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Sample records for adaptive image enhancement

  1. Local adaptive contrast enhancement for color images

    NASA Astrophysics Data System (ADS)

    Dijk, Judith; den Hollander, Richard J. M.; Schavemaker, John G. M.; Schutte, Klamer

    2007-04-01

    A camera or display usually has a smaller dynamic range than the human eye. For this reason, objects that can be detected by the naked eye may not be visible in recorded images. Lighting is here an important factor; improper local lighting impairs visibility of details or even entire objects. When a human is observing a scene with different kinds of lighting, such as shadows, he will need to see details in both the dark and light parts of the scene. For grey value images such as IR imagery, algorithms have been developed in which the local contrast of the image is enhanced using local adaptive techniques. In this paper, we present how such algorithms can be adapted so that details in color images are enhanced while color information is retained. We propose to apply the contrast enhancement on color images by applying a grey value contrast enhancement algorithm to the luminance channel of the color signal. The color coordinates of the signal will remain the same. Care is taken that the saturation change is not too high. Gamut mapping is performed so that the output can be displayed on a monitor. The proposed technique can for instance be used by operators monitoring movements of people in order to detect suspicious behavior. To do this effectively, specific individuals should both be easy to recognize and track. This requires optimal local contrast, and is sometimes much helped by color when tracking a person with colored clothes. In such applications, enhanced local contrast in color images leads to more effective monitoring.

  2. 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.

  3. Adaptive Intuitionistic Fuzzy Enhancement of Brain Tumor MR Images

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

    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.

  4. 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

  5. Adaptive Intuitionistic Fuzzy Enhancement of Brain Tumor MR Images.

    PubMed

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

    2016-10-27

    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.

  6. The new adaptive enhancement algorithm on the degraded color images

    NASA Astrophysics Data System (ADS)

    Xue, Rong Kun; He, Wei; Li, Yufeng

    2016-10-01

    Based on the scene characteristics of frequency distribution in the degraded color images, the MSRCR method and wavelet transform in the paper are introduced respectively to enhance color images and the advantages and disadvantages of them are analyzed combining with the experiment, then the combination of improved MSRCR method and wavelet transform are proposed to enhance color images, it uses wavelet to decompose color images in order to increase the coefficient of low-level details and reduce top-level details to highlight the scene information, meanwhile, the method of improved MSRCR is used to enhance the low-frequency components of degraded images processed by wavelet, then the adaptive equalization is carried on to further enhance images, finally, the enhanced color images are acquired with the reconstruction of all the coefficients brought by the wavelet transform. Through the evaluation of the experimental results and data analysis, it shows that the method proposed in the paper is better than the separate use of wavelet transform and MSRCR method.

  7. 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.

  8. Enhancing image quality in cleared tissue with adaptive optics

    NASA Astrophysics Data System (ADS)

    Reinig, Marc R.; Novak, Samuel W.; Tao, Xiaodong; Bentolila, Laurent A.; Roberts, Dustin G.; MacKenzie-Graham, Allan; Godshalk, Sirie E.; Raven, Mary A.; Knowles, David W.; Kubby, Joel

    2016-12-01

    Our ability to see fine detail at depth in tissues is limited by scattering and other refractive characteristics of the tissue. For fixed tissue, we can limit scattering with a variety of clearing protocols. This allows us to see deeper but not necessarily clearer. Refractive aberrations caused by the bulk index of refraction of the tissue and its variations continue to limit our ability to see fine detail. Refractive aberrations are made up of spherical and other Zernike modes, which can be significant at depth. Spherical aberration that is common across the imaging field can be corrected using an objective correcting collar, although this can require manual intervention. Other aberrations may vary across the imaging field and can only be effectively corrected using adaptive optics. Adaptive optics can also correct other aberrations simultaneously with the spherical aberration, eliminating manual intervention and speeding imaging. We use an adaptive optics two-photon microscope to examine the impact of the spherical and higher order aberrations on imaging and contrast the effect of compensating only for spherical aberration against compensating for the first 22 Zernike aberrations in two tissue types. Increase in image intensity by 1.6× and reduction of root mean square error by 3× are demonstrated.

  9. 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.

  10. Infrared image gray adaptive adjusting enhancement algorithm based on gray redundancy histogram-dealing technique

    NASA Astrophysics Data System (ADS)

    Hao, Zi-long; Liu, Yong; Chen, Ruo-wang

    2016-11-01

    In view of the histogram equalizing algorithm to enhance image in digital image processing, an Infrared Image Gray adaptive adjusting Enhancement Algorithm Based on Gray Redundancy Histogram-dealing Technique is proposed. The algorithm is based on the determination of the entire image gray value, enhanced or lowered the image's overall gray value by increasing appropriate gray points, and then use gray-level redundancy HE method to compress the gray-scale of the image. The algorithm can enhance image detail information. Through MATLAB simulation, this paper compares the algorithm with the histogram equalization method and the algorithm based on gray redundancy histogram-dealing technique , and verifies the effectiveness of the algorithm.

  11. Adaptive gamma correction based on cumulative histogram for enhancing near-infrared images

    NASA Astrophysics Data System (ADS)

    Huang, Zhenghua; Zhang, Tianxu; Li, Qian; Fang, Hao

    2016-11-01

    Histogram-based methods have been proven their ability in image enhancement. To improve low contrast while preserving details and high brightness in near-infrared images, a novel method called adaptive gamma correction based on cumulative histogram (AGCCH) is studied in this paper. This novel image enhancement method improves the contrast of local pixels through adaptive gamma correction (AGC), which is formed by incorporating a cumulative histogram or cumulative sub-histogram into the weighting distribution. Both qualitatively and quantitatively, experimental results demonstrate that the proposed image enhancement with the AGCCH method can perform well in brightness preservation, contrast enhancement, and detail preservation, and it is superior to previous state-of-the-art methods.

  12. Retinal imaging system with adaptive optics enhanced with pupil tracking

    NASA Astrophysics Data System (ADS)

    Sahin, Betul; Lamory, Barbara; Levecq, Xavier; Vabre, Laurent; Dainty, Chris

    2011-03-01

    A compact retinal camera with adaptive optics which was designed for clinical practice was used to test a new adaptive optics control algorithm to correct for the angular ray deviations of a model eye. The new control algorithm is based on pupil movements rather than the measurement of the slopes of the wavefront with an optoelectronic sensor. The method for the control algorithm was based on the hypothesis that majority of the changes of the aberrations of the eye are due to head and eye movements and it is possible to correct for the aberrations of the eye by shifting the paraxial correction according to the new position of the pupil. Since the fixational eye movements are very small, the eye movements are assumed to be translational rather than rotational. Using the new control algorithm it was possible to simulate the aberrations of the moving model eye based on pupil tracking. The RMS of the residual wavefront error of the simulation had a magnitude similar to the RMS of the residual wavefront error of the adaptive optics correction based on optoelectronic sensor for angular ray deviations. If our hypothesis is true and other factors such as the tear film or the crystalline lens fluctuations do not cause changes in the aberrations of the eye as much as motion does, the method is expected to work in vivo as it did for a model eye which had no intrinsic factors that cause aberration changes.

  13. Adaptive Image Enhancement for Tracing 3D Morphologies of Neurons and Brain Vasculatures.

    PubMed

    Zhou, Zhi; Sorensen, Staci; Zeng, Hongkui; Hawrylycz, Michael; Peng, Hanchuan

    2015-04-01

    It is important to digitally reconstruct the 3D morphology of neurons and brain vasculatures. A number of previous methods have been proposed to automate the reconstruction process. However, in many cases, noise and low signal contrast with respect to the image background still hamper our ability to use automation methods directly. Here, we propose an adaptive image enhancement method specifically designed to improve the signal-to-noise ratio of several types of individual neurons and brain vasculature images. Our method is based on detecting the salient features of fibrous structures, e.g. the axon and dendrites combined with adaptive estimation of the optimal context windows where such saliency would be detected. We tested this method for a range of brain image datasets and imaging modalities, including bright-field, confocal and multiphoton fluorescent images of neurons, and magnetic resonance angiograms. Applying our adaptive enhancement to these datasets led to improved accuracy and speed in automated tracing of complicated morphology of neurons and vasculatures.

  14. 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.

  15. 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

  16. Investigation on improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering

    NASA Astrophysics Data System (ADS)

    Zeng, Bangze; Zhu, Youpan; Li, Zemin; Hu, Dechao; Luo, Lin; Zhao, Deli; Huang, Juan

    2014-11-01

    Duo to infrared image with low contrast, big noise and unclear visual effect, target is very difficult to observed and identified. This paper presents an improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering (AHSS-GF). Based on the fact that the human eyes are very sensitive to the edges and lines, the author proposed to extract the details and textures by using the gradient filtering. New histogram could be acquired by calculating the sum of original histogram based on fixed window. With the minimum value for cut-off point, author carried on histogram statistical stretching. After the proper weights given to the details and background, the detail-enhanced results could be acquired finally. The results indicate image contrast could be improved and the details and textures could be enhanced effectively as well.

  17. 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

  18. 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.

  19. Structured light 3D depth map enhancement and gesture recognition using image content adaptive filtering

    NASA Astrophysics Data System (ADS)

    Ramachandra, Vikas; Nash, James; Atanassov, Kalin; Goma, Sergio

    2013-03-01

    A structured-light system for depth estimation is a type of 3D active sensor that consists of a structured-light projector that projects an illumination pattern on the scene (e.g. mask with vertical stripes) and a camera which captures the illuminated scene. Based on the received patterns, depths of different regions in the scene can be inferred. In this paper, we use side information in the form of image structure to enhance the depth map. This side information is obtained from the received light pattern image reflected by the scene itself. The processing steps run real time. This post-processing stage in the form of depth map enhancement can be used for better hand gesture recognition, as is illustrated in this paper.

  20. 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

  1. 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.

  2. 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.

  3. Adaptive Image Denoising by Mixture Adaptation.

    PubMed

    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. The 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.

  4. Wide-field retinal optical coherence tomography with wavefront sensorless adaptive optics for enhanced imaging of targeted regions

    PubMed Central

    Polans, James; Keller, Brenton; Carrasco-Zevallos, Oscar M.; LaRocca, Francesco; Cole, Elijah; Whitson, Heather E.; Lad, Eleonora M.; Farsiu, Sina; Izatt, Joseph A.

    2016-01-01

    The peripheral retina of the human eye offers a unique opportunity for assessment and monitoring of ocular diseases. We have developed a novel wide-field (>70°) optical coherence tomography system (WF-OCT) equipped with wavefront sensorless adaptive optics (WSAO) for enhancing the visualization of smaller (<25°) targeted regions in the peripheral retina. We iterated the WSAO algorithm at the speed of individual OCT B-scans (~20 ms) by using raw spectral interferograms to calculate the optimization metric. Our WSAO approach with a 3 mm beam diameter permitted primarily low- but also high- order peripheral wavefront correction in less than 10 seconds. In preliminary imaging studies in five normal human subjects, we quantified statistically significant changes with WSAO correction, corresponding to a 10.4% improvement in average pixel brightness (signal) and 7.0% improvement in high frequency content (resolution) when visualizing 1 mm (~3.5°) B-scans of the peripheral (>23°) retina. We demonstrated the ability of our WF-OCT system to acquire non wavefront-corrected wide-field images rapidly, which could then be used to locate regions of interest, zoom into targeted features, and visualize the same region at different time points. A pilot clinical study was conducted on seven healthy volunteers and two subjects with prodromal Alzheimer’s disease which illustrated the capability to image Drusen-like pathologies as far as 32.5° from the fovea in un-averaged volume scans. This work suggests that the proposed combination of WF-OCT and WSAO may find applications in the diagnosis and treatment of ocular, and potentially neurodegenerative, diseases of the peripheral retina, including diabetes and Alzheimer’s disease. PMID:28101398

  5. Wide-field retinal optical coherence tomography with wavefront sensorless adaptive optics for enhanced imaging of targeted regions.

    PubMed

    Polans, James; Keller, Brenton; Carrasco-Zevallos, Oscar M; LaRocca, Francesco; Cole, Elijah; Whitson, Heather E; Lad, Eleonora M; Farsiu, Sina; Izatt, Joseph A

    2017-01-01

    The peripheral retina of the human eye offers a unique opportunity for assessment and monitoring of ocular diseases. We have developed a novel wide-field (>70°) optical coherence tomography system (WF-OCT) equipped with wavefront sensorless adaptive optics (WSAO) for enhancing the visualization of smaller (<25°) targeted regions in the peripheral retina. We iterated the WSAO algorithm at the speed of individual OCT B-scans (~20 ms) by using raw spectral interferograms to calculate the optimization metric. Our WSAO approach with a 3 mm beam diameter permitted primarily low- but also high- order peripheral wavefront correction in less than 10 seconds. In preliminary imaging studies in five normal human subjects, we quantified statistically significant changes with WSAO correction, corresponding to a 10.4% improvement in average pixel brightness (signal) and 7.0% improvement in high frequency content (resolution) when visualizing 1 mm (~3.5°) B-scans of the peripheral (>23°) retina. We demonstrated the ability of our WF-OCT system to acquire non wavefront-corrected wide-field images rapidly, which could then be used to locate regions of interest, zoom into targeted features, and visualize the same region at different time points. A pilot clinical study was conducted on seven healthy volunteers and two subjects with prodromal Alzheimer's disease which illustrated the capability to image Drusen-like pathologies as far as 32.5° from the fovea in un-averaged volume scans. This work suggests that the proposed combination of WF-OCT and WSAO may find applications in the diagnosis and treatment of ocular, and potentially neurodegenerative, diseases of the peripheral retina, including diabetes and Alzheimer's disease.

  6. 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

  7. Image enhancement for radiography inspection

    NASA Astrophysics Data System (ADS)

    Wang, Xin; Wong, Brian Stephen; Guan, Tui Chen

    2005-04-01

    The x-ray radiographic testing method is often used for detecting defects as a non-destructive testing method (NDT). In many cases, NDT is used for aircraft components, welds, etc. Hence, the backgrounds are always more complex than a piece of steel. Radiographic images are low contrast, dark and high noise image. It is difficult to detect defects directly. So, image enhancement is a significant part of automated radiography inspection system. Histogram equalization and median filter are the most frequently used techniques to enhance the radiographic images. In this paper, the adaptive histogram equalization and contrast limited histogram equalization are compared with histogram equalization. The adaptive wavelet thresholding is compared with median filter. Through comparative analysis, the contrast limited histogram equalization and adaptive wavelet thresholding can enhance perception of defects better.

  8. 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.

  9. Adaptive wiener image restoration kernel

    SciTech Connect

    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.

  10. Countermeasures to Enhance Sensorimotor Adaptability

    NASA Technical Reports Server (NTRS)

    Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Brady, R. A.; Batson, C. C.; Miller, C. A.; Cohen, H. S.

    2011-01-01

    During exploration-class missions, sensorimotor disturbances may lead to disruption in the ability to ambulate and perform functional tasks during the initial introduction to a novel gravitational environment following a landing on a planetary surface. The goal of our current project is to develop a sensorimotor adaptability (SA) training program to facilitate rapid adaptation to novel gravitational environments. We have developed a unique training system comprised of a treadmill placed on a motion-base facing a virtual visual scene that provides an unstable walking surface combined with incongruent visual flow designed to enhance sensorimotor adaptability. We have conducted a series of studies that have shown: Training using a combination of modified visual flow and support surface motion during treadmill walking enhances locomotor adaptability to a novel sensorimotor environment. Trained individuals become more proficient at performing multiple competing tasks while walking during adaptation to novel discordant sensorimotor conditions. Trained subjects can retain their increased level of adaptability over a six months period. SA training is effective in producing increased adaptability in a more complex over-ground ambulatory task on an obstacle course. This confirms that for a complex task like walking, treadmill training contains enough of the critical features of overground walking to be an effective training modality. The structure of individual training sessions can be optimized to promote fast/strategic motor learning. Training sessions that each contain short-duration exposures to multiple perturbation stimuli allows subjects to acquire a greater ability to rapidly reorganize appropriate response strategies when encountering a novel sensory environment. Individual sensory biases (i.e. increased visual dependency) can predict adaptive responses to novel sensory environments suggesting that customized training prescriptions can be developed to enhance

  11. 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.

  12. Fully parallel adaptive finite element simulation using the simplified spherical harmonics approximations for frequency-domain fluorescence-enhanced optical imaging

    NASA Astrophysics Data System (ADS)

    Lu, Yujie; Zhu, Banghe; Shen, Haiou; Rasmussen, John C.; Wang, Ge; Sevick-Muraca, Eva M.

    2011-03-01

    Fluorescence-enhanced optical imaging/tomography may play an important role in preclinical research and clinical diagnostics as a type of optical molecular. Time- and frequency-domain measurement can acquire more measurement information, reducing the ill-posedness and improving the reconstruction quality of fluorescence-enhanced optical tomography. Although the diffusion approximation (DA) theory has been extensively in optical imaging, high-order photon migration models must be further investigated for application to complex and small tissue volumes. In this paper, a frequency-domain fully parallel adaptive finite element solver is developed with the simplified spherical harmonics (SPN) approximations. To fully evaluate the performance of the SPN approximations, a fast tetrahedron-based Monte Carlo simulator suitable for complex heterogeneous geometries is developed using the convolution strategy to realize the simulation of the fluorescence excitation and emission. With simple and real digital mouse phantoms, the results show that the significant precision and speed improvements are obtained from the parallel adaptive mesh evolution strategy.

  13. Hessian-LoG filtering for enhancement and detection of photoreceptor cells in adaptive optics retinal images.

    PubMed

    Lazareva, Anfisa; Liatsis, Panos; Rauscher, Franziska G

    2016-01-01

    Automated analysis of retinal images plays a vital role in the examination, diagnosis, and prognosis of healthy and pathological retinas. Retinal disorders and the associated visual loss can be interpreted via quantitative correlations, based on measurements of photoreceptor loss. Therefore, it is important to develop reliable tools for identification of photoreceptor cells. In this paper, an automated algorithm is proposed, based on the use of the Hessian-Laplacian of Gaussian filter, which allows enhancement and detection of photoreceptor cells. The performance of the proposed technique is evaluated on both synthetic and high-resolution retinal images, in terms of packing density. The results on the synthetic data were compared against ground truth as well as cone counts obtained by the Li and Roorda algorithm. For the synthetic datasets, our method showed an average detection accuracy of 98.8%, compared to 93.9% for the Li and Roorda approach. The packing density estimates calculated on the retinal datasets were validated against manual counts and the results obtained by a proprietary software from Imagine Eyes and the Li and Roorda algorithm. Among the tested methods, the proposed approach showed the closest agreement with manual counting.

  14. 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.

  15. 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.

  16. Imaging an Adapted Dentoalveolar Complex

    PubMed Central

    Herber, Ralf-Peter; Fong, Justine; Lucas, Seth A.; Ho, Sunita P.

    2012-01-01

    Adaptation of a rat dentoalveolar complex was illustrated using various imaging modalities. Micro-X-ray computed tomography for 3D modeling, combined with complementary techniques, including image processing, scanning electron microscopy, fluorochrome labeling, conventional histology (H&E, TRAP), and immunohistochemistry (RANKL, OPN) elucidated the dynamic nature of bone, the periodontal ligament-space, and cementum in the rat periodontium. Tomography and electron microscopy illustrated structural adaptation of calcified tissues at a higher resolution. Ongoing biomineralization was analyzed using fluorochrome labeling, and by evaluating attenuation profiles using virtual sections from 3D tomographies. Osteoclastic distribution as a function of anatomical location was illustrated by combining histology, immunohistochemistry, and tomography. While tomography and SEM provided past resorption-related events, future adaptive changes were deduced by identifying matrix biomolecules using immunohistochemistry. Thus, a dynamic picture of the dentoalveolar complex in rats was illustrated. PMID:22567314

  17. 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.

  18. IIR algorithms for adaptive line enhancement

    SciTech Connect

    David, R.A.; Stearns, S.D.; Elliott, G.R.; Etter, D.M.

    1983-01-01

    We introduce a simple IIR structure for the adaptive line enhancer. Two algorithms based on gradient-search techniques are presented for adapting the structure. Results from experiments which utilized real data as well as computer simulations are provided.

  19. Local adaptive tone mapping for video enhancement

    NASA Astrophysics Data System (ADS)

    Lachine, Vladimir; Dai, Min (.

    2015-03-01

    As new technologies like High Dynamic Range cameras, AMOLED and high resolution displays emerge on consumer electronics market, it becomes very important to deliver the best picture quality for mobile devices. Tone Mapping (TM) is a popular technique to enhance visual quality. However, the traditional implementation of Tone Mapping procedure is limited by pixel's value to value mapping, and the performance is restricted in terms of local sharpness and colorfulness. To overcome the drawbacks of traditional TM, we propose a spatial-frequency based framework in this paper. In the proposed solution, intensity component of an input video/image signal is split on low pass filtered (LPF) and high pass filtered (HPF) bands. Tone Mapping (TM) function is applied to LPF band to improve the global contrast/brightness, and HPF band is added back afterwards to keep the local contrast. The HPF band may be adjusted by a coring function to avoid noise boosting and signal overshooting. Colorfulness of an original image may be preserved or enhanced by chroma components correction by means of saturation function. Localized content adaptation is further improved by dividing an image to a set of non-overlapped regions and modifying each region individually. The suggested framework allows users to implement a wide range of tone mapping applications with perceptional local sharpness and colorfulness preserved or enhanced. Corresponding hardware circuit may be integrated in camera, video or display pipeline with minimal hardware budget

  20. Novel Nonlinear Hybrid Filters for Image Enhancement

    NASA Astrophysics Data System (ADS)

    Peng, Shaomin

    1995-01-01

    Image noise removal and enhancement are important subjects in image processing. Nonlinear techniques for image enhancement and noise reduction challenge the linear techniques by improving image quality while removing noise. The purpose of this thesis is devoted to systematically unifying theory and techniques for mixed noise removal and image enhancement, and to developing new techniques for removing large amounts of mixed Gaussian and impulsive noise while preserving image details. In this thesis, we introduce three new hybrid filters which combine linear and nonlinear filters to produce new hybrid filters capable of removing large amounts of mixed noise. To efficiently use the ambiguous information in an image, both fuzzy set concepts and fuzzy logic operating rules are utilized in the filter design techniques. The three new filters include the single level trained fuzzy filter (SLTF), the multi-level adaptive fuzzy filter (MLAF), and the decision directed window adaptive hybrid filter (DDWAH). The SLTF filter is designed to remove large amounts of mixed noise by combining an impulse filter with a fuzzy filter. The efficiency of the SLTF filter in removing large amounts of mixed noise while preserving image edges is demonstrated. The MLAF filter is an adaptive SLTF filter which uses the local variance of image gray scales to adapt the weights used in the linear portion of the filter to local image statistics. The MLAF filter provides improved visual performance compared to the SLTF filter. The adaptive DDWAH filter uses local statistics to adapt the window size of the filter to local statistics. This approach prevents distortion of small objects in the image, and removes noise more effectively than non-adaptive filters. The experimental results clearly show the improved noise removal performance and good edge preservation properties. Theoretical analysis verifies the measured results.

  1. Degraded document image enhancement

    NASA Astrophysics Data System (ADS)

    Agam, G.; Bal, G.; Frieder, G.; Frieder, O.

    2007-01-01

    Poor quality documents are obtained in various situations such as historical document collections, legal archives, security investigations, and documents found in clandestine locations. Such documents are often scanned for automated analysis, further processing, and archiving. Due to the nature of such documents, degraded document images are often hard to read, have low contrast, and are corrupted by various artifacts. We describe a novel approach for the enhancement of such documents based on probabilistic models which increases the contrast, and thus, readability of such documents under various degradations. The enhancement produced by the proposed approach can be viewed under different viewing conditions if desired. The proposed approach was evaluated qualitatively and compared to standard enhancement techniques on a subset of historical documents obtained from the Yad Vashem Holocaust museum. In addition, quantitative performance was evaluated based on synthetically generated data corrupted under various degradation models. Preliminary results demonstrate the effectiveness of the proposed approach.

  2. 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.

  3. Image enhancement system for mobile displays

    NASA Astrophysics Data System (ADS)

    Parkkinen, Jaana; Nenonen, Petri

    2005-02-01

    In this paper, we present a system for enhancing digital photography on mobile displays. The system is using adaptive filtering and display specific methods for maximizing the subjective quality of images. Because mobile platforms have a limited amount of memory and processing power, we describe computationally efficient scaling and enhancement algorithms that are especially suitable for mobile devices and displays. We also show how a proper arrangement of these algorithms forms an image processing chain that is optimized for mobile use. The developed image enhancement system has been implemented using the Nokia Series60 platform and tested on imaging phones. Tests and results show that significant improvement of quality can be achieved with this solution within the processing power and memory limitations that mobile platforms set.

  4. Adaptive overlapped sub-blocks contrast enhancement

    NASA Astrophysics Data System (ADS)

    Chen, Anqiu; Yuan, Fei; Liu, Jing; Liu, Siqi; Li, An; Zheng, Zhenrong

    2016-09-01

    In this paper, an overlapped sub-block gray-level average method for contrast enhancement is presented. The digital image correction of uneven illumination under microscope transmittance is a problem in image processing, also sometimes the image in the dark place need to correct the uneven problem. A new correction method was proposed based on the mask method and sub-blocks gray-level average method because Traditional mask method and background fitting method are restricted due to application scenarios, and the corrected image brightness is low by using background fitting method, so it has some limitations of the application. In this paper, we introduce a new method called AOSCE for image contrast enhancement. The image is divided into many sub-blocks which are overlapped, calculate the average gray-level of the whole image as M and the calculate the average gray-level of each one as mi, next for each block it can get d = mi - m, each block minus d to get a new image, and then get the minimum gray-level of each block into a matrix DD to get the background, and use bilinearity to get the same scale of the image. over fitting the image in matlab in order to get smoother image, then minus the background to get the contrast enhancement image.

  5. 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.

  6. Next generation high resolution adaptive optics fundus imager

    NASA Astrophysics Data System (ADS)

    Fournier, P.; Erry, G. R. G.; Otten, L. J.; Larichev, A.; Irochnikov, N.

    2005-12-01

    The spatial resolution of retinal images is limited by the presence of static and time-varying aberrations present within the eye. An updated High Resolution Adaptive Optics Fundus Imager (HRAOFI) has been built based on the development from the first prototype unit. This entirely new unit was designed and fabricated to increase opto-mechanical integration and ease-of-use through a new user interface. Improved camera systems for the Shack-Hartmann sensor and for the scene image were implemented to enhance the image quality and the frequency of the Adaptive Optics (AO) control loop. An optimized illumination system that uses specific wavelength bands was applied to increase the specificity of the images. Sample images of clinical trials of retinas, taken with and without the system, are shown. Data on the performance of this system will be presented, demonstrating the ability to calculate near diffraction-limited images.

  7. Improvement of ultrasound speckle image velocimetry using image enhancement techniques.

    PubMed

    Yeom, Eunseop; Nam, Kweon-Ho; Paeng, Dong-Guk; Lee, Sang Joon

    2014-01-01

    Ultrasound-based techniques have been developed and widely used in noninvasive measurement of blood velocity. Speckle image velocimetry (SIV), which applies a cross-correlation algorithm to consecutive B-mode images of blood flow has often been employed owing to its better spatial resolution compared with conventional Doppler-based measurement techniques. The SIV technique utilizes speckles backscattered from red blood cell (RBC) aggregates as flow tracers. Hence, the intensity and size of such speckles are highly dependent on hemodynamic conditions. The grayscale intensity of speckle images varies along the radial direction of blood vessels because of the shear rate dependence of RBC aggregation. This inhomogeneous distribution of echo speckles decreases the signal-to-noise ratio (SNR) of a cross-correlation analysis and produces spurious results. In the present study, image-enhancement techniques such as contrast-limited adaptive histogram equalization (CLAHE), min/max technique, and subtraction of background image (SB) method were applied to speckle images to achieve a more accurate SIV measurement. A mechanical sector ultrasound scanner was used to obtain ultrasound speckle images from rat blood under steady and pulsatile flows. The effects of the image-enhancement techniques on SIV analysis were evaluated by comparing image intensities, velocities, and cross-correlation maps. The velocity profiles and wall shear rate (WSR) obtained from RBC suspension images were compared with the analytical solution for validation. In addition, the image-enhancement techniques were applied to in vivo measurement of blood flow in human vein. The experimental results of both in vitro and in vivo SIV measurements show that the intensity gradient in heterogeneous speckles has substantial influence on the cross-correlation analysis. The image-enhancement techniques used in this study can minimize errors encountered in ultrasound SIV measurement in which RBCs are used as flow

  8. ALISA: adaptive learning image and signal analysis

    NASA Astrophysics Data System (ADS)

    Bock, Peter

    1999-01-01

    ALISA (Adaptive Learning Image and Signal Analysis) is an adaptive statistical learning engine that may be used to detect and classify the surfaces and boundaries of objects in images. The engine has been designed, implemented, and tested at both the George Washington University and the Research Institute for Applied Knowledge Processing in Ulm, Germany over the last nine years with major funding from Robert Bosch GmbH and Lockheed-Martin Corporation. The design of ALISA was inspired by the multi-path cortical- column architecture and adaptive functions of the mammalian visual cortex.

  9. 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.

  10. 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.

  11. 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...

  12. Adapted polarization state contrast image.

    PubMed

    Richert, Michael; Orlik, Xavier; De Martino, Antonello

    2009-08-03

    We propose a general method to maximize the polarimetric contrast between an object and its background using a predetermined illumination polarization state. After a first estimation of the polarimetric properties of the scene by classical Mueller imaging, we evaluate the incident polarized field that induces scattered polarization states by the object and background, as opposite as possible on the Poincar e sphere. With a detection method optimized for a 2-channel imaging system, Monte Carlo simulations of low flux coherent imaging are performed with various objects and backgrounds having different properties of retardance, dichroism and depolarization. With respect to classical Mueller imaging, possibly associated to the polar decomposition, our results show a noticeable increase in the Bhattacharyya distance used as our contrast parameter.

  13. Extreme Adaptive Optics Planet Imager

    NASA Astrophysics Data System (ADS)

    Macintosh, B.; Graham, J. R.; Ghez, A.; Kalas, P.; Lloyd, J.; Makidon, R.; Olivier, S.; Patience, J.; Perrin, M.; Poyneer, L.; Severson, S.; Sheinis, A.; Sivaramakrishnan, A.; Troy, M.; Wallace, J.; Wilhelmsen, J.

    2002-12-01

    Direct detection of photons emitted or reflected by extrasolar planets is the next major step in extrasolar planet studies. Current adaptive optics (AO) systems, with <300 subapertures and Strehl ratio 0.4-0.7, can achieve contrast levels of 106 at 2" separations; this is sufficient to see very young planets in wide orbits but insufficient to detect solar systems more like our own. Contrast levels of 107 - 108 in the near-IR are needed to probe a significant part of the extrasolar planet phase space. The NSF Center for Adaptive Optics is carrying out a design study for a dedicated ultra-high-contrast "Extreme" adaptive optics system for an 8-10m telescope. With 3000 controlled subapertures it should achieve Strehl ratios > 0.9 in the near-IR. Using a spatially filtered wavefront sensor, the system will be optimized to control scattered light over a large radius and suppress artifacts caused static errors. We predict that it will achieve contrast levels of 107-108 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. The system will be capable of a variety of high-contrast science including studying circumstellar dust disks at densities a factor of 10-100 lower than currently feasible and a systematic inventory of other solar systems on 10-100 AU scale. This work was supported by the NSF Science and Technology Center for Adaptive Optics, managed by UC Santa Cruz under AST-9876783. Portions of this work was performed under the auspices of the U.S. Department of Energy, under contract No. W-7405-Eng-48.

  14. Image-Specific Prior Adaptation for Denoising.

    PubMed

    Lu, Xin; Lin, Zhe; Jin, Hailin; Yang, Jianchao; Wang, James Z

    2015-12-01

    Image priors are essential to many image restoration applications, including denoising, deblurring, and inpainting. Existing methods use either priors from the given image (internal) or priors from a separate collection of images (external). We find through statistical analysis that unifying the internal and external patch priors may yield a better patch prior. We propose a novel prior learning algorithm that combines the strength of both internal and external priors. In particular, we first learn a generic Gaussian mixture model from a collection of training images and then adapt the model to the given image by simultaneously adding additional components and refining the component parameters. We apply this image-specific prior to image denoising. The experimental results show that our approach yields better or competitive denoising results in terms of both the peak signal-to-noise ratio and structural similarity.

  15. Enhanced imaging process for xeroradiography

    NASA Astrophysics Data System (ADS)

    Fender, William D.; Zanrosso, Eddie M.

    1993-09-01

    An enhanced mammographic imaging process has been developed which is based on the conventional powder-toner selenium technology used in the Xerox 125/126 x-ray imaging system. The process is derived from improvements in the amorphous selenium x-ray photoconductor, the blue powder toner and the aerosol powder dispersion process. Comparisons of image quality and x-ray dose using the Xerox aluminum-wedge breast phantom and the Radiation Measurements Model 152D breast phantom have been made between the new Enhanced Process, the standard Xerox 125/126 System and screen-film at mammographic x-ray exposure parameters typical for each modality. When comparing the Enhanced Xeromammographic Process with the standard 125/126 System, a distinct advantage is seen for the Enhanced equivalent mass detection and superior fiber and speck detection. The broader imaging latitude of enhanced and standard Xeroradiography, in comparison to film, is illustrated in images made using the aluminum-wedge breast phantom.

