to the rod-and-frame illusion – an illusion disproportionately driven by both local and global effects depending on frame size – was measured before and after adaptation to left- and right-shifting prisms. A significant increase in rod-and-frame susceptibility was found for the left-shifting prism group, suggesting that adaptation caused an increase in local processing effects. The results of a second experiment confirmed that leftward prism adaptation enhances local processing, as assessed with susceptibility to the simultaneous-tilt illusion. A final experiment employed a more specific measure of the global effect typically associated with the rod-andframe illusion, and found that although the global effect was somewhat diminished after leftward prism adaptation, the trend failed to reach significance (p = .078). Rightward prism adaptation had no significant effects on performance in any of the experiments. Combined, these findings indicate that leftward prism adaptation in healthy individuals can simulate the local processing bias of neglect patients primarily through an increased sensitivity to local visual cues, and confirm that prism adaptation not only modulates lateral shifts of attention, but also prompts shifts from one level of processing to another. PMID:24560913

  5. Adaptation to leftward-shifting prisms enhances local processing in healthy individuals.

    PubMed

    Reed, Scott A; Dassonville, Paul

    2014-04-01

    In healthy individuals, adaptation to left-shifting prisms has been shown to simulate the symptoms of hemispatial neglect, including a reduction in global processing that approximates the local bias observed in neglect patients. The current study tested whether leftward prism adaptation can more specifically enhance local processing abilities. In three experiments, the impact of local and global processing was assessed through tasks that measure susceptibility to illusions that are known to be driven by local or global contextual effects. Susceptibility to the rod-and-frame illusion - an illusion disproportionately driven by both local and global effects depending on frame size - was measured before and after adaptation to left- and right-shifting prisms. A significant increase in rod-and-frame susceptibility was found for the left-shifting prism group, suggesting that adaptation caused an increase in local processing effects. The results of a second experiment confirmed that leftward prism adaptation enhances local processing, as assessed with susceptibility to the simultaneous-tilt illusion. A final experiment employed a more specific measure of the global effect typically associated with the rod-and-frame illusion, and found that although the global effect was somewhat diminished after leftward prism adaptation, the trend failed to reach significance (p=.078). Rightward prism adaptation had no significant effects on performance in any of the experiments. Combined, these findings indicate that leftward prism adaptation in healthy individuals can simulate the local processing bias of neglect patients primarily through an increased sensitivity to local visual cues, and confirm that prism adaptation not only modulates lateral shifts of attention, but also prompts shifts from one level of processing to another.

  6. Overcoming the distortion problem in image-enhanced fluoroscopy

    NASA Astrophysics Data System (ADS)

    West, Jay B.; Khadem, Rasool; Maurer, Calvin R., Jr.

    2003-05-01

    In this paper, we examine the problem of image distortion influoroscopy, in particular its effect applications in image-guided surgery that make use of tracking and calibration techniques to relate a point in physical space in the operating room (OR)to the corresponding pointin an intraoperative fluoroscopic image. We call such applications image-enhanced fluoroscopy. In order to derive the relationship between physical space and a fluoroscopic image, two sets of parameters must be known. The first set describes the pose of the fluoroscope at the time when the image was taken; these parameters are usually estimated by rigidly attaching a device to the fluoroscope that is able to be tracked by either an optical or magnetic tracking system present in the OR. The second set of parameters describes the projection model of the fluoroscope itself: this set includes focal length and X-ray source position relative to the image intensifier. In the case that we examine here, these values are estimated using a set of BBs of known geometry placed between the X-ray source and the image intensifier. Because the image intensifier is not perfectly planar, and also because of ambient magnetic fields, the image displayed by the fluoroscope does not match that predicted by a linear projection model. Using the known geometry of the BBs appearing in the image, we may attempt to recover the image that would be given by a linear projection. We call this process dewarping. In this paper, we address the question of the optimal dewarp function. Although a fifth-order polynomial is commonly used, we show that a third-order polynomial is superior. We use real fluoroscope images to demonstrate the potential dangers of using too high a polynomial order for the dewarping process.

