Sample records for adaptive image processing

  1. Adaptive Algorithms for Automated Processing of Document Images

    DTIC Science & Technology

    2011-01-01

    ABSTRACT Title of dissertation: ADAPTIVE ALGORITHMS FOR AUTOMATED PROCESSING OF DOCUMENT IMAGES Mudit Agrawal, Doctor of Philosophy, 2011...2011 4. TITLE AND SUBTITLE Adaptive Algorithms for Automated Processing of Document Images 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...ALGORITHMS FOR AUTOMATED PROCESSING OF DOCUMENT IMAGES by Mudit Agrawal Dissertation submitted to the Faculty of the Graduate School of the University

  2. A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines.

    PubMed

    Khan, Arif Ul Maula; Mikut, Ralf; Reischl, Markus

    2016-01-01

    The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts.

  3. A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines

    PubMed Central

    Mikut, Ralf; Reischl, Markus

    2016-01-01

    The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts. PMID:27764213

  4. Pre-processing, registration and selection of adaptive optics corrected retinal images.

    PubMed

    Ramaswamy, Gomathy; Devaney, Nicholas

    2013-07-01

    In this paper, the aim is to demonstrate enhanced processing of sequences of fundus images obtained using a commercial AO flood illumination system. The purpose of the work is to (1) correct for uneven illumination at the retina (2) automatically select the best quality images and (3) precisely register the best images. Adaptive optics corrected retinal images are pre-processed to correct uneven illumination using different methods; subtracting or dividing by the average filtered image, homomorphic filtering and a wavelet based approach. These images are evaluated to measure the image quality using various parameters, including sharpness, variance, power spectrum kurtosis and contrast. We have carried out the registration in two stages; a coarse stage using cross-correlation followed by fine registration using two approaches; parabolic interpolation on the peak of the cross-correlation and maximum-likelihood estimation. The angle of rotation of the images is measured using a combination of peak tracking and Procrustes transformation. We have found that a wavelet approach (Daubechies 4 wavelet at 6th level decomposition) provides good illumination correction with clear improvement in image sharpness and contrast. The assessment of image quality using a 'Designer metric' works well when compared to visual evaluation, although it is highly correlated with other metrics. In image registration, sub-pixel translation measured using parabolic interpolation on the peak of the cross-correlation function and maximum-likelihood estimation are found to give very similar results (RMS difference 0.047 pixels). We have confirmed that correcting rotation of the images provides a significant improvement, especially at the edges of the image. We observed that selecting the better quality frames (e.g. best 75% images) for image registration gives improved resolution, at the expense of poorer signal-to-noise. The sharpness map of the registered and de-rotated images shows increased

  5. Post-processing of adaptive optics images based on frame selection and multi-frame blind deconvolution

    NASA Astrophysics Data System (ADS)

    Tian, Yu; Rao, Changhui; Wei, Kai

    2008-07-01

    The adaptive optics can only partially compensate the image blurred by atmospheric turbulence due to the observing condition and hardware restriction. A post-processing method based on frame selection and multi-frames blind deconvolution to improve images partially corrected by adaptive optics is proposed. The appropriate frames which are suitable for blind deconvolution from the recorded AO close-loop frames series are selected by the frame selection technique and then do the multi-frame blind deconvolution. There is no priori knowledge except for the positive constraint in blind deconvolution. It is benefit for the use of multi-frame images to improve the stability and convergence of the blind deconvolution algorithm. The method had been applied in the image restoration of celestial bodies which were observed by 1.2m telescope equipped with 61-element adaptive optical system at Yunnan Observatory. The results show that the method can effectively improve the images partially corrected by adaptive optics.

  6. Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing.

    PubMed

    Leong, Siow Hoo; Ong, Seng Huat

    2017-01-01

    This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.

  7. Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing

    PubMed Central

    Leong, Siow Hoo

    2017-01-01

    This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index. PMID:28686634

  8. Adaptive nonlinear L2 and L3 filters for speckled image processing

    NASA Astrophysics Data System (ADS)

    Lukin, Vladimir V.; Melnik, Vladimir P.; Chemerovsky, Victor I.; Astola, Jaakko T.

    1997-04-01

    Here we propose adaptive nonlinear filters based on calculation and analysis of two or three order statistics in a scanning window. They are designed for processing images corrupted by severe speckle noise with non-symmetrical. (Rayleigh or one-side exponential) distribution laws; impulsive noise can be also present. The proposed filtering algorithms provide trade-off between impulsive noise can be also present. The proposed filtering algorithms provide trade-off between efficient speckle noise suppression, robustness, good edge/detail preservation, low computational complexity, preservation of average level for homogeneous regions of images. Quantitative evaluations of the characteristics of the proposed filter are presented as well as the results of the application to real synthetic aperture radar and ultrasound medical images.

  9. [A study of the process by which a school-age child adapted to body image changes following open-heart surgery].

    PubMed

    Lin, Heng-Ching; Tsai, Jia-Ling

    2006-10-01

    This case report attempts to explore the adaptive process of body image changes in school-age children suffering from congenital ventricular septal defect (VSD) following open-heart surgery. After establishing trust relationship, we applied atraumatic care, projective communication techniques, interviews, behavioral observation, storytelling and play in our interaction with that child. We found the child experienced "body image disturbance" after open-heart surgery and underwent a four stage adaptive process as follows: (1) Impact (questioning, perception of punishment for wrongdoing, loss, anger); (2) Retreat (denial, anxiety, withdrawal, escaping social contact, inferiority); (3) Acknowledgment (cognitive change, active participation, future-oriented concerns); and (4) Reconstruction (positive self-image, reconstructing body image). Nursing intervention provided the case with more opportunities for sensory feedback and positive reinforcement and also assisted the patient to adopt a positive view of the situation and then to reconstruct and realize the meaning of such surgery. We reinforced the social supporting system to promote self-confidence, self-esteem, and self-value. The child finally accepted the wounds resulting from the operation as a symbol of "bravery"; a breakthrough likely to help in the child's re-entrance to school and normalization of life. Study findings both enhanced pediatric nurse understanding of the adaptive process involved in body image change and provided knowledge essential to designing flexible-option nursing interventions tailored to meet the demands of different adaptation stages. Obviously, such a caring model designed to meet the differing needs of different body image changes has the potential to benefit of body image integration greatly and can provide the pediatric nursing framework in the future.

  10. Mass Detection in Mammographic Images Using Wavelet Processing and Adaptive Threshold Technique.

    PubMed

    Vikhe, P S; Thool, V R

    2016-04-01

    Detection of mass in mammogram for early diagnosis of breast cancer is a significant assignment in the reduction of the mortality rate. However, in some cases, screening of mass is difficult task for radiologist, due to variation in contrast, fuzzy edges and noisy mammograms. Masses and micro-calcifications are the distinctive signs for diagnosis of breast cancer. This paper presents, a method for mass enhancement using piecewise linear operator in combination with wavelet processing from mammographic images. The method includes, artifact suppression and pectoral muscle removal based on morphological operations. Finally, mass segmentation for detection using adaptive threshold technique is carried out to separate the mass from background. The proposed method has been tested on 130 (45 + 85) images with 90.9 and 91 % True Positive Fraction (TPF) at 2.35 and 2.1 average False Positive Per Image(FP/I) from two different databases, namely Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammography (DDSM). The obtained results show that, the proposed technique gives improved diagnosis in the early breast cancer detection.

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

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

    Druckmueller, M., E-mail: druckmuller@fme.vutbr.cz

    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. A cost-effective line-based light-balancing technique using adaptive processing.

    PubMed

    Hsia, Shih-Chang; Chen, Ming-Huei; Chen, Yu-Min

    2006-09-01

    The camera imaging system has been widely used; however, the displaying image appears to have an unequal light distribution. This paper presents novel light-balancing techniques to compensate uneven illumination based on adaptive signal processing. For text image processing, first, we estimate the background level and then process each pixel with nonuniform gain. This algorithm can balance the light distribution while keeping a high contrast in the image. For graph image processing, the adaptive section control using piecewise nonlinear gain is proposed to equalize the histogram. Simulations show that the performance of light balance is better than the other methods. Moreover, we employ line-based processing to efficiently reduce the memory requirement and the computational cost to make it applicable in real-time systems.

  13. Adaptive noise correction of dual-energy computed tomography images.

    PubMed

    Maia, Rafael Simon; Jacob, Christian; Hara, Amy K; Silva, Alvin C; Pavlicek, William; Mitchell, J Ross

    2016-04-01

    Noise reduction in material density images is a necessary preprocessing step for the correct interpretation of dual-energy computed tomography (DECT) images. In this paper we describe a new method based on a local adaptive processing to reduce noise in DECT images An adaptive neighborhood Wiener (ANW) filter was implemented and customized to use local characteristics of material density images. The ANW filter employs a three-level wavelet approach, combined with the application of an anisotropic diffusion filter. Material density images and virtual monochromatic images are noise corrected with two resulting noise maps. The algorithm was applied and quantitatively evaluated in a set of 36 images. From that set of images, three are shown here, and nine more are shown in the online supplementary material. Processed images had higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) than the raw material density images. The average improvements in SNR and CNR for the material density images were 56.5 and 54.75%, respectively. We developed a new DECT noise reduction algorithm. We demonstrate throughout a series of quantitative analyses that the algorithm improves the quality of material density images and virtual monochromatic images.

  14. 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.

  15. Advanced technology development for image gathering, coding, and processing

    NASA Technical Reports Server (NTRS)

    Huck, Friedrich O.

    1990-01-01

    Three overlapping areas of research activities are presented: (1) Information theory and optimal filtering are extended to visual information acquisition and processing. The goal is to provide a comprehensive methodology for quantitatively assessing the end-to-end performance of image gathering, coding, and processing. (2) Focal-plane processing techniques and technology are developed to combine effectively image gathering with coding. The emphasis is on low-level vision processing akin to the retinal processing in human vision. (3) A breadboard adaptive image-coding system is being assembled. This system will be used to develop and evaluate a number of advanced image-coding technologies and techniques as well as research the concept of adaptive image coding.

  16. NASA End-to-End Data System /NEEDS/ information adaptive system - Performing image processing onboard the spacecraft

    NASA Technical Reports Server (NTRS)

    Kelly, W. L.; Howle, W. M.; Meredith, B. D.

    1980-01-01

    The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onbaord image processing. Since the IAS is a data preprocessing system which is closely coupled to the sensor system, it serves as a first step in providing a 'Smart' imaging sensor. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner and provide the opportunity to design sensor systems which can be reconfigured in near real time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

  17. Efficient generation of discontinuity-preserving adaptive triangulations from range images.

    PubMed

    Garcia, Miguel Angel; Sappa, Angel Domingo

    2004-10-01

    This paper presents an efficient technique for generating adaptive triangular meshes from range images. The algorithm consists of two stages. First, a user-defined number of points is adaptively sampled from the given range image. Those points are chosen by taking into account the surface shapes represented in the range image in such a way that points tend to group in areas of high curvature and to disperse in low-variation regions. This selection process is done through a noniterative, inherently parallel algorithm in order to gain efficiency. Once the image has been subsampled, the second stage applies a two and one half-dimensional Delaunay triangulation to obtain an initial triangular mesh. To favor the preservation of surface and orientation discontinuities (jump and crease edges) present in the original range image, the aforementioned triangular mesh is iteratively modified by applying an efficient edge flipping technique. Results with real range images show accurate triangular approximations of the given range images with low processing times.

  18. Fast digital zooming system using directionally adaptive image interpolation and restoration.

    PubMed

    Kang, Wonseok; Jeon, Jaehwan; Yu, Soohwan; Paik, Joonki

    2014-01-01

    This paper presents a fast digital zooming system for mobile consumer cameras using directionally adaptive image interpolation and restoration methods. The proposed interpolation algorithm performs edge refinement along the initially estimated edge orientation using directionally steerable filters. Either the directionally weighted linear or adaptive cubic-spline interpolation filter is then selectively used according to the refined edge orientation for removing jagged artifacts in the slanted edge region. A novel image restoration algorithm is also presented for removing blurring artifacts caused by the linear or cubic-spline interpolation using the directionally adaptive truncated constrained least squares (TCLS) filter. Both proposed steerable filter-based interpolation and the TCLS-based restoration filters have a finite impulse response (FIR) structure for real time processing in an image signal processing (ISP) chain. Experimental results show that the proposed digital zooming system provides high-quality magnified images with FIR filter-based fast computational structure.