  16. 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

  17. 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.

  18. 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.

  19. Local image registration by adaptive filtering.

    PubMed

    Caner, Gulcin; Tekalp, A Murat; Sharma, Gaurav; Heinzelman, Wendi

    2006-10-01

    We propose a new adaptive filtering framework for local image registration, which compensates for the effect of local distortions/displacements without explicitly estimating a distortion/displacement field. To this effect, we formulate local image registration as a two-dimensional (2-D) system identification problem with spatially varying system parameters. We utilize a 2-D adaptive filtering framework to identify the locally varying system parameters, where a new block adaptive filtering scheme is introduced. We discuss the conditions under which the adaptive filter coefficients conform to a local displacement vector at each pixel. Experimental results demonstrate that the proposed 2-D adaptive filtering framework is very successful in modeling and compensation of both local distortions, such as Stirmark attacks, and local motion, such as in the presence of a parallax field. In particular, we show that the proposed method can provide image registration to: a) enable reliable detection of watermarks following a Stirmark attack in nonblind detection scenarios, b) compensate for lens distortions, and c) align multiview images with nonparametric local motion.

  20. Color image diffusion using adaptive bilateral filter.

    PubMed

    Xie, Jun; Ann Heng, Pheng

    2005-01-01

    In this paper, we propose an approach to diffuse color images based on the bilateral filter. Real image data has a level of uncertainty that is manifested in the variability of measures assigned to pixels. This uncertainty is usually interpreted as noise and considered an undesirable component of the image data. Image diffusion can smooth away small-scale structures and noise while retaining important features, thus improving the performances for many image processing algorithms such as image compression, segmentation and recognition. The bilateral filter is noniterative, simple and fast. It has been shown to give similar and possibly better filtering results than iterative approaches. However, the performance of this filter is greatly affected by the choose of the parameters of filtering kernels. In order to remove noise and maintain the significant features on images, we extend the bilateral filter by introducing an adaptive domain spread into the nonlinear diffusion scheme. For color images, we employ the CIE-Lab color system to describe input images and the filtering process is operated using three channels together. Our analysis shows that the proposed method is more suitable for preserving strong edges on noisy images than the original bilateral filter. Empirical results on both nature images and color medical images confirm the novel method's advantages, and show it can diffuse various kinds of color images correctly and efficiently.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Adaptive discrete cosine transform based image coding

    NASA Astrophysics Data System (ADS)

    Hu, Neng-Chung; Luoh, Shyan-Wen

    1996-04-01

    In this discrete cosine transform (DCT) based image coding, the DCT kernel matrix is decomposed into a product of two matrices. The first matrix is called the discrete cosine preprocessing transform (DCPT), whose kernels are plus or minus 1 or plus or minus one- half. The second matrix is the postprocessing stage treated as a correction stage that converts the DCPT to the DCT. On applying the DCPT to image coding, image blocks are processed by the DCPT, then a decision is made to determine whether the processed image blocks are inactive or active in the DCPT domain. If the processed image blocks are inactive, then the compactness of the processed image blocks is the same as that of the image blocks processed by the DCT. However, if the processed image blocks are active, a correction process is required; this is achieved by multiplying the processed image block by the postprocessing stage. As a result, this adaptive image coding achieves the same performance as the DCT image coding, and both the overall computation and the round-off error are reduced, because both the DCPT and the postprocessing stage can be implemented by distributed arithmetic or fast computation algorithms.

  6. 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.

  7. 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.

  8. Adaptive fuzzy segmentation of magnetic resonance images.

    PubMed

    Pham, D L; Prince, J L

    1999-09-01

    An algorithm is presented for the fuzzy segmentation of two-dimensional (2-D) and three-dimensional (3-D) multispectral magnetic resonance (MR) images that have been corrupted by intensity inhomogeneities, also known as shading artifacts. The algorithm is an extension of the 2-D adaptive fuzzy C-means algorithm (2-D AFCM) presented in previous work by the authors. This algorithm models the intensity inhomogeneities as a gain field that causes image intensities to smoothly and slowly vary through the image space. It iteratively adapts to the intensity inhomogeneities and is completely automated. In this paper, we fully generalize 2-D AFCM to three-dimensional (3-D) multispectral images. Because of the potential size of 3-D image data, we also describe a new faster multigrid-based algorithm for its implementation. We show, using simulated MR data, that 3-D AFCM yields lower error rates than both the standard fuzzy C-means (FCM) algorithm and two other competing methods, when segmenting corrupted images. Its efficacy is further demonstrated using real 3-D scalar and multispectral MR brain images.

  9. 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.

  10. 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

  11. Multi-scale Adaptive Computational Ghost Imaging

    PubMed Central

    Sun, Shuai; Liu, Wei-Tao; Lin, Hui-Zu; Zhang, Er-Feng; Liu, Ji-Ying; Li, Quan; Chen, Ping-Xing

    2016-01-01

    In some cases of imaging, wide spatial range and high spatial resolution are both required, which requests high performance of detection devices and huge resource consumption for data processing. We propose and demonstrate a multi-scale adaptive imaging method based on the idea of computational ghost imaging, which can obtain a rough outline of the whole scene with a wide range then accordingly find out the interested parts and achieve high-resolution details of those parts, by controlling the field of view and the transverse coherence width of the pseudo-thermal field illuminated on the scene with a spatial light modulator. Compared to typical ghost imaging, the resource consumption can be dramatically reduced using our scheme. PMID:27841339

  12. Multi-scale Adaptive Computational Ghost Imaging

    NASA Astrophysics Data System (ADS)

    Sun, Shuai; Liu, Wei-Tao; Lin, Hui-Zu; Zhang, Er-Feng; Liu, Ji-Ying; Li, Quan; Chen, Ping-Xing

    2016-11-01

    In some cases of imaging, wide spatial range and high spatial resolution are both required, which requests high performance of detection devices and huge resource consumption for data processing. We propose and demonstrate a multi-scale adaptive imaging method based on the idea of computational ghost imaging, which can obtain a rough outline of the whole scene with a wide range then accordingly find out the interested parts and achieve high-resolution details of those parts, by controlling the field of view and the transverse coherence width of the pseudo-thermal field illuminated on the scene with a spatial light modulator. Compared to typical ghost imaging, the resource consumption can be dramatically reduced using our scheme.

  13. Efficient adaptive thresholding with image masks

    NASA Astrophysics Data System (ADS)

    Oh, Young-Taek; Hwang, Youngkyoo; Kim, Jung-Bae; Bang, Won-Chul

    2014-03-01

    Adaptive thresholding is a useful technique for document analysis. In medical image processing, it is also helpful for segmenting structures, such as diaphragms or blood vessels. This technique sets a threshold using local information around a pixel, then binarizes the pixel according to the value. Although this technique is robust to changes in illumination, it takes a significant amount of time to compute thresholds because it requires adding all of the neighboring pixels. Integral images can alleviate this overhead; however, medical images, such as ultrasound, often come with image masks, and ordinary algorithms often cause artifacts. The main problem is that the shape of the summing area is not rectangular near the boundaries of the image mask. For example, the threshold at the boundary of the mask is incorrect because pixels on the mask image are also counted. Our key idea to cope with this problem is computing the integral image for the image mask to count the valid number of pixels. Our method is implemented on a GPU using CUDA, and experimental results show that our algorithm is 164 times faster than a naïve CPU algorithm for averaging.

  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. Adaptive directional lifting-based wavelet transform for image coding.

    PubMed

    Ding, Wenpeng; Wu, Feng; Wu, Xiaolin; Li, Shipeng; Li, Houqiang

    2007-02-01

    We present a novel 2-D wavelet transform scheme of adaptive directional lifting (ADL) in image coding. Instead of alternately applying horizontal and vertical lifting, as in present practice, ADL performs lifting-based prediction in local windows in the direction of high pixel correlation. Hence, it adapts far better to the image orientation features in local windows. The ADL transform is achieved by existing 1-D wavelets and is seamlessly integrated into the global wavelet transform. The predicting and updating signals of ADL can be derived even at the fractional pixel precision level to achieve high directional resolution, while still maintaining perfect reconstruction. To enhance the ADL performance, a rate-distortion optimized directional segmentation scheme is also proposed to form and code a hierarchical image partition adapting to local features. Experimental results show that the proposed ADL-based image coding technique outperforms JPEG 2000 in both PSNR and visual quality, with the improvement up to 2.0 dB on images with rich orientation features.

  16. Adaptive image segmentation applied to plant reproduction by tissue culture

    NASA Astrophysics Data System (ADS)

    Vazquez Rueda, Martin G.; Hahn, Federico; Zapata, Jose L.

    1997-04-01

    This paper presents that experimental results obtained on indoor tissue culture using the adaptive image segmentation system. The performance of the adaptive technique is contrasted with different non-adaptive techniques commonly used in the computer vision field to demonstrate the improvement provided by the adaptive image segmentation system.

  17. Image Modeling and Enhancement via Structured Sparse Model Selection

    DTIC Science & Technology

    2010-01-01

    signal estimation is then calculated with the selected model. The model selection leads to a guaranteed near optimal denoising estimator. The degree...are adapted to the image of interest and are computed with a simple and fast procedure. State-of-the-art results are shown in image denoising ...deblurring, and inpainting. Index Terms— Model selection, structured sparsity, best basis, denoising , deblurring, inpainting 1. INTRODUCTION Image enhancement

  18. 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

  19. Laser Image Contrast Enhancement System

    NASA Technical Reports Server (NTRS)

    Kurtz, Robert L. (Inventor); Holmes, Richard R. (Inventor); Witherow, William K. (Inventor)

    2002-01-01

    An optical image enhancement system provides improved image contrast in imaging of a target in high temperature surroundings such as a furnace. The optical system includes a source of vertically polarized light such as laser and a beam splitter for receiving the light and directing the light toward the target. A retardation plate is affixed to a target-facing surface of the beam splitter and a vertical polarizer is disposed along a common optical path with the beam splitter between the retardation plate and the target. A horizontal polarizer disposed in the common optical path, receives light passing through a surface of the beam splitter opposed to the target-facing surface. An image detector is disposed at one end of the optical path. A band pass filter having a band pass filter characteristic matching the frequency of the vertically polarized light source is disposed in the path between the horizontal polarizer and the image detector. The use of circular polarization, together with cross polarizers, enables the reflected light to be passed to the detector while blocking thermal radiation.

  20. 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.

  1. Uneven illumination removal and image enhancement using empirical mode decomposition

    NASA Astrophysics Data System (ADS)

    Pei, Soo-Chang; Hsiao, Yu-Zhe; Tzeng, Mary; Chang, Feng Ju

    2013-10-01

    Uneven light distribution problems often arise in poorly scanned text or text-photo images and natural images taken by digital camera. An innovative image-processing technique for uneven illumination removal using empirical mode decomposition (EMD) is proposed. The EMD is local, adaptive, and useful for analyzing nonlinear and nonstationary signals. In this method, we decompose images by EMD and get the background level locally and adaptively. This algorithm can enhance the local reflectance in the image while removing uneven illumination for black/white text images, text-photo images, and natural color/gray-level images. The proposed technique can be very helpful for image and text recognition. The EMD can also be applied to the three color channels (RGB) of color images separately to estimate the reflectances of the three color channels. After we relight these channels using white light and the estimated reflectances, a simple color constancy task can be performed to correct certain poorly lighted color images. Our technique is compared with recently proposed methods for correcting images with uneven illumination and the experimental results demonstrated that the proposed approach can effectively enhance natural color/gray-level images and make text and text-photo images more readable under uneven illumination.

  2. Adaptive marginal median filter for colour images.

    PubMed

    Morillas, Samuel; Gregori, Valentín; Sapena, Almanzor

    2011-01-01

    This paper describes a new filter for impulse noise reduction in colour images which is aimed at improving the noise reduction capability of the classical vector median filter. The filter is inspired by the application of a vector marginal median filtering process over a selected group of pixels in each filtering window. This selection, which is based on the vector median, along with the application of the marginal median operation constitutes an adaptive process that leads to a more robust filter design. Also, the proposed method is able to process colour images without introducing colour artifacts. Experimental results show that the images filtered with the proposed method contain less noisy pixels than those obtained through the vector median filter.

  3. Adaptive dispersion compensation for guided wave imaging

    NASA Astrophysics Data System (ADS)

    Hall, James S.; Michaels, Jennifer E.

    2012-05-01

    Ultrasonic guided waves offer the promise of fast and reliable methods for interrogating large, plate-like structures. Distributed arrays of permanently attached, inexpensive piezoelectric transducers have thus been proposed as a cost-effective means to excite and measure ultrasonic guided waves for structural health monitoring (SHM) applications. Guided wave data recorded from a distributed array of transducers are often analyzed and interpreted through the use of guided wave imaging algorithms, such as conventional delay-and-sum imaging or the more recently applied minimum variance imaging. Both imaging algorithms perform reasonably well using signal envelopes, but can exhibit significant performance improvements when phase information is used. However, the use of phase information inherently requires knowledge of the dispersion relations, which are often not known to a sufficient degree of accuracy for high quality imaging since they are very sensitive to environmental conditions such as temperature, pressure, and loading. This work seeks to perform improved imaging with phase information by leveraging adaptive dispersion estimates obtained from in situ measurements. Experimentally obtained data from a distributed array is used to validate the proposed approach.

  4. Adaptive ladar receiver for multispectral imaging

    NASA Astrophysics Data System (ADS)

    Johnson, Kenneth; Vaidyanathan, Mohan; Xue, Song; Tennant, William E.; Kozlowski, Lester J.; Hughes, Gary W.; Smith, Duane D.

    2001-09-01

    We are developing a novel 2D focal plane array (FPA) with read-out integrated circuit (ROIC) on a single chip for 3D laser radar imaging. The ladar will provide high-resolution range and range-resolved intensity images for detection and identification of difficult targets. The initial full imaging-camera-on-a-chip system will be a 64 by 64 element, 100-micrometers pixel-size detector array that is directly bump bonded to a low-noise 64 by 64 array silicon CMOS-based ROIC. The architecture is scalable to 256 by 256 or higher arrays depending on the system application. The system will provide all the required electronic processing at pixel level and the smart FPA enables directly producing the 3D or 4D format data to be captured with a single laser pulse. The detector arrays are made of uncooled InGaAs PIN device for SWIR imaging at 1.5 micrometers wavelength and cooled HgCdTe PIN device for MWIR imaging at 3.8 micrometers wavelength. We are also investigating concepts using multi-color detector arrays for simultaneous imaging at multiple wavelengths that would provide additional spectral dimension capability for enhanced detection and identification of deep-hide targets. The system is suited for flash ladar imaging, for combat identification of ground targets from airborne platforms, flash-ladar imaging seekers, and autonomous robotic/automotive vehicle navigation and collision avoidance applications.

  5. Adaptive photoacoustic imaging quality optimization with EMD and reconstruction

    NASA Astrophysics Data System (ADS)

    Guo, Chengwen; Ding, Yao; Yuan, Jie; Xu, Guan; Wang, Xueding; Carson, Paul L.

    2016-10-01

    Biomedical photoacoustic (PA) signal is characterized with extremely low signal to noise ratio which will yield significant artifacts in photoacoustic tomography (PAT) images. Since PA signals acquired by ultrasound transducers are non-linear and non-stationary, traditional data analysis methods such as Fourier and wavelet method cannot give useful information for further research. In this paper, we introduce an adaptive method to improve the quality of PA imaging based on empirical mode decomposition (EMD) and reconstruction. Data acquired by ultrasound transducers are adaptively decomposed into several intrinsic mode functions (IMFs) after a sifting pre-process. Since noise is randomly distributed in different IMFs, depressing IMFs with more noise while enhancing IMFs with less noise can effectively enhance the quality of reconstructed PAT images. However, searching optimal parameters by means of brute force searching algorithms will cost too much time, which prevent this method from practical use. To find parameters within reasonable time, heuristic algorithms, which are designed for finding good solutions more efficiently when traditional methods are too slow, are adopted in our method. Two of the heuristic algorithms, Simulated Annealing Algorithm, a probabilistic method to approximate the global optimal solution, and Artificial Bee Colony Algorithm, an optimization method inspired by the foraging behavior of bee swarm, are selected to search optimal parameters of IMFs in this paper. The effectiveness of our proposed method is proved both on simulated data and PA signals from real biomedical tissue, which might bear the potential for future clinical PA imaging de-noising.

  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 Flight Control for Aircraft Safety Enhancements

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Gregory, Irene M.; Joshi, Suresh M.

    2008-01-01

    This poster presents the current adaptive control research being conducted at NASA ARC and LaRC in support of the Integrated Resilient Aircraft Control (IRAC) project. The technique "Approximate Stability Margin Analysis of Hybrid Direct-Indirect Adaptive Control" has been developed at NASA ARC to address the needs for stability margin metrics for adaptive control that potentially enables future V&V of adaptive systems. The technique "Direct Adaptive Control With Unknown Actuator Failures" is developed at NASA LaRC to deal with unknown actuator failures. The technique "Adaptive Control with Adaptive Pilot Element" is being researched at NASA LaRC to investigate the effects of pilot interactions with adaptive flight control that can have implications of stability and performance.

  8. Enhancing climate Adaptation Capacity for Drinking Water ...

    EPA Pesticide Factsheets

    Journal article This paper considers the adaptation capacity of conventional water treatment systems. A modeling framework is used to illustrate climate adaptation mechanisms that could enable conventional treatment systems to accommodate water quality impairments.

  9. 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.

  10. 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.

  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. 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.

  13. Selected annotated bibliographies for adaptive filtering of digital image data

    USGS Publications Warehouse

    Mayers, Margaret; Wood, Lynnette

    1988-01-01

    Digital spatial filtering is an important tool both for enhancing the information content of satellite image data and for implementing cosmetic effects which make the imagery more interpretable and appealing to the eye. Spatial filtering is a context-dependent operation that alters the gray level of a pixel by computing a weighted average formed from the gray level values of other pixels in the immediate vicinity.Traditional spatial filtering involves passing a particular filter or set of filters over an entire image. This assumes that the filter parameter values are appropriate for the entire image, which in turn is based on the assumption that the statistics of the image are constant over the image. However, the statistics of an image may vary widely over the image, requiring an adaptive or "smart" filter whose parameters change as a function of the local statistical properties of the image. Then a pixel would be averaged only with more typical members of the same population. This annotated bibliography cites some of the work done in the area of adaptive filtering. The methods usually fall into two categories, (a) those that segment the image into subregions, each assumed to have stationary statistics, and use a different filter on each subregion, and (b) those that use a two-dimensional "sliding window" to continuously estimate the filter either the spatial or frequency domain, or may utilize both domains. They may be used to deal with images degraded by space variant noise, to suppress undesirable local radiometric statistics while enforcing desirable (user-defined) statistics, to treat problems where space-variant point spread functions are involved, to segment images into regions of constant value for classification, or to "tune" images in order to remove (nonstationary) variations in illumination, noise, contrast, shadows, or haze.Since adpative filtering, like nonadaptive filtering, is used in image processing to accomplish various goals, this bibliography

  14. 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.

  15. Adaptive system for eye-fundus imaging

    SciTech Connect

    Larichev, A V; Ivanov, P V; Iroshnikov, N G; Shmalgauzen, V I; Otten, L J

    2002-10-31

    A compact adaptive system capable of imaging a human-eye retina with a spatial resolution as high as 6 {mu}m and a field of view of 15{sup 0} is developed. It is shown that a modal bimorph corrector with nonlocalised response functions provides the efficient suppression of dynamic aberrations of a human eye. The residual root-mean-square error in correction of aberrations of a real eye with nonparalysed accommodation lies in the range of 0.1 - 0.15 {mu}m.

  16. Imaging Radio Galaxies with Adaptive Optics

    NASA Astrophysics Data System (ADS)

    de Vries, W. H.; van Breugel, W. J. M.; Quirrenbach, A.; Roberts, J.; Fidkowski, K.

    2000-12-01

    We present 42 milli-arcsecond resolution Adaptive Optics near-infrared images of 3C 452 and 3C 294, two powerful radio galaxies at z=0.081 and z=1.79 respectively, obtained with the NIRSPEC/SCAM+AO instrument on the Keck telescope. The observations provide unprecedented morphological detail of radio galaxy components like nuclear dust-lanes, off-centered or binary nuclei, and merger induced starforming structures; all of which are key features in understanding galaxy formation and the onset of powerful radio emission. Complementary optical HST imaging data are used to construct high resolution color images, which, for the first time, have matching optical and near-IR resolutions. Based on these maps, the extra-nuclear structural morphologies and compositions of both galaxies are discussed. Furthermore, detailed brightness profile analysis of 3C 452 allows a direct comparison to a large literature sample of nearby ellipticals, all of which have been observed in the optical and near-IR by HST. Both the imaging data and the profile information on 3C 452 are consistent with it being a relative diminutive and well-evolved elliptical, in stark contrast to 3C 294 which seems to be in its initial formation throes with an active AGN off-centered from the main body of the galaxy. These results are discussed further within the framework of radio galaxy triggering and the formation of massive ellipticals. The work of WdV and WvB was performed under the auspices of the U.S. Department of Energy by University of California Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48. The work at UCSD has been supported by the NSF Science and Technology Center for Adaptive Optics, under agreement No. AST-98-76783.

  17. 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

  18. 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.

  19. 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.

  20. Adaptive compression of remote sensing stereo image pairs

    NASA Astrophysics Data System (ADS)

    Li, Yunsong; Yan, Ruomei; Wu, Chengke; Wang, Keyan; Li, Shizhong; Wang, Yu

    2010-09-01

    According to the data characteristics of remote sensing stereo image pairs, a novel adaptive compression algorithm based on the combination of feature-based image matching (FBM), area-based image matching (ABM), and region-based disparity estimation is proposed. First, the Scale Invariant Feature Transform (SIFT) and the Sobel operator are carried out for texture classification. Second, an improved ABM is used in the flat area, while the disparity estimation is used in the alpine area. The radiation compensation is applied to further improve the performance. Finally, the residual image and the reference image are compressed by JPEG2000 independently. The new algorithm provides a reasonable prediction in different areas according to the image textures, which improves the precision of the sensed image. The experimental results show that the PSNR of the proposed algorithm can obtain up to about 3dB's gain compared with the traditional algorithm at low or medium bitrates, and the DTM and subjective quality is also obviously enhanced.

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

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

    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 image denoising by targeted databases.

    PubMed

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

    2015-07-01

    We propose a data-dependent denoising procedure to restore noisy images. Different from existing denoising algorithms which search for patches from either the noisy image or a generic database, the new algorithm finds patches from a database that contains relevant patches. We formulate the denoising problem as an optimal filter design problem and make two contributions. First, we determine the basis function of the denoising filter by solving a group sparsity minimization problem. The optimization formulation generalizes existing denoising algorithms and offers systematic analysis of the performance. Improvement methods are proposed to enhance the patch search process. Second, we determine the spectral coefficients of the denoising filter by considering a localized Bayesian prior. The localized prior leverages the similarity of the targeted database, alleviates the intensive Bayesian computation, and links the new method to the classical linear minimum mean squared error estimation. We demonstrate applications of the proposed method in a variety of scenarios, including text images, multiview images, and face images. Experimental results show the superiority of the new algorithm over existing methods.

  3. 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.

  4. Adaptive image steganography using contourlet transform

    NASA Astrophysics Data System (ADS)

    Fakhredanesh, Mohammad; Rahmati, Mohammad; Safabakhsh, Reza

    2013-10-01

    This work presents adaptive image steganography methods which locate suitable regions for embedding by contourlet transform, while embedded message bits are carried in discrete cosine transform coefficients. The first proposed method utilizes contourlet transform coefficients to select contour regions of the image. In the embedding procedure, some of the contourlet transform coefficients may change which may cause errors at the message extraction phase. We propose a novel iterative procedure to resolve such problems. In addition, we have proposed an improved version of the first method in which it uses an advanced embedding operation to boost its security. Experimental results show that the proposed base method is an imperceptible image steganography method with zero retrieval error rate. Comparisons with other steganography methods which utilize contourlet transform show that our proposed method is able to retrieve all messages perfectly, whereas the others fail. Moreover, the proposed method outperforms the ContSteg method in terms of PSNR and the higher-order statistics steganalysis method. Experimental evaluations of our methods with the well known DCT-based steganography algorithms have demonstrated that our improved method has superior performance in terms of PSNR and SSIM, and is more secure against the steganalysis attack.

  5. Testing of hardware implementation of infrared image enhancing algorithm

    NASA Astrophysics Data System (ADS)

    Dulski, R.; Sosnowski, T.; PiÄ tkowski, T.; Trzaskawka, P.; Kastek, M.; Kucharz, J.

    2012-10-01

    The interpretation of IR images depends on radiative properties of observed objects and surrounding scenery. Skills and experience of an observer itself are also of great importance. The solution to improve the effectiveness of observation is utilization of algorithm of image enhancing capable to improve the image quality and the same effectiveness of object detection. The paper presents results of testing the hardware implementation of IR image enhancing algorithm based on histogram processing. Main issue in hardware implementation of complex procedures for image enhancing algorithms is high computational cost. As a result implementation of complex algorithms using general purpose processors and software usually does not bring satisfactory results. Because of high efficiency requirements and the need of parallel operation, the ALTERA's EP2C35F672 FPGA device was used. It provides sufficient processing speed combined with relatively low power consumption. A digital image processing and control module was designed and constructed around two main integrated circuits: a FPGA device and a microcontroller. Programmable FPGA device performs image data processing operations which requires considerable computing power. It also generates the control signals for array readout, performs NUC correction and bad pixel mapping, generates the control signals for display module and finally executes complex image processing algorithms. Implemented adaptive algorithm is based on plateau histogram equalization. Tests were performed on real IR images of different types of objects registered in different spectral bands. The simulations and laboratory experiments proved the correct operation of the designed system in executing the sophisticated image enhancement.

  6. Infrared image enhancement based on human visual properties

    NASA Astrophysics Data System (ADS)

    Chen, Hongyu; Hui, Bin

    2015-10-01

    With the development of modern military, infrared imaging technology is widely used in this field. However, limited by the mechanism of infrared imaging and the detector, infrared images have the disadvantages of low contrast and blurry edge by comparison with the visible image. These shortcomings lead infrared image unsuitable to be observed by both human and computer. Thus image enhancement is required. Traditional image enhancement methods on the application of infrared image, without taking into account the human visual properties, is not convenient for the human observation. This article purposes a new method that combines the layering idea with the human visual properties to enhance the infrared image. The proposed method relies on bilateral filtering to separate a base component, which contains the large amplitude signal and must be compressed, from a detail component, which must be expanded because it contains the small signal variations related to fine texture. The base component is mapped into the proper range which is 8-bit using the human visual properties, and the detail component is applied the method of adaptive gain control. Finally, the two parts are recombined and quantized to 8-bit domain. Experimental results show that this algorithm exceeds most current image enhancement methods in solving the problems of low contrast and blurry detail.

  7. A partial differential equation-based general framework adapted to Rayleigh's, Rician's and Gaussian's distributed noise for restoration and enhancement of magnetic resonance image.

    PubMed

    Yadav, Ram Bharos; Srivastava, Subodh; Srivastava, Rajeev

    2016-01-01

    The proposed framework is obtained by casting the noise removal problem into a variational framework. This framework automatically identifies the various types of noise present in the magnetic resonance image and filters them by choosing an appropriate filter. This filter includes two terms: the first term is a data likelihood term and the second term is a prior function. The first term is obtained by minimizing the negative log likelihood of the corresponding probability density functions: Gaussian or Rayleigh or Rician. Further, due to the ill-posedness of the likelihood term, a prior function is needed. This paper examines three partial differential equation based priors which include total variation based prior, anisotropic diffusion based prior, and a complex diffusion (CD) based prior. A regularization parameter is used to balance the trade-off between data fidelity term and prior. The finite difference scheme is used for discretization of the proposed method. The performance analysis and comparative study of the proposed method with other standard methods is presented for brain web dataset at varying noise levels in terms of peak signal-to-noise ratio, mean square error, structure similarity index map, and correlation parameter. From the simulation results, it is observed that the proposed framework with CD based prior is performing better in comparison to other priors in consideration.

  8. A partial differential equation-based general framework adapted to Rayleigh's, Rician's and Gaussian's distributed noise for restoration and enhancement of magnetic resonance image

    PubMed Central

    Yadav, Ram Bharos; Srivastava, Subodh; Srivastava, Rajeev

    2016-01-01

    The proposed framework is obtained by casting the noise removal problem into a variational framework. This framework automatically identifies the various types of noise present in the magnetic resonance image and filters them by choosing an appropriate filter. This filter includes two terms: the first term is a data likelihood term and the second term is a prior function. The first term is obtained by minimizing the negative log likelihood of the corresponding probability density functions: Gaussian or Rayleigh or Rician. Further, due to the ill-posedness of the likelihood term, a prior function is needed. This paper examines three partial differential equation based priors which include total variation based prior, anisotropic diffusion based prior, and a complex diffusion (CD) based prior. A regularization parameter is used to balance the trade-off between data fidelity term and prior. The finite difference scheme is used for discretization of the proposed method. The performance analysis and comparative study of the proposed method with other standard methods is presented for brain web dataset at varying noise levels in terms of peak signal-to-noise ratio, mean square error, structure similarity index map, and correlation parameter. From the simulation results, it is observed that the proposed framework with CD based prior is performing better in comparison to other priors in consideration. PMID:28144118

  9. Short-Term Neural Adaptation to Simultaneous Bifocal Images

    PubMed Central

    Radhakrishnan, Aiswaryah; Dorronsoro, Carlos; Sawides, Lucie; Marcos, Susana

    2014-01-01

    Simultaneous vision is an increasingly used solution for the correction of presbyopia (the age-related loss of ability to focus near images). Simultaneous Vision corrections, normally delivered in the form of contact or intraocular lenses, project on the patient's retina a focused image for near vision superimposed with a degraded image for far vision, or a focused image for far vision superimposed with the defocused image of the near scene. It is expected that patients with these corrections are able to adapt to the complex Simultaneous Vision retinal images, although the mechanisms or the extent to which this happens is not known. We studied the neural adaptation to simultaneous vision by studying changes in the Natural Perceived Focus and in the Perceptual Score of image quality in subjects after exposure to Simultaneous Vision. We show that Natural Perceived Focus shifts after a brief period of adaptation to a Simultaneous Vision blur, similar to adaptation to Pure Defocus. This shift strongly correlates with the magnitude and proportion of defocus in the adapting image. The magnitude of defocus affects perceived quality of Simultaneous Vision images, with 0.5 D defocus scored lowest and beyond 1.5 D scored “sharp”. Adaptation to Simultaneous Vision shifts the Perceptual Score of these images towards higher rankings. Larger improvements occurred when testing simultaneous images with the same magnitude of defocus as the adapting images, indicating that wearing a particular bifocal correction improves the perception of images provided by that correction. PMID:24664087

  10. 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,

  11. 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.

  12. Error Argumentation Enhance Adaptability in Adults With Low Motor Ability.

    PubMed

    Lee, Chi-Mei; Bo, Jin

    2016-01-01

    The authors focused on young adults with varying degrees of motor difficulties and examined their adaptability in a visuomotor adaptation task where the visual feedback of participants' movement error was presented with either 1:1 ratio (i.e., regular feedback schedule) or 1:2 ratio (i.e., enhanced feedback schedule). Within-subject design was used with two feedback schedules counter-balanced and separated for 10 days. Results revealed that participants with greater motor difficulties showed less adaptability than those with normal motor abilities in the regular feedback schedule; however, all participants demonstrated similar level of adaptability in the enhanced feedback schedule. The results suggest that error argumentation enhances adaptability in adults with low motor ability.

  13. An image enhancement technique using nonlinear transfer function and unsharp masking in multispectral endoscope

    NASA Astrophysics Data System (ADS)

    Zhang, Kejian; Wang, Huan; Yuan, Bo; Wang, Liqiang

    2017-01-01

    This paper studies the realization of image processing algorithm of multispectral endoscope. The research contents include: local brightness enhancement and adaptive contrast enhancement. Firstly, this paper transforms the image from the RGB space to the HSV space, and then carries on the image enhancement processing to the V space, finally transforms to the RGB space. Local brightness enhancement algorithm divides V space image into smaller windows, and then calculates the nonlinear transfer function of each window, which enhances the pixels in the window, and finally the contrast of brightness enhanced image is restored. The adaptive contrast enhancement adopts the unsharp mask technique based on the guided filter. First of all, this paper uses guided filter to the RGB channel of the original image and gets the unsharp mask of each channel, then plus a scaled image which is the result of the original image subtracts the unsharp mask. So the enhancement of the image is achieved. This paper uses subjective evaluation criteria and enhance factor α to evaluate the effect of enhancement. And this paper compares the enhancement effect of the proposed image enhancement algorithm and the traditional algorithm. The results show that the α of histogram equalization is smallest and AINDANE method is better than histogram equalization. The proposed method has the best α. The subjective evaluation also shows that the effect of HE is not satisfactory and the proposed method enhances the detail information tremendously. The subjective and objective criteria shows that the proposed method produces better enhancement effect.