  7. Experimental Demonstration of Adaptive Infrared Multispectral Imaging using Plasmonic Filter Array

    PubMed Central

    Jang, Woo-Yong; Ku, Zahyun; Jeon, Jiyeon; Kim, Jun Oh; Lee, Sang Jun; Park, James; Noyola, Michael J.; Urbas, Augustine

    2016-01-01

    In our previous theoretical study, we performed target detection using a plasmonic sensor array incorporating the data-processing technique termed “algorithmic spectrometry”. We achieved the reconstruction of a target spectrum by extracting intensity at multiple wavelengths with high resolution from the image data obtained from the plasmonic array. The ultimate goal is to develop a full-scale focal plane array with a plasmonic opto-coupler in order to move towards the next generation of versatile infrared cameras. To this end, and as an intermediate step, this paper reports the experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios. Each plasmonic filter was designed using periodic circular holes perforated through a gold layer, and an enhanced target detection strategy was proposed to refine the original spectrometry concept for spatial and spectral computation of the data measured from the plasmonic array. Both the spectrum of blackbody radiation and a metal ring object at multiple wavelengths were successfully reconstructed using the weighted superposition of plasmonic output images as specified in the proposed detection strategy. In addition, plasmonic filter arrays were theoretically tested on a target at extremely high temperature as a challenging scenario for the detection scheme. PMID:27721506

  8. Experimental Demonstration of Adaptive Infrared Multispectral Imaging using Plasmonic Filter Array

    NASA Astrophysics Data System (ADS)

    Jang, Woo-Yong; Ku, Zahyun; Jeon, Jiyeon; Kim, Jun Oh; Lee, Sang Jun; Park, James; Noyola, Michael J.; Urbas, Augustine

    2016-10-01

    In our previous theoretical study, we performed target detection using a plasmonic sensor array incorporating the data-processing technique termed “algorithmic spectrometry”. We achieved the reconstruction of a target spectrum by extracting intensity at multiple wavelengths with high resolution from the image data obtained from the plasmonic array. The ultimate goal is to develop a full-scale focal plane array with a plasmonic opto-coupler in order to move towards the next generation of versatile infrared cameras. To this end, and as an intermediate step, this paper reports the experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios. Each plasmonic filter was designed using periodic circular holes perforated through a gold layer, and an enhanced target detection strategy was proposed to refine the original spectrometry concept for spatial and spectral computation of the data measured from the plasmonic array. Both the spectrum of blackbody radiation and a metal ring object at multiple wavelengths were successfully reconstructed using the weighted superposition of plasmonic output images as specified in the proposed detection strategy. In addition, plasmonic filter arrays were theoretically tested on a target at extremely high temperature as a challenging scenario for the detection scheme.

  9. Determining the imaging plane of a retinal capillary layer in adaptive optical imaging

    NASA Astrophysics Data System (ADS)

    Yang, Le-Bao; Hu, Li-Fa; Li, Da-Yu; Cao, Zhao-Liang; Mu, Quan-Quan; Ma, Ji; Xuan, Li

    2016-09-01

    Even in the early stage, endocrine metabolism disease may lead to micro aneurysms in retinal capillaries whose diameters are less than 10 μm. However, the fundus cameras used in clinic diagnosis can only obtain images of vessels larger than 20 μm in diameter. The human retina is a thin and multiple layer tissue, and the layer of capillaries less than 10 μm in diameter only exists in the inner nuclear layer. The layer thickness of capillaries less than 10 μm in diameter is about 40 μm and the distance range to rod&cone cell surface is tens of micrometers, which varies from person to person. Therefore, determining reasonable capillary layer (CL) position in different human eyes is very difficult. In this paper, we propose a method to determine the position of retinal CL based on the rod&cone cell layer. The public positions of CL are recognized with 15 subjects from 40 to 59 years old, and the imaging planes of CL are calculated by the effective focal length of the human eye. High resolution retinal capillary imaging results obtained from 17 subjects with a liquid crystal adaptive optics system (LCAOS) validate our method. All of the subjects’ CLs have public positions from 127 μm to 147 μm from the rod&cone cell layer, which is influenced by the depth of focus. Project supported by the National Natural Science Foundation of China (Grant Nos. 11174274, 11174279, 61205021, 11204299, 61475152, and 61405194).

  10. Determining the imaging plane of a retinal capillary layer in adaptive optical imaging

    NASA Astrophysics Data System (ADS)

    Yang, Le-Bao; Hu, Li-Fa; Li, Da-Yu; Cao, Zhao-Liang; Mu, Quan-Quan; Ma, Ji; Xuan, Li

    2016-09-01

    Even in the early stage, endocrine metabolism disease may lead to micro aneurysms in retinal capillaries whose diameters are less than 10 μm. However, the fundus cameras used in clinic diagnosis can only obtain images of vessels larger than 20 μm in diameter. The human retina is a thin and multiple layer tissue, and the layer of capillaries less than 10 μm in diameter only exists in the inner nuclear layer. The layer thickness of capillaries less than 10 μm in diameter is about 40 μm and the distance range to rod&cone cell surface is tens of micrometers, which varies from person to person. Therefore, determining reasonable capillary layer (CL) position in different human eyes is very difficult. In this paper, we propose a method to determine the position of retinal CL based on the rod&cone cell layer. The public positions of CL are recognized with 15 subjects from 40 to 59 years old, and the imaging planes of CL are calculated by the effective focal length of the human eye. High resolution retinal capillary imaging results obtained from 17 subjects with a liquid crystal adaptive optics system (LCAOS) validate our method. All of the subjects’ CLs have public positions from 127 μm to 147 μm from the rod&cone cell layer, which is influenced by the depth of focus. Project supported by the National Natural Science Foundation of China (Grant Nos. 11174274, 11174279, 61205021, 11204299, 61475152, and 61405194).