  19. Experiments with recursive estimation in astronomical image processing

    NASA Technical Reports Server (NTRS)

    Busko, I.

    1992-01-01

    Recursive estimation concepts were applied to image enhancement problems since the 70's. However, very few applications in the particular area of astronomical image processing are known. These concepts were derived, for 2-dimensional images, from the well-known theory of Kalman filtering in one dimension. The historic reasons for application of these techniques to digital images are related to the images' scanned nature, in which the temporal output of a scanner device can be processed on-line by techniques borrowed directly from 1-dimensional recursive signal analysis. However, recursive estimation has particular properties that make it attractive even in modern days, when big computer memories make the full scanned image available to the processor at any given time. One particularly important aspect is the ability of recursive techniques to deal with non-stationary phenomena, that is, phenomena which have their statistical properties variable in time (or position in a 2-D image). Many image processing methods make underlying stationary assumptions either for the stochastic field being imaged, for the imaging system properties, or both. They will underperform, or even fail, when applied to images that deviate significantly from stationarity. Recursive methods, on the contrary, make it feasible to perform adaptive processing, that is, to process the image by a processor with properties tuned to the image's local statistical properties. Recursive estimation can be used to build estimates of images degraded by such phenomena as noise and blur. We show examples of recursive adaptive processing of astronomical images, using several local statistical properties to drive the adaptive processor, as average signal intensity, signal-to-noise and autocorrelation function. Software was developed under IRAF, and as such will be made available to interested users.

  20. Clinical image processing engine

    NASA Astrophysics Data System (ADS)

    Han, Wei; Yao, Jianhua; Chen, Jeremy; Summers, Ronald

    2009-02-01

    Our group provides clinical image processing services to various institutes at NIH. We develop or adapt image processing programs for a variety of applications. However, each program requires a human operator to select a specific set of images and execute the program, as well as store the results appropriately for later use. To improve efficiency, we design a parallelized clinical image processing engine (CIPE) to streamline and parallelize our service. The engine takes DICOM images from a PACS server, sorts and distributes the images to different applications, multithreads the execution of applications, and collects results from the applications. The engine consists of four modules: a listener, a router, a job manager and a data manager. A template filter in XML format is defined to specify the image specification for each application. A MySQL database is created to store and manage the incoming DICOM images and application results. The engine achieves two important goals: reduce the amount of time and manpower required to process medical images, and reduce the turnaround time for responding. We tested our engine on three different applications with 12 datasets and demonstrated that the engine improved the efficiency dramatically.

  1. Adaptive-optics optical coherence tomography processing using a graphics processing unit.

    PubMed

    Shafer, Brandon A; Kriske, Jeffery E; Kocaoglu, Omer P; Turner, Timothy L; Liu, Zhuolin; Lee, John Jaehwan; Miller, Donald T

    2014-01-01

    Graphics processing units are increasingly being used for scientific computing for their powerful parallel processing abilities, and moderate price compared to super computers and computing grids. In this paper we have used a general purpose graphics processing unit to process adaptive-optics optical coherence tomography (AOOCT) images in real time. Increasing the processing speed of AOOCT is an essential step in moving the super high resolution technology closer to clinical viability.

  2. SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

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

    Iliopoulos, AS; Sun, X; Floros, D

    Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well asmore » histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to

  3. Twofold processing for denoising ultrasound medical images.

    PubMed

    Kishore, P V V; Kumar, K V V; Kumar, D Anil; Prasad, M V D; Goutham, E N D; Rahul, R; Krishna, C B S Vamsi; Sandeep, Y

    2015-01-01

    Ultrasound medical (US) imaging non-invasively pictures inside of a human body for disease diagnostics. Speckle noise attacks ultrasound images degrading their visual quality. A twofold processing algorithm is proposed in this work to reduce this multiplicative speckle noise. First fold used block based thresholding, both hard (BHT) and soft (BST), on pixels in wavelet domain with 8, 16, 32 and 64 non-overlapping block sizes. This first fold process is a better denoising method for reducing speckle and also inducing object of interest blurring. The second fold process initiates to restore object boundaries and texture with adaptive wavelet fusion. The degraded object restoration in block thresholded US image is carried through wavelet coefficient fusion of object in original US mage and block thresholded US image. Fusion rules and wavelet decomposition levels are made adaptive for each block using gradient histograms with normalized differential mean (NDF) to introduce highest level of contrast between the denoised pixels and the object pixels in the resultant image. Thus the proposed twofold methods are named as adaptive NDF block fusion with hard and soft thresholding (ANBF-HT and ANBF-ST). The results indicate visual quality improvement to an interesting level with the proposed twofold processing, where the first fold removes noise and second fold restores object properties. Peak signal to noise ratio (PSNR), normalized cross correlation coefficient (NCC), edge strength (ES), image quality Index (IQI) and structural similarity index (SSIM), measure the quantitative quality of the twofold processing technique. Validation of the proposed method is done by comparing with anisotropic diffusion (AD), total variational filtering (TVF) and empirical mode decomposition (EMD) for enhancement of US images. The US images are provided by AMMA hospital radiology labs at Vijayawada, India.

  4. Information theoretic methods for image processing algorithm optimization

    NASA Astrophysics Data System (ADS)

    Prokushkin, Sergey F.; Galil, Erez

    2015-01-01

    Modern image processing pipelines (e.g., those used in digital cameras) are full of advanced, highly adaptive filters that often have a large number of tunable parameters (sometimes > 100). This makes the calibration procedure for these filters very complex, and the optimal results barely achievable in the manual calibration; thus an automated approach is a must. We will discuss an information theory based metric for evaluation of algorithm adaptive characteristics ("adaptivity criterion") using noise reduction algorithms as an example. The method allows finding an "orthogonal decomposition" of the filter parameter space into the "filter adaptivity" and "filter strength" directions. This metric can be used as a cost function in automatic filter optimization. Since it is a measure of a physical "information restoration" rather than perceived image quality, it helps to reduce the set of the filter parameters to a smaller subset that is easier for a human operator to tune and achieve a better subjective image quality. With appropriate adjustments, the criterion can be used for assessment of the whole imaging system (sensor plus post-processing).

  5. Single image interpolation via adaptive nonlocal sparsity-based modeling.

    PubMed

    Romano, Yaniv; Protter, Matan; Elad, Michael

    2014-07-01

    Single image interpolation is a central and extensively studied problem in image processing. A common approach toward the treatment of this problem in recent years is to divide the given image into overlapping patches and process each of them based on a model for natural image patches. Adaptive sparse representation modeling is one such promising image prior, which has been shown to be powerful in filling-in missing pixels in an image. Another force that such algorithms may use is the self-similarity that exists within natural images. Processing groups of related patches together exploits their correspondence, leading often times to improved results. In this paper, we propose a novel image interpolation method, which combines these two forces-nonlocal self-similarities and sparse representation modeling. The proposed method is contrasted with competitive and related algorithms, and demonstrated to achieve state-of-the-art results.

  6. Adaptive image contrast enhancement using generalizations of histogram equalization.

    PubMed

    Stark, J A

    2000-01-01

    This paper proposes a scheme for adaptive image-contrast enhancement based on a generalization of histogram equalization (HE). HE is a useful technique for improving image contrast, but its effect is too severe for many purposes. However, dramatically different results can be obtained with relatively minor modifications. A concise description of adaptive HE is set out, and this framework is used in a discussion of past suggestions for variations on HE. A key feature of this formalism is a "cumulation function," which is used to generate a grey level mapping from the local histogram. By choosing alternative forms of cumulation function one can achieve a wide variety of effects. A specific form is proposed. Through the variation of one or two parameters, the resulting process can produce a range of degrees of contrast enhancement, at one extreme leaving the image unchanged, at another yielding full adaptive equalization.

  7. Adaptive optics images restoration based on frame selection and multi-framd blind deconvolution

    NASA Astrophysics Data System (ADS)

    Tian, Y.; Rao, C. H.; Wei, K.

    2008-10-01

    The adaptive optics can only partially compensate the image blurred by atmospheric turbulent due to the observing condition and hardware restriction. A post-processing method based on frame selection and multi-frame blind deconvolution to improve images partially corrected by adaptive optics is proposed. The appropriate frames which are picked out by frame selection technique is deconvolved. There is no priori knowledge except the positive constraint. The method has been applied in the image restoration of celestial bodies which were observed by 1.2m telescope equipped with 61-element adaptive optical system in Yunnan Observatory. The results showed that the method can effectively improve the images partially corrected by adaptive optics.

  8. 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.

  9. Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking.

    PubMed

    Monno, Yusuke; Kiku, Daisuke; Tanaka, Masayuki; Okutomi, Masatoshi

    2017-12-01

    Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking.

  10. 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

  11. 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.

  12. Speckle imaging through turbulent atmosphere based on adaptable pupil segmentation.

    PubMed

    Loktev, Mikhail; Soloviev, Oleg; Savenko, Svyatoslav; Vdovin, Gleb

    2011-07-15

    We report on the first results to our knowledge obtained with adaptable multiaperture imaging through turbulence on a horizontal atmospheric path. We show that the resolution can be improved by adaptively matching the size of the subaperture to the characteristic size of the turbulence. Further improvement is achieved by the deconvolution of a number of subimages registered simultaneously through multiple subapertures. Different implementations of multiaperture geometry, including pupil multiplication, pupil image sampling, and a plenoptic telescope, are considered. Resolution improvement has been demonstrated on a ∼550 m horizontal turbulent path, using a combination of aperture sampling, speckle image processing, and, optionally, frame selection. © 2011 Optical Society of America

  13. Speckle imaging through turbulent atmosphere based on adaptable pupil segmentation

    NASA Astrophysics Data System (ADS)

    Loktev, Mikhail; Soloviev, Oleg; Savenko, Svyatoslav; Vdovin, Gleb

    2011-07-01

    We report on the first results to our knowledge obtained with adaptable multiaperture imaging through turbulence on a horizontal atmospheric path. We show that the resolution can be improved by adaptively matching the size of the subaperture to the characteristic size of the turbulence. Further improvement is achieved by the deconvolution of a number of subimages registered simultaneously through multiple subapertures. Different implementations of multiaperture geometry, including pupil multiplication, pupil image sampling, and a plenoptic telescope, are considered. Resolution improvement has been demonstrated on a ˜550m horizontal turbulent path, using a combination of aperture sampling, speckle image processing, and, optionally, frame selection.

  14. 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.

  15. Adaptive wiener image restoration kernel

    DOEpatents

    Yuan, Ding [Henderson, NV

    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.

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

    PubMed Central

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

    2015-01-01

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

  17. 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.

  18. Intermediate view reconstruction using adaptive disparity search algorithm for real-time 3D processing

    NASA Astrophysics Data System (ADS)

    Bae, Kyung-hoon; Park, Changhan; Kim, Eun-soo

    2008-03-01

    In this paper, intermediate view reconstruction (IVR) using adaptive disparity search algorithm (ASDA) is for realtime 3-dimensional (3D) processing proposed. The proposed algorithm can reduce processing time of disparity estimation by selecting adaptive disparity search range. Also, the proposed algorithm can increase the quality of the 3D imaging. That is, by adaptively predicting the mutual correlation between stereo images pair using the proposed algorithm, the bandwidth of stereo input images pair can be compressed to the level of a conventional 2D image and a predicted image also can be effectively reconstructed using a reference image and disparity vectors. From some experiments, stereo sequences of 'Pot Plant' and 'IVO', it is shown that the proposed algorithm improves the PSNRs of a reconstructed image to about 4.8 dB by comparing with that of conventional algorithms, and reduces the Synthesizing time of a reconstructed image to about 7.02 sec by comparing with that of conventional algorithms.