  14. Image Quality Improvement in Adaptive Optics Scanning Laser Ophthalmoscopy Assisted Capillary Visualization Using B-spline-based Elastic Image Registration

    PubMed Central

    Uji, Akihito; Ooto, Sotaro; Hangai, Masanori; Arichika, Shigeta; Yoshimura, Nagahisa

    2013-01-01

    Purpose To investigate the effect of B-spline-based elastic image registration on adaptive optics scanning laser ophthalmoscopy (AO-SLO)-assisted capillary visualization. Methods AO-SLO videos were acquired from parafoveal areas in the eyes of healthy subjects and patients with various diseases. After nonlinear image registration, the image quality of capillary images constructed from AO-SLO videos using motion contrast enhancement was compared before and after B-spline-based elastic (nonlinear) image registration performed using ImageJ. For objective comparison of image quality, contrast-to-noise ratios (CNRS) for vessel images were calculated. For subjective comparison, experienced ophthalmologists ranked images on a 5-point scale. Results All AO-SLO videos were successfully stabilized by elastic image registration. CNR was significantly higher in capillary images stabilized by elastic image registration than in those stabilized without registration. The average ratio of CNR in images with elastic image registration to CNR in images without elastic image registration was 2.10 ± 1.73, with no significant difference in the ratio between patients and healthy subjects. Improvement of image quality was also supported by expert comparison. Conclusions Use of B-spline-based elastic image registration in AO-SLO-assisted capillary visualization was effective for enhancing image quality both objectively and subjectively. PMID:24265796

  15. Stochastic Adaptive Control and Estimation Enhancement

    DTIC Science & Technology

    1990-02-01

    ilM(k-S)1.izt-) (p. 1 and then the time after which the jump n’-* ’𔃻 takes place (i.e.. the sojourn time) is chosen 11 flp~ij) gil "’(n s~i,.k 39...Asilmar ant. pp 61-5. 184.Control or High Performance Aircraft using Adaptive ( Gil N.H. Ghalson and R.L. Moose. "Maneuverirng Target Aerstim ati nd...N It Dec. 1988. [ Gil N.H. Gholson and R.L. Moose, "Maneuveringl1(k.1) Is known, thus Target Tracking Using Adaptive State Estimation.- IEEE

  16. Robust adaptive digital watermark for still images using hybrid modulation

    NASA Astrophysics Data System (ADS)

    Alturki, Faisal T.; Mersereau, Russell M.

    2001-08-01

    A digital watermark is a short sequence of information containing an owner identity or copyright information embedded in a way that is difficult to erase. We present a new oblivious digital watermarking technique for copyright protection of still images. The technique embeds the watermark in a subset of low to mid frequency coefficients. A key is used to randomly select a group of coefficients from that subset for watermark embedding. The original phases of the selected coefficients are removed and the new phases are set in accordance with the embedded watermark. Since the coefficients are selected at random, the powers of the low magnitude coefficients are increased to enhance their immunity against image attacks. To cope with small geometric attacks, a replica of the watermark is embedded by dividing the image into sub-blocks and taking the DCT of these blocks. The watermark is embedded in the DC component of some of these blocks selected in an adaptive way using quantization techniques. A major advantage of this technique is its complete suppression of the noise due to the host image. The robustness of the technique to a number of standard image processing attacks is demonstrated using the criteria of the latest Stirmark benchmark test.

  17. 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…

  18. Edge enhanced morphology for infrared image analysis

    NASA Astrophysics Data System (ADS)

    Bai, Xiangzhi; Liu, Haonan

    2017-01-01

    Edge information is one of the critical information for infrared images. Morphological operators have been widely used for infrared image analysis. However, the edge information in infrared image is weak and the morphological operators could not well utilize the edge information of infrared images. To strengthen the edge information in morphological operators, the edge enhanced morphology is proposed in this paper. Firstly, the edge enhanced dilation and erosion operators are given and analyzed. Secondly, the pseudo operators which are derived from the edge enhanced dilation and erosion operators are defined. Finally, the applications for infrared image analysis are shown to verify the effectiveness of the proposed edge enhanced morphological operators. The proposed edge enhanced morphological operators are useful for the applications related to edge features, which could be extended to wide area of applications.

  19. Adaptive MOEMS mirrors for medical imaging

    NASA Astrophysics Data System (ADS)

    Fayek, Reda; Ibrahim, Hany

    2007-03-01

    This paper presents micro-electro-mechanical-systems (MEMS) optical elements with high angular deflection arranged in arrays to perform dynamic laser beam focusing and scanning. Each element selectively addresses a portion of the laser beam. These devices are useful in medical and research applications including laser-scanning microscopy, confocal microscopes, and laser capture micro-dissection. Such laser-based imaging and diagnostic instruments involve complex laser beam manipulations. These often require compound lenses and mirrors that introduce misalignment, attenuation, distortion and light scatter. Instead of using expensive spherical and aspherical lenses and/or mirrors for sophisticated laser beam manipulations, we propose scalable adaptive micro-opto-electro-mechanical-systems (MOEMS) arrays to recapture optical performance and compensate for aberrations, distortions and imperfections introduced by inexpensive optics. A high-density array of small, individually addressable, MOEMS elements is similar to a Fresnel mirror. A scalable 2D array of micro-mirrors approximates spherical or arbitrary surface mirrors of different apertures. A proof of concept prototype was built using PolyMUMP TM due to its reliability, low cost and limited post processing requirements. Low-density arrays (2x2 arrays of square elements, 250x250μm each) were designed, fabricated, and tested. Electrostatic comb fingers actuate the edges of the square mirrors with a low actuation voltage of 20 V - 50 V. CoventorWare TM was used for the design, 3D modeling and motion simulations. Initial results are encouraging. The array is adaptive, configurable and scalable with low actuation voltage and a large tuning range. Individual element addressability would allow versatile uses. Future research will increase deflection angles and maximize reflective area.

  20. Dictionary-enhanced imaging cytometry

    PubMed Central

    Orth, Antony; Schaak, Diane; Schonbrun, Ethan

    2017-01-01

    State-of-the-art high-throughput microscopes are now capable of recording image data at a phenomenal rate, imaging entire microscope slides in minutes. In this paper we investigate how a large image set can be used to perform automated cell classification and denoising. To this end, we acquire an image library consisting of over one quarter-million white blood cell (WBC) nuclei together with CD15/CD16 protein expression for each cell. We show that the WBC nucleus images alone can be used to replicate CD expression-based gating, even in the presence of significant imaging noise. We also demonstrate that accurate estimates of white blood cell images can be recovered from extremely noisy images by comparing with a reference dictionary. This has implications for dose-limited imaging when samples belong to a highly restricted class such as a well-studied cell type. Furthermore, large image libraries may endow microscopes with capabilities beyond their hardware specifications in terms of sensitivity and resolution. We call for researchers to crowd source large image libraries of common cell lines to explore this possibility. PMID:28225061

  1. Dictionary-enhanced imaging cytometry

    NASA Astrophysics Data System (ADS)

    Orth, Antony; Schaak, Diane; Schonbrun, Ethan

    2017-02-01

    State-of-the-art high-throughput microscopes are now capable of recording image data at a phenomenal rate, imaging entire microscope slides in minutes. In this paper we investigate how a large image set can be used to perform automated cell classification and denoising. To this end, we acquire an image library consisting of over one quarter-million white blood cell (WBC) nuclei together with CD15/CD16 protein expression for each cell. We show that the WBC nucleus images alone can be used to replicate CD expression-based gating, even in the presence of significant imaging noise. We also demonstrate that accurate estimates of white blood cell images can be recovered from extremely noisy images by comparing with a reference dictionary. This has implications for dose-limited imaging when samples belong to a highly restricted class such as a well-studied cell type. Furthermore, large image libraries may endow microscopes with capabilities beyond their hardware specifications in terms of sensitivity and resolution. We call for researchers to crowd source large image libraries of common cell lines to explore this possibility.

  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. An Adaptive Framework for Image and Video Sensing

    DTIC Science & Technology

    2005-03-01

    bandwidth on the camera transmission or memory is not optimally utilized. In this paper we outline a framework for an adaptive sensor where the spatial and...scene can be realized, with small distortion. Keywords: Adaptive Imaging, Varying Sampling Rate, Image Content Measure, Scene Adaptive, Camera ...second order effect on the spatio-temporal trade-off. Figure 1 is an example of the spatio-temporal sampling rate tradeoff in a typical camera (e.g

  4. 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

  5. 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.

  6. 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.

  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. 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.

  9. Diffraction enhanced x-ray imaging

    SciTech Connect

    Thomlinson, W.; Zhong, Z.; Chapman, D.; Johnston, R.E.; Sayers, D.

    1997-09-01

    Diffraction enhanced imaging (DEI) is a new x-ray radiographic imaging modality using synchrotron x-rays which produces images of thick absorbing objects that are almost completely free of scatter. They show dramatically improved contrast over standard imaging applied to the same phantoms. The contrast is based not only on attenuation but also the refraction and diffraction properties of the sample. The diffraction component and the apparent absorption component (absorption plus extinction contrast) can each be determined independently. This imaging method may improve the image quality for medical applications such as mammography.

  10. Theory and Application of Image Enhancement

    DTIC Science & Technology

    1994-02-01

    op onines 1. Imno Mai 3.M imag Ui a yoe l U.S ArmONg iOneerPM Waterways Experiment Station CatalogingVri-Publication Data r Ellis, Michael G. Theory...morphological transforms, edge detection , image crispening, noise cleaning, and other enhancement techniques. The FY92 program, IMAGE92, was completely...USENET Source CDROM X11RIGNU INFO-MAC CUG Library 2 Chapter I The Image Enhancement Pro*e. A Fiber Distributed Data Interface (FDDI) network

  11. Adaptive feature-specific imaging: a face recognition example.

    PubMed

    Baheti, Pawan K; Neifeld, Mark A

    2008-04-01

    We present an adaptive feature-specific imaging (AFSI) system and consider its application to a face recognition task. The proposed system makes use of previous measurements to adapt the projection basis at each step. Using sequential hypothesis testing, we compare AFSI with static-FSI (SFSI) and static or adaptive conventional imaging in terms of the number of measurements required to achieve a specified probability of misclassification (Pe). The AFSI system exhibits significant improvement compared to SFSI and conventional imaging at low signal-to-noise ratio (SNR). It is shown that for M=4 hypotheses and desired Pe=10(-2), AFSI requires 100 times fewer measurements than the adaptive conventional imager at SNR= -20 dB. We also show a trade-off, in terms of average detection time, between measurement SNR and adaptation advantage, resulting in an optimal value of integration time (equivalent to SNR) per measurement.

  12. 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.

  13. Stochastic Adaptive Control and Estimation Enhancement

    DTIC Science & Technology

    1989-09-01

    total Zu(N-J)’Gj’Q(N)FxIN-1)ou (N-I)I’[ R (N- 1) ’(N I Gil probability theorem to (4.3) yields J*(k.k 3 - min ( Ejx(kl 0(k)x(k) - u(k)’R(klu(k) trQ(N)VI m...Is Independent of Mil), I-k*2 .... N If Dec. 1988. [ Gil N.H. Gholson and R.L. Moose, "ManeuveringM(k.1J Is known, thus Target Tracking Using Adaptive...Control and A(t) =_ J1N X(i,t) is uniformly bounded. Quasi-Variational Inequalities, Gauthier- Villars , . (t9. tER4 , exits 0’ at most a countable

  14. 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

  15. 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.

  16. Curvature adaptive optics and low light imaging

    NASA Astrophysics Data System (ADS)

    Ftaclas, C.; Chun, M.; Kuhn, J.; Ritter, J.

    We review the basic approach of curvature adaptive optics (AO) and show how its many advantages arise. A curvature wave front sensor (WFS) measures exactly what a curvature deformable mirror (DM) generates. This leads to the computational and operational simplicity of a nearly diagonal control matrix. The DM automatically reconstructs the wave front based on WFS curvature measurements. Thus, there is no formal wave front reconstruction. This poses an interesting challenge to post-processing of AO images. Physical continuity of the DM and the reconstruction of phase from wave front curvature data assure that each actuated region of the DM corrects local phase, tip-tilt and focus. This gain in per-channel correction efficiency, combined with the need for only one pixel per channel detector reads in the WFS allows the use of photon counting detectors for wave front sensing. We note that the use of photon counting detectors implies penalty-free combination of correction channels either in the WFS or on the DM. This effectively decouples bright and faint source performance in that one no longer predicts the other. The application of curvature AO to the low light moving target detection problem, and explore the resulting challenges to components and control systems. Rapidly moving targets impose high-speed operation posing new requirements unique to curvature components. On the plus side, curvature wave front sensors, unlike their Shack-Hartmann counterparts, are tunable for optimum sensitivity to seeing and we are examining autonomous optimization of the WFS to respond to rapid changes in seeing.

  17. Photographic image enhancement and processing

    NASA Technical Reports Server (NTRS)

    Lockwood, H. E.

    1975-01-01

    Image processing techniques (computer and photographic) are described which are used within the JSC Photographic Technology Division. Two purely photographic techniques used for specific subject isolation are discussed in detail. Sample imagery is included.

  18. An adaptive filter for smoothing noisy radar images

    NASA Technical Reports Server (NTRS)

    Frost, V. S.; Stiles, J. A.; Shanmugam, K. S.; Holtzman, J. C.; Smith, S. A.

    1981-01-01

    A spatial domain adaptive Wiener filter for smoothing radar images corrupted by multiplicative noise is presented. The filter is optimum in a minimum mean squared error sense, computationally efficient, and preserves edges in the image better than other filters. The proposed algorithm can also be used for processing optical images with illumination variations that have a multiplicative effect.

  19. Noise-adaptive nonlinear diffusion filtering of MR images with spatially varying noise levels.

    PubMed

    Samsonov, Alexei A; Johnson, Chris R

    2004-10-01

    Anisotropic diffusion filtering is widely used for MR image enhancement. However, the anisotropic filter is nonoptimal for MR images with spatially varying noise levels, such as images reconstructed from sensitivity-encoded data and intensity inhomogeneity-corrected images. In this work, a new method for filtering MR images with spatially varying noise levels is presented. In the new method, a priori information regarding the image noise level spatial distribution is utilized for the local adjustment of the anisotropic diffusion filter. Our new method was validated and compared with the standard filter on simulated and real MRI data. The noise-adaptive method was demonstrated to outperform the standard anisotropic diffusion filter in both image error reduction and image signal-to-noise ratio (SNR) improvement. The method was also applied to inhomogeneity-corrected and sensitivity encoding (SENSE) images. The new filter was shown to improve segmentation of MR brain images with spatially varying noise levels.

  20. 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.

  1. Adaptation Aftereffects in the Perception of Radiological Images

    PubMed Central

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

    2013-01-01

    Radiologists must classify and interpret medical images on the basis of visual inspection. We examined how the perception of radiological scans might be affected by common processes of adaptation in the visual system. Adaptation selectively adjusts sensitivity to the properties of the stimulus in current view, inducing an aftereffect in the appearance of stimuli viewed subsequently. These perceptual changes have been found to affect many visual attributes, but whether they are relevant to medical image perception is not well understood. To examine this we tested whether aftereffects could be generated by the characteristic spatial structure of radiological scans, and whether this could bias their appearance along dimensions that are routinely used to classify them. Measurements were focused on the effects of adaptation to images of normal mammograms, and were tested in observers who were not radiologists. Tissue density in mammograms is evaluated visually and ranges from "dense" to "fatty." Arrays of images varying in intermediate levels between these categories were created by blending dense and fatty images with different weights. Observers first adapted by viewing image samples of dense or fatty tissue, and then judged the appearance of the intermediate images by using a texture matching task. This revealed pronounced perceptual aftereffects – prior exposure to dense images caused an intermediate image to appear more fatty and vice versa. Moreover, the appearance of the adapting images themselves changed with prolonged viewing, so that they became less distinctive as textures. These aftereffects could not be accounted for by the contrast differences or power spectra of the images, and instead tended to follow from the phase spectrum. Our results suggest that observers can selectively adapt to the properties of radiological images, and that this selectivity could strongly impact the perceived textural characteristics of the images. PMID:24146833

  2. 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.

  3. Adaptive coupling and enhanced synchronization in coupled phase oscillators

    NASA Astrophysics Data System (ADS)

    Ren, Quansheng; Zhao, Jianye

    2007-07-01

    We study the dynamics of an adaptive coupled array of phase oscillators. The adaptive law is designed in such a way that the coupling grows stronger for the pairs which have larger phase incoherence. The proposed scheme enhances the synchronization and achieves a more reasonable coupling dynamics for the network of oscillators with different intrinsic frequencies. The synchronization speed and the steady-state phase difference can be adjusted by the parameters of the adaptive law. Besides global coupling, nearest-neighbor ring coupling is also considered to demonstrate the generality of the method.

  4. 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.

  5. An adaptive enhancement algorithm for infrared video based on modified k-means clustering

    NASA Astrophysics Data System (ADS)

    Zhang, Linze; Wang, Jingqi; Wu, Wen

    2016-09-01

    In this paper, we have proposed a video enhancement algorithm to improve the output video of the infrared camera. Sometimes the video obtained by infrared camera is very dark since there is no clear target. In this case, infrared video should be divided into frame images by frame extraction, in order to carry out the image enhancement. For the first frame image, which can be divided into k sub images by using K-means clustering according to the gray interval it occupies before k sub images' histogram equalization according to the amount of information per sub image, we used a method to solve a problem that final cluster centers close to each other in some cases; and for the other frame images, their initial cluster centers can be determined by the final clustering centers of the previous ones, and the histogram equalization of each sub image will be carried out after image segmentation based on K-means clustering. The histogram equalization can make the gray value of the image to the whole gray level, and the gray level of each sub image is determined by the ratio of pixels to a frame image. Experimental results show that this algorithm can improve the contrast of infrared video where night target is not obvious which lead to a dim scene, and reduce the negative effect given by the overexposed pixels adaptively in a certain range.

  6. 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.

  7. 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.

  8. An adaptive optics biomicroscope for mouse retinal imaging

    NASA Astrophysics Data System (ADS)

    Biss, David P.; Webb, Robert H.; Zhou, Yaopeng; Bifano, Thomas G.; Zamiri, Parisa; Lin, Charles P.

    2007-02-01

    In studying retinal disease on a microscopic level, in vivo imaging has allowed researchers to track disease progression in a single animal over time without sacrificing large numbers of animals for statistical studies. Historically, a drawback of in vivo retinal imaging, when compared to ex vivo imaging, is decreased image resolution due to aberrations present in the mouse eye. Adaptive optics has successfully corrected phase aberrations introduced the eye in ophthalmic imaging in humans. We are using adaptive optics to correct for aberrations introduced by the mouse eye in hopes of achieving cellular resolution retinal images of mice in vivo. In addition to using a wavefront sensor to drive the adaptive optic element, we explore the using image data to correct for wavefront aberrations introduced by the mouse eye. Image data, in the form of the confocal detection pinhole intensity are used as the feedback mechanism to control the MEMS deformable mirror in the adaptive optics system. Correction for wavefront sensing and sensor-less adaptive optics systems are presented.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. A dual-modal retinal imaging system with adaptive optics

    PubMed Central

    Meadway, Alexander; Girkin, Christopher A.; Zhang, Yuhua

    2013-01-01

    An adaptive optics scanning laser ophthalmoscope (AO-SLO) is adapted to provide optical coherence tomography (OCT) imaging. The AO-SLO function is unchanged. The system uses the same light source, scanning optics, and adaptive optics in both imaging modes. The result is a dual-modal system that can acquire retinal images in both en face and cross-section planes at the single cell level. A new spectral shaping method is developed to reduce the large sidelobes in the coherence profile of the OCT imaging when a non-ideal source is used with a minimal introduction of noise. The technique uses a combination of two existing digital techniques. The thickness and position of the traditionally named inner segment/outer segment junction are measured from individual photoreceptors. In-vivo images of healthy and diseased human retinas are demonstrated. PMID:24514529

  14. Spectrally Adaptable Compressive Sensing Imaging System

    DTIC Science & Technology

    2014-05-01

    2D coded projections. The underlying spectral 3D data cube is then recovered using compressed sensing (CS) reconstruction algorithms which assume...introduced in [?], is a remarkable imaging architecture that allows capturing spectral imaging information of a 3D cube with just a single 2D mea...allows capturing spectral imaging information of a 3D cube with just a single 2D measurement of the coded and spectrally dispersed source field

  15. Towards Adaptive High-Resolution Images Retrieval Schemes

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

    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.

  16. 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.

  17. Spatially adaptive regularized iterative high-resolution image reconstruction algorithm

    NASA Astrophysics Data System (ADS)

    Lim, Won Bae; Park, Min K.; Kang, Moon Gi

    2000-12-01

    High resolution images are often required in applications such as remote sensing, frame freeze in video, military and medical imaging. Digital image sensor arrays, which are used for image acquisition in many imaging systems, are not dense enough to prevent aliasing, so the acquired images will be degraded by aliasing effects. To prevent aliasing without loss of resolution, a dense detector array is required. But it may be very costly or unavailable, thus, many imaging systems are designed to allow some level of aliasing during image acquisition. The purpose of our work is to reconstruct an unaliased high resolution image from the acquired aliased image sequence. In this paper, we propose a spatially adaptive regularized iterative high resolution image reconstruction algorithm for blurred, noisy and down-sampled image sequences. The proposed approach is based on a Constrained Least Squares (CLS) high resolution reconstruction algorithm, with spatially adaptive regularization operators and parameters. These regularization terms are shown to improve the reconstructed image quality by forcing smoothness, while preserving edges in the reconstructed high resolution image. Accurate sub-pixel motion registration is the key of the success of the high resolution image reconstruction algorithm. However, sub-pixel motion registration may have some level of registration error. Therefore, a reconstruction algorithm which is robust against the registration error is required. The registration algorithm uses a gradient based sub-pixel motion estimator which provides shift information for each of the recorded frames. The proposed algorithm is based on a technique of high resolution image reconstruction, and it solves spatially adaptive regularized constrained least square minimization functionals. In this paper, we show that the reconstruction algorithm gives dramatic improvements in the resolution of the reconstructed image and is effective in handling the aliased information. The

  18. Block-based adaptive lifting schemes for multiband image compression

    NASA Astrophysics Data System (ADS)

    Masmoudi, Hela; Benazza-Benyahia, Amel; Pesquet, Jean-Christophe

    2004-02-01

    In this paper, we are interested in designing lifting schemes adapted to the statistics of the wavelet coefficients of multiband images for compression applications. More precisely, nonseparable vector lifting schemes are used in order to capture simultaneously the spatial and the spectral redundancies. The underlying operators are then computed in order to minimize the entropy of the resulting multiresolution representation. To this respect, we have developed a new iterative block-based classification algorithm. Simulation tests carried out on remotely sensed multispectral images indicate that a substantial gain in terms of bit-rate is achieved by the proposed adaptive coding method w.r.t the non-adaptive one.

  19. Rapid adaptation in visual cortex to the structure of images.

    PubMed

    Müller, J R; Metha, A B; Krauskopf, J; Lennie, P

    1999-08-27

    Complex cells in striate cortex of macaque showed a rapid pattern-specific adaptation. Adaptation made cells more sensitive to orientation change near the adapting orientation. It reduced correlations among the responses of populations of cells, thereby increasing the information transmitted by each action potential. These changes were brought about by brief exposures to stationary patterns, on the time scale of a single fixation. Thus, if successive fixations expose neurons' receptive fields to images with similar but not identical structure, adaptation will remove correlations and improve discriminability.

  20. 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.

  1. 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

  2. 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.

  3. Image denoising via adaptive eigenvectors of graph Laplacian

    NASA Astrophysics Data System (ADS)

    Chen, Ying; Tang, Yibin; Xu, Ning; Zhou, Lin; Zhao, Li

    2016-07-01

    An image denoising method via adaptive eigenvectors of graph Laplacian (EGL) is proposed. Unlike the trivial parameter setting of the used eigenvectors in the traditional EGL method, in our method, the eigenvectors are adaptively selected in the whole denoising procedure. In detail, a rough image is first built with the eigenvectors from the noisy image, where the eigenvectors are selected by using the deviation estimation of the clean image. Subsequently, a guided image is effectively restored with a weighted average of the noisy and rough images. In this operation, the average coefficient is adaptively obtained to set the deviation of the guided image to approximately that of the clean image. Finally, the denoised image is achieved by a group-sparse model with the pattern from the guided image, where the eigenvectors are chosen in the error control of the noise deviation. Moreover, a modified group orthogonal matching pursuit algorithm is developed to efficiently solve the above group sparse model. The experiments show that our method not only improves the practicality of the EGL methods with the dependence reduction of the parameter setting, but also can outperform some well-developed denoising methods, especially for noise with large deviations.

  4. 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

  5. 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

  6. 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.

  7. Edge-preserving image compression using adaptive lifting wavelet transform

    NASA Astrophysics Data System (ADS)

    Zhang, Libao; Qiu, Bingchang

    2015-07-01

    In this paper, a novel 2-D adaptive lifting wavelet transform is presented. The proposed algorithm is designed to further reduce the high-frequency energy of wavelet transform, improve the image compression efficiency and preserve the edge or texture of original images more effectively. In this paper, a new optional direction set, covering the surrounding integer pixels and sub-pixels, is designed. Hence, our algorithm adapts far better to the image orientation features in local image blocks. To obtain the computationally efficient and coding performance, the complete processes of 2-D adaptive lifting wavelet transform is introduced and implemented. Compared with the traditional lifting-based wavelet transform, the adaptive directional lifting and the direction-adaptive discrete wavelet transform, the new structure reduces the high-frequency wavelet coefficients more effectively, and the texture structures of the reconstructed images are more refined and clear than that of the other methods. The peak signal-to-noise ratio and the subjective quality of the reconstructed images are significantly improved.

  8. SPECKLE NOISE SUBTRACTION AND SUPPRESSION WITH ADAPTIVE OPTICS CORONAGRAPHIC IMAGING

    SciTech Connect

    Ren Deqing; Dou Jiangpei; Zhang Xi; Zhu Yongtian

    2012-07-10

    Future ground-based direct imaging of exoplanets depends critically on high-contrast coronagraph and wave-front manipulation. A coronagraph is designed to remove most of the unaberrated starlight. Because of the wave-front error, which is inherit from the atmospheric turbulence from ground observations, a coronagraph cannot deliver its theoretical performance, and speckle noise will limit the high-contrast imaging performance. Recently, extreme adaptive optics, which can deliver an extremely high Strehl ratio, is being developed for such a challenging mission. In this publication, we show that barely taking a long-exposure image does not provide much gain for coronagraphic imaging with adaptive optics. We further discuss a speckle subtraction and suppression technique that fully takes advantage of the high contrast provided by the coronagraph, as well as the wave front corrected by the adaptive optics. This technique works well for coronagraphic imaging with conventional adaptive optics with a moderate Strehl ratio, as well as for extreme adaptive optics with a high Strehl ratio. We show how to substrate and suppress speckle noise efficiently up to the third order, which is critical for future ground-based high-contrast imaging. Numerical simulations are conducted to fully demonstrate this technique.

  9. 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.

  10. 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.

  11. FPGA implementation of image enhancement techniques

    NASA Astrophysics Data System (ADS)

    Kumar, Karan; Jain, Aditya; Srivastava, Atul Kumar

    2009-06-01

    The objective of this paper is designing, modeling, simulation and synthesis of four Image Enhancement techniques on FPGA. Image Enhancement Algorithms can be classified as point processing Techniques, in which operation is done on pixel level and Spatial Filtering Technique, in which operation is performed within neighborhood of a pixel. Algorithms of all the techniques are studied and hardware circuits are realized for them. Then hardware logic is modeled in Matlab Simulink using Xilinx System Generator Block set and synthesized onto Virtex4 xc4vsx35-10ff668 FPGA chip. Using hardware co-simulation feature of FPGA kit, the algorithms developed are validated.

  12. 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.

  13. Metal Nanostructures for Detection and Imaging Enhancements

    DTIC Science & Technology

    2011-01-03

    source spectrum, is delivered into a pig adipose sample. OCT is a widely used optical imaging technique for the diagnoses of many diseases [27-29... Fahr , C. Rockstuhl, and F. Lederer, “Engineering the randomness for enhanced absorption in solar cells,” Appl. Phys. Lett. 92, 171114 (2008). 7. T...Rockstuhl, S. Fahr , and F. Lederer, “Absorption enhancement in solar cells by localized plasmon polaritons,” J. Appl. Phys. 104, 123102 (2008). 31. A

  14. Climate Change Adaptation Among Tibetan Pastoralists: Challenges in Enhancing Local Adaptation Through Policy Support

    NASA Astrophysics Data System (ADS)

    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.

  15. 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.

  16. Dynamical weights and enhanced synchronization in adaptive complex networks.

    PubMed

    Zhou, Changsong; Kurths, Jürgen

    2006-04-28

    Dynamical organization of connection weights is studied in scale-free networks of chaotic oscillators, where the coupling strength of a node from its neighbors develops adaptively according to the local synchronization property between the node and its neighbors. We find that when complete synchronization is achieved, the coupling strength becomes weighted and correlated with the topology due to a hierarchical transition to synchronization in heterogeneous networks. Importantly, such an adaptive process enhances significantly the synchronizability of the networks, which could have meaningful implications in the manipulation of dynamical networks.

  17. Image super-resolution via adaptive filtering and regularization

    NASA Astrophysics Data System (ADS)

    Ren, Jingbo; Wu, Hao; Dong, Weisheng; Shi, Guangming

    2014-11-01

    Image super-resolution (SR) is widely used in the fields of civil and military, especially for the low-resolution remote sensing images limited by the sensor. Single-image SR refers to the task of restoring a high-resolution (HR) image from the low-resolution image coupled with some prior knowledge as a regularization term. One classic method regularizes image by total variation (TV) and/or wavelet or some other transform which introduce some artifacts. To compress these shortages, a new framework for single image SR is proposed by utilizing an adaptive filter before regularization. The key of our model is that the adaptive filter is used to remove the spatial relevance among pixels first and then only the high frequency (HF) part, which is sparser in TV and transform domain, is considered as the regularization term. Concretely, through transforming the original model, the SR question can be solved by two alternate iteration sub-problems. Before each iteration, the adaptive filter should be updated to estimate the initial HF. A high quality HF part and HR image can be obtained by solving the first and second sub-problem, respectively. In experimental part, a set of remote sensing images captured by Landsat satellites are tested to demonstrate the effectiveness of the proposed framework. Experimental results show the outstanding performance of the proposed method in quantitative evaluation and visual fidelity compared with the state-of-the-art methods.

  18. Adaptive optics image restoration algorithm based on wavefront reconstruction and adaptive total variation method

    NASA Astrophysics Data System (ADS)

    Li, Dongming; Zhang, Lijuan; Wang, Ting; Liu, Huan; Yang, Jinhua; Chen, Guifen

    2016-11-01

    To improve the adaptive optics (AO) image's quality, we study the AO image restoration algorithm based on wavefront reconstruction technology and adaptive total variation (TV) method in this paper. Firstly, the wavefront reconstruction using Zernike polynomial is used for initial estimated for the point spread function (PSF). Then, we develop our proposed iterative solutions for AO images restoration, addressing the joint deconvolution issue. The image restoration experiments are performed to verify the image restoration effect of our proposed algorithm. The experimental results show that, compared with the RL-IBD algorithm and Wiener-IBD algorithm, we can see that GMG measures (for real AO image) from our algorithm are increased by 36.92%, and 27.44% respectively, and the computation time are decreased by 7.2%, and 3.4% respectively, and its estimation accuracy is significantly improved.

  19. 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.

  20. 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.

  1. Adaptive textural segmentation of medical images

    NASA Astrophysics Data System (ADS)

    Kuklinski, Walter S.; Frost, Gordon S.; MacLaughlin, Thomas

    1992-06-01

    A number of important problems in medical imaging can be described as segmentation problems. Previous fractal-based image segmentation algorithms have used either the local fractal dimension alone or the local fractal dimension and the corresponding image intensity as features for subsequent pattern recognition algorithms. An image segmentation algorithm that utilized the local fractal dimension, image intensity, and the correlation coefficient of the local fractal dimension regression analysis computation, to produce a three-dimension feature space that was partitioned to identify specific pixels of dental radiographs as being either bone, teeth, or a boundary between bone and teeth also has been reported. In this work we formulated the segmentation process as a configurational optimization problem and discuss the application of simulated annealing optimization methods to the solution of this specific optimization problem. The configurational optimization method allows information about both, the degree of correspondence between a candidate segment and an assumed textural model, and morphological information about the candidate segment to be used in the segmentation process. To apply this configurational optimization technique with a fractal textural model however, requires the estimation of the fractal dimension of an irregularly shaped candidate segment. The potential utility of a discrete Gerchberg-Papoulis bandlimited extrapolation algorithm to the estimation of the fractal dimension of an irregularly shaped candidate segment is also discussed.