  11. Darkfield adapter for whole slide imaging: adapting a darkfield internal reflection illumination system to extend WSI applications.

    PubMed

    Kawano, Yoshihiro; Higgins, Christopher; Yamamoto, Yasuhito; Nyhus, Julie; Bernard, Amy; Dong, Hong-Wei; Karten, Harvey J; Schilling, Tobias

    2013-01-01

    We present a new method for whole slide darkfield imaging. Whole Slide Imaging (WSI), also sometimes called virtual slide or virtual microscopy technology, produces images that simultaneously provide high resolution and a wide field of observation that can encompass the entire section, extending far beyond any single field of view. For example, a brain slice can be imaged so that both overall morphology and individual neuronal detail can be seen. We extended the capabilities of traditional whole slide systems and developed a prototype system for darkfield internal reflection illumination (DIRI). Our darkfield system uses an ultra-thin light-emitting diode (LED) light source to illuminate slide specimens from the edge of the slide. We used a new type of side illumination, a variation on the internal reflection method, to illuminate the specimen and create a darkfield image. This system has four main advantages over traditional darkfield: (1) no oil condenser is required for high resolution imaging (2) there is less scatter from dust and dirt on the slide specimen (3) there is less halo, providing a more natural darkfield contrast image, and (4) the motorized system produces darkfield, brightfield and fluorescence images. The WSI method sometimes allows us to image using fewer stains. For instance, diaminobenzidine (DAB) and fluorescent staining are helpful tools for observing protein localization and volume in tissues. However, these methods usually require counter-staining in order to visualize tissue structure, limiting the accuracy of localization of labeled cells within the complex multiple regions of typical neurohistological preparations. Darkfield imaging works on the basis of light scattering from refractive index mismatches in the sample. It is a label-free method of producing contrast in a sample. We propose that adapting darkfield imaging to WSI is very useful, particularly when researchers require additional structural information without the use of

  12. Resiliency of the Multiscale Retinex Image Enhancement Algorithm

    NASA Technical Reports Server (NTRS)

    Rahman, Zia-Ur; Jobson, Daniel J.; Woodell, Glenn A.

    1998-01-01

    The multiscale retinex with color restoration (MSRCR) continues to prove itself in extensive testing to be very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition, However, issues remain with regard to the resiliency of the MSRCR to different image sources and arbitrary image manipulations which may have been applied prior to retinex processing. In this paper we define these areas of concern, provide experimental results, and, examine the effects of commonly occurring image manipulation on retinex performance. In virtually all cases the MSRCR is highly resilient to the effects of both the image source variations and commonly encountered prior image-processing. Significant artifacts are primarily observed for the case of selective color channel clipping in large dark zones in a image. These issues are of concerning the processing of digital image archives and other applications where there is neither control over the image acquisition process, nor knowledge about any processing done on th data beforehand.

  13. Color contrast enhancement method of infrared polarization fused image

    NASA Astrophysics Data System (ADS)

    Yang, Fan; Xie, Chen

    2015-10-01

    As the traditional color fusion method based on color transfer algorithm has an issue that the color of target and background is similar. A kind of infrared polarization image color fusion method based on color contrast enhancement was proposed. Firstly the infrared radiation intensity image and the polarization image were color fused, and then color transfer technology was used between color reference image and initial fused image in the YCbCr color space. Secondly Otsu segmentation method was used to extract the target area image from infrared polarization image. Lastly the H,S,I component of the color fusion image which obtained by color transfer was adjusted to obtain the final fused image by using target area in the HSI space. Experimental results show that, the fused result which obtained by the proposed method is rich in detail and makes the contrast of target and background more outstanding. And then the ability of target detection and identification can be improved by the method.