  19. Adaptive hyperspectral imager: design, modeling, and control

    NASA Astrophysics Data System (ADS)

    McGregor, Scot; Lacroix, Simon; Monmayrant, Antoine

    2015-08-01

    An adaptive, hyperspectral imager is presented. We propose a system with easily adaptable spectral resolution, adjustable acquisition time, and high spatial resolution which is independent of spectral resolution. The system yields the possibility to define a variety of acquisition schemes, and in particular near snapshot acquisitions that may be used to measure the spectral content of given or automatically detected regions of interest. The proposed system is modelled and simulated, and tests on a first prototype validate the approach to achieve near snapshot spectral acquisitions without resorting to any computationally heavy post-processing, nor cumbersome calibration

  20. Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE)

    PubMed Central

    Sharif, Behzad; Derbyshire, J. Andrew; Faranesh, Anthony Z.; Bresler, Yoram

    2010-01-01

    MR imaging of the human heart without explicit cardiac synchronization promises to extend the applicability of cardiac MR to a larger patient population and potentially expand its diagnostic capabilities. However, conventional non-gated imaging techniques typically suffer from low image quality or inadequate spatio-temporal resolution and fidelity. Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE) is a highly-accelerated non-gated dynamic imaging method that enables artifact-free imaging with high spatio-temporal resolutions by utilizing novel computational techniques to optimize the imaging process. In addition to using parallel imaging, the method gains acceleration from a physiologically-driven spatio-temporal support model; hence, it is doubly accelerated. The support model is patient-adaptive, i.e., its geometry depends on dynamics of the imaged slice, e.g., subject’s heart-rate and heart location within the slice. The proposed method is also doubly adaptive as it adapts both the acquisition and reconstruction schemes. Based on the theory of time-sequential sampling, the proposed framework explicitly accounts for speed limitations of gradient encoding and provides performance guarantees on achievable image quality. The presented in-vivo results demonstrate the effectiveness and feasibility of the PARADISE method for high resolution non-gated cardiac MRI during a short breath-hold. PMID:20665794

  1. Fission gas bubble identification using MATLAB's image processing toolbox

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

    Collette, R.

    Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to bemore » the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.« less

  2. Processing Of Binary Images

    NASA Astrophysics Data System (ADS)

    Hou, H. S.

    1985-07-01

    An overview of the recent progress in the area of digital processing of binary images in the context of document processing is presented here. The topics covered include input scan, adaptive thresholding, halftoning, scaling and resolution conversion, data compression, character recognition, electronic mail, digital typography, and output scan. Emphasis has been placed on illustrating the basic principles rather than descriptions of a particular system. Recent technology advances and research in this field are also mentioned.

  3. Survey of adaptive image coding techniques

    NASA Technical Reports Server (NTRS)

    Habibi, A.

    1977-01-01

    The general problem of image data compression is discussed briefly with attention given to the use of Karhunen-Loeve transforms, suboptimal systems, and block quantization. A survey is then conducted encompassing the four categories of adaptive systems: (1) adaptive transform coding (adaptive sampling, adaptive quantization, etc.), (2) adaptive predictive coding (adaptive delta modulation, adaptive DPCM encoding, etc.), (3) adaptive cluster coding (blob algorithms and the multispectral cluster coding technique), and (4) adaptive entropy coding.

  4. 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.

  5. Seam tracking with adaptive image capture for fine-tuning of a high power laser welding process

    NASA Astrophysics Data System (ADS)

    Lahdenoja, Olli; Säntti, Tero; Laiho, Mika; Paasio, Ari; Poikonen, Jonne K.

    2015-02-01

    This paper presents the development of methods for real-time fine-tuning of a high power laser welding process of thick steel by using a compact smart camera system. When performing welding in butt-joint configuration, the laser beam's location needs to be adjusted exactly according to the seam line in order to allow the injected energy to be absorbed uniformly into both steel sheets. In this paper, on-line extraction of seam parameters is targeted by taking advantage of a combination of dynamic image intensity compression, image segmentation with a focal-plane processor ASIC, and Hough transform on an associated FPGA. Additional filtering of Hough line candidates based on temporal windowing is further applied to reduce unrealistic frame-to-frame tracking variations. The proposed methods are implemented in Matlab by using image data captured with adaptive integration time. The simulations are performed in a hardware oriented way to allow real-time implementation of the algorithms on the smart camera system.

  6. Adaptive Microwave Staring Correlated Imaging for Targets Appearing in Discrete Clusters.

    PubMed

    Tian, Chao; Jiang, Zheng; Chen, Weidong; Wang, Dongjin

    2017-10-21

    Microwave staring correlated imaging (MSCI) can achieve ultra-high resolution in real aperture staring radar imaging using the correlated imaging process (CIP) under all-weather and all-day circumstances. The CIP must combine the received echo signal with the temporal-spatial stochastic radiation field. However, a precondition of the CIP is that the continuous imaging region must be discretized to a fine grid, and the measurement matrix should be accurately computed, which makes the imaging process highly complex when the MSCI system observes a wide area. This paper proposes an adaptive imaging approach for the targets in discrete clusters to reduce the complexity of the CIP. The approach is divided into two main stages. First, as discrete clustered targets are distributed in different range strips in the imaging region, the transmitters of the MSCI emit narrow-pulse waveforms to separate the echoes of the targets in different strips in the time domain; using spectral entropy, a modified method robust against noise is put forward to detect the echoes of the discrete clustered targets, based on which the strips with targets can be adaptively located. Second, in a strip with targets, the matched filter reconstruction algorithm is used to locate the regions with targets, and only the regions of interest are discretized to a fine grid; sparse recovery is used, and the band exclusion is used to maintain the non-correlation of the dictionary. Simulation results are presented to demonstrate that the proposed approach can accurately and adaptively locate the regions with targets and obtain high-quality reconstructed images.

  7. 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.

  8. Adaptive tight frame based medical image reconstruction: a proof-of-concept study for computed tomography

    NASA Astrophysics Data System (ADS)

    Zhou, Weifeng; Cai, Jian-Feng; Gao, Hao

    2013-12-01

    A popular approach for medical image reconstruction has been through the sparsity regularization, assuming the targeted image can be well approximated by sparse coefficients under some properly designed system. The wavelet tight frame is such a widely used system due to its capability for sparsely approximating piecewise-smooth functions, such as medical images. However, using a fixed system may not always be optimal for reconstructing a variety of diversified images. Recently, the method based on the adaptive over-complete dictionary that is specific to structures of the targeted images has demonstrated its superiority for image processing. This work is to develop the adaptive wavelet tight frame method image reconstruction. The proposed scheme first constructs the adaptive wavelet tight frame that is task specific, and then reconstructs the image of interest by solving an l1-regularized minimization problem using the constructed adaptive tight frame system. The proof-of-concept study is performed for computed tomography (CT), and the simulation results suggest that the adaptive tight frame method improves the reconstructed CT image quality from the traditional tight frame method.

  9. Visual adaptation and the amplitude spectra of radiological images.

    PubMed

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

    2018-01-01

    We examined how visual sensitivity and perception are affected by adaptation to the characteristic amplitude spectra of X-ray mammography images. Because of the transmissive nature of X-ray photons, these images have relatively more low-frequency variability than natural images, a difference that is captured by a steeper slope of the amplitude spectrum (~ - 1.5) compared to the ~ 1/f (slope of - 1) spectra common to natural scenes. Radiologists inspecting these images are therefore exposed to a different balance of spectral components, and we measured how this exposure might alter spatial vision. Observers (who were not radiologists) were adapted to images of normal mammograms or the same images sharpened by filtering the amplitude spectra to shallower slopes. Prior adaptation to the original mammograms significantly biased judgments of image focus relative to the sharpened images, demonstrating that the images are sufficient to induce substantial after-effects. The adaptation also induced strong losses in threshold contrast sensitivity that were selective for lower spatial frequencies, though these losses were very similar to the threshold changes induced by the sharpened images. Visual search for targets (Gaussian blobs) added to the images was also not differentially affected by adaptation to the original or sharper images. These results complement our previous studies examining how observers adapt to the textural properties or phase spectra of mammograms. Like the phase spectrum, adaptation to the amplitude spectrum of mammograms alters spatial sensitivity and visual judgments about the images. However, unlike the phase spectrum, adaptation to the amplitude spectra did not confer a selective performance advantage relative to more natural spectra.

  10. 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

  11. Adaptive enhancement for nonuniform illumination images via nonlinear mapping

    NASA Astrophysics Data System (ADS)

    Wang, Yanfang; Huang, Qian; Hu, Jing

    2017-09-01

    Nonuniform illumination images suffer from degenerated details because of underexposure, overexposure, or a combination of both. To improve the visual quality of color images, underexposure regions should be lightened, whereas overexposure areas need to be dimmed properly. However, discriminating between underexposure and overexposure is troublesome. Compared with traditional methods that produce a fixed demarcation value throughout an image, the proposed demarcation changes as local luminance varies, thus is suitable for manipulating complicated illumination. Based on this locally adaptive demarcation, a nonlinear modification is applied to image luminance. Further, with the modified luminance, we propose a nonlinear process to reconstruct a luminance-enhanced color image. For every pixel, this nonlinear process takes the luminance change and the original chromaticity into account, thus trying to avoid exaggerated colors at dark areas and depressed colors at highly bright regions. Finally, to improve image contrast, a local and image-dependent exponential technique is designed and applied to the RGB channels of the obtained color image. Experimental results demonstrate that our method produces good contrast and vivid color for both nonuniform illumination images and images with normal illumination.

  12. Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images.

    PubMed

    Ramaswamy, Gomathy; Lombardo, Marco; Devaney, Nicholas

    2014-06-01

    Glaucoma is the leading cause of preventable blindness in the western world. Investigation of high-resolution retinal nerve fiber layer (RNFL) images in patients may lead to new indicators of its onset. Adaptive optics (AO) can provide diffraction-limited images of the retina, providing new opportunities for earlier detection of neuroretinal pathologies. However, precise processing is required to correct for three effects in sequences of AO-assisted, flood-illumination images: uneven illumination, residual image motion and image rotation. This processing can be challenging for images of the RNFL due to their low contrast and lack of clearly noticeable features. Here we develop specific processing techniques and show that their application leads to improved image quality on the nerve fiber bundles. This in turn improves the reliability of measures of fiber texture such as the correlation of Gray-Level Co-occurrence Matrix (GLCM).

  13. Prism adaptation does not alter configural processing of faces

    PubMed Central

    Bultitude, Janet H.; Downing, Paul E.; Rafal, Robert D.

    2013-01-01

    Patients with hemispatial neglect (‘neglect’) following a brain lesion show difficulty responding or orienting to objects and events on the left side of space. Substantial evidence supports the use of a sensorimotor training technique called prism adaptation as a treatment for neglect. Reaching for visual targets viewed through prismatic lenses that induce a rightward shift in the visual image results in a leftward recalibration of reaching movements that is accompanied by a reduction of symptoms in patients with neglect. The understanding of prism adaptation has also been advanced through studies of healthy participants, in whom adaptation to leftward prismatic shifts results in temporary neglect-like performance. Interestingly, prism adaptation can also alter aspects of non-lateralised spatial attention. We previously demonstrated that prism adaptation alters the extent to which neglect patients and healthy participants process local features versus global configurations of visual stimuli. Since deficits in non-lateralised spatial attention are thought to contribute to the severity of neglect symptoms, it is possible that the effect of prism adaptation on these deficits contributes to its efficacy. This study examines the pervasiveness of the effects of prism adaptation on perception by examining the effect of prism adaptation on configural face processing using a composite face task. The composite face task is a persuasive demonstration of the automatic global-level processing of faces: the top and bottom halves of two familiar faces form a seemingly new, unknown face when viewed together. Participants identified the top or bottom halves of composite faces before and after prism adaptation. Sensorimotor adaptation was confirmed by significant pointing aftereffect, however there was no significant change in the extent to which the irrelevant face half interfered with processing. The results support the proposal that the therapeutic effects of prism adaptation