  2. Lossless image compression based on optimal prediction, adaptive lifting, and conditional arithmetic coding.

    PubMed

    Boulgouris, N V; Tzovaras, D; Strintzis, M G

    2001-01-01

    The optimal predictors of a lifting scheme in the general n-dimensional case are obtained and applied for the lossless compression of still images using first quincunx sampling and then simple row-column sampling. In each case, the efficiency of the linear predictors is enhanced nonlinearly. Directional postprocessing is used in the quincunx case, and adaptive-length postprocessing in the row-column case. Both methods are seen to perform well. The resulting nonlinear interpolation schemes achieve extremely efficient image decorrelation. We further investigate context modeling and adaptive arithmetic coding of wavelet coefficients in a lossless compression framework. Special attention is given to the modeling contexts and the adaptation of the arithmetic coder to the actual data. Experimental evaluation shows that the best of the resulting coders produces better results than other known algorithms for multiresolution-based lossless image coding.

  3. Feature and contrast enhancement of mammographic image based on multiscale analysis and morphology.

    PubMed

    Wu, Shibin; Yu, Shaode; Yang, Yuhan; 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).

  4. 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

  5. Photonics-enhanced smart imaging systems

    NASA Astrophysics Data System (ADS)

    Ottevaere, Heidi; Belay, Gebirie Y.; Thienpont, Hugo

    2016-09-01

    We discuss different photonics-enhanced multichannel multiresolution imaging systems in which the different channels have different imaging properties, namely a different FOV and angular resolution, over different areas of an image sensor. This could allow different image processing algorithms to be implemented to process the different images. A basic threechannel multiresolution imaging system was designed at 587.6 nm where each of the three channels consist of four aspherical lens surfaces. These lenses have been fabricated in PMMA through ultra-precision diamond tooling and afterwards assembled with aperture stops, baffles and a commercial CMOS sensor. To reduce the influence of chromatic aberrations, hybrid lenses, which contain diffractive surfaces on top of refractive ones, have been included within the previous designs of the three channels. These hybrid lenses have also been fabricated through ultra-precision diamond tooling, assembled and verified in an experimental demonstration. The three channels with hybrid lenses show better image quality (both in the simulation and experiment) compared to the purely refractive three channel design. Because of a limited depth of field of the aforementioned multichannel multiresolution imaging systems, a voltage tunable lens has been integrated in the first channel to extend the depth of field of the overall system. The refocusing capability has significantly improved the depth of field of the system and ranged from 0.25 m to infinity compared to 9 m to infinity for the aforementioned basic three-channel multiresolution imaging system.

  6. Resolution enhancement in medical ultrasound imaging

    PubMed Central

    Ploquin, Marie; Basarab, Adrian; Kouamé, Denis

    2015-01-01

    Abstract. 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

  7. 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

  8. Image segmentation by EM-based adaptive pulse coupled neural networks in brain magnetic resonance imaging.

    PubMed

    Fu, J C; Chen, C C; Chai, J W; Wong, S T C; Li, I C

    2010-06-01

    We propose an automatic hybrid image segmentation model that integrates the statistical expectation maximization (EM) model and the spatial pulse coupled neural network (PCNN) for brain magnetic resonance imaging (MRI) segmentation. In addition, an adaptive mechanism is developed to fine tune the PCNN parameters. The EM model serves two functions: evaluation of the PCNN image segmentation and adaptive adjustment of the PCNN parameters for optimal segmentation. To evaluate the performance of the adaptive EM-PCNN, we use it to segment MR brain image into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). The performance of the adaptive EM-PCNN is compared with that of the non-adaptive EM-PCNN, EM, and Bias Corrected Fuzzy C-Means (BCFCM) algorithms. The result is four sets of boundaries for the GM and the brain parenchyma (GM+WM), the two regions of most interest in medical research and clinical applications. Each set of boundaries is compared with the golden standard to evaluate the segmentation performance. The adaptive EM-PCNN significantly outperforms the non-adaptive EM-PCNN, EM, and BCFCM algorithms in gray mater segmentation. In brain parenchyma segmentation, the adaptive EM-PCNN significantly outperforms the BCFCM only. However, the adaptive EM-PCNN is better than the non-adaptive EM-PCNN and EM on average. We conclude that of the three approaches, the adaptive EM-PCNN yields the best results for gray matter and brain parenchyma segmentation.

  9. 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.

  10. 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.

  11. 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.

  12. An improved adaptive IHS method for image fusion

    NASA Astrophysics Data System (ADS)

    Wang, Ting

    2015-12-01

    An improved adaptive intensity-hue-saturation (IHS) method is proposed for image fusion in this paper based on the adaptive IHS (AIHS) method and its improved method(IAIHS). Through improved method, the weighting matrix, which decides how many spatial details in the panchromatic (Pan) image should be injected into the multispectral (MS) image, is defined on the basis of the linear relationship of the edges of Pan and MS image. At the same time, a modulation parameter t is used to balance the spatial resolution and spectral resolution of the fusion image. Experiments showed that the improved method can improve spectral quality and maintain spatial resolution compared with the AIHS and IAIHS methods.

  13. 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

  14. Adaptive Compression of Multisensor Image Data

    DTIC Science & Technology

    1992-03-01

    upsample and reconstruct the subimages which are then added together to form the reconstructed image. In order to prevent distortions resulting from...smooth surfaces such as metallic or painted objects have predominantly path A reflections and that rougher surfaces such as soils and vegetation support

  15. Adaptive filtering for reduction of speckle in ultrasonic pulse-echo images.

    PubMed

    Bamber, J C; Daft, C

    1986-01-01

    Current medical ultrasonic scanning instrumentation permits the display of fine image detail (speckle) which does not transfer useful information but degrades the apparent low contrast resolution in the image. An adaptive two-dimensional filter has been developed which uses local features of image texture to recognize and maximally low-pass filter those parts of the image which correspond to fully developed speckle, while substantially preserving information associated with resolved-object structure. A first implementation of the filter is described which uses the ratio of the local variance and the local mean as the speckle recognition feature. Preliminary results of applying this form of display processing to medical ultrasound images are very encouraging; it appears that the visual perception of features such as small discrete structures, subtle fluctuations in mean echo level and changes in image texture may be enhanced relative to that for unprocessed images.

  16. Single-shot adaptive measurement for quantum-enhanced metrology

    NASA Astrophysics Data System (ADS)

    Palittpongarnpim, Pantita; Wittek, Peter; Sanders, Barry C.

    2016-09-01

    Quantum-enhanced metrology aims to estimate an unknown parameter such that the precision scales better than the shot-noise bound. Single-shot adaptive quantum-enhanced metrology (AQEM) is a promising approach that uses feedback to tweak the quantum process according to previous measurement outcomes. Techniques and formalism for the adaptive case are quite different from the usual non-adaptive quantum metrology approach due to the causal relationship between measurements and outcomes. We construct a formal framework for AQEM by modeling the procedure as a decision-making process, and we derive the imprecision and the Craḿer- Rao lower bound with explicit dependence on the feedback policy. We also explain the reinforcement learning approach for generating quantum control policies, which is adopted due to the optimal policy being non-trivial to devise. Applying a learning algorithm based on differential evolution enables us to attain imprecision for adaptive interferometric phase estimation, which turns out to be SQL when non-entangled particles are used in the scheme.

  17. Development of a Countermeasure to Enhance Postflight Locomotor Adaptability

    NASA Technical Reports Server (NTRS)

    Bloomberg, Jacob J.

    2006-01-01

    Astronauts returning from space flight experience locomotor dysfunction following their return to Earth. Our laboratory is currently developing a gait adaptability training program that is designed to facilitate recovery of locomotor function following a return to a gravitational environment. The training program exploits the ability of the sensorimotor system to generalize from exposure to multiple adaptive challenges during training so that the gait control system essentially learns to learn and therefore can reorganize more rapidly when faced with a novel adaptive challenge. We have previously confirmed that subjects participating in adaptive generalization training programs using a variety of visuomotor distortions can enhance their ability to adapt to a novel sensorimotor environment. Importantly, this increased adaptability was retained even one month after completion of the training period. Adaptive generalization has been observed in a variety of other tasks requiring sensorimotor transformations including manual control tasks and reaching (Bock et al., 2001, Seidler, 2003) and obstacle avoidance during walking (Lam and Dietz, 2004). Taken together, the evidence suggests that a training regimen exposing crewmembers to variation in locomotor conditions, with repeated transitions among states, may enhance their ability to learn how to reassemble appropriate locomotor patterns upon return from microgravity. We believe exposure to this type of training will extend crewmembers locomotor behavioral repertoires, facilitating the return of functional mobility after long duration space flight. Our proposed training protocol will compel subjects to develop new behavioral solutions under varying sensorimotor demands. Over time subjects will learn to create appropriate locomotor solution more rapidly enabling acquisition of mobility sooner after long-duration space flight. Our laboratory is currently developing adaptive generalization training procedures and the

  18. 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.

  19. Image enhancement technology research for army applications

    NASA Astrophysics Data System (ADS)

    Schwering, Piet B. W.; Kemp, Rob A. W.; Schutte, Klamer

    2013-06-01

    Recognition and identification ranges are limited to the quality of the images. Both the received contrast and the spatial resolution determine if objects are recognizable. Several aspects affect the image quality. First of all the sensor itself. The image quality depends on the size of the infrared detector array and the sensitivity. Second, also the intervening atmosphere, in particular over longer ranges, has an impact on the image quality. It degrades the contrast, due to transmission effects, as well as it influences the resolution, due to turbulence blur, of the image. We present studies in the field of infrared image enhancement. Several techniques are described: noise reduction, super resolution, turbulence compensation, contrast enhancement, stabilization. These techniques operate in real-time on COTS/MOTS platforms. They are especially effective in the army theatre, where long horizontal paths, and short line-of-sight limited urban operations are both present. Application of these techniques on observation masts, such as on military camp sites, and on UAVs and moving ground vehicles are discussed. Examples will be presented from several trials in which these techniques were demonstrated, including the presentation of test results.

  20. Enhanced dynamic range x-ray imaging.

    PubMed

    Haidekker, Mark A; Morrison, Logan Dain-Kelley; Sharma, Ajay; Burke, Emily

    2017-03-01

    X-ray images can suffer from excess contrast. Often, image exposure is chosen to visually optimize the region of interest, but at the expense of over- and underexposed regions elsewhere in the image. When image values are interpreted quantitatively as projected absorption, both over- and underexposure leads to the loss of quantitative information. We propose to combine multiple exposures into a composite that uses only pixels from those exposures in which they are neither under- nor overexposed. The composite image is created in analogy to visible-light high dynamic range photography. We present the mathematical framework for the recovery of absorbance from such composite images and demonstrate the method with biological and non-biological samples. We also show with an aluminum step-wedge that accurate recovery of step thickness from the absorbance values is possible, thereby highlighting the quantitative nature of the presented method. Due to the higher amount of detail encoded in an enhanced dynamic range x-ray image, we expect that the number of retaken images can be reduced, and patient exposure overall reduced. We also envision that the method can improve dual energy absorptiometry and even computed tomography by reducing the number of low-exposure ("photon-starved") projections.

  1. 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.

  2. 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.

  3. 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.

  4. Adaptive dictionary learning in sparse gradient domain for image recovery.

    PubMed

    Liu, Qiegen; Wang, Shanshan; Ying, Leslie; Peng, Xi; Zhu, Yanjie; Liang, Dong

    2013-12-01

    Image recovery from undersampled data has always been challenging due to its implicit ill-posed nature but becomes fascinating with the emerging compressed sensing (CS) theory. This paper proposes a novel gradient based dictionary learning method for image recovery, which effectively integrates the popular total variation (TV) and dictionary learning technique into the same framework. Specifically, we first train dictionaries from the horizontal and vertical gradients of the image and then reconstruct the desired image using the sparse representations of both derivatives. The proposed method enables local features in the gradient images to be captured effectively, and can be viewed as an adaptive extension of the TV regularization. The results of various experiments on MR images consistently demonstrate that the proposed algorithm efficiently recovers images and presents advantages over the current leading CS reconstruction approaches.

  5. An adaptive nonlocal means scheme for medical image denoising

    NASA Astrophysics Data System (ADS)

    Thaipanich, Tanaphol; Kuo, C.-C. Jay

    2010-03-01

    Medical images often consist of low-contrast objects corrupted by random noise arising in the image acquisition process. Thus, image denoising is one of the fundamental tasks required by medical imaging analysis. In this work, we investigate an adaptive denoising scheme based on the nonlocal (NL)-means algorithm for medical imaging applications. In contrast with the traditional NL-means algorithm, the proposed adaptive NL-means (ANL-means) denoising scheme has three unique features. First, it employs the singular value decomposition (SVD) method and the K-means clustering (K-means) technique for robust classification of blocks in noisy images. Second, the local window is adaptively adjusted to match the local property of a block. Finally, a rotated block matching algorithm is adopted for better similarity matching. Experimental results from both additive white Gaussian noise (AWGN) and Rician noise are given to demonstrate the superior performance of the proposed ANL denoising technique over various image denoising benchmarks in term of both PSNR and perceptual quality comparison.

  6. Image registration for DSA quality enhancement.

    PubMed

    Buzug, T M; Weese, J

    1998-01-01

    A generalized framework for histogram-based similarity measures is presented and applied to the image-enhancement task in digital subtraction angiography (DSA). The class of differentiable, strictly convex weighting functions is identified as suitable weightings of histograms for measuring the degree of clustering that goes along with registration. With respect to computation time, the energy similarity measure is the function of choice for the registration of mask and contrast image prior to subtraction. The robustness of the energy measure is studied for geometrical image distortions like rotation and scaling. Additionally, it is investigated how the histogram binning and inhomogeneous motion inside the templates influence the quality of the similarity measure. Finally, the registration success for the automated procedure is compared with the manually shift-corrected image pair of the head.

  7. 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.

  8. [Curvelet denoising algorithm for medical ultrasound image based on adaptive threshold].

    PubMed

    Zhuang, Zhemin; Yao, Weike; Yang, Jinyao; Li, FenLan; Yuan, Ye

    2014-11-01

    The traditional denoising algorithm for ultrasound images would lost a lot of details and weak edge information when suppressing speckle noise. A new denoising algorithm of adaptive threshold based on curvelet transform is proposed in this paper. The algorithm utilizes differences of coefficients' local variance between texture and smooth region in each layer of ultrasound image to define fuzzy regions and membership functions. In the end, using the adaptive threshold that determine by the membership function to denoise the ultrasound image. The experimental text shows that the algorithm can reduce the speckle noise effectively and retain the detail information of original image at the same time, thus it can greatly enhance the performance of B ultrasound instrument.

  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 conductance filtering for spatially varying noise in PET images

    NASA Astrophysics Data System (ADS)

    Padfield, Dirk R.; Manjeshwar, Ravindra

    2006-03-01

    PET images that have been reconstructed with unregularized algorithms are commonly smoothed with linear Gaussian filters to control noise. Since these filters are spatially invariant, they degrade feature contrast in the image, compromising lesion detectability. Edge-preserving smoothing filters can differentially preserve edges and features while smoothing noise. These filters assume spatially uniform noise models. However, the noise in PET images is spatially variant, approximately following a Poisson behavior. Therefore, different regions of a PET image need smoothing by different amounts. In this work, we introduce an adaptive filter, based on anisotropic diffusion, designed specifically to overcome this problem. In this algorithm, the diffusion is varied according to a local estimate of the noise using either the local median or the grayscale image opening to weight the conductance parameter. The algorithm is thus tailored to the task of smoothing PET images, or any image with Poisson-like noise characteristics, by adapting itself to varying noise while preserving significant features in the image. This filter was compared with Gaussian smoothing and a representative anisotropic diffusion method using three quantitative task-relevant metrics calculated on simulated PET images with lesions in the lung and liver. The contrast gain and noise ratio metrics were used to measure the ability to do accurate quantitation; the Channelized Hotelling Observer lesion detectability index was used to quantify lesion detectability. The adaptive filter improved the signal-to-noise ratio by more than 45% and lesion detectability by more than 55% over the Gaussian filter while producing "natural" looking images and consistent image quality across different anatomical regions.

  11. Characterization of Diffraction-Enhanced Imaging

    SciTech Connect

    Kao, T.; Connor, D; Dilmanian, F; Faulconer, L; Liu, T; Parham, C; Pisano, E; Zhong, Z

    2009-01-01

    Diffraction-enhanced imaging (DEI) is a new x-ray imaging modality that has been shown to enhance contrast between normal and cancerous breast tissues. In this study, diffraction-enhanced imaging in computed tomography (DEI-CT) mode was used to quantitatively characterize the refraction contrasts of the organized structures associated with invasive human breast cancer. Using a high-sensitivity Si (3 3 3) reflection, the individual features of breast cancer, including masses, calcifications and spiculations, were observed. DEI-CT yields 14, 5 and 7 times higher CT numbers and 10, 9 and 6 times higher signal-to-noise ratios (SNR) for masses, calcifications and spiculations, respectively, as compared to conventional CT of the same specimen performed using the same detector, x-ray energy and dose. Furthermore, DEI-CT at ten times lower dose yields better SNR than conventional CT. In light of the recent development of a compact DEI prototype using an x-ray tube as its source, these results, acquired at a clinically relevant x-ray energy for which a pre-clinical DEI prototype currently exists, suggest the potential of clinical implementation of mammography with DEI-CT to provide high-contrast, high-resolution images of breast cancer (Parham 2006 PhD Dissertation University of North Carolina at Chapel Hill).

  12. 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.

  13. 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

  14. Fast HDR image upscaling using locally adapted linear filters

    NASA Astrophysics Data System (ADS)

    Talebi, Hossein; Su, Guan-Ming; Yin, Peng

    2015-02-01

    A new method for upscaling high dynamic range (HDR) images is introduced in this paper. Overshooting artifact is the common problem when using linear filters such as bicubic interpolation. This problem is visually more noticeable while working on HDR images where there exist more transitions from dark to bright. Our proposed method is capable of handling these artifacts by computing a simple gradient map which enables the filter to be locally adapted to the image content. This adaptation consists of first, clustering pixels into regions with similar edge structures and second, learning the shape and length of our symmetric linear filter for each of these pixel groups. This new filter can be implemented in a separable fashion which perfectly fits hardware implementations. Our experimental results show that training our filter with HDR images can effectively reduce the overshooting artifacts and improve upon the visual quality of the existing linear upscaling approaches.

  15. Adaptive colour transformation of retinal images for stroke prediction.

    PubMed

    Unnikrishnan, Premith; Aliahmad, Behzad; Kawasaki, Ryo; Kumar, Dinesh

    2013-01-01

    Identifying lesions in the retinal vasculature using Retinal imaging is most often done on the green channel. However, the effect of colour and single channel analysis on feature extraction has not yet been studied. In this paper an adaptive colour transformation has been investigated and validated on retinal images associated with 10-year stroke prediction, using principle component analysis (PCA). Histogram analysis indicated that while each colour channel image had a uni-modal distribution, the second component of the PCA had a bimodal distribution, and showed significantly improved separation between the retinal vasculature and the background. The experiments showed that using adaptive colour transformation, the sensitivity and specificity were both higher (AUC 0.73) compared with when single green channel was used (AUC 0.63) for the same database and image features.

  16. 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.

  17. 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.

  18. Stereoscopic adapter based system using HMD and image processing software for supporting inner ear operations performed using operating microscope

    NASA Astrophysics Data System (ADS)

    Leśniewski, Marcin; Kujawińska, Malgorzata; Kucharski, Tomasz; Niemczyk, Kazimierz

    2006-02-01

    Recently surgery requires extensive support from imaging technologies in order to increase effectiveness and safety of operations. One of important tasks is to enhance visualisation of quasi-phase (transparent) 3D structures. In this paper authors present a few of practical hardware solutions using of operational stereoscopic microscope with two image acquisition channels, stereoscopic adapter and Helmet Mounted Display (HMD) for stereoscopic visualization of operational field "in real time". Special attention is paid to the development of opto- mechanical unit. The authors focus on searching cheap, accurate and ergonomic solutions. A few proposals are analyzed: typical stereoscopic adapter with two image acquisition channels equipped with developed software for image low contrast enhancement for stereoscopic observation in stereoscopic HMD of operational field, visual - picture adapter (real operational view through microscope channels or processed operational field images observation in "real time").

  19. 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.

  20. Interpretation techniques. [image enhancement and pattern recognition

    NASA Technical Reports Server (NTRS)

    Dragg, J. L.

    1974-01-01

    The image enhancement and geometric correction and registration techniques developed and/or demonstrated on ERTS data are relatively mature and greatly enhance the utility of the data for a large variety of users. Pattern recognition was improved by the use of signature extension, feature extension, and other classification techniques. Many of these techniques need to be developed and generalized to become operationally useful. Advancements in the mass precision processing of ERTS were demonstrated, providing the hope for future earth resources data to be provided in a more readily usable state. Also in evidence is an increasing and healthy interaction between the techniques developers and the user/applications investigators.

  1. Image fusion for dynamic contrast enhanced magnetic resonance imaging

    PubMed Central

    Twellmann, Thorsten; Saalbach, Axel; Gerstung, Olaf; Leach, Martin O; Nattkemper, Tim W

    2004-01-01

    Background Multivariate imaging techniques such as dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) have been shown to provide valuable information for medical diagnosis. Even though these techniques provide new information, integrating and evaluating the much wider range of information is a challenging task for the human observer. This task may be assisted with the use of image fusion algorithms. Methods In this paper, image fusion based on Kernel Principal Component Analysis (KPCA) is proposed for the first time. It is demonstrated that a priori knowledge about the data domain can be easily incorporated into the parametrisation of the KPCA, leading to task-oriented visualisations of the multivariate data. The results of the fusion process are compared with those of the well-known and established standard linear Principal Component Analysis (PCA) by means of temporal sequences of 3D MRI volumes from six patients who took part in a breast cancer screening study. Results The PCA and KPCA algorithms are able to integrate information from a sequence of MRI volumes into informative gray value or colour images. By incorporating a priori knowledge, the fusion process can be automated and optimised in order to visualise suspicious lesions with high contrast to normal tissue. Conclusion Our machine learning based image fusion approach maps the full signal space of a temporal DCE-MRI sequence to a single meaningful visualisation with good tissue/lesion contrast and thus supports the radiologist during manual image evaluation. PMID:15494072

  2. An adaptive Kalman filter for ECG signal enhancement.

    PubMed

    Vullings, Rik; de Vries, Bert; Bergmans, Jan W M

    2011-04-01

    The ongoing trend of ECG monitoring techniques to become more ambulatory and less obtrusive generally comes at the expense of decreased signal quality. To enhance this quality, consecutive ECG complexes can be averaged triggered on the heartbeat, exploiting the quasi-periodicity of the ECG. However, this averaging constitutes a tradeoff between improvement of the SNR and loss of clinically relevant physiological signal dynamics. Using a bayesian framework, in this paper, a sequential averaging filter is developed that, in essence, adaptively varies the number of complexes included in the averaging based on the characteristics of the ECG signal. The filter has the form of an adaptive Kalman filter. The adaptive estimation of the process and measurement noise covariances is performed by maximizing the bayesian evidence function of the sequential ECG estimation and by exploiting the spatial correlation between several simultaneously recorded ECG signals, respectively. The noise covariance estimates thus obtained render the filter capable of ascribing more weight to newly arriving data when these data contain morphological variability, and of reducing this weight in cases of no morphological variability. The filter is evaluated by applying it to a variety of ECG signals. To gauge the relevance of the adaptive noise-covariance estimation, the performance of the filter is compared to that of a Kalman filter with fixed, (a posteriori) optimized noise covariance. This comparison demonstrates that, without using a priori knowledge on signal characteristics, the filter with adaptive noise estimation performs similar to the filter with optimized fixed noise covariance, favoring the adaptive filter in cases where no a priori information is available or where signal characteristics are expected to fluctuate.

  3. Adaptive lifting scheme of wavelet transforms for image compression

    NASA Astrophysics Data System (ADS)

    Wu, Yu; Wang, Guoyin; Nie, Neng

    2001-03-01

    Aiming at the demand of adaptive wavelet transforms via lifting, a three-stage lifting scheme (predict-update-adapt) is proposed according to common two-stage lifting scheme (predict-update) in this paper. The second stage is updating stage. The third is adaptive predicting stage. Our scheme is an update-then-predict scheme that can detect jumps in image from the updated data and it needs not any more additional information. The first stage is the key in our scheme. It is the interim of updating. Its coefficient can be adjusted to adapt to data to achieve a better result. In the adaptive predicting stage, we use symmetric prediction filters in the smooth area of image, while asymmetric prediction filters at the edge of jumps to reduce predicting errors. We design these filters using spatial method directly. The inherent relationships between the coefficients of the first stage and the other stages are found and presented by equations. Thus, the design result is a class of filters with coefficient that are no longer invariant. Simulation result of image coding with our scheme is good.

  4. Adaptive wavelet transform algorithm for lossy image compression

    NASA Astrophysics Data System (ADS)

    Pogrebnyak, Oleksiy B.; Ramirez, Pablo M.; Acevedo Mosqueda, Marco Antonio

    2004-11-01

    A new algorithm of locally adaptive wavelet transform based on the modified lifting scheme is presented. It performs an adaptation of the wavelet high-pass filter at the prediction stage to the local image data activity. The proposed algorithm uses the generalized framework for the lifting scheme that permits to obtain easily different wavelet filter coefficients in the case of the (~N, N) lifting. Changing wavelet filter order and different control parameters, one can obtain the desired filter frequency response. It is proposed to perform the hard switching between different wavelet lifting filter outputs according to the local data activity estimate. The proposed adaptive transform possesses a good energy compaction. The designed algorithm was tested on different images. The obtained simulation results show that the visual and quantitative quality of the restored images is high. The distortions are less in the vicinity of high spatial activity details comparing to the non-adaptive transform, which introduces ringing artifacts. The designed algorithm can be used for lossy image compression and in the noise suppression applications.

  5. 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.

  6. 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).

  7. 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.

  8. Range Imaging for Underwater Vision Enhancement

    SciTech Connect

    Rish, J.W.; Blume, B.; Nellums, B.; Sackos, J.; Foster, J.; Wood, J.L.

    1999-04-19

    This paper presents results from a series of preliminary tests to evaluate a scannerless range-imaging device as a potential sensory enhancement tool for divers and as a potential identification sensor for deployment on small unmanned underwater vehicles. The device, developed by Sandia National Laboratories, forms an image on the basis of point-to-point range to the target rather than an intensity map. The range image is constructed through a classical continuous wave phase detection technique in which the light source is amplitude modulated at radio frequencies. The receiver incorporates a gain-modulated image intensifier, and range information is calculated on the basis of the phase difference between the transmitted and reflected signal. The initial feasibility test at the Coastal Systems Station showed the device to be effective at imaging low-contrast underwater targets such as concertina wire. It also demonstrated success at imaging a 21-inch sphere at a depth of 10 feet in the water column through a wavy air-water interface.

  9. The simulation of adaptive optical image even and pulse noise and research of image quality evaluation

    NASA Astrophysics Data System (ADS)

    Wen, Changli; Xu, Yuannan; Xu, Rong; Liu, Changhai; Men, Tao; Niu, Wei

    2013-09-01

    As optical image becomes more and more important in adaptive optics area, and adaptive optical telescopes play a more and more important role in the detection system on the ground, and the images we get are so many that we need find a suitable method to choose good quality images automatically in order to save human power, people pay more and more attention in image's evaluation methods and their characteristics. According to different image degradation model, the applicability of different image's quality evaluation method will be different. Researchers have paid most attention in how to improve or build new method to evaluate degraded images. Now we should change our way to take some research in the models of degradation of images, the reasons of image degradation, and the relations among different degraded images and different image quality evaluation methods. In this paper, we build models of even noise and pulse noise based on their definition and get degraded images using these models, and we take research in six kinds of usual image quality evaluation methods such as square error method, sum of multi-power of grey scale method, entropy method, Fisher function method, Sobel method, and sum of grads method, and we make computer software for these methods to use easily to evaluate all kinds of images input. Then we evaluate the images' qualities with different evaluation methods and analyze the results of six kinds of methods, and finally we get many important results. Such as the characteristics of every method for evaluating qualities of degraded images of even noise, the characteristics of every method for evaluating qualities of degraded images of pulse noise, and the best method to evaluate images which affected by tow kinds of noise both and the characteristics of this method. These results are important to image's choosing automatically, and this will help we to manage the images we get through adaptive optical telescopes base on the ground.

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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.

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

    PubMed Central

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

    2012-01-01

    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. PMID:22312577

  16. 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

  17. Adaptive image coding based on cubic-spline interpolation

    NASA Astrophysics Data System (ADS)

    Jiang, Jian-Xing; Hong, Shao-Hua; Lin, Tsung-Ching; Wang, Lin; Truong, Trieu-Kien

    2014-09-01

    It has been investigated that at low bit rates, downsampling prior to coding and upsampling after decoding can achieve better compression performance than standard coding algorithms, e.g., JPEG and H. 264/AVC. However, at high bit rates, the sampling-based schemes generate more distortion. Additionally, the maximum bit rate for the sampling-based scheme to outperform the standard algorithm is image-dependent. In this paper, a practical adaptive image coding algorithm based on the cubic-spline interpolation (CSI) is proposed. This proposed algorithm adaptively selects the image coding method from CSI-based modified JPEG and standard JPEG under a given target bit rate utilizing the so called ρ-domain analysis. The experimental results indicate that compared with the standard JPEG, the proposed algorithm can show better performance at low bit rates and maintain the same performance at high bit rates.

  18. 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

  19. Wavelet domain image restoration with adaptive edge-preserving regularization.

    PubMed

    Belge, M; Kilmer, M E; Miller, E L

    2000-01-01

    In this paper, we consider a wavelet based edge-preserving regularization scheme for use in linear image restoration problems. Our efforts build on a collection of mathematical results indicating that wavelets are especially useful for representing functions that contain discontinuities (i.e., edges in two dimensions or jumps in one dimension). We interpret the resulting theory in a statistical signal processing framework and obtain a highly flexible framework for adapting the degree of regularization to the local structure of the underlying image. In particular, we are able to adapt quite easily to scale-varying and orientation-varying features in the image while simultaneously retaining the edge preservation properties of the regularizer. We demonstrate a half-quadratic algorithm for obtaining the restorations from observed data.

  20. An adaptive multi-feature segmentation model for infrared image

    NASA Astrophysics Data System (ADS)

    Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

    2016-04-01

    Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    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.

  3. Normalized iterative denoising ghost imaging based on the adaptive threshold

    NASA Astrophysics Data System (ADS)

    Li, Gaoliang; Yang, Zhaohua; Zhao, Yan; Yan, Ruitao; Liu, Xia; Liu, Baolei

    2017-02-01

    An approach for improving ghost imaging (GI) quality is proposed. In this paper, an iteration model based on normalized GI is built through theoretical analysis. An adaptive threshold value is selected in the iteration model. The initial value of the iteration model is estimated as a step to remove the correlated noise. The simulation and experimental results reveal that the proposed strategy reconstructs a better image than traditional and normalized GI, without adding complexity. The NIDGI-AT scheme does not require prior information regarding the object, and can also choose the threshold adaptively. More importantly, the signal-to-noise ratio (SNR) of the reconstructed image is greatly improved. Therefore, this methodology represents another step towards practical real-world applications.

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

    PubMed Central

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

    2015-01-01

    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. PMID:25909024

  5. 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.

  6. Adaptive wavelet transform algorithm for image compression applications

    NASA Astrophysics Data System (ADS)

    Pogrebnyak, Oleksiy B.; Manrique Ramirez, Pablo

    2003-11-01

    A new algorithm of locally adaptive wavelet transform is presented. The algorithm implements the integer-to-integer lifting scheme. It performs an adaptation of the wavelet function at the prediction stage to the local image data activity. The proposed algorithm is based on the generalized framework for the lifting scheme that permits to obtain easily different wavelet coefficients in the case of the (N~,N) lifting. It is proposed to perform the hard switching between (2, 4) and (4, 4) lifting filter outputs according to an estimate of the local data activity. When the data activity is high, i.e., in the vicinity of edges, the (4, 4) lifting is performed. Otherwise, in the plain areas, the (2,4) decomposition coefficients are calculated. The calculations are rather simples that permit the implementation of the designed algorithm in fixed point DSP processors. The proposed adaptive transform possesses the perfect restoration of the processed data and possesses good energy compactation. The designed algorithm was tested on different images. The proposed adaptive transform algorithm can be used for image/signal lossless compression.

  7. 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.

  8. 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.

  9. 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.

  10. Enhanced damage characterization using wavefield imaging methods

    NASA Astrophysics Data System (ADS)

    Blackshire, James L.