  14. Augmented multisensory feedback enhances locomotor adaptation in humans with incomplete spinal cord injury.

    PubMed

    Yen, Sheng-Che; Landry, Jill M; Wu, Ming

    2014-06-01

    Different forms of augmented feedback may engage different motor learning pathways, but it is unclear how these pathways interact with each other, especially in patients with incomplete spinal cord injury (SCI). The purpose of this study was to test whether augmented multisensory feedback could enhance aftereffects following short term locomotor training (i.e., adaptation) in patients with incomplete SCI. A total of 10 subjects with incomplete SCI were recruited to perform locomotor adaptation. Three types of augmented feedback were provided during the adaptation: (a) computerized visual cues showing the actual and target stride length (augmented visual feedback); (b) a swing resistance applied to the leg (augmented proprioceptive feedback); (c) a combination of the visual cues and resistance (augmented multisensory feedback). The results showed that subjects' stride length increased in all conditions following the adaptation, but the increase was greater and retained longer in the multisensory feedback condition. The multisensory feedback provided in this study may engage both explicit and implicit learning pathways during the adaptation and in turn enhance the aftereffect. The results implied that multisensory feedback may be used as an adjunctive approach to enhance gait recovery in humans with SCI. PMID:24746604

  15. Image enhancement and segmentation of fluid-filled structures in 3D ultrasound images

    NASA Astrophysics Data System (ADS)

    Chalana, Vikram; Dudycha, Stephen; McMorrow, Gerald

    2003-05-01

    Segmentation of fluid-filled structures, such as the urinary bladder, from three-dimensional ultrasound images is necessary for measuring their volume. This paper describes a system for image enhancement, segmentation and volume measurement of fluid-filled structures on 3D ultrasound images. The system was applied for the measurement of urinary bladder volume. Results show an average error of less than 10% in the estimation of the total bladder volume.

  16. Multichannel Speech Enhancement Based on Generalized Gamma Prior Distribution with Its Online Adaptive Estimation

    NASA Astrophysics Data System (ADS)

    Dat, Tran Huy; Takeda, Kazuya; Itakura, Fumitada

    We present a multichannel speech enhancement method based on MAP speech spectral magnitude estimation using a generalized gamma model of speech prior distribution, where the model parameters are adapted from actual noisy speech in a frame-by-frame manner. The utilization of a more general prior distribution with its online adaptive estimation is shown to be effective for speech spectral estimation in noisy environments. Furthermore, the multi-channel information in terms of cross-channel statistics are shown to be useful to better adapt the prior distribution parameters to the actual observation, resulting in better performance of speech enhancement algorithm. We tested the proposed algorithm in an in-car speech database and obtained significant improvements of the speech recognition performance, particularly under non-stationary noise conditions such as music, air-conditioner and open window.

  17. Adaptive Memory: Young Children Show Enhanced Retention of Fitness-Related Information

    ERIC Educational Resources Information Center

    Aslan, Alp; Bauml, Karl-Heinz T.

    2012-01-01

    Evolutionary psychologists propose that human cognition evolved through natural selection to solve adaptive problems related to survival and reproduction, with its ultimate function being the enhancement of reproductive fitness. Following this proposal and the evolutionary-developmental view that ancestral selection pressures operated not only on…

  18. Can Survival Processing Enhance Story Memory? Testing the Generalizability of the Adaptive Memory Framework

    ERIC Educational Resources Information Center

    Seamon, John G.; Bohn, Justin M.; Coddington, Inslee E.; Ebling, Maritza C.; Grund, Ethan M.; Haring, Catherine T.; Jang, Sue-Jung; Kim, Daniel; Liong, Christopher; Paley, Frances M.; Pang, Luke K.; Siddique, Ashik H.

    2012-01-01

    Research from the adaptive memory framework shows that thinking about words in terms of their survival value in an incidental learning task enhances their free recall relative to other semantic encoding strategies and intentional learning (Nairne, Pandeirada, & Thompson, 2008). We found similar results. When participants used incidental survival…

  19. Non-adaptive and adaptive hybrid approaches for enhancing water quality management

    NASA Astrophysics Data System (ADS)

    Kalwij, Ineke M.; Peralta, Richard C.

    2008-09-01

    SummaryUsing optimization to help solve groundwater management problems cost-effectively is becoming increasingly important. Hybrid optimization approaches, that combine two or more optimization algorithms, will become valuable and common tools for addressing complex nonlinear hydrologic problems. Hybrid heuristic optimizers have capabilities far beyond those of a simple genetic algorithm (SGA), and are continuously improving. SGAs having only parent selection, crossover, and mutation are inefficient and rarely used for optimizing contaminant transport management. Even an advanced genetic algorithm (AGA) that includes elitism (to emphasize using the best strategies as parents) and healing (to help assure optimal strategy feasibility) is undesirably inefficient. Much more efficient than an AGA is the presented hybrid (AGCT), which adds comprehensive tabu search (TS) features to an AGA. TS mechanisms (TS probability, tabu list size, search coarseness and solution space size, and a TS threshold value) force the optimizer to search portions of the solution space that yield superior pumping strategies, and to avoid reproducing similar or inferior strategies. An AGCT characteristic is that TS con