  14. Prism adaptation does not alter configural processing of faces.

    PubMed

    Bultitude, Janet H; Downing, Paul E; Rafal, Robert D

    2013-01-01

    Patients with hemispatial neglect ('neglect') following a brain lesion show difficulty responding or orienting to objects and events on the left side of space. Substantial evidence supports the use of a sensorimotor training technique called prism adaptation as a treatment for neglect. Reaching for visual targets viewed through prismatic lenses that induce a rightward shift in the visual image results in a leftward recalibration of reaching movements that is accompanied by a reduction of symptoms in patients with neglect. The understanding of prism adaptation has also been advanced through studies of healthy participants, in whom adaptation to leftward prismatic shifts results in temporary neglect-like performance. Interestingly, prism adaptation can also alter aspects of non-lateralised spatial attention. We previously demonstrated that prism adaptation alters the extent to which neglect patients and healthy participants process local features versus global configurations of visual stimuli. Since deficits in non-lateralised spatial attention are thought to contribute to the severity of neglect symptoms, it is possible that the effect of prism adaptation on these deficits contributes to its efficacy. This study examines the pervasiveness of the effects of prism adaptation on perception by examining the effect of prism adaptation on configural face processing using a composite face task. The composite face task is a persuasive demonstration of the automatic global-level processing of faces: the top and bottom halves of two familiar faces form a seemingly new, unknown face when viewed together. Participants identified the top or bottom halves of composite faces before and after prism adaptation. Sensorimotor adaptation was confirmed by significant pointing aftereffect, however there was no significant change in the extent to which the irrelevant face half interfered with processing. The results support the proposal that the therapeutic effects of prism adaptation are

  15. A Remote Sensing Image Fusion Method based on adaptive dictionary learning

    NASA Astrophysics Data System (ADS)

    He, Tongdi; Che, Zongxi

    2018-01-01

    This paper discusses using a remote sensing fusion method, based on' adaptive sparse representation (ASP)', to provide improved spectral information, reduce data redundancy and decrease system complexity. First, the training sample set is formed by taking random blocks from the images to be fused, the dictionary is then constructed using the training samples, and the remaining terms are clustered to obtain the complete dictionary by iterated processing at each step. Second, the self-adaptive weighted coefficient rule of regional energy is used to select the feature fusion coefficients and complete the reconstruction of the image blocks. Finally, the reconstructed image blocks are rearranged and an average is taken to obtain the final fused images. Experimental results show that the proposed method is superior to other traditional remote sensing image fusion methods in both spectral information preservation and spatial resolution.

  16. 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

  17. Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking †

    PubMed Central

    Kiku, Daisuke; Okutomi, Masatoshi

    2017-01-01

    Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking. PMID:29194407

  18. Adaptive and robust statistical methods for processing near-field scanning microwave microscopy images.

    PubMed

    Coakley, K J; Imtiaz, A; Wallis, T M; Weber, J C; Berweger, S; Kabos, P

    2015-03-01

    Near-field scanning microwave microscopy offers great potential to facilitate characterization, development and modeling of materials. By acquiring microwave images at multiple frequencies and amplitudes (along with the other modalities) one can study material and device physics at different lateral and depth scales. Images are typically noisy and contaminated by artifacts that can vary from scan line to scan line and planar-like trends due to sample tilt errors. Here, we level images based on an estimate of a smooth 2-d trend determined with a robust implementation of a local regression method. In this robust approach, features and outliers which are not due to the trend are automatically downweighted. We denoise images with the Adaptive Weights Smoothing method. This method smooths out additive noise while preserving edge-like features in images. We demonstrate the feasibility of our methods on topography images and microwave |S11| images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion. Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical. Published by Elsevier B.V.

  19. Microscopy mineral image enhancement based on improved adaptive threshold in nonsubsampled shearlet transform domain

    NASA Astrophysics Data System (ADS)

    Li, Liangliang; Si, Yujuan; Jia, Zhenhong

    2018-03-01

    In this paper, a novel microscopy mineral image enhancement method based on adaptive threshold in non-subsampled shearlet transform (NSST) domain is proposed. First, the image is decomposed into one low-frequency sub-band and several high-frequency sub-bands. Second, the gamma correction is applied to process the low-frequency sub-band coefficients, and the improved adaptive threshold is adopted to suppress the noise of the high-frequency sub-bands coefficients. Third, the processed coefficients are reconstructed with the inverse NSST. Finally, the unsharp filter is used to enhance the details of the reconstructed image. Experimental results on various microscopy mineral images demonstrated that the proposed approach has a better enhancement effect in terms of objective metric and subjective metric.

  20. Integrating digital topology in image-processing libraries.

    PubMed

    Lamy, Julien

    2007-01-01

    This paper describes a method to integrate digital topology informations in image-processing libraries. This additional information allows a library user to write algorithms respecting topological constraints, for example, a seed fill or a skeletonization algorithm. As digital topology is absent from most image-processing libraries, such constraints cannot be fulfilled. We describe and give code samples for all the structures necessary for this integration, and show a use case in the form of a homotopic thinning filter inside ITK. The obtained filter can be up to a hundred times as fast as ITK's thinning filter and works for any image dimension. This paper mainly deals of integration within ITK, but can be adapted with only minor modifications to other image-processing libraries.

  1. Adaptive texture filtering for defect inspection in ultrasound images

    NASA Astrophysics Data System (ADS)

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

    1993-05-01

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

  2. Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images

    PubMed Central

    Ramaswamy, Gomathy; Lombardo, Marco; Devaney, Nicholas

    2014-01-01

    Glaucoma is the leading cause of preventable blindness in the western world. Investigation of high-resolution retinal nerve fiber layer (RNFL) images in patients may lead to new indicators of its onset. Adaptive optics (AO) can provide diffraction-limited images of the retina, providing new opportunities for earlier detection of neuroretinal pathologies. However, precise processing is required to correct for three effects in sequences of AO-assisted, flood-illumination images: uneven illumination, residual image motion and image rotation. This processing can be challenging for images of the RNFL due to their low contrast and lack of clearly noticeable features. Here we develop specific processing techniques and show that their application leads to improved image quality on the nerve fiber bundles. This in turn improves the reliability of measures of fiber texture such as the correlation of Gray-Level Co-occurrence Matrix (GLCM). PMID:24940551

  3. Fission gas bubble identification using MATLAB's image processing toolbox

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

    Collette, R.; King, J.; Keiser, Jr., D.

    Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

  4. Fission gas bubble identification using MATLAB's image processing toolbox

    DOE PAGES

    Collette, R.; King, J.; Keiser, Jr., D.; ...

    2016-06-08

    Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

  5. Real-time blind deconvolution of retinal images in adaptive optics scanning laser ophthalmoscopy

    NASA Astrophysics Data System (ADS)

    Li, Hao; Lu, Jing; Shi, Guohua; Zhang, Yudong

    2011-06-01

    With the use of adaptive optics (AO), the ocular aberrations can be compensated to get high-resolution image of living human retina. However, the wavefront correction is not perfect due to the wavefront measure error and hardware restrictions. Thus, it is necessary to use a deconvolution algorithm to recover the retinal images. In this paper, a blind deconvolution technique called Incremental Wiener filter is used to restore the adaptive optics confocal scanning laser ophthalmoscope (AOSLO) images. The point-spread function (PSF) measured by wavefront sensor is only used as an initial value of our algorithm. We also realize the Incremental Wiener filter on graphics processing unit (GPU) in real-time. When the image size is 512 × 480 pixels, six iterations of our algorithm only spend about 10 ms. Retinal blood vessels as well as cells in retinal images are restored by our algorithm, and the PSFs are also revised. Retinal images with and without adaptive optics are both restored. The results show that Incremental Wiener filter reduces the noises and improve the image quality.

  6. Adaptive Image Processing Methods for Improving Contaminant Detection Accuracy on Poultry Carcasses

    USDA-ARS?s Scientific Manuscript database

    Technical Abstract A real-time multispectral imaging system has demonstrated a science-based tool for fecal and ingesta contaminant detection during poultry processing. In order to implement this imaging system at commercial poultry processing industry, the false positives must be removed. For doi...

  7. Image Processing: A State-of-the-Art Way to Learn Science.

    ERIC Educational Resources Information Center

    Raphael, Jacqueline; Greenberg, Richard

    1995-01-01

    Teachers participating in the Image Processing for Teaching Process, begun at the University of Arizona's Lunar and Planetary Laboratory in 1989, find this technology ideal for encouraging student discovery, promoting constructivist science or math experiences, and adapting in classrooms. Because image processing is not a computerized text, it…

  8. Comparison of an adaptive local thresholding method on CBCT and µCT endodontic images

    NASA Astrophysics Data System (ADS)

    Michetti, Jérôme; Basarab, Adrian; Diemer, Franck; Kouame, Denis

    2018-01-01

    Root canal segmentation on cone beam computed tomography (CBCT) images is difficult because of the noise level, resolution limitations, beam hardening and dental morphological variations. An image processing framework, based on an adaptive local threshold method, was evaluated on CBCT images acquired on extracted teeth. A comparison with high quality segmented endodontic images on micro computed tomography (µCT) images acquired from the same teeth was carried out using a dedicated registration process. Each segmented tooth was evaluated according to volume and root canal sections through the area and the Feret’s diameter. The proposed method is shown to overcome the limitations of CBCT and to provide an automated and adaptive complete endodontic segmentation. Despite a slight underestimation (-4, 08%), the local threshold segmentation method based on edge-detection was shown to be fast and accurate. Strong correlations between CBCT and µCT segmentations were found both for the root canal area and diameter (respectively 0.98 and 0.88). Our findings suggest that combining CBCT imaging with this image processing framework may benefit experimental endodontology, teaching and could represent a first development step towards the clinical use of endodontic CBCT segmentation during pulp cavity treatment.

  9. A Prototype Instrument for Adaptive SPECT Imaging

    PubMed Central

    Freed, Melanie; Kupinski, Matthew A.; Furenlid, Lars R.; Barrett, Harrison H.

    2015-01-01

    We have designed and constructed a small-animal adaptive SPECT imaging system as a prototype for quantifying the potential benefit of adaptive SPECT imaging over the traditional fixed geometry approach. The optical design of the system is based on filling the detector with the object for each viewing angle, maximizing the sensitivity, and optimizing the resolution in the projection images. Additional feedback rules for determining the optimal geometry of the system can be easily added to the existing control software. Preliminary data have been taken of a phantom with a small, hot, offset lesion in a flat background in both adaptive and fixed geometry modes. Comparison of the predicted system behavior with the actual system behavior is presented along with recommendations for system improvements. PMID:26346820

  10. Technical note: DIRART--A software suite for deformable image registration and adaptive radiotherapy research.

    PubMed

    Yang, Deshan; Brame, Scott; El Naqa, Issam; Aditya, Apte; Wu, Yu; Goddu, S Murty; Mutic, Sasa; Deasy, Joseph O; Low, Daniel A

    2011-01-01

    Recent years have witnessed tremendous progress in image guide radiotherapy technology and a growing interest in the possibilities for adapting treatment planning and delivery over the course of treatment. One obstacle faced by the research community has been the lack of a comprehensive open-source software toolkit dedicated for adaptive radiotherapy (ART). To address this need, the authors have developed a software suite called the Deformable Image Registration and Adaptive Radiotherapy Toolkit (DIRART). DIRART is an open-source toolkit developed in MATLAB. It is designed in an object-oriented style with focus on user-friendliness, features, and flexibility. It contains four classes of DIR algorithms, including the newer inverse consistency algorithms to provide consistent displacement vector field in both directions. It also contains common ART functions, an integrated graphical user interface, a variety of visualization and image-processing features, dose metric analysis functions, and interface routines. These interface routines make DIRART a powerful complement to the Computational Environment for Radiotherapy Research (CERR) and popular image-processing toolkits such as ITK. DIRART provides a set of image processing/registration algorithms and postprocessing functions to facilitate the development and testing of DIR algorithms. It also offers a good amount of options for DIR results visualization, evaluation, and validation. By exchanging data with treatment planning systems via DICOM-RT files and CERR, and by bringing image registration algorithms closer to radiotherapy applications, DIRART is potentially a convenient and flexible platform that may facilitate ART and DIR research. 0 2011 Ameri-

  11. Image Understanding by Image-Seeking Adaptive Networks (ISAN).

    DTIC Science & Technology

    1987-08-10

    our reserch on adaptive neural networks in the visual and sensory-motor cortex of cats. We demonstrate that, under certain conditions, plasticity is...understanding in organisms proceeds directly from adaptively seeking whole images and not via a preliminary analysis of elementary features, followed by object...empirical reserch has always been that ultimately any neural system has to serve behavior and that behavior serves survival. Evolutionary selection makes it

  12. 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).