    2017-02-01

    Wavefield imaging methods are becoming a popular tool for characterizing and studying elastic field interactions in a wide variety of material systems. By using a scanning laser vibrometry detection system, the transient displacement fields generated by an ultrasonic source can be visualized and studied in detail. As a tool for quantitative nondestructive evaluation, the visualization of elastic waves provides a unique opportunity for understanding the scattering of elastic waves from insipient damage, where the detection and characterization of damage features using ultrasound can be enhanced in many instances. In the present effort, the detection and direct imaging of fatigue cracks in metals, and delaminations in composites, is described. An examination of the transient displacement fields near the scattering sites show additional details related to the local damage morphology, which can be difficult to account for using traditional far-field NDE sensing methods. A combination of forward models and experimental wavefield imaging methods were used to explore enhancement opportunities for the full 3-dimensional characterization of surface-breaking cracks and delaminations.

  11. Raster image adaptation for mobile devices using profiles

    NASA Astrophysics Data System (ADS)

    Rosenbaum, René; Hamann, Bernd

    2012-02-01

    Focusing on digital imagery, this paper introduces a strategy to handle heterogeneous hardware in mobile environments. Constrained system resources of most mobile viewing devices require contents that are tailored to the requirements of the user and the capabilities of the device. Appropriate image adaptation is still an unsolved research question. Due to the complexity of the problem, available solutions are either too resource-intensive or inflexible to be more generally applicable. The proposed approach is based on scalable image compression and progressive refinement as well as data and user profiles. A scalable image is created once and used multiple times for different kinds of devices and user requirements. Profiles available on the server side allow for an image representation that is adapted to the most important resources in mobile computing: screen space, computing power, and the volume of the transmitted data. Options for progressively refining content thereby allow for a fluent viewing experience during adaptation. Due to its flexibility and low complexity, the proposed solution is much more general compared to related approaches. To document the advantages of our approach we provide empirical results obtained in experiments with an implementation of the method.

  12. 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.

  13. Enhanced adaptive loop filter for motion compensated frame.

    PubMed

    Yoo, Young-Joe; Seo, Chan-Won; Han, Jong-Ki; Nguyen, Truong Q

    2011-08-01

    We propose an adaptive loop filter to remove the redundancy between current and motion compensated frames so that the residual signal is minimized, thus coding efficiency increases. The loop filter coefficients and offset are optimized for each frame or a set of blocks to minimize the total energy of the residual signal resulting from motion estimation and compensation. The optimized loop filter with offset is applied for the set of blocks where the filtering process gives coding gain based upon rate-distortion cost. The proposed loop filter is used for the motion compensated frame whereas the conventional adaptive interpolation filter (AIF) is applied to the reference frames to interpolate the subpixel values. Another conventional scheme adaptive loop filter (ALF), is used after deblocking filtering to enhance quality of reconstructed frames, not to minimize energy of residual signal. The proposed loop filter can be used in combination with the AIF and ALF. Experimental results show that proposed algorithm provides the averaged bit reduction of 8% compared to conventional H.264/AVC scheme. When the proposed scheme is combined with AIF and ALF, the coding gain increases even further.

  14. Supersampling multiframe blind deconvolution resolution enhancement of adaptive-optics-compensated imagery of LEO satellites

    NASA Astrophysics Data System (ADS)

    Gerwe, David R.; Lee, David J.; Barchers, Jeffrey D.

    2000-10-01

    A post-processing methodology for reconstructing undersampled image sequences with randomly varying blur is described which can provide image enhancement beyond the sampling resolution of the sensor. This method is demonstrated on simulated imagery and on adaptive optics compensated imagery taken by the Starfire Optical Range 3.5 meter telescope that has been artificially undersampled. Also shown are the results of multiframe blind deconvolution of some of the highest quality optical imagery of low earth orbit satellites collected with a ground based telescope to date. The algorithm used is a generalization of multiframe blind deconvolution techniques which includes a representation of spatial sampling by the focal plane array elements in the forward stochastic model of the imaging system. This generalization enables the random shifts and shape of the adaptive compensated PSF to be used to partially eliminate the aliasing effects associated with sub- Nyquist sampling of the image by the focal plane array. The method could be used to reduce resolution loss which occurs when imaging in wide FOV modes.

  15. 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.

  16. 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.

  17. An adaptive optics imaging system designed for clinical use

    PubMed Central

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

    2015-01-01

    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

  18. Adaptive multispectral image processing for the detection of targets in terrain clutter

    NASA Astrophysics Data System (ADS)

    Hoff, Lawrence E.; Zeidler, James R.; Yerkes, Christopher R.

    1992-08-01

    In passive detection of small infrared targets in image data, we are faced with the difficult task of enhancing some characteristic of the target or signal while suppressing the clutter or background image noise. We reported that an effective means by which targets may be identified is to exploit characteristics which exist between scenes measured in different bands in the long wave infrared region of the electromagnetic spectrum. These methods are broadly termed multispectral techniques. In this paper we present a method by which a two- dimensional least-mean square adaptive filter is used to distinguish between target and clutter using multispectral techniques.

  19. 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.

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

    PubMed

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

    2014-03-21

    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.

  1. Image segmentation on adaptive edge-preserving smoothing

    NASA Astrophysics Data System (ADS)

    He, Kun; Wang, Dan; Zheng, Xiuqing

    2016-09-01

    Nowadays, typical active contour models are widely applied in image segmentation. However, they perform badly on real images with inhomogeneous subregions. In order to overcome the drawback, this paper proposes an edge-preserving smoothing image segmentation algorithm. At first, this paper analyzes the edge-preserving smoothing conditions for image segmentation and constructs an edge-preserving smoothing model inspired by total variation. The proposed model has the ability to smooth inhomogeneous subregions and preserve edges. Then, a kind of clustering algorithm, which reasonably trades off edge-preserving and subregion-smoothing according to the local information, is employed to learn the edge-preserving parameter adaptively. At last, according to the confidence level of segmentation subregions, this paper constructs a smoothing convergence condition to avoid oversmoothing. Experiments indicate that the proposed algorithm has superior performance in precision, recall, and F-measure compared with other segmentation algorithms, and it is insensitive to noise and inhomogeneous-regions.

  2. Multiwavelength adaptive optical fundus camera and continuous retinal imaging

    NASA Astrophysics Data System (ADS)

    Yang, Han-sheng; Li, Min; Dai, Yun; Zhang, Yu-dong

    2009-08-01

    We have constructed a new version of retinal imaging system with chromatic aberration concerned and the correlated optical design presented in this article is based on the adaptive optics fundus camera modality. In our system, three typical wavelengths of 550nm, 650nm and 480nm were selected. Longitude chromatic aberration (LCA) was traded off to a minimum using ZEMAX program. The whole setup was actually evaluated on human subjects and retinal imaging was performed at continuous frame rates up to 20 Hz. Raw videos at parafovea locations were collected, and cone mosaics as well as retinal vasculature were clearly observed in one single clip. In addition, comparisons under different illumination conditions were also made to confirm our design. Image contrast and the Strehl ratio were effectively increased after dynamic correction of high order aberrations. This system is expected to bring new applications in functional imaging of human retina.

  3. Studies of an Adaptive Kaczmarz Method for Electrical Impedance Imaging

    NASA Astrophysics Data System (ADS)

    Li, Taoran; Isaacson, David; Newell, Jonathan C.; Saulnier, Gary J.

    2013-04-01

    We present an adaptive Kaczmarz method for solving the inverse problem in electrical impedance tomography and determining the conductivity distribution inside an object from electrical measurements made on the surface. To best characterize an unknown conductivity distribution and avoid inverting the Jacobian-related term JTJ which could be expensive in terms of memory storage in large scale problems, we propose to solve the inverse problem by adaptively updating both the optimal current pattern with improved distinguishability and the conductivity estimate at each iteration. With a novel subset scheme, the memory-efficient reconstruction algorithm which appropriately combines the optimal current pattern generation and the Kaczmarz method can produce accurate and stable solutions adaptively compared to traditional Kaczmarz and Gauss-Newton type methods. Several reconstruction image metrics are used to quantitatively evaluate the performance of the simulation results.

  4. Image compression with QM-AYA adaptive binary arithmetic coder

    NASA Astrophysics Data System (ADS)

    Cheng, Joe-Ming; Langdon, Glen G., Jr.

    1993-01-01

    The Q-coder has been reported in the literature, and is a renorm-driven binary adaptive arithmetic coder. A similar renorm-driven coder, the QM coder, uses the same approach with an initial attack to more rapidly estimate the statistics in the beginning, and with a different state table. The QM coder is the adaptive binary arithmetic coder employed in the JBIG and JPEG image compression algorithms. The QM-AYA arithmetic coder is similar to the QM coder, with a different state table, that offers balanced improvements to the QM probability estimation for the less skewed distributions. The QM-AYA performs better when the probability estimate is near 0.5 for each binary symbol. An approach for constructing effective index change tables for Q-coder type adaptation is discussed.

  5. Shape-adaptable hyperlens for acoustic magnifying imaging

    NASA Astrophysics Data System (ADS)

    Zhang, Hongkuan; Zhou, Xiaoming; Hu, Gengkai

    2016-11-01

    Previous prototypes of acoustic hyperlens consist of rigid channels, which are unable to adapt in shape to the object under detection. We propose to overcome this limitation by employing soft plastic tubes that could guide acoustics with robustness against bending deformation. Based on the idea of soft-tube acoustics, acoustic magnifying hyperlens with planar input and output surfaces has been fabricated and validated experimentally. The shape-adaption capability of the soft-tube hyperlens is demonstrated by a controlled experiment, in which the magnifying super-resolution images remain stable when the lens input surface is curved. Our study suggests a feasible route toward constructing the flexible channel-structured acoustic metamaterials with the shape-adaption capability, opening then an additional degree of freedom for full control of sound.

  6. 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.

  7. A novel adaptive noise filtering method for SAR images

    NASA Astrophysics Data System (ADS)

    Li, Weibin; He, Mingyi

    2009-08-01

    In the most application situation, signal or image always is corrupted by additive noise. As a result there are mass methods to remove the additive noise while few approaches can work well for the multiplicative noise. The paper presents an improved MAP-based filter for multiplicative noise by adaptive window denoising technique. A Gamma noise models is discussed and a preprocessing technique to differential the matured and un-matured pixel is applied to get accurate estimate for Equivalent Number of Looks. Also the adaptive local window growth and 3 different denoise strategies are applied to smooth noise while keep its subtle information according to its local statistics feature. The simulation results show that the performance is better than existing filter. Several image experiments demonstrate its theoretical performance.

  8. Adaptive noise Wiener filter for scanning electron microscope imaging system.

    PubMed

    Sim, K S; Teh, V; Nia, M E

    2016-01-01

    Noise on scanning electron microscope (SEM) images is studied. Gaussian noise is the most common type of noise in SEM image. We developed a new noise reduction filter based on the Wiener filter. We compared the performance of this new filter namely adaptive noise Wiener (ANW) filter, with four common existing filters as well as average filter, median filter, Gaussian smoothing filter and the Wiener filter. Based on the experiments results the proposed new filter has better performance on different noise variance comparing to the other existing noise removal filters in the experiments.

  9. Adaptive zero-tree structure for curved wavelet image coding

    NASA Astrophysics Data System (ADS)

    Zhang, Liang; Wang, Demin; Vincent, André

    2006-02-01

    We investigate the issue of efficient data organization and representation of the curved wavelet coefficients [curved wavelet transform (WT)]. We present an adaptive zero-tree structure that exploits the cross-subband similarity of the curved wavelet transform. In the embedded zero-tree wavelet (EZW) and the set partitioning in hierarchical trees (SPIHT), the parent-child relationship is defined in such a way that a parent has four children, restricted to a square of 2×2 pixels, the parent-child relationship in the adaptive zero-tree structure varies according to the curves along which the curved WT is performed. Five child patterns were determined based on different combinations of curve orientation. A new image coder was then developed based on this adaptive zero-tree structure and the set-partitioning technique. Experimental results using synthetic and natural images showed the effectiveness of the proposed adaptive zero-tree structure for encoding of the curved wavelet coefficients. The coding gain of the proposed coder can be up to 1.2 dB in terms of peak SNR (PSNR) compared to the SPIHT coder. Subjective evaluation shows that the proposed coder preserves lines and edges better than the SPIHT coder.

  10. 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.

  11. Dynamic optical aberration correction with adaptive coded apertures techniques in conformal imaging

    NASA Astrophysics Data System (ADS)

    Li, Yan; Hu, Bin; Zhang, Pengbin; Zhang, Binglong

    2015-02-01

    Conformal imaging systems are confronted with dynamic aberration in optical design processing. In classical optical designs, for combination high requirements of field of view, optical speed, environmental adaption and imaging quality, further enhancements can be achieved only by the introduction of increased complexity of aberration corrector. In recent years of computational imaging, the adaptive coded apertures techniques which has several potential advantages over more traditional optical systems is particularly suitable for military infrared imaging systems. The merits of this new concept include low mass, volume and moments of inertia, potentially lower costs, graceful failure modes, steerable fields of regard with no macroscopic moving parts. Example application for conformal imaging system design where the elements of a set of binary coded aperture masks are applied are optimization designed is presented in this paper, simulation results show that the optical performance is closely related to the mask design and the reconstruction algorithm optimization. As a dynamic aberration corrector, a binary-amplitude mask located at the aperture stop is optimized to mitigate dynamic optical aberrations when the field of regard changes and allow sufficient information to be recorded by the detector for the recovery of a sharp image using digital image restoration in conformal optical system.

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

    PubMed

    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.

  13. 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

  14. Adaptive fusion of infrared and visible images in dynamic scene

    NASA Astrophysics Data System (ADS)

    Yang, Guang; Yin, Yafeng; Man, Hong; Desai, Sachi

    2011-11-01

    Multiple modalities sensor fusion has been widely employed in various surveillance and military applications. A variety of image fusion techniques including PCA, wavelet, curvelet and HSV has been proposed in recent years to improve human visual perception for object detection. One of the main challenges for visible and infrared image fusion is to automatically determine an optimal fusion strategy for different input scenes along with an acceptable computational cost. This paper, we propose a fast and adaptive feature selection based image fusion method to obtain high a contrast image from visible and infrared sensors for targets detection. At first, fuzzy c-means clustering is applied on the infrared image to highlight possible hotspot regions, which will be considered as potential targets' locations. After that, the region surrounding the target area is segmented as the background regions. Then image fusion is locally applied on the selected target and background regions by computing different linear combination of color components from registered visible and infrared images. After obtaining different fused images, histogram distributions are computed on these local fusion images as the fusion feature set. The variance ratio which is based on Linear Discriminative Analysis (LDA) measure is employed to sort the feature set and the most discriminative one is selected for the whole image fusion. As the feature selection is performed over time, the process will dynamically determine the most suitable feature for the image fusion in different scenes. Experiment is conducted on the OSU Color-Thermal database, and TNO Human Factor dataset. The fusion results indicate that our proposed method achieved a competitive performance compared with other fusion algorithms at a relatively low computational cost.

  15. Adaptive Nonlocal Sparse Representation for Dual-Camera Compressive Hyperspectral Imaging.

    PubMed

    Wang, Lizhi; Xiong, Zhiwei; Shi, Guangming; Wu, Feng; Zeng, Wenjun

    2016-10-25

    Leveraging the compressive sensing (CS) theory, coded aperture snapshot spectral imaging (CASSI) provides an efficient solution to recover 3D hyperspectral data from a 2D measurement. The dual-camera design of CASSI, by adding an uncoded panchromatic measurement, enhances the reconstruction fidelity while maintaining the snapshot advantage. In this paper, we propose an adaptive nonlocal sparse representation (ANSR) model to boost the performance of dualcamera compressive hyperspectral imaging (DCCHI). Specifically, the CS reconstruction problem is formulated as a 3D cube based sparse representation to make full use of the nonlocal similarity in both the spatial and spectral domains. Our key observation is that, the panchromatic image, besides playing the role of direct measurement, can be further exploited to help the nonlocal similarity estimation. Therefore, we design a joint similarity metric by adaptively combining the internal similarity within the reconstructed hyperspectral image and the external similarity within the panchromatic image. In this way, the fidelity of CS reconstruction is greatly enhanced. Both simulation and hardware experimental results show significant improvement of the proposed method over the state-of-the-art.

  16. 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.

  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. 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

  19. 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.

  20. 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

  1. An adaptive Gaussian model for satellite image deblurring.

    PubMed

    Jalobeanu, André; Blanc-Féraud, Laure; Zerubia, Josiane

    2004-04-01

    The deconvolution of blurred and noisy satellite images is an ill-posed inverse problem, which can be regularized within a Bayesian context by using an a priori model of the reconstructed solution. Since real satellite data show spatially variant characteristics, we propose here to use an inhomogeneous model. We use the maximum likelihood estimator (MLE) to estimate its parameters and we show that the MLE computed on the corrupted image is not suitable for image deconvolution because it is not robust to noise. We then show that the estimation is correct only if it is made from the original image. Since this image is unknown, we need to compute an approximation of sufficiently good quality to provide useful estimation results. Such an approximation is provided by a wavelet-based deconvolution algorithm. Thus, a hybrid method is first used to estimate the space-variant parameters from this image and then to compute the regularized solution. The obtained results on high resolution satellite images simultaneously exhibit sharp edges, correctly restored textures, and a high SNR in homogeneous areas, since the proposed technique adapts to the local characteristics of the data.

  2. 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.

  3. Adaptive SPECT imaging with crossed-slit apertures

    NASA Astrophysics Data System (ADS)

    Durko, Heather L.; Furenlid, Lars R.

    2014-09-01

    Preclinical single-photon emission computed tomography (SPECT) is an essential tool for studying the pro-gression, 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.

  4. 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.

  5. 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

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

    PubMed

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

    2016-10-17

    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.

  7. 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.

  8. Enhanced live cell imaging via photonic crystal enhanced fluorescence microscopy.

    PubMed

    Chen, Weili; Long, Kenneth D; Yu, Hojeong; Tan, Yafang; Choi, Ji Sun; Harley, Brendan A; Cunningham, Brian T

    2014-11-21

    We demonstrate photonic crystal enhanced fluorescence (PCEF) microscopy as a surface-specific fluorescence imaging technique to study the adhesion of live cells by visualizing variations in cell-substrate gap distance. This approach utilizes a photonic crystal surface incorporated into a standard microscope slide as the substrate for cell adhesion, and a microscope integrated with a custom illumination source as the detection instrument. When illuminated with a monochromatic light source, angle-specific optical resonances supported by the photonic crystal enable efficient excitation of surface-confined and amplified electromagnetic fields when excited at an on-resonance condition, while no field enhancement occurs when the same photonic crystal is illuminated in an off-resonance state. By mapping the fluorescence enhancement factor for fluorophore-tagged cellular components between on- and off-resonance states and comparing the results to numerical calculations, the vertical distance of labelled cellular components from the photonic crystal substrate can be estimated, providing critical and quantitative information regarding the spatial distribution of the specific components of cells attaching to a surface. As an initial demonstration of the concept, 3T3 fibroblast cells were grown on fibronectin-coated photonic crystals with fluorophore-labelled plasma membrane or nucleus. We demonstrate that PCEF microscopy is capable of providing information about the spatial distribution of cell-surface interactions at the single-cell level that is not available from other existing forms of microscopy, and that the approach is amenable to large fields of view, without the need for coupling prisms, coupling fluids, or special microscope objectives.

  9. Enhanced live cell imaging via photonic crystal enhanced fluorescence microscopy†

    PubMed Central

    Chen, Weili; Long, Kenneth D.; Yu, Hojeong; Tan, Yafang; Choi, Ji Sun; Harley, Brendan A.; Cunningham, Brian T.

    2014-01-01

    We demonstrate photonic crystal enhanced fluorescence (PCEF) microscopy as a surface-specific fluorescence imaging technique to study the adhesion of live cells by visualizing variations in cell-substrate gap distance. This approach utilizes a photonic crystal surface incorporated into a standard microscope slide as the substrate for cell adhesion, and a microscope integrated with a custom illumination source as the detection instrument. When illuminated with a monochromatic light source, angle-specific optical resonances supported by the photonic crystal enable efficient excitation of surface-confined and amplified electromagnetic fields when excited at an on-resonance condition, while no field enhancement occurs when the same photonic crystal is illuminated in an off-resonance state. By mapping the fluorescence enhancement factor for fluorophore-tagged cellular components between on- and off-resonance states and comparing the results to numerical calculations, the vertical distance of labelled cellular components from the photonic crystal substrate can be estimated, providing critical and quantitative information regarding the spatial distribution of the specific components of cells attaching to a surface. As an initial demonstration of the concept, 3T3 fibroblast cells were grown on fibronectin-coated photonic crystals with fluorophore-labelled plasma membrane or nucleus. We demonstrate that PCEF microscopy is capable of providing information about the spatial distribution of cell-surface interactions at the single-cell level that is not available from other existing forms of microscopy, and that the approach is amenable to large fields of view, without the need for coupling prisms, coupling fluids, or special microscope objectives. PMID:25265458

  10. 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.

  11. 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.

  12. Optical contrast enhancement of high-resolution ocular fundus imaging in vivo using polarimetry

    NASA Astrophysics Data System (ADS)

    Yang, Hansheng; Rao, Xuejun; Zhang, Yudong

    2007-11-01

    The adaptive optics (AO) retina imaging was performed with contrast enhancement by characterizing polarization parameters of the living retina. A removable pair of polarization state generating unit near the optical source and analysis unit near the CCD camera was incorporated into the basic 37-channle deformable mirror AO microscopic ophthalmoscope. Double-pass imaging polarimetry of the human eye was carried out, then incomplete Mueller matrix was calculated and analyzed to optimize the retina imaging condition using polarized light, which caused the subretinal structures with different polarization properties to emerge from the scattering light background, so the contrast of the image can be substantially enhanced. This method is demonstrated briefly and its validity was tested in the laboratory. The high-resolution images of ocular fundus are compared with 8-frame-averaging images we obtained prior to this method. The experiment results now show improved visualization of fundus structures to some extent without greatly sacrificing image resolution.

  13. 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.

  14. 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.

  15. Adaptively wavelet-based image denoising algorithm with edge preserving

    NASA Astrophysics Data System (ADS)

    Tan, Yihua; Tian, Jinwen; Liu, Jian

    2006-02-01

    A new wavelet-based image denoising algorithm, which exploits the edge information hidden in the corrupted image, is presented. Firstly, a canny-like edge detector identifies the edges in each subband. Secondly, multiplying the wavelet coefficients in neighboring scales is implemented to suppress the noise while magnifying the edge information, and the result is utilized to exclude the fake edges. The isolated edge pixel is also identified as noise. Unlike the thresholding method, after that we use local window filter in the wavelet domain to remove noise in which the variance estimation is elaborated to utilize the edge information. This method is adaptive to local image details, and can achieve better performance than the methods of state of the art.

  16. 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).

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. Adaptive coded aperture imaging: progress and potential future applications

    NASA Astrophysics Data System (ADS)

    Gottesman, Stephen R.; Isser, Abraham; Gigioli, George W., Jr.

    2011-09-01

    Interest in Adaptive Coded Aperture Imaging (ACAI) continues to grow as the optical and systems engineering community becomes increasingly aware of ACAI's potential benefits in the design and performance of both imaging and non-imaging systems , such as good angular resolution (IFOV), wide distortion-free field of view (FOV), excellent image quality, and light weight construct. In this presentation we first review the accomplishments made over the past five years, then expand on previously published work to show how replacement of conventional imaging optics with coded apertures can lead to a reduction in system size and weight. We also present a trade space analysis of key design parameters of coded apertures and review potential applications as replacement for traditional imaging optics. Results will be presented, based on last year's work of our investigation into the trade space of IFOV, resolution, effective focal length, and wavelength of incident radiation for coded aperture architectures. Finally we discuss the potential application of coded apertures for replacing objective lenses of night vision goggles (NVGs).

  2. A level crossing enhancement scheme for chest radiograph images.

    PubMed

    Nagesha; Kumar, G Hemantha

    2007-10-01

    A new approach for contrast enhancement of chest radiograph image data is presented. Existing methods for image enhancement focus mainly on the properties of the image to be processed while excluding any consideration of the observer characteristics. In several applications, particularly in the medical imaging area, effective contrast enhancement for diagnostic purposes can be achieved by including certain basic human visual properties. In this paper we shall present a novel (recursive) algorithm that tailors the required amount of contrast enhancement based on a combination of the optimal phase representation and the theory of projection onto a convex set. Constraints of maximum bandwidth of the image data, appropriate knowledge of the amplitude value of the image data, heuristic limitations and level crossing measurements serve to impose additional information. So that, the enhanced image data may better converge to the good quality image.

  3. HDR Pathological Image Enhancement Based on Improved Bias Field Correction and Guided Image Filter

    PubMed Central

    Zhu, Ganzheng; Li, Siqi; Gong, Shang; Yang, Benqiang; Zhang, Libo

    2016-01-01

    Pathological image enhancement is a significant topic in the field of pathological image processing. This paper proposes a high dynamic range (HDR) pathological image enhancement method based on improved bias field correction and guided image filter (GIF). Firstly, a preprocessing including stain normalization and wavelet denoising is performed for Haematoxylin and Eosin (H and E) stained pathological image. Then, an improved bias field correction model is developed to enhance the influence of light for high-frequency part in image and correct the intensity inhomogeneity and detail discontinuity of image. Next, HDR pathological image is generated based on least square method using low dynamic range (LDR) image, H and E channel images. Finally, the fine enhanced image is acquired after the detail enhancement process. Experiments with 140 pathological images demonstrate the performance advantages of our proposed method as compared with related work. PMID:28116303

  4. 2-micron Adaptive Optics Images of Titan from the W.M. Keck Telescope

    NASA Astrophysics Data System (ADS)

    Gibbard, S. G.; Macintosh, B. A.; Max, C. E.; de Pater, I.; Roe, H. G.; Marchis, F.

    2001-12-01

    Saturn's largest moon Titan is the only satellite in the solar system with a substantial atmosphere, which consists mainly of nitrogen and a few percent methane. Photolysis of methane creates a hydrocarbon haze in Titan's atmosphere that is opaque to visible light. However, in the infrared there are `windows' between methane absorption bands in which the surface of Titan can be imaged. We have observed Titan over the period of 1999-2001 using the adaptive optics system on the 10-meter W.M. Keck Telescope. Using adaptive optics allows us to observe Titan with a resolution of 0.04 arcseconds, or approximately 20 resolution elements across the satellite's disk. We will report on adaptive optics images of Titan taken in 1999-2001 at K band (1.95-2.29 microns). The images are enhanced by application of the MISTRAL iterative image deconvolution routine. Using this data combined with atmospheric modeling, we are able to determine Titan's surface albedo at this wavelength and properties of its hydrocarbon haze layer. This research was supported in part by the STC Program of the National Science Foundation under Agreement No. AST-9876783, and in part under the auspices of the US Department of Energy at Lawrence Livermore National Laboratory, Univ. of Calif. under contract No. W-7405-Eng-48.

  5. Feature-Enhanced, Model-Based Sparse Aperture Imaging

    DTIC Science & Technology

    2008-03-01

    imaging, anisotropy characterization, feature-enhanced imaging, inverse problems, superresolution , anisotropy, sparse signal representation, overcomplete...number of such activities ourselves, and we provide very brief information on some of them here. We have developed a superresolution technique for...enhanced, superresolution image reconstruction. This framework provides a number of desirable features including preservation of anisotropic scatterers

  6. 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.

  7. Wavelet-Based Speech Enhancement Using Time-Frequency Adaptation

    NASA Astrophysics Data System (ADS)

    Wang, Kun-Ching

    2003-12-01

    Wavelet denoising is commonly used for speech enhancement because of the simplicity of its implementation. However, the conventional methods generate the presence of musical residual noise while thresholding the background noise. The unvoiced components of speech are often eliminated from this method. In this paper, a novel algorithm of wavelet coefficient threshold (WCT) based on time-frequency adaptation is proposed. In addition, an unvoiced speech enhancement algorithm is also integrated into the system to improve the intelligibility of speech. The wavelet coefficient threshold (WCT) of each subband is first temporally adjusted according to the value of a posterior signal-to-noise ratio (SNR). To prevent the degradation of unvoiced sounds during noise, the algorithm utilizes a simple speech/noise detector (SND) and further divides speech signal into unvoiced and voiced sounds. Then, we apply appropriate wavelet thresholding according to voiced/unvoiced (V/U) decision. Based on the masking properties of human auditory system, a perceptual gain factor is adopted into wavelet thresholding for suppressing musical residual noise. Simulation results show that the proposed method is capable of reducing noise with little speech degradation and the overall performance is superior to several competitive methods.

  8. Adaptive link-layer intelligence for enhanced ad hoc networking

    NASA Astrophysics Data System (ADS)

    MacLennan, James; Walburg, Bill; Nevins, Larry; Hartup, David

    2005-05-01

    Networked radio systems that utilize self-forming, fault tolerant techniques offer needed communication functions for Homeland Security and Law Enforcement agencies. The use of an ad hoc mesh network architecture solves some of the problems inherent to the wireless physical layer such as interferers, multi-path fading, shadowing, and loss of line-of-site. These effects severely limit the performance of current 802.11 wireless network implementations. This paper describes the use of Adaptive Link-layer Intelligence for Enhanced ad hoc Networking. This technology enhances recognition and characterization of sources of wireless channel perturbations and predicts their effects on wireless link quality. Identifying and predicting channel problems at the link level improves dynamic route discovery, circumvents channel disruptions before they cause a link failure, and increases communications reliability and data rate. First Responders, Homeland Security, and Law Enforcement agencies operating in locations lacking infrastructure, such as Urban Search and Rescue (USAR) operations, can benefit from increased communications reliability in highly impaired channels that are typical in disaster response scenarios.

  9. Design and FPGA implementation of real-time automatic image enhancement algorithm

    NASA Astrophysics Data System (ADS)

    Dong, GuoWei; Hou, ZuoXun; Tang, Qi; Pan, Zheng; Li, Xin

    2016-11-01

    In order to improve image processing quality and boost processing rate, this paper proposes an real-time automatic image enhancement algorithm. It is based on the histogram equalization algorithm and the piecewise linear enhancement algorithm, and it calculate the relationship of the histogram and the piecewise linear function by analyzing the histogram distribution for adaptive image enhancement. Furthermore, the corresponding FPGA processing modules are designed to implement the methods. Especially, the high-performance parallel pipelined technology and inner potential parallel processing ability of the modules are paid more attention to ensure the real-time processing ability of the complete system. The simulations and the experimentations show that the algorithm is based on the design and implementation of FPGA hardware circuit less cost on hardware, high real-time performance, the good processing performance in different sceneries. The algorithm can effectively improve the image quality, and would have wide prospect on imaging processing field.

  10. 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

  11. Hybrid regularizers-based adaptive anisotropic diffusion for image denoising.

    PubMed

    Liu, Kui; Tan, Jieqing; Ai, Liefu

    2016-01-01

    To eliminate the staircasing effect for total variation filter and synchronously avoid the edges blurring for fourth-order PDE filter, a hybrid regularizers-based adaptive anisotropic diffusion is proposed for image denoising. In the proposed model, the [Formula: see text]-norm is considered as the fidelity term and the regularization term is composed of a total variation regularization and a fourth-order filter. The two filters can be adaptively selected according to the diffusion function. When the pixels locate at the edges, the total variation filter is selected to filter the image, which can preserve the edges. When the pixels belong to the flat regions, the fourth-order filter is adopted to smooth the image, which can eliminate the staircase artifacts. In addition, the split Bregman and relaxation approach are employed in our numerical algorithm to speed up the computation. Experimental results demonstrate that our proposed model outperforms the state-of-the-art models cited in the paper in both the qualitative and quantitative evaluations.

  12. Adaptive clutter rejection for ultrasound color Doppler imaging

    NASA Astrophysics Data System (ADS)

    Yoo, Yang Mo; Managuli, Ravi; Kim, Yongmin

    2005-04-01

    We have developed a new adaptive clutter rejection technique where an optimum clutter filter is dynamically selected according to the varying clutter characteristics in ultrasound color Doppler imaging. The selection criteria have been established based on the underlying clutter characteristics (i.e., the maximum instantaneous clutter velocity and the clutter power) and the properties of various candidate clutter filters (e.g., projection-initialized infinite impulse response and polynomial regression). We obtained an average improvement of 3.97 dB and 3.27 dB in flow signal-to-clutter-ratio (SCR) compared to the conventional and down-mixing methods, respectively. These preliminary results indicate that the proposed adaptive clutter rejection method could improve the sensitivity and accuracy in flow velocity estimation for ultrasound color Doppler imaging. For a 192 x 256 color Doppler image with an ensemble size of 10, the proposed method takes only 57.2 ms, which is less than the acquisition time. Thus, the proposed method could be implemented in modern ultrasound systems, while providing improved clutter rejection and more accurate velocity estimation in real time.

  13. Adaptive Kaczmarz Method for Image Reconstruction in Electrical Impedance Tomography

    PubMed Central

    Li, Taoran; Kao, Tzu-Jen; Isaacson, David; Newell, Jonathan C.; Saulnier, Gary J.

    2013-01-01

    We present an adaptive Kaczmarz method for solving the inverse problem in electrical impedance tomography and determining the conductivity distribution inside an object from electrical measurements made on the surface. To best characterize an unknown conductivity distribution and avoid inverting the Jacobian-related term JTJ which could be expensive in terms of computation cost and memory in large scale problems, we propose solving the inverse problem by applying the optimal current patterns for distinguishing the actual conductivity from the conductivity estimate between each iteration of the block Kaczmarz algorithm. With a novel subset scheme, the memory-efficient reconstruction algorithm which appropriately combines the optimal current pattern generation with the Kaczmarz method can produce more accurate and stable solutions adaptively as compared to traditional Kaczmarz and Gauss-Newton type methods. Choices of initial current pattern estimates are discussed in the paper. Several reconstruction image metrics are used to quantitatively evaluate the performance of the simulation results. PMID:23718952

  14. 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.

  15. 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.

  16. Sparse diffraction imaging method using an adaptive reweighting homotopy algorithm

    NASA Astrophysics Data System (ADS)

    Yu, Caixia; Zhao, Jingtao; Wang, Yanfei; Qiu, Zhen

    2017-02-01

    Seismic diffractions carry valuable information from subsurface small-scale geologic discontinuities, such as faults, cavities and other features associated with hydrocarbon reservoirs. However, seismic imaging methods mainly use reflection theory for constructing imaging models, which means a smooth constraint on imaging conditions. In fact, diffractors occupy a small account of distributions in an imaging model and possess discontinuous characteristics. In mathematics, this kind of phenomena can be described by the sparse optimization theory. Therefore, we propose a diffraction imaging method based on a sparsity-constraint model for studying diffractors. A reweighted L 2-norm and L 1-norm minimization model is investigated, where the L 2 term requests a least-square error between modeled diffractions and observed diffractions and the L 1 term imposes sparsity on the solution. In order to efficiently solve this model, we use an adaptive reweighting homotopy algorithm that updates the solutions by tracking a path along inexpensive homotopy steps. Numerical examples and field data application demonstrate the feasibility of the proposed method and show its significance for detecting small-scale discontinuities in a seismic section. The proposed method has an advantage in improving the focusing ability of diffractions and reducing the migration artifacts.

  17. Image processing techniques for noise removal, enhancement and segmentation of cartilage OCT images.

    PubMed

    Rogowska, Jadwiga; Brezinski, Mark E

    2002-02-21

    Osteoarthritis, whose hallmark is the progressive loss of joint cartilage, is a major cause of morbidity worldwide. Recently, optical coherence tomography (OCT) has demonstrated considerable promise for the assessment of articular cartilage. Among the most important parameters to be assessed is cartilage width. However, detection of the bone cartilage interface is critical for the assessment of cartilage width. At present, the quantitative evaluations of cartilage thickness are being done using manual tracing of cartilage-bone borders. Since data is being obtained near video rate with OCT, automated identification of the bone-cartilage interface is critical. In order to automate the process of boundary detection on OCT images, there is a need for developing new image processing techniques. In this paper we describe the image processing techniques for speckle removal, image enhancement and segmentation of cartilage OCT images. In particular, this paper focuses on rabbit cartilage since this is an important animal model for testing both chondroprotective agents and cartilage repair techniques. In this study, a variety of techniques were examined. Ultimately, by combining an adaptive filtering technique with edge detection (vertical gradient, Sobel edge detection), cartilage edges can be detected. The procedure requires several steps and can be automated. Once the cartilage edges are outlined, the cartilage thickness can be measured.

  18. 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.

  19. 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.

  20. Analysis on enhanced depth of field for integral imaging microscope.

    PubMed

    Lim, Young-Tae; Park, Jae-Hyeung; Kwon, Ki-Chul; Kim, Nam

    2012-10-08

    Depth of field of the integral imaging microscope is studied. In the integral imaging microscope, 3-D information is encoded as a form of elemental images Distance between intermediate plane and object point decides the number of elemental image and depth of field of integral imaging microscope. From the analysis, it is found that depth of field of the reconstructed depth plane image by computational integral imaging reconstruction is longer than depth of field of optical microscope. From analyzed relationship, experiment using integral imaging microscopy and conventional microscopy is also performed to confirm enhanced depth of field of integral imaging microscopy.

  1. Satellite Imaging with Adaptive Optics on a 1 M Telescope

    NASA Astrophysics Data System (ADS)

    Bennet, F.; Price, I.; Rigaut, F.; Copeland, M.

    2016-09-01

    The Research School of Astronomy and Astrophysics at the Mount Stromlo Observatory in Canberra, Australia, have been developing adaptive optic (AO) systems for space situational awareness applications. We report on the development and demonstration of an AO system for satellite imaging using a 1 m telescope. The system uses the orbiting object as a natural guide star to measure atmospheric turbulence, and a deformable mirror to provide an optical correction. The AO system utilised modern, high speed and low noise EMCCD technology on both the wavefront sensor and imaging camera to achieve high performance, achieving a Strehl ratio in excess of 30% at 870 nm. Images are post processed with lucky imaging algorithms to further improve the final image quality. We demonstrate the AO system on stellar targets and Iridium satellites, achieving a near diffraction limited full width at half maximum. A specialised realtime controller allows our system to achieve a bandwidth above 100 Hz, with the wavefront sensor and control loop running at 2 kHz. The AO systems we are developing show how ground-based optical sensors can be used to manage the space environment. AO imaging systems can be used for satellite surveillance, while laser ranging can be used to determine precise orbital data used in the critical conjunction analysis required to maintain a safe space environment. We have focused on making this system compact, expandable, and versatile. We are continuing to develop this platform for other space situational awareness applications such as geosynchronous satellite astrometry, space debris characterisation, satellite imaging, and ground-to-space laser communication.

  2. Epiphyseal and physeal cartilage: normal gadolinium-enhanced MR imaging.

    PubMed

    Li, Xiaoming; Wang, Renfa; Li, Yonggang; Tang, Lihua; Hu, Junwu; Xu, Anhui

    2005-01-01

    To evaluate the normal appearance of epiphyseal and physeal cartilage on Gadolinium (Gd)-enhanced MR imaging. The appearance and enhancement ratios of 20 proximal and distal femoral epiphyses in 10 normal piglets were analyzed on Gd-enhanced MR images. The correlation of the MR imaging appearance with corresponding histological findings of immature epiphyses was examined. Our results showed that Gd-enhanced MRI could differentiate the differences in enhancement between physeal and epiphyseal cartilage and show vascular canals within the epiphyseal cartilage. Enhanced ratios in the physeal were greater than those in the epiphyseal cartilage (P < 0.005). It is concluded that Gd-enhanced MR imaging reveals epiphyseal vascular canals and shows difference in enhancement of physeal and epiphyseal cartilage.

  3. 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.

  4. 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.

  5. Image denoising using a directional adaptive diffusion filter

    NASA Astrophysics Data System (ADS)

    Zhao, Cuifang; Shi, Caicheng; He, Peikun

    2006-11-01

    Partial differential equations (PDEs) are well-known due to their good processing results which it can not only smooth the noise but also preserve the edges. But the shortcomings of these processes came to being noticed by people. In some sense, PDE filter is called "cartoon model" as it produces an approximation of the input image, use the same diffusion model and parameters to process noise and signal because it can not differentiate them, therefore, the image is naturally modified toward piecewise constant functions. A new method called a directional adaptive diffusion filter is proposed in the paper, which combines PDE mode with wavelet transform. The undecimated discrete wavelet transform (UDWT) is carried out to get different frequency bands which have obviously directional selectivity and more redundancy details. Experimental results show that the proposed method provides a performance better to preserve textures, small details and global information.

  6. 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

  7. 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.

  8. Epithelium-stroma classification via convolutional neural networks and unsupervised domain adaptation in histopathological images.

    PubMed

    Huang, Yue; Zheng, Han; Liu, Chi; Ding, Xinghao; Rohde, Gustavo

    2017-04-06

    Epithelium-stroma classification is a necessary preprocessing step in histopathological image analysis. Current deep learning based recognition methods for histology data require collection of large volumes of labeled data in order to train a new neural network when there are changes to the image acquisition procedure. However, it is extremely expensive for pathologists to manually label sufficient volumes of data for each pathology study in a professional manner, which results in limitations in real-world applications. A very simple but effective deep learning method, that introduces the concept of unsupervised domain adaptation to a simple convolutional neural network (CNN), has been proposed in this paper. Inspired by transfer learning, our work assumes that the training data and testing data follow different distributions, and there is an adaptation operation to more accurately estimate the kernels in CNN in feature extraction, in order to enhance performance by transferring knowledge from labeled data in source domain to unlabeled data in target domain. The model has been evaluated using three independent public epithelium-stroma datasets by cross-dataset validations. The experimental results demonstrate that for epithelium-stroma classification, the proposed framework outperforms the state-of-the-art deep neural network model, and it also achieves better performance than other existing deep domain adaptation methods. The proposed model can be considered to be a better option for real-world applications in histopathological image analysis, since there is no longer a requirement for large-scale labeled data in each specified domain.

  9. Fast unsupervised Bayesian image segmentation with adaptive spatial regularisation.

    PubMed

    Pereyra, Marcelo; McLaughlin, Stephen

    2017-03-15

    This paper presents a new Bayesian estimation technique for hidden Potts-Markov random fields with unknown regularisation parameters, with application to fast unsupervised K-class image segmentation. The technique is derived by first removing the regularisation parameter from the Bayesian model by marginalisation, followed by a small-variance-asymptotic (SVA) analysis in which the spatial regularisation and the integer-constrained terms of the Potts model are decoupled. The evaluation of this SVA Bayesian estimator is then relaxed into a problem that can be computed efficiently by iteratively solving a convex total-variation denoising problem and a least-squares clustering (K-means) problem, both of which can be solved straightforwardly, even in high-dimensions, and with parallel computing techniques. This leads to a fast fully unsupervised Bayesian image segmentation methodology in which the strength of the spatial regularisation is adapted automatically to the observed image during the inference procedure, and that can be easily applied in large 2D and 3D scenarios or in applications requiring low computing times. Experimental results on synthetic and real images, as well as extensive comparisons with state-ofthe- art algorithms, confirm that the proposed methodology offer extremely fast convergence and produces accurate segmentation results, with the important additional advantage of self-adjusting regularisation parameters.

  10. Sensorless adaptive optics system based on image second moment measurements

    NASA Astrophysics Data System (ADS)

    Agbana, Temitope E.; Yang, Huizhen; Soloviev, Oleg; Vdovin, Gleb; Verhaegen, Michel

    2016-04-01

    This paper presents experimental results of a static aberration control algorithm based on the linear relation be- tween mean square of the aberration gradient and the second moment of point spread function for the generation of control signal input for a deformable mirror (DM). Results presented in the work of Yang et al.1 suggested a good feasibility of the method for correction of static aberration for point and extended sources. However, a practical realisation of the algorithm has not been demonstrated. The goal of this article is to check the method experimentally in the real conditions of the present noise, finite dynamic range of the imaging camera, and system misalignments. The experiments have shown strong dependence of the linearity of the relationship on image noise and overall image intensity, which depends on the aberration level. Also, the restoration capability and the rate of convergence of the AO system for aberrations generated by the deformable mirror are experi- mentally investigated. The presented approach as well as the experimental results finds practical application in compensation of static aberration in adaptive microscopic imaging system.

  11. 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

  12. The enhanced MODIS airborne simulator hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Guerin, Daniel C.; Fisher, John; Graham, Edward R.

    2011-06-01

    The EMAS-HS or Enhanced MODIS Airborne Simulator is an upgrade to the solar reflected and thermal infrared channels of NASA's MODIS Airborne Simulator (MAS). In the solar reflected bands, the MAS scanner functionality will be augmented with the addition of this separate pushbroom hyperspectral instrument. As well as increasing the spectral resolution of MAS beyond 10 nm, this spectrometer is designed to maintain a stable calibration that can be transferred to the existing MAS sensor. The design emphasizes environmental control and on-board radiometric stability monitoring. The system is designed for high-altitude missions on the ER-2 and the Global Hawk platforms. System trades optimize performance in MODIS spectral bands that support land, cloud, aerosol, and atmospheric water studies. The primary science mission driving the development is high altitude cloud imaging, with secondary missions possible for ocean color. The sensor uses two Offner spectrometers to cover the 380-2400 nm spectral range. It features an all-reflective telescope with a 50° full field-of-view. A dichroic cold mirror will split the image from the telescope, with longer radiation transmitted to the SWIR spectrometer. The VNIR spectrometer uses a TE-cooled Si CCD detector that samples the spectrum at 2.5 nm intervals, while the SWIR spectrometer uses a Stirling-cooled hybrid HgCdTe detector to sample the spectrum at 10 nm per band. Both spectrometers will feature 1.05 mRad instantaneous fields-of-view registered to the MAS scanner IFOV's.

  13. 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.

  14. 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.

  15. Single Cell Imaging of the Chick Retina with Adaptive Optics

    PubMed Central

    Headington, Kenneth; Choi, Stacey S.; Nickla, Debora; Doble, Nathan

    2012-01-01

    Purpose The chick eye is extensively used as a model in the study of myopia and its progression; however, analysis of the photoreceptor mosaic has required the use of excised retina due to the uncorrected optical aberrations in the lens and cornea. This study implemented high resolution adaptive optics (AO) retinal imaging to visualize the chick cone mosaic in vivo. Methods The New England College of Optometry (NECO) AO fundus camera was modified to allow high resolution in vivo imaging on 2 six-week-old White Leghorn chicks (Gallus gallus domesticus) – labeled chick A and chick B. Multiple, adjacent images, each with a 2.5° field of view, were taken and subsequently montaged together. This process was repeated at varying retinal locations measured from the tip of the pecten. Automated software was used to determine the cone spacing and density at each location. Voronoi analysis was applied to determine the packing arrangement of the cones. Results In both chicks, cone photoreceptors were clearly visible at all retinal locations imaged. Cone densities measured at 36° nasal-12° superior retina from the pecten tip for chick A and 40° nasal-12° superior retina for chick B were 21,714±543 and 26,105±653 cones/mm2 respectively. For chick B, a further 11 locations immediately surrounding the pecten were imaged, with cone densities ranging from 20,980±524 to 25,148±629 cones/mm2. Conclusion In vivo analysis of the cone density and its packing characteristics are now possible in the chick eye through AO imaging, which has important implications for future studies of myopia and ocular disease research. PMID:21950701

  16. 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.

  17. 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.

  18. Human body region enhancement method based on Kinect infrared imaging

    NASA Astrophysics Data System (ADS)

    Yang, Lei; Fan, Yubo; Song, Xiaowei; Cai, Wenjing

    2016-10-01

    To effectively improve the low contrast of human body region in the infrared images, a combing method of several enhancement methods is utilized to enhance the human body region. Firstly, for the infrared images acquired by Kinect, in order to improve the overall contrast of the infrared images, an Optimal Contrast-Tone Mapping (OCTM) method with multi-iterations is applied to balance the contrast of low-luminosity infrared images. Secondly, to enhance the human body region better, a Level Set algorithm is employed to improve the contour edges of human body region. Finally, to further improve the human body region in infrared images, Laplacian Pyramid decomposition is adopted to enhance the contour-improved human body region. Meanwhile, the background area without human body region is processed by bilateral filtering to improve the overall effect. With theoretical analysis and experimental verification, the results show that the proposed method could effectively enhance the human body region of such infrared images.

  19. 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.

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

    PubMed Central

    Wang, Changmiao; Jia, Fucang; Wu, Jianhuang; Li, Guanglin

    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

  1. 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.

  2. 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

  3. 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.

  4. CT imaging of enhanced oil recovery experiments

    SciTech Connect

    Gall, B.L.

    1992-12-01

    X-ray computerized tomography (Cr) has been used to study fluid distributions during chemical enhanced oil recovery experiments. Four CT-monitored corefloods were conducted, and oil saturation distributions were calculated at various stages of the experiments. Results suggested that this technique could add significant information toward interpretation and evaluation of surfactant/polymer EOR recovery methods. CT-monitored tracer tests provided information about flow properties in the core samples. Nonuniform fluid advance could be observed, even in core that appeared uniform by visual inspection. Porosity distribution maps based on CT density calculations also showed the presence of different porosity layers that affected fluid movement through the cores. Several types of CT-monitored corefloods were conducted. Comparisons were made for CT-monitored corefloods using chemical systems that were highly successful in reducing residual oil saturations in laboratory experiments and less successful systems. Changes were made in surfactant formulation and in concentration of the mobility control polymer. Use of a poor mobility control agent failed to move oil that was not initially displaced by the injected surfactant solution; even when a good'' surfactant system was used. Use of a less favorable surfactant system with adequate mobility control could produce as much oil as the use of a good surfactant system with inadequate mobility control. The role of mobility control, therefore, becomes a critical parameter for successful application of chemical EOR. Continuation of efforts to use CT imaging in connection with chemical EOR evaluations is recommended.

  5. CT imaging of enhanced oil recovery experiments

    SciTech Connect

    Gall, B.L.

    1992-12-01

    X-ray computerized tomography (Cr) has been used to study fluid distributions during chemical enhanced oil recovery experiments. Four CT-monitored corefloods were conducted, and oil saturation distributions were calculated at various stages of the experiments. Results suggested that this technique could add significant information toward interpretation and evaluation of surfactant/polymer EOR recovery methods. CT-monitored tracer tests provided information about flow properties in the core samples. Nonuniform fluid advance could be observed, even in core that appeared uniform by visual inspection. Porosity distribution maps based on CT density calculations also showed the presence of different porosity layers that affected fluid movement through the cores. Several types of CT-monitored corefloods were conducted. Comparisons were made for CT-monitored corefloods using chemical systems that were highly successful in reducing residual oil saturations in laboratory experiments and less successful systems. Changes were made in surfactant formulation and in concentration of the mobility control polymer. Use of a poor mobility control agent failed to move oil that was not initially displaced by the injected surfactant solution; even when a ``good`` surfactant system was used. Use of a less favorable surfactant system with adequate mobility control could produce as much oil as the use of a good surfactant system with inadequate mobility control. The role of mobility control, therefore, becomes a critical parameter for successful application of chemical EOR. Continuation of efforts to use CT imaging in connection with chemical EOR evaluations is recommended.

  6. 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.

  7. An infrared image enhancement algorithm based on HVS

    NASA Astrophysics Data System (ADS)

    Xue, Rongkun; He, Wei; Liu, Jiahui; Li, Yufeng

    2016-10-01

    Because the infrared images have the disadvantage of low contrast and fuzzy edges, it is not suitable for us to observe them, so it is necessary to first make enhanced processing before recognition. Though the existing enhancement methods do not take into account the characteristics of HVS, the visual effect of the processed images is not good. Therefore, the paper proposes an enhancement algorithm of infrared images that combine multi-resolution wavelet transform with Retinex theory, it blends with the characteristics of HVS in order to make high-frequency details of infrared images strengthen and illumination uniformity strength and the brightness of IR images moderate. Through experimental results and data analysis, it not only improves the infrared images of low contrast and fuzzy detail, but also suppresses the noise in images to strengthen the overall visual effect of the infrared images.

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

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

    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 could

  9. Discontinuity enhancement based on time-variant seismic image deblurring

    NASA Astrophysics Data System (ADS)

    Wang, Yi; Lu, Wenkai

    2016-12-01

    Post-stack 3D seismic data is spatially blurred by the effects of migration operators with limited aperture widths, which is not conducive to discontinuity (such as fault, channel, etc.) detection. By approximating the migration blur with a time-invariant point spread function (TIPSF), seismic image deblurring methods have been used to obtain data with enhanced discontinuity. Better discontinuity detection results can be achieved on the deblurred data than on the original data. Since the migration blurs are always time-dependent, a time-variant PSF (TVPSF) estimation method is proposed in this paper to approximate these blurs. In our method, initial PSFs corresponding to each horizontal time slice (HTS) from a 3D seismic data are first obtained. Then, PSFs corresponding to adjacent time slices are divided into the same categories based on their similarities. With average PSFs calculated in each category, linear interpolation is performed to estimate PSFs for the whole data set. Finally, we perform seismic image deblurring HTS by HTS with these estimated PSFs. To suit different signal-to-noise ratios (SNR) in these HTSs of the 3D seismic data, the whitening factor of the Wiener filter for each HTS is adjusted adaptively. Using field dataset examples, we demonstrate that the performance of our proposed TVPSF method outperforms the TIPSF method.

  10. 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.

  11. 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.

  12. Enhancing Stellar Spectroscopy with Extreme Adaptive Optics and Photonics

    NASA Astrophysics Data System (ADS)

    Jovanovic, N.; Schwab, C.; Cvetojevic, N.; Guyon, O.; Martinache, F.

    2016-12-01

    Extreme adaptive optics (AO) systems are now in operation across the globe. These systems, capable of high order wavefront correction, deliver Strehl ratios of ∼ 90 % in the near-infrared. Originally intended for the direct imaging of exoplanets, these systems are often equipped with advanced coronagraphs that suppress the on-axis-star, interferometers to calibrate wavefront errors, and low order wavefront sensors to stabilize any tip/tilt residuals to a degree never seen before. Such systems are well positioned to facilitate the detailed spectroscopic characterization of faint substellar companions at small angular separations from the host star. Additionally, the increased light concentration of the point-spread function and the unprecedented stability create opportunities in other fields of astronomy as well, including spectroscopy. With such Strehl ratios, efficient injection into single-mode fibers (SMFs) or photonic lanterns becomes possible. With diffraction-limited components feeding the instrument, calibrating a spectrograph’s line profile becomes considerably easier, as modal noise or imperfect scrambling of the fiber output are no longer an issue. It also opens up the possibility of exploiting photonic technologies for their advanced functionalities, inherent replicability, and small, lightweight footprint to design and build future instrumentation. In this work, we outline how extreme AO systems will enable advanced photonic and diffraction-limited technologies to be exploited in spectrograph design and the impact it will have on spectroscopy. We illustrate that the precision of an instrument based on these technologies, with light injected from an efficient SMF feed would be entirely limited by the spectral content and stellar noise alone on cool stars and would be capable of achieving a radial velocity precision of several m/s; the level required for detecting an exo-Earth in the habitable zone of a nearby M-dwarf.

  13. ADAPTIVE OPTICS IMAGES OF KEPLER OBJECTS OF INTEREST

    SciTech Connect

    Adams, E. R.; Dupree, A. K.; Ciardi, D. R.; Gautier, T. N. III; Kulesa, C.; McCarthy, D.

    2012-08-15

    All transiting planets are at risk of contamination by blends with nearby, unresolved stars. Blends dilute the transit signal, causing the planet to appear smaller than it really is, or produce a false-positive detection when the target star is blended with eclipsing binary stars. This paper reports on high spatial-resolution adaptive optics images of 90 Kepler planetary candidates. Companion stars are detected as close as 0.''1 from the target star. Images were taken in the near-infrared (J and Ks bands) with ARIES on the MMT and PHARO on the Palomar Hale 200 inch telescope. Most objects (60%) have at least one star within 6'' separation and a magnitude difference of 9. Eighteen objects (20%) have at least one companion within 2'' of the target star; six companions (7%) are closer than 0.''5. Most of these companions were previously unknown, and the associated planetary candidates should receive additional scrutiny. Limits are placed on the presence of additional companions for every system observed, which can be used to validate planets statistically using the BLENDER method. Validation is particularly critical for low-mass, potentially Earth-like worlds, which are not detectable with current-generation radial velocity techniques. High-resolution images are thus a crucial component of any transit follow-up program.

  14. Adaptive Optics Images of Kepler Objects of Interest

    NASA Astrophysics Data System (ADS)

    Adams, E. R.; Ciardi, D. R.; Dupree, A. K.; Gautier, T. N., III; Kulesa, C.; McCarthy, D.

    2012-08-01

    All transiting planets are at risk of contamination by blends with nearby, unresolved stars. Blends dilute the transit signal, causing the planet to appear smaller than it really is, or produce a false-positive detection when the target star is blended with eclipsing binary stars. This paper reports on high spatial-resolution adaptive optics images of 90 Kepler planetary candidates. Companion stars are detected as close as 0farcs1 from the target star. Images were taken in the near-infrared (J and Ks bands) with ARIES on the MMT and PHARO on the Palomar Hale 200 inch telescope. Most objects (60%) have at least one star within 6'' separation and a magnitude difference of 9. Eighteen objects (20%) have at least one companion within 2'' of the target star; six companions (7%) are closer than 0farcs5. Most of these companions were previously unknown, and the associated planetary candidates should receive additional scrutiny. Limits are placed on the presence of additional companions for every system observed, which can be used to validate planets statistically using the BLENDER method. Validation is particularly critical for low-mass, potentially Earth-like worlds, which are not detectable with current-generation radial velocity techniques. High-resolution images are thus a crucial component of any transit follow-up program. Based on observations obtained at the MMT Observatory, a joint facility of the Smithsonian Institution and the University of Arizona.

  15. 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.

  16. Keck Adaptive Optics Images of Uranus and Its Rings

    NASA Astrophysics Data System (ADS)

    de Pater, Imke; Gibbard, S. G.; Macintosh, B. A.; Roe, H. G.; Gavel, D. T.; Max, C. E.

    2002-12-01

    We present adaptive optic images of Uranus obtained with the 10-m W. M. Keck II telescope in June 2000, at wavelengths between 1 and 2.4 μm. The angular resolution of the images is ˜0.06-0.09″. We identified eight small cloud features on Uranus's disk, four of which were in the northern hemisphere. The latter features are ˜1000-2000 km in extent and located in the upper troposphere, above the methane cloud, at pressures between 0.5 and 1 bar. Our data have been combined with HST data by Hammel et al. (2001, Icarus153, 229-235); the combination of Keck and HST data allowed derivation of an accurate wind velocity profile. Our images further show Uranus's entire ring system: the asymmetric ɛ ring, as well as the three groups of inner rings (outward from Uranus): the rings 6+5+4, α+β, and the η+γ+δ rings. We derived the equivalent I/ F width and ring particle reflectivity for each group of rings. Typical particle albedos are ˜0.04-0.05, in good agreement with HST data at 0.9 μm.

  17. Adaptive Optics Retinal Imaging – Clinical Opportunities and Challenges

    PubMed Central

    Carroll, Joseph; Kay, David B.; Scoles, Drew; Dubra, Alfredo; Lombardo, Marco

    2014-01-01

    The array of therapeutic options available to clinicians for treating retinal disease is expanding. With these advances comes the need for better understanding of the etiology of these diseases on a cellular level as well as improved non-invasive tools for identifying the best candidates for given therapies and monitoring the efficacy of those therapies. While spectral domain optical coherence tomography (SD-OCT) offers a widely available tool for clinicians to assay the living retina, it suffers from poor lateral resolution due to the eye’s monochromatic aberrations. Adaptive optics (AO) is a technique to compensate for the eye’s aberrations and provide nearly diffraction-limited resolution. The result is the ability to visualize the living retina with cellular resolution. While AO is unquestionably a powerful research tool, many clinicians remain undecided on the clinical potential of AO imaging – putting many at a crossroads with respect to adoption of this technology. This review will briefly summarize the current state of AO retinal imaging, discuss current as well as future clinical applications of AO retinal imaging, and finally provide some discussion of research needs to facilitate more widespread clinical use. PMID:23621343

  18. Knowledge-based image bandwidth compression and enhancement

    NASA Astrophysics Data System (ADS)

    Saghri, John A.; Tescher, Andrew G.

    1987-01-01

    Techniques for incorporating a priori knowledge in the digital coding and bandwidth compression of image data are described and demonstrated. An algorithm for identifying and highlighting thin lines and point objects prior to coding is presented, and the precoding enhancement of a slightly smoothed version of the image is shown to be more effective than enhancement of the original image. Also considered are readjustment of the local distortion parameter and variable-block-size coding. The line-segment criteria employed in the classification are listed in a table, and sample images demonstrating the effectiveness of the enhancement techniques are presented.

  19. An adaptive controller for enhancing operator performance during teleoperation

    NASA Technical Reports Server (NTRS)

    Carignan, Craig R.; Tarrant, Janice M.; Mosier, Gary E.

    1989-01-01

    An adaptive controller is developed for adjusting robot arm parameters while manipulating payloads of unknown mass and inertia. The controller is tested experimentally in a master/slave configuration where the adaptive slave arm is commanded via human operator inputs from a master. Kinematically similar six-joint master and slave arms are used with the last three joints locked for simplification. After a brief initial adaptation period for the unloaded arm, the slave arm retrieves different size payloads and maneuvers them about the workspace. Comparisons are then drawn with similar tasks where the adaptation is turned off. Several simplifications of the controller dynamics are also addressed and experimentally verified.

  20. 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.

  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. 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.

  3. 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

  4. Adaptive bit truncation and compensation method for EZW image coding

    NASA Astrophysics Data System (ADS)

    Dai, Sheng-Kui; Zhu, Guangxi; Wang, Yao

    2003-09-01

    The embedded zero-tree wavelet algorithm (EZW) is widely adopted to compress wavelet coefficients of images with the property that the bits stream can be truncated and produced anywhere. The lower bit plane of the wavelet coefficents is verified to be less important than the higher bit plane. Therefore it can be truncated and not encoded. Based on experiments, a generalized function, which can provide a glancing guide for EZW encoder to intelligently decide the number of low bit plane to be truncated, is deduced in this paper. In the EZW decoder, a simple method is presented to compensate for the truncated wavelet coefficients, and finally it can surprisingly enhance the quality of reconstructed image and spend scarcely any additional cost at the same time.

  5. 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.

  6. 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…

  7. Pattern matching and adaptive image segmentation applied to plant reproduction by tissue culture

    NASA Astrophysics Data System (ADS)

    Vazquez Rueda, Martin G.; Hahn, Federico

    1999-03-01

    This paper shows the results obtained in a system vision applied to plant reproduction by tissue culture using adaptive image segmentation and pattern matching algorithms, this analysis improves the number of tissue obtained and minimize errors, the image features of tissue are considered join to statistical analysis to determine the best match and results. Tests make on potato plants are used to present comparative results with original images processed with adaptive segmentation algorithm and non adaptive algorithms and pattern matching.

  8. Multi-modal automatic montaging of adaptive optics retinal images

    PubMed Central

    Chen, Min; Cooper, Robert F.; Han, Grace K.; Gee, James; Brainard, David H.; Morgan, Jessica I. W.

    2016-01-01

    We present a fully automated adaptive optics (AO) retinal image montaging algorithm using classic scale invariant feature transform with random sample consensus for outlier removal. Our approach is capable of using information from multiple AO modalities (confocal, split detection, and dark field) and can accurately detect discontinuities in the montage. The algorithm output is compared to manual montaging by evaluating the similarity of the overlapping regions after montaging, and calculating the detection rate of discontinuities in the montage. Our results show that the proposed algorithm has high alignment accuracy and a discontinuity detection rate that is comparable (and often superior) to manual montaging. In addition, we analyze and show the benefits of using multiple modalities in the montaging process. We provide the algorithm presented in this paper as open-source and freely available to download. PMID:28018714

  9. Speckle statistics in adaptive optics images at visible wavelengths

    NASA Astrophysics Data System (ADS)

    Stangalini, Marco; Pedichini, Fernando; Ambrosino, Filippo; Centrone, Mauro; Del Moro, Dario

    2016-07-01

    Residual speckles in adaptive optics (AO) images represent a well known limitation to the achievement of the contrast needed for faint stellar companions detection. Speckles in AO imagery can be the result of either residual atmospheric aberrations, not corrected by the AO, or slowly evolving aberrations induced by the optical system. In this work we take advantage of new high temporal cadence (1 ms) data acquired by the SHARK forerunner experiment at the Large Binocular Telescope (LBT), to characterize the AO residual speckles at visible waveleghts. By means of an automatic identification of speckles, we study the main statistical properties of AO residuals. In addition, we also study the memory of the process, and thus the clearance time of the atmospheric aberrations, by using information Theory. These information are useful for increasing the realism of numerical simulations aimed at assessing the instrumental performances, and for the application of post-processing techniques on AO imagery.

  10. Multi-modal automatic montaging of adaptive optics retinal images.

    PubMed

    Chen, Min; Cooper, Robert F; Han, Grace K; Gee, James; Brainard, David H; Morgan, Jessica I W

    2016-12-01

    We present a fully automated adaptive optics (AO) retinal image montaging algorithm using classic scale invariant feature transform with random sample consensus for outlier removal. Our approach is capable of using information from multiple AO modalities (confocal, split detection, and dark field) and can accurately detect discontinuities in the montage. The algorithm output is compared to manual montaging by evaluating the similarity of the overlapping regions after montaging, and calculating the detection rate of discontinuities in the montage. Our results show that the proposed algorithm has high alignment accuracy and a discontinuity detection rate that is comparable (and often superior) to manual montaging. In addition, we analyze and show the benefits of using multiple modalities in the montaging process. We provide the algorithm presented in this paper as open-source and freely available to download.