  13. “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

  14. Correlation processing for correction of phase distortions in subaperture imaging.

    PubMed

    Tavh, B; Karaman, M

    1999-01-01

    Ultrasonic subaperture imaging combines synthetic aperture and phased array approaches and permits low-cost systems with improved image quality. In subaperture processing, a large array is synthesized using echo signals collected from a number of receive subapertures by multiple firings of a phased transmit subaperture. Tissue inhomogeneities and displacements in subaperture imaging may cause significant phase distortions on received echo signals. Correlation processing on reference echo signals can be used for correction of the phase distortions, for which the accuracy and robustness are critically limited by the signal correlation. In this study, we explore correlation processing techniques for adaptive subaperture imaging with phase correction for motion and tissue inhomogeneities. The proposed techniques use new subaperture data acquisition schemes to produce reference signal sets with improved signal correlation. The experimental test results were obtained using raw radio frequency (RF) data acquired from two different phantoms with 3.5 MHz, 128-element transducer array. The results show that phase distortions can effectively be compensated by the proposed techniques in real-time adaptive subaperture imaging.

  15. Coherent Image Layout using an Adaptive Visual Vocabulary

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

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

    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 aremore » 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.« less

  16. 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

  17. Review of Medical Image Classification using the Adaptive Neuro-Fuzzy Inference System

    PubMed Central

    Hosseini, Monireh Sheikh; Zekri, Maryam

    2012-01-01

    Image classification is an issue that utilizes image processing, pattern recognition and classification methods. Automatic medical image classification is a progressive area in image classification, and it is expected to be more developed in the future. Because of this fact, automatic diagnosis can assist pathologists by providing second opinions and reducing their workload. This paper reviews the application of the adaptive neuro-fuzzy inference system (ANFIS) as a classifier in medical image classification during the past 16 years. ANFIS is a fuzzy inference system (FIS) implemented in the framework of an adaptive fuzzy neural network. It combines the explicit knowledge representation of an FIS with the learning power of artificial neural networks. The objective of ANFIS is to integrate the best features of fuzzy systems and neural networks. A brief comparison with other classifiers, main advantages and drawbacks of this classifier are investigated. PMID:23493054

  18. Adaptive regularization of the NL-means: application to image and video denoising.

    PubMed

    Sutour, Camille; Deledalle, Charles-Alban; Aujol, Jean-François

    2014-08-01

    Image denoising is a central problem in image processing and it is often a necessary step prior to higher level analysis such as segmentation, reconstruction, or super-resolution. The nonlocal means (NL-means) perform denoising by exploiting the natural redundancy of patterns inside an image; they perform a weighted average of pixels whose neighborhoods (patches) are close to each other. This reduces significantly the noise while preserving most of the image content. While it performs well on flat areas and textures, it suffers from two opposite drawbacks: it might over-smooth low-contrasted areas or leave a residual noise around edges and singular structures. Denoising can also be performed by total variation minimization-the Rudin, Osher and Fatemi model-which leads to restore regular images, but it is prone to over-smooth textures, staircasing effects, and contrast losses. We introduce in this paper a variational approach that corrects the over-smoothing and reduces the residual noise of the NL-means by adaptively regularizing nonlocal methods with the total variation. The proposed regularized NL-means algorithm combines these methods and reduces both of their respective defaults by minimizing an adaptive total variation with a nonlocal data fidelity term. Besides, this model adapts to different noise statistics and a fast solution can be obtained in the general case of the exponential family. We develop this model for image denoising and we adapt it to video denoising with 3D patches.

  19. Feature-Motivated Simplified Adaptive PCNN-Based Medical Image Fusion Algorithm in NSST Domain.

    PubMed

    Ganasala, Padma; Kumar, Vinod

    2016-02-01

    Multimodality medical image fusion plays a vital role in diagnosis, treatment planning, and follow-up studies of various diseases. It provides a composite image containing critical information of source images required for better localization and definition of different organs and lesions. In the state-of-the-art image fusion methods based on nonsubsampled shearlet transform (NSST) and pulse-coupled neural network (PCNN), authors have used normalized coefficient value to motivate the PCNN-processing both low-frequency (LF) and high-frequency (HF) sub-bands. This makes the fused image blurred and decreases its contrast. The main objective of this work is to design an image fusion method that gives the fused image with better contrast, more detail information, and suitable for clinical use. We propose a novel image fusion method utilizing feature-motivated adaptive PCNN in NSST domain for fusion of anatomical images. The basic PCNN model is simplified, and adaptive-linking strength is used. Different features are used to motivate the PCNN-processing LF and HF sub-bands. The proposed method is extended for fusion of functional image with an anatomical image in improved nonlinear intensity hue and saturation (INIHS) color model. Extensive fusion experiments have been performed on CT-MRI and SPECT-MRI datasets. Visual and quantitative analysis of experimental results proved that the proposed method provides satisfactory fusion outcome compared to other image fusion methods.

  20. Natural language processing and visualization in the molecular imaging domain.

    PubMed

    Tulipano, P Karina; Tao, Ying; Millar, William S; Zanzonico, Pat; Kolbert, Katherine; Xu, Hua; Yu, Hong; Chen, Lifeng; Lussier, Yves A; Friedman, Carol

    2007-06-01

    Molecular imaging is at the crossroads of genomic sciences and medical imaging. Information within the molecular imaging literature could be used to link to genomic and imaging information resources and to organize and index images in a way that is potentially useful to researchers. A number of natural language processing (NLP) systems are available to automatically extract information from genomic literature. One existing NLP system, known as BioMedLEE, automatically extracts biological information consisting of biomolecular substances and phenotypic data. This paper focuses on the adaptation, evaluation, and application of BioMedLEE to the molecular imaging domain. In order to adapt BioMedLEE for this domain, we extend an existing molecular imaging terminology and incorporate it into BioMedLEE. BioMedLEE's performance is assessed with a formal evaluation study. The system's performance, measured as recall and precision, is 0.74 (95% CI: [.70-.76]) and 0.70 (95% CI [.63-.76]), respectively. We adapt a JAVA viewer known as PGviewer for the simultaneous visualization of images with NLP extracted information.

  1. Adaptive optics imaging of geographic atrophy.

    PubMed

    Gocho, Kiyoko; Sarda, Valérie; Falah, Sabrina; Sahel, José-Alain; Sennlaub, Florian; Benchaboune, Mustapha; Ullern, Martine; Paques, Michel

    2013-05-01

    To report the findings of en face adaptive optics (AO) near infrared (NIR) reflectance fundus flood imaging in eyes with geographic atrophy (GA). Observational clinical study of AO NIR fundus imaging was performed in 12 eyes of nine patients with GA, and in seven controls using a flood illumination camera operating at 840 nm, in addition to routine clinical examination. To document short term and midterm changes, AO imaging sessions were repeated in four patients (mean interval between sessions 21 days; median follow up 6 months). As compared with scanning laser ophthalmoscope imaging, AO NIR imaging improved the resolution of the changes affecting the RPE. Multiple hyporeflective clumps were seen within and around GA areas. Time-lapse imaging revealed micrometric-scale details of the emergence and progression of areas of atrophy as well as the complex kinetics of some hyporeflective clumps. Such dynamic changes were observed within as well as outside atrophic areas. in eyes affected by GA, AO nir imaging allows high resolution documentation of the extent of RPE damage. this also revealed that a complex, dynamic process of redistribution of hyporeflective clumps throughout the posterior pole precedes and accompanies the emergence and progression of atrophy. therefore, these clumps are probably also a biomarker of rpe damage. AO NIR imaging may, therefore, be of interest to detect the earliest stages, to document the retinal pathology and to monitor the progression oF GA. (ClinicalTrials.gov number, NCT01546181.).

  2. Road sign recognition with fuzzy adaptive pre-processing models.

    PubMed

    Lin, Chien-Chuan; Wang, Ming-Shi

    2012-01-01

    A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance.

  3. Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

    PubMed Central

    Lin, Chien-Chuan; Wang, Ming-Shi

    2012-01-01

    A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

  4. An adaptive clustering algorithm for image matching based on corner feature

    NASA Astrophysics Data System (ADS)

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

    2018-04-01

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

  5. Edge enhancement and image equalization by unsharp masking using self-adaptive photochromic filters.

    PubMed

    Ferrari, José A; Flores, Jorge L; Perciante, César D; Frins, Erna

    2009-07-01

    A new method for real-time edge enhancement and image equalization using photochromic filters is presented. The reversible self-adaptive capacity of photochromic materials is used for creating an unsharp mask of the original image. This unsharp mask produces a kind of self filtering of the original image. Unlike the usual Fourier (coherent) image processing, the technique we propose can also be used with incoherent illumination. Validation experiments with Bacteriorhodopsin and photochromic glass are presented.

  6. Multiple Auto-Adapting Color Balancing for Large Number of Images

    NASA Astrophysics Data System (ADS)

    Zhou, X.

    2015-04-01

    This paper presents a powerful technology of color balance between images. It does not only work for small number of images but also work for unlimited large number of images. Multiple adaptive methods are used. To obtain color seamless mosaic dataset, local color is adjusted adaptively towards the target color. Local statistics of the source images are computed based on the so-called adaptive dodging window. The adaptive target colors are statistically computed according to multiple target models. The gamma function is derived from the adaptive target and the adaptive source local stats. It is applied to the source images to obtain the color balanced output images. Five target color surface models are proposed. They are color point (or single color), color grid, 1st, 2nd and 3rd 2D polynomials. Least Square Fitting is used to obtain the polynomial target color surfaces. Target color surfaces are automatically computed based on all source images or based on an external target image. Some special objects such as water and snow are filtered by percentage cut or a given mask. Excellent results are achieved. The performance is extremely fast to support on-the-fly color balancing for large number of images (possible of hundreds of thousands images). Detailed algorithm and formulae are described. Rich examples including big mosaic datasets (e.g., contains 36,006 images) are given. Excellent results and performance are presented. The results show that this technology can be successfully used in various imagery to obtain color seamless mosaic. This algorithm has been successfully using in ESRI ArcGis.

  7. Deblurring adaptive optics retinal images using deep convolutional neural networks.

    PubMed

    Fei, Xiao; Zhao, Junlei; Zhao, Haoxin; Yun, Dai; Zhang, Yudong

    2017-12-01

    The adaptive optics (AO) can be used to compensate for ocular aberrations to achieve near diffraction limited high-resolution retinal images. However, many factors such as the limited aberration measurement and correction accuracy with AO, intraocular scatter, imaging noise and so on will degrade the quality of retinal images. Image post processing is an indispensable and economical method to make up for the limitation of AO retinal imaging procedure. In this paper, we proposed a deep learning method to restore the degraded retinal images for the first time. The method directly learned an end-to-end mapping between the blurred and restored retinal images. The mapping was represented as a deep convolutional neural network that was trained to output high-quality images directly from blurry inputs without any preprocessing. This network was validated on synthetically generated retinal images as well as real AO retinal images. The assessment of the restored retinal images demonstrated that the image quality had been significantly improved.

  8. Deblurring adaptive optics retinal images using deep convolutional neural networks

    PubMed Central

    Fei, Xiao; Zhao, Junlei; Zhao, Haoxin; Yun, Dai; Zhang, Yudong

    2017-01-01

    The adaptive optics (AO) can be used to compensate for ocular aberrations to achieve near diffraction limited high-resolution retinal images. However, many factors such as the limited aberration measurement and correction accuracy with AO, intraocular scatter, imaging noise and so on will degrade the quality of retinal images. Image post processing is an indispensable and economical method to make up for the limitation of AO retinal imaging procedure. In this paper, we proposed a deep learning method to restore the degraded retinal images for the first time. The method directly learned an end-to-end mapping between the blurred and restored retinal images. The mapping was represented as a deep convolutional neural network that was trained to output high-quality images directly from blurry inputs without any preprocessing. This network was validated on synthetically generated retinal images as well as real AO retinal images. The assessment of the restored retinal images demonstrated that the image quality had been significantly improved. PMID:29296496

  9. 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.

  10. 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.

  11. Deep architecture neural network-based real-time image processing for image-guided radiotherapy.

    PubMed

    Mori, Shinichiro

    2017-08-01

    To develop real-time image processing for image-guided radiotherapy, we evaluated several neural network models for use with different imaging modalities, including X-ray fluoroscopic image denoising. Setup images of prostate cancer patients were acquired with two oblique X-ray fluoroscopic units. Two types of residual network were designed: a convolutional autoencoder (rCAE) and a convolutional neural network (rCNN). We changed the convolutional kernel size and number of convolutional layers for both networks, and the number of pooling and upsampling layers for rCAE. The ground-truth image was applied to the contrast-limited adaptive histogram equalization (CLAHE) method of image processing. Network models were trained to keep the quality of the output image close to that of the ground-truth image from the input image without image processing. For image denoising evaluation, noisy input images were used for the training. More than 6 convolutional layers with convolutional kernels >5×5 improved image quality. However, this did not allow real-time imaging. After applying a pair of pooling and upsampling layers to both networks, rCAEs with >3 convolutions each and rCNNs with >12 convolutions with a pair of pooling and upsampling layers achieved real-time processing at 30 frames per second (fps) with acceptable image quality. Use of our suggested network achieved real-time image processing for contrast enhancement and image denoising by the use of a conventional modern personal computer. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  12. Meaning of visualizing retinal cone mosaic on adaptive optics images.

    PubMed

    Jacob, Julie; Paques, Michel; Krivosic, Valérie; Dupas, Bénédicte; Couturier, Aude; Kulcsar, Caroline; Tadayoni, Ramin; Massin, Pascale; Gaudric, Alain

    2015-01-01

    To explore the anatomic correlation of the retinal cone mosaic on adaptive optics images. Retrospective nonconsecutive observational case series. A retrospective review of the multimodal imaging charts of 6 patients with focal alteration of the cone mosaic on adaptive optics was performed. Retinal diseases included acute posterior multifocal placoid pigment epitheliopathy (n = 1), hydroxychloroquine retinopathy (n = 1), and macular telangiectasia type 2 (n = 4). High-resolution retinal images were obtained using a flood-illumination adaptive optics camera. Images were recorded using standard imaging modalities: color and red-free fundus camera photography; infrared reflectance scanning laser ophthalmoscopy, fluorescein angiography, indocyanine green angiography, and spectral-domain optical coherence tomography (OCT) images. On OCT, in the marginal zone of the lesions, a disappearance of the interdigitation zone was observed, while the ellipsoid zone was preserved. Image recording demonstrated that such attenuation of the interdigitation zone co-localized with the disappearance of the cone mosaic on adaptive optics images. In 1 case, the restoration of the interdigitation zone paralleled that of the cone mosaic after a 2-month follow-up. Our results suggest that the interdigitation zone could contribute substantially to the reflectance of the cone photoreceptor mosaic. The absence of cones on adaptive optics images does not necessarily mean photoreceptor cell death. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. 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.

  14. In vivo imaging of human photoreceptor mosaic with wavefront sensorless adaptive optics optical coherence tomography.

    PubMed

    Wong, Kevin S K; Jian, Yifan; Cua, Michelle; Bonora, Stefano; Zawadzki, Robert J; Sarunic, Marinko V

    2015-02-01

    Wavefront sensorless adaptive optics optical coherence tomography (WSAO-OCT) is a novel imaging technique for in vivo high-resolution depth-resolved imaging that mitigates some of the challenges encountered with the use of sensor-based adaptive optics designs. This technique replaces the Hartmann Shack wavefront sensor used to measure aberrations with a depth-resolved image-driven optimization algorithm, with the metric based on the OCT volumes acquired in real-time. The custom-built ultrahigh-speed GPU processing platform and fast modal optimization algorithm presented in this paper was essential in enabling real-time, in vivo imaging of human retinas with wavefront sensorless AO correction. WSAO-OCT is especially advantageous for developing a clinical high-resolution retinal imaging system as it enables the use of a compact, low-cost and robust lens-based adaptive optics design. In this report, we describe our WSAO-OCT system for imaging the human photoreceptor mosaic in vivo. We validated our system performance by imaging the retina at several eccentricities, and demonstrated the improvement in photoreceptor visibility with WSAO compensation.

  15. Wavelet Transforms in Parallel Image Processing

    DTIC Science & Technology

    1994-01-27

    NUMBER OF PAGES Object Segmentation, Texture Segmentation, Image Compression, Image 137 Halftoning , Neural Network, Parallel Algorithms, 2D and 3D...Vector Quantization of Wavelet Transform Coefficients ........ ............................. 57 B.1.f Adaptive Image Halftoning based on Wavelet...application has been directed to the adaptive image halftoning . The gray information at a pixel, including its gray value and gradient, is represented by

  16. Some uses of wavelets for imaging dynamic processes in live cochlear structures

    NASA Astrophysics Data System (ADS)

    Boutet de Monvel, J.

    2007-09-01

    A variety of image and signal processing algorithms based on wavelet filtering tools have been developed during the last few decades, that are well adapted to the experimental variability typically encountered in live biological microscopy. A number of processing tools are reviewed, that use wavelets for adaptive image restoration and for motion or brightness variation analysis by optical flow computation. The usefulness of these tools for biological imaging is illustrated in the context of the restoration of images of the inner ear and the analysis of cochlear motion patterns in two and three dimensions. I also report on recent work that aims at capturing fluorescence intensity changes associated with vesicle dynamics at synaptic zones of sensory hair cells. This latest application requires one to separate the intensity variations associated with the physiological process under study from the variations caused by motion of the observed structures. A wavelet optical flow algorithm for doing this is presented, and its effectiveness is demonstrated on artificial and experimental image sequences.

  17. Compensation for the signal processing characteristics of ultrasound B-mode scanners in adaptive speckle reduction.

    PubMed

    Crawford, D C; Bell, D S; Bamber, J C

    1993-01-01

    A systematic method to compensate for nonlinear amplification of individual ultrasound B-scanners has been investigated in order to optimise performance of an adaptive speckle reduction (ASR) filter for a wide range of clinical ultrasonic imaging equipment. Three potential methods have been investigated: (1) a method involving an appropriate selection of the speckle recognition feature was successful when the scanner signal processing executes simple logarithmic compressions; (2) an inverse transform (decompression) of the B-mode image was effective in correcting for the measured characteristics of image data compression when the algorithm was implemented in full floating point arithmetic; (3) characterising the behaviour of the statistical speckle recognition feature under conditions of speckle noise was found to be the method of choice for implementation of the adaptive speckle reduction algorithm in limited precision integer arithmetic. In this example, the statistical features of variance and mean were investigated. The third method may be implemented on commercially available fast image processing hardware and is also better suited for transfer into dedicated hardware to facilitate real-time adaptive speckle reduction. A systematic method is described for obtaining ASR calibration data from B-mode images of a speckle producing phantom.

  18. 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. Copyright 2009 Elsevier Ltd. All rights reserved.

  19. Development of an adaptive bilateral filter for evaluating color image difference

    NASA Astrophysics Data System (ADS)

    Wang, Zhaohui; Hardeberg, Jon Yngve

    2012-04-01

    Spatial filtering, which aims to mimic the contrast sensitivity function (CSF) of the human visual system (HVS), has previously been combined with color difference formulae for measuring color image reproduction errors. These spatial filters attenuate imperceptible information in images, unfortunately including high frequency edges, which are believed to be crucial in the process of scene analysis by the HVS. The adaptive bilateral filter represents a novel approach, which avoids the undesirable loss of edge information introduced by CSF-based filtering. The bilateral filter employs two Gaussian smoothing filters in different domains, i.e., spatial domain and intensity domain. We propose a method to decide the parameters, which are designed to be adaptive to the corresponding viewing conditions, and the quantity and homogeneity of information contained in an image. Experiments and discussions are given to support the proposal. A series of perceptual experiments were conducted to evaluate the performance of our approach. The experimental sample images were reproduced with variations in six image attributes: lightness, chroma, hue, compression, noise, and sharpness/blurriness. The Pearson's correlation values between the model-predicted image difference and the observed difference were employed to evaluate the performance, and compare it with that of spatial CIELAB and image appearance model.

  20. 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

  1. Adaptive Spot Detection With Optimal Scale Selection in Fluorescence Microscopy Images.

    PubMed

    Basset, Antoine; Boulanger, Jérôme; Salamero, Jean; Bouthemy, Patrick; Kervrann, Charles

    2015-11-01

    Accurately detecting subcellular particles in fluorescence microscopy is of primary interest for further quantitative analysis such as counting, tracking, or classification. Our primary goal is to segment vesicles likely to share nearly the same size in fluorescence microscopy images. Our method termed adaptive thresholding of Laplacian of Gaussian (LoG) images with autoselected scale (ATLAS) automatically selects the optimal scale corresponding to the most frequent spot size in the image. Four criteria are proposed and compared to determine the optimal scale in a scale-space framework. Then, the segmentation stage amounts to thresholding the LoG of the intensity image. In contrast to other methods, the threshold is locally adapted given a probability of false alarm (PFA) specified by the user for the whole set of images to be processed. The local threshold is automatically derived from the PFA value and local image statistics estimated in a window whose size is not a critical parameter. We also propose a new data set for benchmarking, consisting of six collections of one hundred images each, which exploits backgrounds extracted from real microscopy images. We have carried out an extensive comparative evaluation on several data sets with ground-truth, which demonstrates that ATLAS outperforms existing methods. ATLAS does not need any fine parameter tuning and requires very low computation time. Convincing results are also reported on real total internal reflection fluorescence microscopy images.

  2. Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images.

    PubMed

    Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

    2015-05-22

    In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures.

  3. Adaptive Deblurring of Noisy Images

    DTIC Science & Technology

    2007-10-01

    deblurring filter adaptively by estimating energy of the signal and noise of the image to determine the passband and transition-band of the filter...The deblurring filter design criteria are: a) filter magnitude is less than one at the frequencies where the noise is stronger than the desired signal...filter is able to deblur the image by a desired amount based on the estimated or known blurring function while suppressing the noise in the output

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

    PubMed

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

    2013-12-02

    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.

  5. Image interpolation by adaptive 2-D autoregressive modeling and soft-decision estimation.

    PubMed

    Zhang, Xiangjun; Wu, Xiaolin

    2008-06-01

    The challenge of image interpolation is to preserve spatial details. We propose a soft-decision interpolation technique that estimates missing pixels in groups rather than one at a time. The new technique learns and adapts to varying scene structures using a 2-D piecewise autoregressive model. The model parameters are estimated in a moving window in the input low-resolution image. The pixel structure dictated by the learnt model is enforced by the soft-decision estimation process onto a block of pixels, including both observed and estimated. The result is equivalent to that of a high-order adaptive nonseparable 2-D interpolation filter. This new image interpolation approach preserves spatial coherence of interpolated images better than the existing methods, and it produces the best results so far over a wide range of scenes in both PSNR measure and subjective visual quality. Edges and textures are well preserved, and common interpolation artifacts (blurring, ringing, jaggies, zippering, etc.) are greatly reduced.

  6. 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

  7. Low-rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging

    PubMed Central

    Ravishankar, Saiprasad; Moore, Brian E.; Nadakuditi, Raj Rao; Fessler, Jeffrey A.

    2017-01-01

    Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery from undersampled measurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamic magnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method. PMID:28092528

  8. Low-Rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging.

    PubMed

    Ravishankar, Saiprasad; Moore, Brian E; Nadakuditi, Raj Rao; Fessler, Jeffrey A

    2017-05-01

    Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery fromundersampledmeasurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamicmagnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method.

  9. A wavelet domain adaptive image watermarking method based on chaotic encryption

    NASA Astrophysics Data System (ADS)

    Wei, Fang; Liu, Jian; Cao, Hanqiang; Yang, Jun

    2009-10-01

    A digital watermarking technique is a specific branch of steganography, which can be used in various applications, provides a novel way to solve security problems for multimedia information. In this paper, we proposed a kind of wavelet domain adaptive image digital watermarking method using chaotic stream encrypt and human eye visual property. The secret information that can be seen as a watermarking is hidden into a host image, which can be publicly accessed, so the transportation of the secret information will not attract the attention of illegal receiver. The experimental results show that the method is invisible and robust against some image processing.

  10. Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS)

    NASA Technical Reports Server (NTRS)

    Masek, Jeffrey G.