  11. Efficient cultural heritage image restoration with nonuniform illumination enhancement

    NASA Astrophysics Data System (ADS)

    Jmal, Marwa; Souidene, Wided; Attia, Rabah

    2017-01-01

    Cultural heritage digitization has been of research interest for several decades. For such, the quality of the stored images should be pleasant to see. However, as images captured by digital devices may include undesirable effects, conducting an enhancement on the image is essential. In this context, we present a framework for the purpose of cultural heritage image illumination enhancement. First, a mapping curve based on saturation feedback is created to adjust the contrast. Then illumination is enhanced by applying a modified homomorphic filter in the frequency domain. The technique employs an optimization search process based on the efficient golden section search algorithm to compute the optimal parameters to produce the enhanced image. Finally, a color restoration function is applied to overcome the problem of color violation. The resulted image represents a trade-off among local contrast improvement, detail enhancement, and preserving the naturalness of the image. Experiments are conducted on a collected dataset of cultural heritage images and compared to some of the state-of-the-art image enhancement methods using a set of quantitative assessments criteria. Results have shown that our proposed approach is able to accomplish a wide set of the performance goals.

  12. 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.

  13. 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

  14. Photometric Calibration of the Gemini South Adaptive Optics Imager

    NASA Astrophysics Data System (ADS)

    Stevenson, Sarah Anne; Rodrigo Carrasco Damele, Eleazar; Thomas-Osip, Joanna

    2017-01-01

    The Gemini South Adaptive Optics Imager (GSAOI) is an instrument available on the Gemini South telescope at Cerro Pachon, Chile, utilizing the Gemini Multi-Conjugate Adaptive Optics System (GeMS). In order to allow users to easily perform photometry with this instrument and to monitor any changes in the instrument in the future, we seek to set up a process for performing photometric calibration with standard star observations taken across the time of the instrument’s operation. We construct a Python-based pipeline that includes IRAF wrappers for reduction and combines the AstroPy photutils package and original Python scripts with the IRAF apphot and photcal packages to carry out photometry and linear regression fitting. Using the pipeline, we examine standard star observations made with GSAOI on 68 nights between 2013 and 2015 in order to determine the nightly photometric zero points in the J, H, Kshort, and K bands. This work is based on observations obtained at the Gemini Observatory, processed using the Gemini IRAF and gemini_python packages, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the National Research Council (Canada), CONICYT (Chile), Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina), and Ministério da Ciência, Tecnologia e Inovação (Brazil).

  15. 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.

  16. The Atmosphere of Uranus as Imaged with Keck Adaptive Optics

    NASA Astrophysics Data System (ADS)

    Hammel, H. B.; de Pater, I.; Gibbard, S. G.; Lockwood, G. W.; Rages, K.

    2004-12-01

    Adaptive optics imaging of Uranus was obtained with NIRC2 on the Keck II 10-meter telescope in October 2003 and July 2004 through J, H, and K' filters. Dozens of discrete features were detected in the atmosphere of Uranus. We report the first measurements of winds northward of +43 deg, the first direct measurement of equatorial winds, and the highest wind velocity seen yet on Uranus. At northern mid-latitudes, the winds may have accelerated when compared to earlier HST and Keck observations; southern wind speeds have not changed since Voyager measurements in 1986. The equator of Uranus exhibits a subtle wave structure, with diffuse patches roughly every 30 degs in longitude. There is no sign of a northern "polar collar" as is seen in the south, but a number of discrete features seen at the "expected" latitudes may signal its early stages of development. The largest cloud features on Uranus show complex structure extending over tens of degrees. On 4 July 2004, we detected a southern hemispheric cloud feature on Uranus at K', the first detection of a southern feature at or longward of 2 microns. H images showed an extended structure whose condensed core was co-located with the K'-bright feature. The core exhibited marked brightness variation, fading within just a few days. The initial brightness at K' indicates that the core's scattering particles reached altitudes above the 1-bar level, with the extended H feature residing below 1.1 bars. The core's rapid disappearance at K' indicates dynamical processes in the local vertical aerosol structure. HBH acknowledges support from NASA grants NAG5-11961 and NAG5-10451. IdP acknowledges support from NSF and the Technology Center for Adaptive Optics, managed by UCSC under cooperative agreement No. AST-9876783. SGG's work was performed under the auspices of the U.S. DoE National Nuclear Security Administration by the UC, LLNL under contract No. W-7405-Eng-48.

  17. 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.

  18. Region-based retrieval of remote sensing image patches with adaptive image segmentation

    NASA Astrophysics Data System (ADS)

    Li, Shijin; Zhu, Jiali; Zhu, Yuelong; Feng, Jun

    2012-06-01

    Over the past four decades, the satellite imaging sensors have acquired huge quantities of Earth- observation data. Content-based image retrieval allows for fast and effective queries of remote sensing images. Here, we take the following two issues into consideration. Firstly, different features and their combination should be chosen for different land covers. Secondly, for the block dividing strategy and the complexities of the remote sensing images, it can not effectively retrieve some small target areas scattered in multiple nontarget blocks. Aiming at the above two issues, a new region-based retrieval method with adaptive image segmentation is proposed. In order to improve the accuracy of remote sensing image segmentation, feature selection and weighing is performed by two-stage clustering, and image segmentation is accomplished based on the chosen features and mean shift procedure. Meanwhile, for the homogeneous characteristics of remote sensing land covers, a new regional representation and matching scheme are adopted to perform image retrieval. Experimental results on retrieving various land covers show that the method can avoid the impact of traditional blocking strategies, and can achieve an average percentage of 19% higher precision with the same level of recall rate, than the relevance feedback method for small target areas.

  19. Color enhancement in multispectral image of human skin

    NASA Astrophysics Data System (ADS)

    Mitsui, Masanori; Murakami, Yuri; Obi, Takashi; Yamaguchi, Masahiro; Ohyama, Nagaaki

    2003-07-01

    Multispectral imaging is receiving attention in medical color imaging, as high-fidelity color information can be acquired by the multispectral image capturing. On the other hand, as color enhancement in medical color image is effective for distinguishing lesion from normal part, we apply a new technique for color enhancement using multispectral image to enhance the features contained in a certain spectral band, without changing the average color distribution of original image. In this method, to keep the average color distribution, KL transform is applied to spectral data, and only high-order KL coefficients are amplified in the enhancement. Multispectral images of human skin of bruised arm are captured by 16-band multispectral camera, and the proposed color enhancement is applied. The resultant images are compared with the color images reproduced assuming CIE D65 illuminant (obtained by natural color reproduction technique). As a result, the proposed technique successfully visualizes unclear bruised lesions, which are almost invisible in natural color images. The proposed technique will provide support tool for the diagnosis in dermatology, visual examination in internal medicine, nursing care for preventing bedsore, and so on.

  20. 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

  1. 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.

  2. Ultrasound Nondestructive Evaluation (NDE) Imaging with Transducer Arrays and Adaptive Processing

    PubMed Central

    Li, Minghui; Hayward, Gordon

    2012-01-01

    This paper addresses the challenging problem of ultrasonic non-destructive evaluation (NDE) imaging with adaptive transducer arrays. In NDE applications, most materials like concrete, stainless steel and carbon-reinforced composites used extensively in industries and civil engineering exhibit heterogeneous internal structure. When inspected using ultrasound, the signals from defects are significantly corrupted by the echoes form randomly distributed scatterers, even defects that are much larger than these random reflectors are difficult to detect with the conventional delay-and-sum operation. We propose to apply adaptive beamforming to the received data samples to reduce the interference and clutter noise. Beamforming is to manipulate the array beam pattern by appropriately weighting the per-element delayed data samples prior to summing them. The adaptive weights are computed from the statistical analysis of the data samples. This delay-weight-and-sum process can be explained as applying a lateral spatial filter to the signals across the probe aperture. Simulations show that the clutter noise is reduced by more than 30 dB and the lateral resolution is enhanced simultaneously when adaptive beamforming is applied. In experiments inspecting a steel block with side-drilled holes, good quantitative agreement with simulation results is demonstrated. PMID:22368457

  3. Astronomical image denoising by means of improved adaptive backtracking-based matching pursuit algorithm.

    PubMed

    Liu, Qianshun; Bai, Jian; Yu, Feihong

    2014-11-10

    In an effort to improve compressive sensing and spare signal reconstruction by way of the backtracking-based adaptive orthogonal matching pursuit (BAOMP), a new sparse coding algorithm called improved adaptive backtracking-based OMP (ABOMP) is proposed in this study. Many aspects have been improved compared to the original BAOMP method, including replacing the fixed threshold with an adaptive one, adding residual feedback and support set verification, and others. Because of these ameliorations, the proposed algorithm can more precisely choose the atoms. By adding the adaptive step-size mechanism, it requires much less iteration and thus executes more efficiently. Additionally, a simple but effective contrast enhancement method is also adopted to further improve the denoising results and visual effect. By combining the IABOMP algorithm with the state-of-art dictionary learning algorithm K-SVD, the proposed algorithm achieves better denoising effects for astronomical images. Numerous experimental results show that the proposed algorithm performs successfully and effectively on Gaussian and Poisson noise removal.

  4. Ultrasound nondestructive evaluation (NDE) imaging with transducer arrays and adaptive processing.

    PubMed

    Li, Minghui; Hayward, Gordon

    2012-01-01

    This paper addresses the challenging problem of ultrasonic non-destructive evaluation (NDE) imaging with adaptive transducer arrays. In NDE applications, most materials like concrete, stainless steel and carbon-reinforced composites used extensively in industries and civil engineering exhibit heterogeneous internal structure. When inspected using ultrasound, the signals from defects are significantly corrupted by the echoes form randomly distributed scatterers, even defects that are much larger than these random reflectors are difficult to detect with the conventional delay-and-sum operation. We propose to apply adaptive beamforming to the received data samples to reduce the interference and clutter noise. Beamforming is to manipulate the array beam pattern by appropriately weighting the per-element delayed data samples prior to summing them. The adaptive weights are computed from the statistical analysis of the data samples. This delay-weight-and-sum process can be explained as applying a lateral spatial filter to the signals across the probe aperture. Simulations show that the clutter noise is reduced by more than 30 dB and the lateral resolution is enhanced simultaneously when adaptive beamforming is applied. In experiments inspecting a steel block with side-drilled holes, good quantitative agreement with simulation results is demonstrated.

  5. Adaptive semisupervised feature selection without graph construction for very-high-resolution remote sensing images

    NASA Astrophysics Data System (ADS)

    Chen, Xi; Qi, Jinzi; Chen, Yushi; Hua, Lizhong; Shao, Guofan

    2016-04-01

    Semisupervised feature selection methods can improve classification performance and enhance model comprehensibility with few labeled objects. However, most of the existing methods require graph construction beforehand, and the resulting heavy computational cost may bring about the failure to accurately capture the local geometry of data. To overcome the problem, adaptive semisupervised feature selection (ASFS) is proposed. In ASFS, the goodness of each feature is measured by linear objective functions based on loss functions and probability distribution matrices. By alternatively optimizing model parameters and automatically adjusting the probabilities of boundary objects, ASFS can measure the genuine characteristics of the data and then rank and select features. The experimental results attest to the effectiveness and practicality of the method in comparison with the latest and state-of-the-art methods on a Worldview II image and a Quickbird II image.

  6. Performance assessment of a pupil tracking system for adaptive optics retinal imaging

    NASA Astrophysics Data System (ADS)

    Sahin, Betul; Harms, Fabrice; Lamory, Barbara

    2008-09-01

    Adaptive Optics (AO) is particularly suitable for correction of aberrations that change over time - a necessity for high resolution imaging of the retina. The rapidly changing aberrations originating from eye movements require wavefront sensors (WFS) with high repetition rates. Our approach is enhancing aberration correction by integrating a Pupil Tracking System (PTS) into the AO loop of the retinal imaging system. In this study we assessed the performance of the PTS developed for this purpose. Tests have demonstrated that the device achieves an accuracy of <15 μm in a +/-2 mm range of eye movements with a standard deviation <10 μm. PTS can tolerate +/-5 mm defocus with an increase of 4 μm in mean standard deviation. In vivo measurements done with temporarily paralyzed pupils have resulted in a precision of approximately 13 μm.

  7. 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.

  8. Image processing technology for enhanced situational awareness

    NASA Astrophysics Data System (ADS)

    Page, S. F.; Smith, M. I.; Hickman, D.

    2009-09-01

    This paper discusses the integration of a number of advanced image and data processing technologies in support of the development of next-generation Situational Awareness systems for counter-terrorism and crime fighting applications. In particular, the paper discusses the European Union Framework 7 'SAMURAI' project, which is investigating novel approaches to interactive Situational Awareness using cooperative networks of heterogeneous imaging sensors. Specific focus is given to novel Data Fusion aspects of the research which aim to improve system performance through intelligently fusing both image data and non image data sources, resolving human-machine conflicts, and refining the Situational Awareness picture. In addition, the paper highlights some recent advances in supporting image processing technologies. Finally, future trends in image-based Situational Awareness are identified, such as Post-Event Analysis (also known as 'Back-Tracking'), and the associated technical challenges are discussed.

  9. 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.

  10. 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

  11. 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

  12. 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,

  13. Progressive image data compression with adaptive scale-space quantization

    NASA Astrophysics Data System (ADS)

    Przelaskowski, Artur

    1999-12-01

    Some improvements of embedded zerotree wavelet algorithm are considere. Compression methods tested here are based on dyadic wavelet image decomposition, scalar quantization and coding in progressive fashion. Profitable coders with embedded form of code and rate fixing abilities like Shapiro EZW and Said nad Pearlman SPIHT are modified to improve compression efficiency. We explore the modifications of the initial threshold value, reconstruction levels and quantization scheme in SPIHT algorithm. Additionally, we present the result of the best filter bank selection. The most efficient biorthogonal filter banks are tested. Significant efficiency improvement of SPIHT coder was finally noticed even up to 0.9dB of PSNR in some cases. Because of the problems with optimization of quantization scheme in embedded coder we propose another solution: adaptive threshold selection of wavelet coefficients in progressive coding scheme. Two versions of this coder are tested: progressive in quality and resolution. As a result, improved compression effectiveness is achieved - close to 1.3 dB in comparison to SPIHT for image Barbara. All proposed algorithms are optimized automatically and are not time-consuming. But sometimes the most efficient solution must be found in iterative way. Final results are competitive across the most efficient wavelet coders.

  14. 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

  15. A novel visible and infrared image fusion algorithm based on detail enhancement

    NASA Astrophysics Data System (ADS)

    Wang, Bo

    2016-11-01

    In order to improve the characteristic information of the fused images, we propose a novel infrared and visible image fusion algorithm based on image detail enhancement in this paper, the bilateral filter and dynamic range partitioning (BF & DRP) are used to improve the original infrared image, and the multi-scale retinex transform (MRT) also is used to deal with image fusion. Firstly a method of bilateral filter and dynamic range partitioning (BF & DRP) was used to improve the details of the low SNR and low contrast original infrared image, by which the edges of targets were strengthened, the noises were suppressed, and the constrast of infrared image was enhanced. Secondly, and finally, the multi-scale retinex transform was used to improve the fusion of visible and infrared image, by combining the multi-scale transform and regional fusion where the adaptive low frequency and high frequency coefficient were considered, which effectively suppressed the noises and enhanced the details.. Experimental results proved the effectiveness of the proposed image fusion method. The salient color and texture feature of visible image was well preserved, the important details of infrared and visible image were highlighted. The results show that this algorithm is better than traditional image fusion method, such as wavelet transform, non-sampled contourlet transform, in in standard deviation, information entropy and Average gradient etc.. the algorithm of this paper is able to preserve the details of image, increase the amount of importance characteristic information, is advantageous to the visual performance and distinguishability of fused image for human observation.

  16. 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.

  17. Keck Adaptive Optics Imaging of Uranus and its Rings

    NASA Astrophysics Data System (ADS)

    de Pater, Imke; Roe, H.; Macintosh, B.; Gibbard, S.; Max, C.; Gavel, D.

    2000-10-01

    We observed Uranus with the recently commissioned AO/NIRSPEC system (Adaptive Optics system with the Near-Infrared echelle Spectrograph) on the 10-m W.M. Keck telescope, UT June 17 and 18, 2000. NIRSPEC allows one to take images and spectra simultaneously. Here we will discuss the images at wavelengths between 1 and 2.4 micron. Due to the location of the rings' pericenter, the rings were much brighter in the north than the south, which resulted in excellent ring images. Inside of the ɛ ring at least three more (individually slightly resolved) rings are visible: from the outside inwards these are: 1) combined δ ,γ ,η rings, 2) combined β ,α rings, and 3) combined 4,5,6 rings. On the planet itself we detected at least 8 different cloud features, five of which were in the northern hemisphere. Two features could be tracked over a 40-60 degree longitude range, and yield wind velocities of 175 +/- 35 m/s at a latitude of +30o, and of 120 +/- 40 m/s at +40o latitude. The highest latitude reached by HST NICMOS was +27o, where a velocity of 20 m/s was measured (Karkoschka, 1998). Has the wind speed changed? Or is there a very steep gradient in the profile? Our data suggest the wind profile to be similar to that derived for Neptune, though at reduced velocities. This research was supported in part by the STC Program of the National Science Foundation under Agreement No. AST-9876783, and in part under the auspices of the US Department of Energy at Lawrence Livermore National Laboratory, Univ. of Calif. under contract No. W-7405-Eng-48.

  18. Surface estimation methods with phased-arrays for adaptive ultrasonic imaging in complex components

    NASA Astrophysics Data System (ADS)

    Robert, S.; Calmon, P.; Calvo, M.; Le Jeune, L.; Iakovleva, E.

    2015-03-01

    Immersion ultrasonic testing of structures with complex geometries may be significantly improved by using phased-arrays and specific adaptive algorithms that allow to image flaws under a complex and unknown interface. In this context, this paper presents a comparative study of different Surface Estimation Methods (SEM) available in the CIVA software and used for adaptive imaging. These methods are based either on time-of-flight measurements or on image processing. We also introduce a generalized adaptive method where flaws may be fully imaged with half-skip modes. In this method, both the surface and the back-wall of a complex structure are estimated before imaging flaws.

  19. 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…

  20. Quantum Enhanced Imaging by Entangled States

    DTIC Science & Technology

    2009-07-01

    2009 13 . SUPPLEMENTARY NOTES 14. ABSTRACT The use of entangled states in a prospective standoff imaging sensor has been explored. Specifically... 13 FIGURE 6 UNFOLDED VERSION OF SETUP FOR PSEUDO-THERMAL GHOST IMAGING. ....................... 13 FIGURE 7 SYSTEM...ALONG ATMOSPHERIC PATH. (D)-(E) FFTS OF STARTING AND FINAL DISTRIBUTIONS OF BEAM. ABSCISSA IS IN CYCLES PER METER. ......... 22 FIGURE 13 VARIANCE

  1. Multimedia for mobile environment: image enhanced navigation

    NASA Astrophysics Data System (ADS)

    Gautam, Shantanu; Sarkis, Gabi; Tjandranegara, Edwin; Zelkowitz, Evan; Lu, Yung-Hsiang; Delp, Edward J.

    2006-01-01

    As mobile systems (such as laptops and mobile telephones) continue growing, navigation assistance and location-based services are becoming increasingly important. Existing technology allow mobile users to access Internet services (e.g. email and web surfing), simple multimedia services (e.g. music and video clips), and make telephone calls. However, the potential of advanced multimedia services has not been fully developed, especially multimedia for navigation or location based services. At Purdue University, we are developing an image database, known as LAID, in which every image is annotated with its location, compass heading, acquisition time, and weather conditions. LAID can be used to study several types of navigation problems: A mobile user can take an image and transmit the image to the LAID sever. The server compares the image with the images stored in the database to determine where the user is located. We refer to this as the "forward" navigation problem. The second type of problem is to provide a "virtual tour on demand". A user inputs a starting and an ending addresses and LAID retrieves the images along a route that connects the two addresses. This is a generalization of route planning. Our database currently contains over 20000 images and covers approximately 25% of the city of West Lafayette, Indiana.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. Colorimetry-based edge preservation approach for color image enhancement

    NASA Astrophysics Data System (ADS)

    Suresh, Merugu; Jain, Kamal

    2016-07-01

    "Subpixel-based downsampling" is an approach that can implicitly enhance perceptible image resolution of a downsampled image by managing subpixel-level representation preferably with individual pixel. A subpixel-level representation for color image sample at edge region and color image representation is focused with the problem of directional filtration based on horizontal and vertical orientations using colorimetric color space with the help of saturation and desaturation pixels. A diagonal tracing algorithm and an edge preserving approach with colorimetric color space were used for color image enhancement. Since, there exist high variations at the edge regions, it could not be considered as constant or zero, and when these variations are random the need to compensate these to minimum value and then process for image representation. Finally, the results of the proposed method show much better image information as compared with traditional direct pixel-based methods with increased luminance and chrominance resolutions.

  7. Image-based adaptive optics for in vivo imaging in the hippocampus

    PubMed Central

    Champelovier, D.; Teixeira, J.; Conan, J.-M.; Balla, N.; Mugnier, L. M.; Tressard, T.; Reichinnek, S.; Meimon, S.; Cossart, R.; Rigneault, H.; Monneret, S.; Malvache, A.

    2017-01-01

    Adaptive optics is a promising technique for the improvement of microscopy in tissues. A large palette of indirect and direct wavefront sensing methods has been proposed for in vivo imaging in experimental animal models. Application of most of these methods to complex samples suffers from either intrinsic and/or practical difficulties. Here we show a theoretically optimized wavefront correction method for inhomogeneously labeled biological samples. We demonstrate its performance at a depth of 200 μm in brain tissue within a sparsely labeled region such as the pyramidal cell layer of the hippocampus, with cells expressing GCamP6. This method is designed to be sample-independent thanks to an automatic axial locking on objects of interest through the use of an image-based metric that we designed. Using this method, we show an increase of in vivo imaging quality in the hippocampus. PMID:28220868

  8. Image-based adaptive optics for in vivo imaging in the hippocampus

    NASA Astrophysics Data System (ADS)

    Champelovier, D.; Teixeira, J.; Conan, J.-M.; Balla, N.; Mugnier, L. M.; Tressard, T.; Reichinnek, S.; Meimon, S.; Cossart, R.; Rigneault, H.; Monneret, S.; Malvache, A.

    2017-02-01

    Adaptive optics is a promising technique for the improvement of microscopy in tissues. A large palette of indirect and direct wavefront sensing methods has been proposed for in vivo imaging in experimental animal models. Application of most of these methods to complex samples suffers from either intrinsic and/or practical difficulties. Here we show a theoretically optimized wavefront correction method for inhomogeneously labeled biological samples. We demonstrate its performance at a depth of 200 μm in brain tissue within a sparsely labeled region such as the pyramidal cell layer of the hippocampus, with cells expressing GCamP6. This method is designed to be sample-independent thanks to an automatic axial locking on objects of interest through the use of an image-based metric that we designed. Using this method, we show an increase of in vivo imaging quality in the hippocampus.

  9. 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.

  10. 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

  11. "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.

  12. The value of Gd-EOB-DTPA-enhanced MR imaging in characterizing cirrhotic nodules with atypical enhancement on Gd-DTPA-enhanced MR images

    PubMed Central

    Lin, Ching-Po; Chen, Yao-Li; Chen, Yung-Fang; Chen, Ran-Chou

    2017-01-01

    Purpose To evaluate the utility of Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) in characterizing atypically enhanced cirrhotic nodules detected on conventional Gd-DTPA-enhanced MR images. Materials and methods We enrolled 61 consecutive patients with 88 atypical nodules seen on conventional Gd-DTPA-enhanced MR images who underwent Gd-EOB-DTPA-enhanced MRI within a 3-month period. Using a reference standard, we determined that 58 of the nodules were hepatocellular carcinoma (HCC) and 30 were dysplastic nodules (DNs). Tumor size, signal intensity on precontrast T1-weighted images (T1WI), T2-weighted images (T2WI) and diffusion-weighted images (DWI), and the enhancement patterns seen on dynamic phase and hepatocyte phase images were determined. Results There were significant differences between DNs and HCC in hyperintensity on T2WI, hypointensity on T1WI, hypervascularity on arterial phase images, typical HCC enhancement patterns on dynamic MR images, hypointensity on hepatocyte phase images, and hyperintensity on DWI. The sensitivity and specificity were 79.3% and 83.3% for T2WI, 50.0% and 80.0% for T1WI, 82.8% and 76.7% for DWI, 17.2% and 100% for dynamic MR imaging, 93.1% and 83.3% for hepatocyte phase imaging, and 46.8% and 100% when arterial hypervascularity was combined with hypointensity on hepatocyte-phase imaging. Conclusion Gd-EOB-DTPA-enhanced hepatocyte phase imaging is recommended for patients at high risk for HCC who present with atypical lesions on conventional Gd-DTPA-enhanced MR images. PMID:28355258

  13. 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.

  14. 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.

  15. 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.

  16. Enhanced neutron imaging detector using optical processing

    SciTech Connect

    Hutchinson, D.P.; McElhaney, S.A.

    1992-01-01

    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.

  17. 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.

  18. 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.

  19. 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.

  20. 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%].

  1. Performance Comparison Between Adaptive Line Enhancers and FFT for Fast Carrier Acquisition

    NASA Technical Reports Server (NTRS)

    Yeh, H-G.; Nguyen, T.

    1995-01-01

    Three adaptive line enhancer (ALE) algorithms and architectures, namely conventional ALE, ALE with Double Filtering (ALEDF), and ALE with Coherent Accumulation (ALECA) are investigated for fast carrier acquisition in time-domain.

  2. 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

  3. Enhanced 2D-image upconversion using solid-state lasers.

    PubMed

    Pedersen, Christian; Karamehmedović, Emir; Dam, Jeppe Seidelin; Tidemand-Lichtenberg, Peter

    2009-11-09

    Based on enhanced upconversion, we demonstrate a highly efficient method for converting a full image from one part of the electromagnetic spectrum into a new desired wavelength region. By illuminating a metal transmission mask with a 765 nm Gaussian beam to create an image and subsequently focusing the image inside a nonlinear PPKTP crystal located in the high intra-cavity field of a 1342 nm solid-state Nd:YVO(4) laser, an upconverted image at 488 nm is generated. We have experimentally achieved an upconversion efficiency of 40% under CW conditions. The proposed technique can be further adapted for high efficiency mid-infrared image upconversion where direct and fast detection is difficult or impossible to perform with existing detector technologies.

  4. An enhanced segmentation of blood vessels in retinal images using contourlet.

    PubMed

    Rezatofighi, S H; Roodaki, A; Ahmadi Noubari, H

    2008-01-01

    Retinal images acquired using a fundus camera often contain low grey, low level contrast and are of low dynamic range. This may seriously affect the automatic segmentation stage and subsequent results; hence, it is necessary to carry-out preprocessing to improve image contrast results before segmentation. Here we present a new multi-scale method for retinal image contrast enhancement using Contourlet transform. In this paper, a combination of feature extraction approach which utilizes Local Binary Pattern (LBP), morphological method and spatial image processing is proposed for segmenting the retinal blood vessels in optic fundus images. Furthermore, performance of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multilayer Perceptron (MLP) is investigated in the classification section. The performance of the proposed algorithm is tested on the publicly available DRIVE database. The results are numerically assessed for different proposed algorithms.

  5. Social enhancement can create adaptive, arbitrary and maladaptive cultural traditions.

    PubMed

    Franz, Mathias; Matthews, Luke J

    2010-11-07

    Many animals are known to learn socially, i.e. they are able to acquire new behaviours by using information from other individuals. Researchers distinguish between a number of different social-learning mechanisms such as imitation and social enhancement. Social enhancement is a simple form of social learning that is among the most widespread in animals. However, unlike imitation, it is debated whether social enhancement can create cultural traditions. Based on a recent study on capuchin monkeys, we developed an agent-based model to test the hypotheses that (i) social enhancement can create and maintain stable traditions and (ii) social enhancement can create cultural conformity. Our results supported both hypotheses. A key factor that led to the creation of cultural conformity and traditions was the repeated interaction of individual reinforcement and social enhancement learning. This result emphasizes that the emergence of cultural conformity does not necessarily require cognitively complex mechanisms such as 'copying the majority' or group norms. In addition, we observed that social enhancement can create learning dynamics similar to a 'copy when uncertain' learning strategy. Results from additional analyses also point to situations that should favour the evolution of learning mechanisms more sophisticated than social enhancement.

  6. Enhancing Adaptive Filtering Approaches for Land Data Assimilation Systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent work has presented the initial application of adaptive filtering techniques to land surface data assimilation systems. Such techniques are motivated by our current lack of knowledge concerning the structure of large-scale error in either land surface modeling output or remotely-sensed estima...

  7. Adapting ISA system warnings to enhance user acceptance.

    PubMed

    Jiménez, Felipe; Liang, Yingzhen; Aparicio, Francisco

    2012-09-01

    Inappropriate speed is a major cause of traffic accidents. Different measures have been considered to control traffic speed, and intelligent speed adaptation (ISA) systems are one of the alternatives. These systems know the speed limits and try to improve compliance with them. This paper deals with an informative ISA system that provides the driver with an advance warning before reaching a road section with singular characteristics that require a lower safe speed than the current speed. In spite of the extensive tests performed using ISA systems, few works show how warnings can be adapted to the driver. This paper describes a method to adapt warning parameters (safe speed on curves, zone of influence of a singular stretch, deceleration process and reaction time) to normal driving behavior. The method is based on a set of tests with and without the ISA system. This adjustment, as well as the analysis of driver acceptance before and after the adaptation and changes in driver behavior (changes in speed and path) resulting from the tested ISA regarding a driver's normal driving style, is shown in this paper. The main conclusion is that acceptance by drivers increased significantly after redefining the warning parameters, but the effect of speed homogenization was not reduced.

  8. Structurally enhanced incremental neural learning for image classification with subgraph extraction.

    PubMed

    Yang, Yu-Bin; Li, Ya-Nan; Gao, Yang; Yin, Hujun; Tang, Ye

    2014-11-01

    In this paper, a structurally enhanced incremental neural learning technique is proposed to learn a discriminative codebook representation of images for effective image classification applications. In order to accommodate the relationships such as structures and distributions among visual words into the codebook learning process, we develop an online codebook graph learning method based on a novel structurally enhanced incremental learning technique, called as "visualization-induced self-organized incremental neural network (ViSOINN)". The hidden structural information in the images is embedded into the graph representation evolving dynamically with the adaptive and competitive learning mechanism. Afterwards, image features can be coded using a sub-graph extraction process based on the learned codebook graph, and a classifier is subsequently used to complete the image classification task. Compared with other codebook learning algorithms originated from the classical Bag-of-Features (BoF) model, ViSOINN holds the following advantages: (1) it learns codebook efficiently and effectively from a small training set; (2) it models the relationships among visual words in metric scaling fashion, so preserving high discriminative power; (3) it automatically learns the codebook without a fixed pre-defined size; and (4) it enhances and preserves better the structure of the data. These characteristics help to improve image classification performance and make it more suitable for handling large-scale image classification tasks. Experimental results on the widely used Caltech-101 and Caltech-256 benchmark datasets demonstrate that ViSOINN achieves markedly improved performance and reduces the computational cost considerably.

  9. 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.

  10. 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.

  11. 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

  12. Functional magnetic resonance imaging adaptation reveals a noncategorical representation of hue in early visual cortex

    PubMed Central

    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

  13. 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.

  14. 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.

  15. Enhanced Polarimetric Radar Imaging Using Cross-Channel Coupling Constraints

    DTIC Science & Technology

    2014-06-19

    classification. Overall, the jointly enhanced image channels displayed significantly better polarimet- ric preservation compared to the corresponding...Potter, E. Ertin, J. T. Parker , and M. Cetin, “Sparsity and compressed sensing in radar imaging,” Proceedings of the IEEE, vol. 98, no. 6, pp. 1006

  16. Image classification with densely sampled image windows and generalized adaptive multiple kernel learning.

    PubMed

    Yan, Shengye; Xu, Xinxing; Xu, Dong; Lin, Stephen; Li, Xuelong

    2015-03-01

    We present a framework for image classification that extends beyond the window sampling of fixed spatial pyramids and is supported by a new learning algorithm. Based on the observation that fixed spatial pyramids sample a rather limited subset of the possible image windows, we propose a method that accounts for a comprehensive set of windows densely sampled over location, size, and aspect ratio. A concise high-level image feature is derived to effectively deal with this large set of windows, and this higher level of abstraction offers both efficient handling of the dense samples and reduced sensitivity to misalignment. In addition to dense window sampling, we introduce generalized adaptive l(p)-norm multiple kernel learning (GA-MKL) to learn a robust classifier based on multiple base kernels constructed from the new image features and multiple sets of prelearned classifiers from other classes. With GA-MKL, multiple levels of image features are effectively fused, and information is shared among different classifiers. Extensive evaluation on benchmark datasets for object recognition (Caltech256 and Caltech101) and scene recognition (15Scenes) demonstrate that the proposed method outperforms the state-of-the-art under a broad range of settings.

  17. 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.

  18. 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.