    2006-01-01

    The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project is creating a record of forest disturbance and regrowth for North America from the Landsat satellite record, in support of the carbon modeling activities. LEDAPS relies on the decadal Landsat GeoCover data set supplemented by dense image time series for selected locations. Imagery is first atmospherically corrected to surface reflectance, and then change detection algorithms are used to extract disturbance area, type, and frequency. Reuse of the MODIS Land processing system (MODAPS) architecture allows rapid throughput of over 2200 MSS, TM, and ETM+ scenes. Initial ("Beta") surface reflectance products are currently available for testing, and initial continental disturbance products will be available by the middle of 2006.

  11. Corner-point criterion for assessing nonlinear image processing imagers

    NASA Astrophysics Data System (ADS)

    Landeau, Stéphane; Pigois, Laurent; Foing, Jean-Paul; Deshors, Gilles; Swiathy, Greggory

    2017-10-01

    Range performance modeling of optronics imagers attempts to characterize the ability to resolve details in the image. Today, digital image processing is systematically used in conjunction with the optoelectronic system to correct its defects or to exploit tiny detection signals to increase performance. In order to characterize these processing having adaptive and non-linear properties, it becomes necessary to stimulate the imagers with test patterns whose properties are similar to the actual scene image ones, in terms of dynamic range, contours, texture and singular points. This paper presents an approach based on a Corner-Point (CP) resolution criterion, derived from the Probability of Correct Resolution (PCR) of binary fractal patterns. The fundamental principle lies in the respectful perception of the CP direction of one pixel minority value among the majority value of a 2×2 pixels block. The evaluation procedure considers the actual image as its multi-resolution CP transformation, taking the role of Ground Truth (GT). After a spatial registration between the degraded image and the original one, the degradation is statistically measured by comparing the GT with the degraded image CP transformation, in terms of localized PCR at the region of interest. The paper defines this CP criterion and presents the developed evaluation techniques, such as the measurement of the number of CP resolved on the target, the transformation CP and its inverse transform that make it possible to reconstruct an image of the perceived CPs. Then, this criterion is compared with the standard Johnson criterion, in the case of a linear blur and noise degradation. The evaluation of an imaging system integrating an image display and a visual perception is considered, by proposing an analysis scheme combining two methods: a CP measurement for the highly non-linear part (imaging) with real signature test target and conventional methods for the more linear part (displaying). The application to

  12. 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.

  13. A dynamic fuzzy genetic algorithm for natural image segmentation using adaptive mean shift

    NASA Astrophysics Data System (ADS)

    Arfan Jaffar, M.

    2017-01-01

    In this paper, a colour image segmentation approach based on hybridisation of adaptive mean shift (AMS), fuzzy c-mean and genetic algorithms (GAs) is presented. Image segmentation is the perceptual faction of pixels based on some likeness measure. GA with fuzzy behaviour is adapted to maximise the fuzzy separation and minimise the global compactness among the clusters or segments in spatial fuzzy c-mean (sFCM). It adds diversity to the search process to find the global optima. A simple fusion method has been used to combine the clusters to overcome the problem of over segmentation. The results show that our technique outperforms state-of-the-art methods.

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

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

    Ren Deqing; Dou Jiangpei; Zhang Xi

    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 furthermore » 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.« less

  15. 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.

  16. 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.

  17. 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.

  18. Hard real-time beam scheduler enables adaptive images in multi-probe systems

    NASA Astrophysics Data System (ADS)

    Tobias, Richard J.

    2014-03-01

    Real-time embedded-system concepts were adapted to allow an imaging system to responsively control the firing of multiple probes. Large-volume, operator-independent (LVOI) imaging would increase the diagnostic utility of ultrasound. An obstacle to this innovation is the inability of current systems to drive multiple transducers dynamically. Commercial systems schedule scanning with static lists of beams to be fired and processed; here we allow an imager to adapt to changing beam schedule demands, as an intelligent response to incoming image data. An example of scheduling changes is demonstrated with a flexible duplex mode two-transducer application mimicking LVOI imaging. Embedded-system concepts allow an imager to responsively control the firing of multiple probes. Operating systems use powerful dynamic scheduling algorithms, such as fixed priority preemptive scheduling. Even real-time operating systems lack the timing constraints required for ultrasound. Particularly for Doppler modes, events must be scheduled with sub-nanosecond precision, and acquired data is useless without this requirement. A successful scheduler needs unique characteristics. To get close to what would be needed in LVOI imaging, we show two transducers scanning different parts of a subjects leg. When one transducer notices flow in a region where their scans overlap, the system reschedules the other transducer to start flow mode and alter its beams to get a view of the observed vessel and produce a flow measurement. The second transducer does this in a focused region only. This demonstrates key attributes of a successful LVOI system, such as robustness against obstructions and adaptive self-correction.

  19. Image-adaptive and robust digital wavelet-domain watermarking for images

    NASA Astrophysics Data System (ADS)

    Zhao, Yi; Zhang, Liping

    2018-03-01

    We propose a new frequency domain wavelet based watermarking technique. The key idea of our scheme is twofold: multi-tier solution representation of image and odd-even quantization embedding/extracting watermark. Because many complementary watermarks need to be hidden, the watermark image designed is image-adaptive. The meaningful and complementary watermark images was embedded into the original image (host image) by odd-even quantization modifying coefficients, which was selected from the detail wavelet coefficients of the original image, if their magnitudes are larger than their corresponding Just Noticeable Difference thresholds. The tests show good robustness against best-known attacks such as noise addition, image compression, median filtering, clipping as well as geometric transforms. Further research may improve the performance by refining JND thresholds.

  20. 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.]. Copyright 2016, SLACK Incorporated.

  1. Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images

    PubMed Central

    Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

    2015-01-01

    In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures. PMID:26007744

  2. Binocular Multispectral Adaptive Imaging System (BMAIS)

    DTIC Science & Technology

    2010-07-26

    system for pilots that adaptively integrates shortwave infrared (SWIR), visible, near ‐IR (NIR), off‐head thermal, and computer symbology/imagery into...respective areas. BMAIS is a binocular helmet mounted imaging system that features dual shortwave infrared (SWIR) cameras, embedded image processors and...algorithms and fusion of other sensor sites such as forward looking infrared (FLIR) and other aircraft subsystems. BMAIS is attached to the helmet

  3. Dual-modality brain PET-CT image segmentation based on adaptive use of functional and anatomical information.

    PubMed

    Xia, Yong; Eberl, Stefan; Wen, Lingfeng; Fulham, Michael; Feng, David Dagan

    2012-01-01

    Dual medical imaging modalities, such as PET-CT, are now a routine component of clinical practice. Medical image segmentation methods, however, have generally only been applied to single modality images. In this paper, we propose the dual-modality image segmentation model to segment brain PET-CT images into gray matter, white matter and cerebrospinal fluid. This model converts PET-CT image segmentation into an optimization process controlled simultaneously by PET and CT voxel values and spatial constraints. It is innovative in the creation and application of the modality discriminatory power (MDP) coefficient as a weighting scheme to adaptively combine the functional (PET) and anatomical (CT) information on a voxel-by-voxel basis. Our approach relies upon allowing the modality with higher discriminatory power to play a more important role in the segmentation process. We compared the proposed approach to three other image segmentation strategies, including PET-only based segmentation, combination of the results of independent PET image segmentation and CT image segmentation, and simultaneous segmentation of joint PET and CT images without an adaptive weighting scheme. Our results in 21 clinical studies showed that our approach provides the most accurate and reliable segmentation for brain PET-CT images. Copyright © 2011 Elsevier Ltd. All rights reserved.

  4. Image processing of metal surface with structured light

    NASA Astrophysics Data System (ADS)

    Luo, Cong; Feng, Chang; Wang, Congzheng

    2014-09-01

    In structured light vision measurement system, the ideal image of structured light strip, in addition to black background , contains only the gray information of the position of the stripe. However, the actual image contains image noise, complex background and so on, which does not belong to the stripe, and it will cause interference to useful information. To extract the stripe center of mental surface accurately, a new processing method was presented. Through adaptive median filtering, the noise can be preliminary removed, and the noise which introduced by CCD camera and measured environment can be further removed with difference image method. To highlight fine details and enhance the blurred regions between the stripe and noise, the sharping algorithm is used which combine the best features of Laplacian operator and Sobel operator. Morphological opening operation and closing operation are used to compensate the loss of information.Experimental results show that this method is effective in the image processing, not only to restrain the information but also heighten contrast. It is beneficial for the following processing.

  5. 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.

  6. Medical image classification using spatial adjacent histogram based on adaptive local binary patterns.

    PubMed

    Liu, Dong; Wang, Shengsheng; Huang, Dezhi; Deng, Gang; Zeng, Fantao; Chen, Huiling

    2016-05-01

    Medical image recognition is an important task in both computer vision and computational biology. In the field of medical image classification, representing an image based on local binary patterns (LBP) descriptor has become popular. However, most existing LBP-based methods encode the binary patterns in a fixed neighborhood radius and ignore the spatial relationships among local patterns. The ignoring of the spatial relationships in the LBP will cause a poor performance in the process of capturing discriminative features for complex samples, such as medical images obtained by microscope. To address this problem, in this paper we propose a novel method to improve local binary patterns by assigning an adaptive neighborhood radius for each pixel. Based on these adaptive local binary patterns, we further propose a spatial adjacent histogram strategy to encode the micro-structures for image representation. An extensive set of evaluations are performed on four medical datasets which show that the proposed method significantly improves standard LBP and compares favorably with several other prevailing approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Adaptive Optical System for Retina Imaging Approaches Clinic Applications

    NASA Astrophysics Data System (ADS)

    Ling, N.; Zhang, Y.; Rao, X.; Wang, C.; Hu, Y.; Jiang, W.; Jiang, C.

    We presented "A small adaptive optical system on table for human retinal imaging" at the 3rd Workshop on Adaptive Optics for Industry and Medicine. In this system, a 19 element small deformable mirror was used as wavefront correction element. High resolution images of photo receptors and capillaries of human retina were obtained. In recent two years, at the base of this system a new adaptive optical system for human retina imaging has been developed. The wavefront correction element is a newly developed 37 element deformable mirror. Some modifications have been adopted for easy operation. Experiments for different imaging wavelengths and axial positions were conducted. Mosaic pictures of photoreceptors and capillaries were obtained. 100 normal and abnormal eyes of different ages have been inspected.The first report in the world concerning the most detailed capillary distribution images cover ±3° by ± 3° field around the fovea has been demonstrated. Some preliminary very early diagnosis experiment has been tried in laboratory. This system is being planned to move to the hospital for clinic experiments.

  8. cisTEM, user-friendly software for single-particle image processing.

    PubMed

    Grant, Timothy; Rohou, Alexis; Grigorieff, Nikolaus

    2018-03-07

    We have developed new open-source software called cis TEM (computational imaging system for transmission electron microscopy) for the processing of data for high-resolution electron cryo-microscopy and single-particle averaging. cis TEM features a graphical user interface that is used to submit jobs, monitor their progress, and display results. It implements a full processing pipeline including movie processing, image defocus determination, automatic particle picking, 2D classification, ab-initio 3D map generation from random parameters, 3D classification, and high-resolution refinement and reconstruction. Some of these steps implement newly-developed algorithms; others were adapted from previously published algorithms. The software is optimized to enable processing of typical datasets (2000 micrographs, 200 k - 300 k particles) on a high-end, CPU-based workstation in half a day or less, comparable to GPU-accelerated processing. Jobs can also be scheduled on large computer clusters using flexible run profiles that can be adapted for most computing environments. cis TEM is available for download from cistem.org. © 2018, Grant et al.

  9. cisTEM, user-friendly software for single-particle image processing

    PubMed Central

    2018-01-01

    We have developed new open-source software called cisTEM (computational imaging system for transmission electron microscopy) for the processing of data for high-resolution electron cryo-microscopy and single-particle averaging. cisTEM features a graphical user interface that is used to submit jobs, monitor their progress, and display results. It implements a full processing pipeline including movie processing, image defocus determination, automatic particle picking, 2D classification, ab-initio 3D map generation from random parameters, 3D classification, and high-resolution refinement and reconstruction. Some of these steps implement newly-developed algorithms; others were adapted from previously published algorithms. The software is optimized to enable processing of typical datasets (2000 micrographs, 200 k – 300 k particles) on a high-end, CPU-based workstation in half a day or less, comparable to GPU-accelerated processing. Jobs can also be scheduled on large computer clusters using flexible run profiles that can be adapted for most computing environments. cisTEM is available for download from cistem.org. PMID:29513216

  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. 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.