  19. 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

  20. Gradient histogram estimation and preservation for texture enhanced image denoising.

    PubMed

    Zuo, Wangmeng; Zhang, Lei; Song, Chunwei; Zhang, David; Gao, Huijun

    2014-06-01

    Natural image statistics plays an important role in image denoising, and various natural image priors, including gradient-based, sparse representation-based, and nonlocal self-similarity-based ones, have been widely studied and exploited for noise removal. In spite of the great success of many denoising algorithms, they tend to smooth the fine scale image textures when removing noise, degrading the image visual quality. To address this problem, in this paper, we propose a texture enhanced image denoising method by enforcing the gradient histogram of the denoised image to be close to a reference gradient histogram of the original image. Given the reference gradient histogram, a novel gradient histogram preservation (GHP) algorithm is developed to enhance the texture structures while removing noise. Two region-based variants of GHP are proposed for the denoising of images consisting of regions with different textures. An algorithm is also developed to effectively estimate the reference gradient histogram from the noisy observation of the unknown image. Our experimental results demonstrate that the proposed GHP algorithm can well preserve the texture appearance in the denoised images, making them look more natural.

  1. 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.

  2. Adaptive field-of-view imaging for efficient receive beamforming in medical ultrasound imaging systems.

    PubMed

    Agarwal, Anup; Yoo, Yang Mo; Schneider, Fabio Kurt; Kim, Yongmin

    2008-09-01

    Quadrature demodulation-based phase rotation beamforming (QD-PRBF) is commonly used to support dynamic receive focusing in medical ultrasound systems. However, it is computationally demanding since it requires two demodulation filters for each receive channel. To reduce the computational requirements of QD-PRBF, we have previously developed two-stage demodulation (TSD), which reduces the number of lowpass filters by performing demodulation filtering on summation signals. However, it suffers from image quality degradation due to aliasing at lower beamforming frequencies. To improve the performance of TSD-PRBF with reduced number of beamforming points, we propose a new adaptive field-of-view (AFOV) imaging method. In AFOV imaging, the beamforming frequency is adjusted depending on displayed FOV size and the center frequency of received signals. To study its impact on image quality, simulation was conducted using Field II, phantom data were acquired from a commercial ultrasound machine, and the image quality was quantified using spatial (i.e., axial and lateral) and contrast resolution. The developed beamformer (i.e., TSD-AFOV-PRBF) with 1024 beamforming points provided comparable image resolution to QD-PRBF for typical FOV sizes (e.g., 4.6% and 1.3% degradation in contrast resolution for 160 mm and 112 mm, respectively for a 3.5 MHz transducer). Furthermore, it reduced the number of operations by 86.8% compared to QD-PRBF. These results indicate that the developed TSD-AFOV-PRBF can lower the computational requirement for receive beamforming without significant image quality degradation.

  3. 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

  4. A Programmable Liquid Collimator for Both Coded Aperture Adaptive Imaging and Multiplexed Compton Scatter Tomography

    DTIC Science & Technology

    2012-03-01

    Assessment of COMSCAN, A Compton Backscatter Imaging Camera , for the One-Sided Non-Destructive Inspection of Aerospace Compo- nents. Technical report...A PROGRAMMABLE LIQUID COLLIMATOR FOR BOTH CODED APERTURE ADAPTIVE IMAGING AND MULTIPLEXED COMPTON SCATTER TOMOGRAPHY THESIS Jack G. M. FitzGerald, 2d...LIQUID COLLIMATOR FOR BOTH CODED APERTURE ADAPTIVE IMAGING AND MULTIPLEXED COMPTON SCATTER TOMOGRAPHY THESIS Presented to the Faculty Department of

  5. 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.

  6. Rician noise reduction in magnetic resonance images using adaptive non-local mean and guided image filtering

    NASA Astrophysics Data System (ADS)

    Mahmood, Muhammad Tariq; Chu, Yeon-Ho; Choi, Young-Kyu

    2016-06-01

    This paper proposes a Rician noise reduction method for magnetic resonance (MR) images. The proposed method is based on adaptive non-local mean and guided image filtering techniques. In the first phase, a guidance image is obtained from the noisy image through an adaptive non-local mean filter. Sobel operators are applied to compute the strength of edges which is further used to control the spread of the kernel in non-local mean filtering. In the second phase, the noisy and the guidance images are provided to the guided image filter as input to restore the noise-free image. The improved performance of the proposed method is investigated using the simulated and real data sets of MR images. Its performance is also compared with the previously proposed state-of-the art methods. Comparative analysis demonstrates the superiority of the proposed scheme over the existing approaches.

  7. An improvement to the diffraction-enhanced imaging method that permits imaging of dynamic systems

    NASA Astrophysics Data System (ADS)

    Siu, K. K. W.; Kitchen, M. J.; Pavlov, K. M.; Gillam, J. E.; Lewis, R. A.; Uesugi, K.; Yagi, N.

    2005-08-01

    We present an improvement to the diffraction-enhanced imaging (DEI) method that permits imaging of moving samples or other dynamic systems in real time. The method relies on the use of a thin Bragg analyzer crystal and simultaneous acquisition of the multiple images necessary for the DEI reconstruction of the apparent absorption and refraction images. These images are conventionally acquired at multiple points on the reflectivity curve of an analyzer crystal which presents technical challenges and precludes imaging of moving subjects. We have demonstrated the potential of the technique by taking DEI "movies" of an artificially moving mouse leg joint, acquired at the Biomedical Imaging Centre at SPring-8, Japan.

  8. Image enhancement of optical images for binary system of melanocytes and keratinocytes

    NASA Astrophysics Data System (ADS)

    Takanezawa, S.; Baba, A.; Sako, Y.; Ozaki, Y.; Date, A.; Toyama, K.; Morita, S.

    2013-05-01

    Automatic determination of the cell shapes of large numbers of melanocytes based on optical images of human skin models have been largely unsuccessful (the complexities introduced by dendrites and the melanin pigmentation over the keratinocytes to give unclear outlines). Here, we present an image enhancement procedure for enhancing the contrast of images with removing the non-uniformity of background. The brightness is normalized also for the non-uniform population density of melanocytes.

  9. 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 ...

  10. Color image enhancement using correlated intensity and saturation adjustments

    NASA Astrophysics Data System (ADS)

    Kwok, Ngaiming; Shi, Haiyan; Fang, Gu; Ha, Quang; Yu, Ying-Hao; Wu, Tonghai; Li, Huaizhong; Nguyen, Thai

    2015-07-01

    The enhancement of digital color images needs to be performed in accordance with human perception in terms of hue, saturation, and intensity attributes instead of improving only the contrast. Two approaches were developed in this work, which use a correlated adjustment mechanism incorporating intensity and saturation attributes and provide contrast and saturation enhancements together with brightness consistency. In these algorithms, object edges are emphasized for contrast, and image saturation is increased by boosting the salient regions. Furthermore, intensity and saturation enhancements are carried out in a lattice structure where adjustments are made inter-related for better performance. Experiments were conducted with benchmark and real-world images. Results had shown improvements in image qualities both qualitatively and quantitatively.

  11. 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.

  12. 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

  13. Noise suppression and details enhancement for infrared image via novel prior

    NASA Astrophysics Data System (ADS)

    Fan, Zunlin; Bi, Duyan; He, Linyuan; Ma, Shiping

    2016-01-01

    Infrared images always suffer from blurring edges, fewer details and low signal-to-noise ratio. So, sharpening edges and suppressing noise become the urgent techniques in infrared image technology field. However, they are contradictories in most cases. Hence, to depict correctly infrared image features under low signal-to-noise ratio circumstance, a novel prior, which is immune to noise, is presented in this paper. The proposed method scopes noise suppression and details enhancement. In noise suppression, the prior is introduced into Bayesian model to obtain optimal estimation through iteration. In details enhancement, based on the proposed prior, the final image is obtained by the improved unsharp mask algorithm which enhances adaptively details and edges of optimal estimation. The effectiveness and robustness of the proposed method is analyzed by testing the infrared images obtained from different signal-to-noise ratio conditions. Compared with other well-established methods, the proposed method shows a significant performance in terms of noise suppression, actual scene reappearance, enhancing the details and sharpening edges.

  14. Measurement depth enhancement in terahertz imaging of biological tissues.

    PubMed

    Oh, Seung Jae; Kim, Sang-Hoon; Jeong, Kiyoung; Park, Yeonji; Huh, Yong-Min; Son, Joo-Hiuk; Suh, Jin-Suck

    2013-09-09

    We demonstrate the use of a THz penetration-enhancing agent (THz-PEA) to enhance the terahertz (THz) wave penetration depth in tissues. The THz-PEA is a biocompatible material having absorption lower than that of water, and it is easily absorbed into tissues. When using glycerol as a THz-PEA, the peak value of the THz signal which was transmitted through the fresh tissue and reflected by a metal target, was almost doubled compared to that of tissue without glycerol. THz time-of-flight imaging (B-scan) was used to display the sequential glycerol delivery images. Enhancement of the penetration depth was confirmed after an artificial tumor was located below fresh skin. We thus concluded that the THz-PEA technique can potentially be employed to enhance the image contrast of the abnormal lesions below the skin.

  15. Calculation of intravascular signal in dynamic contrast enhanced-MRI using adaptive complex independent component analysis.

    PubMed

    Mehrabian, Hatef; Chopra, Rajiv; Martel, Anne L

    2013-04-01

    Assessing tumor response to therapy is a crucial step in personalized treatments. Pharmacokinetic (PK) modeling provides quantitative information about tumor perfusion and vascular permeability that are associated with prognostic factors. A fundamental step in most PK analyses is calculating the signal that is generated in the tumor vasculature. This signal is usually inseparable from the extravascular extracellular signal. It was shown previously using in vivo and phantom experiments that independent component analysis (ICA) is capable of calculating the intravascular time-intensity curve in dynamic contrast enhanced (DCE)-MRI. A novel adaptive complex independent component analysis (AC-ICA) technique is developed in this study to calculate the intravascular time-intensity curve and separate this signal from the DCE-MR images of tumors. The use of the complex-valued DCE-MRI images rather than the commonly used magnitude images satisfied the fundamental assumption of ICA, i.e., linear mixing of the sources. Using an adaptive cost function in ICA through estimating the probability distribution of the tumor vasculature at each iteration resulted in a more robust and accurate separation algorithm. The AC-ICA algorithm provided a better estimate for the intravascular time-intensity curve than the previous ICA-based method. A simulation study was also developed in this study to realistically simulate DCE-MRI data of a leaky tissue mimicking phantom. The passage of the MR contrast agent through the leaky phantom was modeled with finite element analysis using a diffusion model. Once the distribution of the contrast agent in the imaging field of view was calculated, DCE-MRI data was generated by solving the Bloch equation for each voxel at each time point. The intravascular time-intensity curve calculation results were compared to the previously proposed ICA-based intravascular time-intensity curve calculation method that applied ICA to the magnitude of the DCE-MRI data

  16. Theory of enhancing thermal imaging through fire

    NASA Astrophysics Data System (ADS)

    Cha, Jae H.; Abbott, A. Lynn; Krapels, Keith A.; Szu, Harold H.

    2014-05-01

    Fire can overwhelm the field of view of a thermal imaging sensor with intensive radiation, and when presented to observers can cause important cues in the scene to go unnoticed due to the limited dynamic range of displays and of the human visual system. Here we propose a computational method, called software-defined camera (SDC), to improve the image quality for an un-cooled thermal imager seeing through fire that obscures lower-temperature objects in the background. To that end, we developed a novel theory for the arbitrary manipulation of optical radiation sources, which is based on rigorous application of Boltzmann's molecular thermodynamics. On this framework it is possible to formulate the problem of identification and selective removal/suppression of the optical radiation sources, and thus to design a blind source separation algorithm. Application of the developed theory should make it possible to design a low-cost specialty SDC that is able to see through high temperature fire for locating a relatively low temperature objects such as a human body.

  17. MR images restoration with the use of fuzzy filter having adaptive membership parameters.

    PubMed

    Güler, I; Toprak, A; Demirhan, A; Karakiş, R

    2008-06-01

    A new fuzzy adaptive median filter is presented for the noise reduction of magnetic resonance images corrupted with heavy impulse (salt and pepper) noise. In this paper, we have proposed a Fuzzy Adaptive Median Filter with Adaptive Membership Parameters (FAMFAMP) for removing highly corrupted salt and pepper noise, with preserving image edges and details. The FAMFAMP filter is an improved version of Adaptive Median Filter (AMF) and is presented in the aim of noise reduction of images corrupted with additive impulse noise. The proposed filter can preserve image details better than AMF while suppressing additive salt and pepper or impulse type noise. In this paper, we placed our preference on bell-shaped membership function with adaptive parameters instead of triangular membership function without variable coefficients in order to observe better results.

  18. “Lucky Averaging”: Quality improvement on Adaptive Optics Scanning Laser Ophthalmoscope Images

    PubMed Central

    Huang, Gang; Zhong, Zhangyi; Zou, Weiyao; Burns, Stephen A.

    2012-01-01

    Adaptive optics(AO) has greatly improved retinal image resolution. However, even with AO, temporal and spatial variations in image quality still occur due to wavefront fluctuations, intra-frame focus shifts and other factors. As a result, aligning and averaging images can produce a mean image that has lower resolution or contrast than the best images within a sequence. To address this, we propose an image post-processing scheme called “lucky averaging”, analogous to lucky imaging (Fried, 1978) based on computing the best local contrast over time. Results from eye data demonstrate improvements in image quality. PMID:21964097

  19. 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

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF DEFENSE Office 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...

  20. 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.

  1. Enhancement Of Visual Evoked Potentials By Adaptive Processing

    NASA Astrophysics Data System (ADS)

    Wolf, W.; Appel, U.; Rauner, H.

    1982-11-01

    Transient evoked potentials (EP) are variations of the on-going electroencephalogram (EEG) in response to the application of sensory stimuli. Since their amplitudes are very small in comparison to the spontaneous EEG, signal extraction methods must be applied to them before their characteristics are measureable. Several signal ex-traction methods which are actually used in EP research are outlined, especially those showing an adaptive characteristic. As a further development, a new method is proposed which considers the on-going EEG preceding the stimulus application for the EP processing. The computational procedure will be described and some preliminary results are given.

  2. Enhancement of astronomical images using digital filtration methods

    NASA Astrophysics Data System (ADS)

    Korovyakovskaya, A. A.; Korovyakovskij, Y. P.

    1982-02-01

    A technique for reconstructing astronomical images using digital filtration is presented. A quantitative description of the factors causing image distortion is presented, and an algorithm for image enhancement is developed. The frequency characteristics of the reconstructing filter are given for the distorting system and the signal-to-noise ratio. Consideration is given to two-dimensional Fourier transform of the large image matrices. The technique is examined for the M 87 radio galaxy and an improvement of 2-3 times in the angular resolution of the original photograph is demonstrated.

  3. 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.

  4. 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.

  5. 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

  6. Efficiency enhancement of RELAP/PANBOX using adaptive spatial kinetics

    SciTech Connect

    Jackson, C.J.; Cacuci, D.G.; Finnemann, H.B.

    1996-12-31

    The coupled RELAP/PANBOX code system was developed to analyze more accurately those pressurized water reactor (PWR) plant transients in which the core neutron flux distribution changes significantly in time. Examples of such transients are those initiated by steam-line breaks and rapid boron dilution events. On the other hand, instances may occur during long thermal-hydraulic transients when the neutron flux shape varies slowly in time. During such slow transients, a one-dimensional (1-D) model in the axial direction or a point-kinetics model, rather than a three-dimensional (3-D) one, would suffice to calculate the power distribution. To switch between 3-D, 1-D, and/or point-kinetics models, it is very advantageous to generate the respective 1-D and/or point-kinetics parameters automatically and internally within the code. In this paper, the authors describe the features of an adaptive spatial kinetics algorithm that performs the switching process between 3-D and 1-D and/or point-kinetics models according to the physical phenomena underlying the specific plant transient under investigation. The adaptive algorithm has been implemented as a module of the core simulation package PANBOX and therefore does not disturb the subroutines that couple PANBOX to RELAP.

  7. Application of adaptive wavelet transforms via lifting in image data compression

    NASA Astrophysics Data System (ADS)

    Ye, Shujiang; Zhang, Ye; Liu, Baisen

    2008-10-01

    The adaptive wavelet transforms via lifting is proposed. In the transform, update filter is selected by the signal's character. Perfect reconstruction is possible without any overhead cost. To make sure the system's stability, in the lifting scheme of adaptive wavelet, update step is placed before prediction step. The Adaptive wavelet transforms via lifting is benefit for the image compression, because of the high stability, the small coefficients of high frequency parts, and the perfect reconstruction. With the adaptive wavelet transforms via lifting and the SPIHT, the image compression is realized in this paper, and the result is pleasant.

  8. 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

  9. Image Enhancement and Display Techniques Applied to SAR580 Images of Ships

    DTIC Science & Technology

    1987-04-01

    applied to the images. This report discusses tht properties of SAR ship returns, reviews the various types of image enhancement techniques applied to...Figures , , a . . . . , , , . . . , . . . . , . . iii I. INTRODUCTION . . . . . . . . . . . . I 2. PROPERTIES OF SAR SHIP IMAGES ... ... ...... I 3...Page 1 Original Ship Photos 5 2 Ship Profile and Plan Views 9 3 SAR Ship Images 14 4 SAR Contour Plots 16 5 SAR Three-Dimensional Plots 19 6 Container

  10. Enhancement of Microbial Biodesulfurization via Genetic Engineering and Adaptive Evolution

    PubMed Central

    Wang, Jia; Butler, Robert R.; Wu, Fan; Pombert, Jean-François; Kilbane, John J.; Stark, Benjamin C.

    2017-01-01

    In previous work from our laboratories a synthetic gene encoding a peptide (“Sulpeptide 1” or “S1”) with a high proportion of methionine and cysteine residues had been designed to act as a sulfur sink and was inserted into the dsz (desulfurization) operon of Rhodococcus erythropolis IGTS8. In the work described here this construct (dszAS1BC) and the intact dsz operon (dszABC) cloned into vector pRESX under control of the (Rhodococcus) kstD promoter were transformed into the desulfurization-negative strain CW25 of Rhodococcus qingshengii. The resulting strains (CW25[pRESX-dszABC] and CW25[pRESX-dszAS1BC]) were subjected to adaptive selection by repeated passages at log phase (up to 100 times) in minimal medium with dibenzothiophene (DBT) as sole sulfur source. For both strains DBT metabolism peaked early in the selection process and then decreased, eventually averaging four times that of the initial transformed cells; the maximum specific activity achieved by CW25[pRESX-dszAS1BC] exceeded that of CW25[pRESX-dszABC]. Growth rates increased by 7-fold (CW25[pRESX-dszABC]) and 13-fold (CW25[pRESX-dszAS1BC]) and these increases were stable. The adaptations of CW25[pRESX-dszAS1BC] were correlated with a 3-5X increase in plasmid copy numbers from those of the initial transformed cells; whole genome sequencing indicated that during its selection processes no mutations occurred to any of the dsz, S1, or other genes and promoters involved in sulfur metabolism, stress response, or DNA methylation, and that the effect of the sulfur sink produced by S1 is likely very small compared to the cells’ overall cysteine and methionine requirements. Nevertheless, a combination of genetic engineering using sulfur sinks and increasing Dsz capability with adaptive selection may be a viable strategy to increase biodesulfurization ability. PMID:28060828

  11. Enhancing imaging systems using transformation optics.

    PubMed

    Smith, David R; Urzhumov, Yaroslav; Kundtz, Nathan B; Landy, Nathan I

    2010-09-27

    We apply the transformation optical technique to modify or improve conventional refractive and gradient index optical imaging devices. In particular, when it is known that a detector will terminate the paths of rays over some surface, more freedom is available in the transformation approach, since the wave behavior over a large portion of the domain becomes unimportant. For the analyzed configurations, quasi-conformal and conformal coordinate transformations can be used, leading to simplified constitutive parameter distributions that, in some cases, can be realized with isotropic index; index-only media can be low-loss and have broad bandwidth. We apply a coordinate transformation to flatten a Maxwell fish-eye lens, forming a near-perfect relay lens; and also flatten the focal surface associated with a conventional refractive lens, such that the system exhibits an ultra-wide field-of-view with reduced aberration.

  12. Adaptive enhancement of magnetoencephalographic signals via multichannel filtering

    SciTech Connect

    Lewis, P.S.

    1989-01-01

    A time-varying spatial/temporal filter for enhancing multichannel magnetoencephalographic (MEG) recordings of evoked responses is described. This filter is based in projections derived from a combination of measured data and a priori models of the expected response. It produces estimates of the evoked fields in single trial measurements. These estimates can reduce the need for signal averaging in some situations. The filter uses the a priori model information to enhance responses where they exist, but avoids creating responses that do not exist. Examples are included of the filter's application to both MEG single trial data containing an auditory evoked field and control data with no evoked field. 5 refs., 7 figs.

  13. 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

  14. 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.

  15. Evaluation of image-enhanced paediatric computed tomography brain examinations.

    PubMed

    Ledenius, K; Stålhammar, F; Wiklund, L M; Fredriksson, C; Forsberg, A; Thilander-Klang, A

    2010-01-01

    The aim of this study was to evaluate the possibility of reducing the radiation dose to paediatric patients undergoing computed tomography (CT) brain examination by using image-enhancing software. Artificial noise was added to the raw data collected from 20 patients aged between 1 and 10 y to simulate tube current reductions of 20, 40 and 60 mA. All images were created in duplicate; one set of images remained unprocessed whereas the other was processed with image-enhancing software. Three paediatric radiologists assessed the image quality based on their ability to visualise the high- and low-contrast structures and their overall impression of the diagnostic value of the image. For patients aged 6-10 y, it was found that dose reductions from 27 mGy (CTDI(vol)) to 23 mGy (15 %) in the upper brain and from 32 to 28 mGy (13 %) in the lower brain were possible for standard diagnostic CT examinations when using the image-enhancing filter. For patients 1-5 y, the results for standard diagnostics in the upper brain were inconclusive, for the lower brain no dose reductions were found possible.

  16. 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.

  17. Restoration and enhancement of textural properties in SAR images using second-order statistics

    NASA Astrophysics Data System (ADS)

    Nezry, Edmond; Kohl, Hans-Guenther; De Groof, Hugo

    1994-12-01

    Local second order properties, describing spatial relations between pixels are introduced into the single-point speckle adaptive filtering processes, in order to account for the effects of speckle spatial correlation and to enhance scene textural properties in the restored image. To this end, texture measures originating, first from local grey level co-occurrence matrices (GLCM), and second from the local autocorrelation functions (ACF) are used. Results obtained on 3-look processed ERS-1 FDC and PRI spaceborne images illustrate the performance allowed by the introduction of these texture measures in the structure retaining speckle adaptive filters. The observable texture in remote sensing images is related to the physical spatial resolution of the sensor. For this reason, other spatial speckle decorrelation methods, more simple and easier to implement, for example post-filtering and linear image resampling, are also presented in this paper. In the particular case of spaceborne SAR imagery, all these methods lead to visually similar results. They produce filtered (radar reflectivity) images visually comparable to optical images.

  18. Instrumentation For Diffraction Enhanced Imaging Experiments At HASYLAB

    SciTech Connect

    Lohmann, M.; Dix, W.-R.; Metge, J.; Reime, B.

    2004-05-12

    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.

  19. Self-adaptive image denoising based on bidimensional empirical mode decomposition (BEMD).

    PubMed

    Guo, Song; Luan, Fangjun; Song, Xiaoyu; Li, Changyou

    2014-01-01

    To better analyze images with the Gaussian white noise, it is necessary to remove the noise before image processing. In this paper, we propose a self-adaptive image denoising method based on bidimensional empirical mode decomposition (BEMD). Firstly, normal probability plot confirms that 2D-IMF of Gaussian white noise images decomposed by BEMD follow the normal distribution. Secondly, energy estimation equation of the ith 2D-IMF (i=2,3,4,......) is proposed referencing that of ith IMF (i=2,3,4,......) obtained by empirical mode decomposition (EMD). Thirdly, the self-adaptive threshold of each 2D-IMF is calculated. Eventually, the algorithm of the self-adaptive image denoising method based on BEMD is described. From the practical perspective, this is applied for denoising of the magnetic resonance images (MRI) of the brain. And the results show it has a better denoising performance compared with other methods.

  20. 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.

  1. Influence of adaptive statistical iterative reconstruction algorithm on image quality in coronary computed tomography angiography

    PubMed Central

    Thygesen, Jesper; Gerke, Oke; Egstrup, Kenneth; Waaler, Dag; Lambrechtsen, Jess

    2016-01-01

    Background Coronary computed tomography angiography (CCTA) requires high spatial and temporal resolution, increased low contrast resolution for the assessment of coronary artery stenosis, plaque detection, and/or non-coronary pathology. Therefore, new reconstruction algorithms, particularly iterative reconstruction (IR) techniques, have been developed in an attempt to improve image quality with no cost in radiation exposure. Purpose To evaluate whether adaptive statistical iterative reconstruction (ASIR) enhances perceived image quality in CCTA compared to filtered back projection (FBP). Material and Methods Thirty patients underwent CCTA due to suspected coronary artery disease. Images were reconstructed using FBP, 30% ASIR, and 60% ASIR. Ninety image sets were evaluated by five observers using the subjective visual grading analysis (VGA) and assessed by proportional odds modeling. Objective quality assessment (contrast, noise, and the contrast-to-noise ratio [CNR]) was analyzed with linear mixed effects modeling on log-transformed data. The need for ethical approval was waived by the local ethics committee as the study only involved anonymously collected clinical data. Results VGA showed significant improvements in sharpness by comparing FBP with ASIR, resulting in odds ratios of 1.54 for 30% ASIR and 1.89 for 60% ASIR (P = 0.004). The objective measures showed significant differences between FBP and 60% ASIR (P < 0.0001) for noise, with an estimated ratio of 0.82, and for CNR, with an estimated ratio of 1.26. Conclusion ASIR improved the subjective image quality of parameter sharpness and, objectively, reduced noise and increased CNR.

  2. Ultrasound image enhancement using structure-based filtering.

    PubMed

    Ueng, Shyh-Kuang; Yen, Cho-Li; Chen, Guan-Zhi

    2014-01-01

    Ultrasound images are prone to speckle noises. Speckles blur features which are essential for diagnosis and assessment. Thus despeckling is a necessity in ultrasound image processing. Linear filters can suppress speckles, but they smooth out features. Median filter based despeckling algorithms produce better results. However, they may produce artifact patterns in the resulted images and oversmooth nonuniform regions. This paper presents an innovative despeckle procedure for ultrasound images. In the proposed method, the diffusion tensor of intensity is computed at each pixel at first. Then the eigensystem of the diffusion tensor is calculated and employed to detect and classify the underlying structure. Based on the classification result, a feasible filter is selected to suppress speckles and enhance features. Test results show that the proposed despeckle method reduces speckles in uniform areas and enhances tissue boundaries and spots.

  3. 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.

  4. Tip Enhanced Raman Spectroscopy and Imaging: an Apical Illumination Geometry

    PubMed Central

    Schultz, Zachary D.; Stranick, Stephan J.; Levin, Ira W.

    2009-01-01

    Results are presented illustrating the use of tip enhanced Raman spectroscopy and imaging in a top-illumination geometry. A radially polarized beam is used to generate an electric field component in the direction of beam propagation, normal to the surface, resulting in a 5× increased enhancement compared to a linearly polarized beam. This multiplicative enhancement facilitates a discrimination of the near field signal from the far field Raman background. The top illumination configuration facilitates the application of TERS for investigating molecules on a variety of surfaces, such as Au, glass, and Si. The near field Raman spectrum is presented of Si(100), rhodamine B, brilliant cresyl blue, and single wall carbon nanotubes. Sufficient enhancement is obtained to permit a sub-diffraction limited resolution Raman imaging of the surface distribution of large bundles of carbon nanotubes of various diameters. PMID:19007457

  5. 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.

  6. Blind image deblurring with edge enhancing total variation regularization

    NASA Astrophysics Data System (ADS)

    Shi, Yu; Hong, Hanyu; Song, Jie; Hua, Xia

    2015-04-01

    Blind image deblurring is an important issue. In this paper, we focus on solving this issue by constrained regularization method. Motivated by the importance of edges to visual perception, the edge-enhancing indicator is introduced to constrain the total variation regularization, and the bilateral filter is used for edge-preserving smoothing. The proposed edge enhancing regularization method aims to smooth preferably within each region and preserve edges. Experiments on simulated and real motion blurred images show that the proposed method is competitive with recent state-of-the-art total variation methods.

  7. 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.

  8. Hybridization can facilitate species invasions, even without enhancing local adaptation

    PubMed Central

    Mesgaran, Mohsen B.; Lewis, Mark A.; Ades, Peter K.; Donohue, Kathleen; Ohadi, Sara; Li, Chengjun

    2016-01-01

    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

  9. Adaptive clutter filter in 2-D color flow imaging based on in vivo I/Q signal.

    PubMed

    Zhou, Xiaoming; Zhang, Congyao; Liu, Dong C

    2014-01-01

    Color flow imaging has been well applied in clinical diagnosis. For the high quality color flow images, clutter filter is important to separate the Doppler signals from blood and tissue. Traditional clutter filters, such as finite impulse response, infinite impulse response and regression filters, were applied, which are based on the hypothesis that the clutter signal is stationary or tissue moves slowly. However, in realistic clinic color flow imaging, the signals are non-stationary signals because of accelerated moving tissue. For most related papers, simulated RF signals are widely used without in vivo I/Q signal. Hence, in this paper, adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, was proposed based on in vivo carotid I/Q signal in realistic color flow imaging. To get the best performance, the optimal polynomial order of polynomial regression filter and the optimal polynomial order for estimation of instantaneous clutter frequency respectively were confirmed. Finally, compared with the mean blood velocity and quality of 2-D color flow image, the experiment results show that adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, can significantly enhance the mean blood velocity and get high quality 2-D color flow image.

  10. An adaptive non-local means filter for denoising live-cell images and improving particle detection.

    PubMed

    Yang, Lei; Parton, Richard; Ball, Graeme; Qiu, Zhen; Greenaway, Alan H; Davis, Ilan; Lu, Weiping

    2010-12-01

    Fluorescence imaging of dynamical processes in live cells often results in a low signal-to-noise ratio. We present a novel feature-preserving non-local means approach to denoise such images to improve feature recovery and particle detection. The commonly used non-local means filter is not optimal for noisy biological images containing small features of interest because image noise prevents accurate determination of the correct coefficients for averaging, leading to over-smoothing and other artifacts. Our adaptive method addresses this problem by constructing a particle feature probability image, which is based on Haar-like feature extraction. The particle probability image is then used to improve the estimation of the correct coefficients for averaging. We show that this filter achieves higher peak signal-to-noise ratio in denoised images and has a greater capability in identifying weak particles when applied to synthetic data. We have applied this approach to live-cell images resulting in enhanced detection of end-binding-protein 1 foci on dynamically extending microtubules in photo-sensitive Drosophila tissues. We show that our feature-preserving non-local means filter can reduce the threshold of imaging conditions required to obtain meaningful data.

  11. The role of the microprocessor in onboard image processing for the information adaptive system

    NASA Technical Reports Server (NTRS)

    Kelly, W. L., IV; Meredith, B. D.

    1980-01-01

    The preliminary design of the Information Adaptive System is presented. The role of the microprocessor in the implementation of the individual processing elements is discussed. Particular emphasis is placed on multispectral image data processing.

  12. Selective polarization imager for contrast enhancement in extended scattering media

    NASA Astrophysics Data System (ADS)

    Miller, Darren Alexis

    Improved imaging and detection of objects through turbid obscurants is a vital problem of current interest to both military and civilian entities. Image quality is severely degraded when obscurant fields such as fog, smoke, dust, etc., lie between an object and the light-collecting optics. Conventional intensity imaging through turbid media suffers from rapid loss of image contrast due to light scattering from particles (e.g. in fog) or random variations of refractive index (e.g. in medical imaging). Intensity imaging does not differentiate between rays scattered off particles in the obscurant field and those reflected off objects within the field. Scattering degrades image quality in all spectral bands (UV, visible, and IR), although the amount of degradation is wavelength dependent. This dissertation features the development of innovative system designs and techniques that utilize scattered radiation's deterministic polarization state evolution to greatly enhance the image contrast of stand-off objects within obscurant fields such as smoke, fog, or dust using active polarized illumination in the visible. The produced sensors acquire and process image data in real time using computationally non-intensive algorithms that differentiate between radiation that scatters or reflects from obscured objects and the radiation from the scattering media, improving image contrast by factors of ten or greater for dense water vapor obscurants.

  13. New algorithm for the passive THz image quality enhancement

    NASA Astrophysics Data System (ADS)

    Trofimov, Vyacheslav A.; Trofimov, Vladislav V.

    2016-04-01

    We propose a new approach for THz image quality enhancing using correlation function between the image under consideration and a standard image. The standard image moves in two directions along a image under analysis. As a result, 2 D correlation function is obtained. Multiplying this function by color number belonging to a grey scale, we restore the image under the analysis. This allows to suppress a noise on a new image. This method allows to see the person clothes details that it means multi-times increasing of the passive THz camera temperature resolution. We discuss a choice of standard image characteristics for an achievement of correlation function for high contrast. Other feature of our approach arises from a possibility of a person image coming to the THz camera by using a computer processing of the image only. It means that we can "decrease" a distance between a person and the passive THz camera. This algorithm is very convenient for using and has a high performance.

  14. 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.

  15. 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