  12. 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

  13. Technical Note: DIRART – A software suite for deformable image registration and adaptive radiotherapy research

    PubMed Central

    Yang, Deshan; Brame, Scott; El Naqa, Issam; Aditya, Apte; Wu, Yu; Murty Goddu, S.; Mutic, Sasa; Deasy, Joseph O.; Low, Daniel A.

    2011-01-01

    Purpose: Recent years have witnessed tremendous progress in image guide radiotherapy technology and a growing interest in the possibilities for adapting treatment planning and delivery over the course of treatment. One obstacle faced by the research community has been the lack of a comprehensive open-source software toolkit dedicated for adaptive radiotherapy (ART). To address this need, the authors have developed a software suite called the Deformable Image Registration and Adaptive Radiotherapy Toolkit (DIRART). Methods:DIRART is an open-source toolkit developed in MATLAB. It is designed in an object-oriented style with focus on user-friendliness, features, and flexibility. It contains four classes of DIR algorithms, including the newer inverse consistency algorithms to provide consistent displacement vector field in both directions. It also contains common ART functions, an integrated graphical user interface, a variety of visualization and image-processing features, dose metric analysis functions, and interface routines. These interface routines make DIRART a powerful complement to the Computational Environment for Radiotherapy Research (CERR) and popular image-processing toolkits such as ITK. Results: DIRART provides a set of image processing∕registration algorithms and postprocessing functions to facilitate the development and testing of DIR algorithms. It also offers a good amount of options for DIR results visualization, evaluation, and validation. Conclusions: By exchanging data with treatment planning systems via DICOM-RT files and CERR, and by bringing image registration algorithms closer to radiotherapy applications, DIRART is potentially a convenient and flexible platform that may facilitate ART and DIR research. PMID:21361176

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

    PubMed

    Cho, Yong Thung; Roan, Michael J

    2009-02-01

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

  15. Processing, Cataloguing and Distribution of Uas Images in Near Real Time

    NASA Astrophysics Data System (ADS)

    Runkel, I.

    2013-08-01

    Why are UAS such a hype? UAS make the data capture flexible, fast and easy. For many applications this is more important than a perfect photogrammetric aerial image block. To ensure, that the advantage of a fast data capturing will be valid up to the end of the processing chain, all intermediate steps like data processing and data dissemination to the customer need to be flexible and fast as well. GEOSYSTEMS has established the whole processing workflow as server/client solution. This is the focus of the presentation. Depending on the image acquisition system the image data can be down linked during the flight to the data processing computer or it is stored on a mobile device and hooked up to the data processing computer after the flight campaign. The image project manager reads the data from the device and georeferences the images according to the position data. The meta data is converted into an ISO conform format and subsequently all georeferenced images are catalogued in the raster data management System ERDAS APOLLO. APOLLO provides the data, respectively the images as an OGC-conform services to the customer. Within seconds the UAV-images are ready to use for GIS application, image processing or direct interpretation via web applications - where ever you want. The whole processing chain is built in a generic manner. It can be adapted to a magnitude of applications. The UAV imageries can be processed and catalogued as single ortho imges or as image mosaic. Furthermore, image data of various cameras can be fusioned. By using WPS (web processing services) image enhancement, image analysis workflows like change detection layers can be calculated and provided to the image analysts. The processing of the WPS runs direct on the raster data management server. The image analyst has no data and no software on his local computer. This workflow is proven to be fast, stable and accurate. It is designed to support time critical applications for security demands - the images

  16. Visible near-diffraction-limited lucky imaging with full-sky laser-assisted adaptive optics

    NASA Astrophysics Data System (ADS)

    Basden, A. G.

    2014-08-01

    Both lucky imaging techniques and adaptive optics require natural guide stars, limiting sky-coverage, even when laser guide stars are used. Lucky imaging techniques become less successful on larger telescopes unless adaptive optics is used, as the fraction of images obtained with well-behaved turbulence across the whole telescope pupil becomes vanishingly small. Here, we introduce a technique combining lucky imaging techniques with tomographic laser guide star adaptive optics systems on large telescopes. This technique does not require any natural guide star for the adaptive optics, and hence offers full sky-coverage adaptive optics correction. In addition, we introduce a new method for lucky image selection based on residual wavefront phase measurements from the adaptive optics wavefront sensors. We perform Monte Carlo modelling of this technique, and demonstrate I-band Strehl ratios of up to 35 per cent in 0.7 arcsec mean seeing conditions with 0.5 m deformable mirror pitch and full adaptive optics sky-coverage. We show that this technique is suitable for use with lucky imaging reference stars as faint as magnitude 18, and fainter if more advanced image selection and centring techniques are used.

  17. On Adapting the Tensor Voting Framework to Robust Color Image Denoising

    NASA Astrophysics Data System (ADS)

    Moreno, Rodrigo; Garcia, Miguel Angel; Puig, Domenec; Julià, Carme

    This paper presents an adaptation of the tensor voting framework for color image denoising, while preserving edges. Tensors are used in order to encode the CIELAB color channels, the uniformity and the edginess of image pixels. A specific voting process is proposed in order to propagate color from a pixel to its neighbors by considering the distance between pixels, the perceptual color difference (by using an optimized version of CIEDE2000), a uniformity measurement and the likelihood of the pixels being impulse noise. The original colors are corrected with those encoded by the tensors obtained after the voting process. Peak to noise ratios and visual inspection show that the proposed methodology has a better performance than state-of-the-art techniques.

  18. Infrared and visible images registration with adaptable local-global feature integration for rail inspection

    NASA Astrophysics Data System (ADS)

    Tang, Chaoqing; Tian, Gui Yun; Chen, Xiaotian; Wu, Jianbo; Li, Kongjing; Meng, Hongying

    2017-12-01

    Active thermography provides infrared images that contain sub-surface defect information, while visible images only reveal surface information. Mapping infrared information to visible images offers more comprehensive visualization for decision-making in rail inspection. However, the common information for registration is limited due to different modalities in both local and global level. For example, rail track which has low temperature contrast reveals rich details in visible images, but turns blurry in the infrared counterparts. This paper proposes a registration algorithm called Edge-Guided Speeded-Up-Robust-Features (EG-SURF) to address this issue. Rather than sequentially integrating local and global information in matching stage which suffered from buckets effect, this algorithm adaptively integrates local and global information into a descriptor to gather more common information before matching. This adaptability consists of two facets, an adaptable weighting factor between local and global information, and an adaptable main direction accuracy. The local information is extracted using SURF while the global information is represented by shape context from edges. Meanwhile, in shape context generation process, edges are weighted according to local scale and decomposed into bins using a vector decomposition manner to provide more accurate descriptor. The proposed algorithm is qualitatively and quantitatively validated using eddy current pulsed thermography scene in the experiments. In comparison with other algorithms, better performance has been achieved.

  19. Automatic detection of cone photoreceptors in split detector adaptive optics scanning light ophthalmoscope images.

    PubMed

    Cunefare, David; Cooper, Robert F; Higgins, Brian; Katz, David F; Dubra, Alfredo; Carroll, Joseph; Farsiu, Sina

    2016-05-01

    Quantitative analysis of the cone photoreceptor mosaic in the living retina is potentially useful for early diagnosis and prognosis of many ocular diseases. Non-confocal split detector based adaptive optics scanning light ophthalmoscope (AOSLO) imaging reveals the cone photoreceptor inner segment mosaics often not visualized on confocal AOSLO imaging. Despite recent advances in automated cone segmentation algorithms for confocal AOSLO imagery, quantitative analysis of split detector AOSLO images is currently a time-consuming manual process. In this paper, we present the fully automatic adaptive filtering and local detection (AFLD) method for detecting cones in split detector AOSLO images. We validated our algorithm on 80 images from 10 subjects, showing an overall mean Dice's coefficient of 0.95 (standard deviation 0.03), when comparing our AFLD algorithm to an expert grader. This is comparable to the inter-observer Dice's coefficient of 0.94 (standard deviation 0.04). To the best of our knowledge, this is the first validated, fully-automated segmentation method which has been applied to split detector AOSLO images.

  20. Adaptive filtering in biological signal processing.

    PubMed

    Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

    1990-01-01

    The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed.

  1. Markov Processes in Image Processing

    NASA Astrophysics Data System (ADS)

    Petrov, E. P.; Kharina, N. L.

    2018-05-01

    Digital images are used as an information carrier in different sciences and technologies. The aspiration to increase the number of bits in the image pixels for the purpose of obtaining more information is observed. In the paper, some methods of compression and contour detection on the basis of two-dimensional Markov chain are offered. Increasing the number of bits on the image pixels will allow one to allocate fine object details more precisely, but it significantly complicates image processing. The methods of image processing do not concede by the efficiency to well-known analogues, but surpass them in processing speed. An image is separated into binary images, and processing is carried out in parallel with each without an increase in speed, when increasing the number of bits on the image pixels. One more advantage of methods is the low consumption of energy resources. Only logical procedures are used and there are no computing operations. The methods can be useful in processing images of any class and assignment in processing systems with a limited time and energy resources.

  2. Voyager image processing at the Image Processing Laboratory

    NASA Astrophysics Data System (ADS)

    Jepsen, P. L.; Mosher, J. A.; Yagi, G. M.; Avis, C. C.; Lorre, J. J.; Garneau, G. W.

    1980-09-01

    This paper discusses new digital processing techniques as applied to the Voyager Imaging Subsystem and devised to explore atmospheric dynamics, spectral variations, and the morphology of Jupiter, Saturn and their satellites. Radiometric and geometric decalibration processes, the modulation transfer function, and processes to determine and remove photometric properties of the atmosphere and surface of Jupiter and its satellites are examined. It is exhibited that selected images can be processed into 'approach at constant longitude' time lapse movies which are useful in observing atmospheric changes of Jupiter. Photographs are included to illustrate various image processing techniques.

  3. Voyager image processing at the Image Processing Laboratory

    NASA Technical Reports Server (NTRS)

    Jepsen, P. L.; Mosher, J. A.; Yagi, G. M.; Avis, C. C.; Lorre, J. J.; Garneau, G. W.

    1980-01-01

    This paper discusses new digital processing techniques as applied to the Voyager Imaging Subsystem and devised to explore atmospheric dynamics, spectral variations, and the morphology of Jupiter, Saturn and their satellites. Radiometric and geometric decalibration processes, the modulation transfer function, and processes to determine and remove photometric properties of the atmosphere and surface of Jupiter and its satellites are examined. It is exhibited that selected images can be processed into 'approach at constant longitude' time lapse movies which are useful in observing atmospheric changes of Jupiter. Photographs are included to illustrate various image processing techniques.

  4. 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.

  5. A synoptic description of coal basins via image processing

    NASA Technical Reports Server (NTRS)

    Farrell, K. W., Jr.; Wherry, D. B.

    1978-01-01

    An existing image processing system is adapted to describe the geologic attributes of a regional coal basin. This scheme handles a map as if it were a matrix, in contrast to more conventional approaches which represent map information in terms of linked polygons. The utility of the image processing approach is demonstrated by a multiattribute analysis of the Herrin No. 6 coal seam in Illinois. Findings include the location of a resource and estimation of tonnage corresponding to constraints on seam thickness, overburden, and Btu value, which are illustrative of the need for new mining technology.

  6. 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.

  7. PCA-based spatially adaptive denoising of CFA images for single-sensor digital cameras.

    PubMed

    Zheng, Lei; Lukac, Rastislav; Wu, Xiaolin; Zhang, David

    2009-04-01

    Single-sensor digital color cameras use a process called color demosiacking to produce full color images from the data captured by a color filter array (CAF). The quality of demosiacked images is degraded due to the sensor noise introduced during the image acquisition process. The conventional solution to combating CFA sensor noise is demosiacking first, followed by a separate denoising processing. This strategy will generate many noise-caused color artifacts in the demosiacking process, which are hard to remove in the denoising process. Few denoising schemes that work directly on the CFA images have been presented because of the difficulties arisen from the red, green and blue interlaced mosaic pattern, yet a well-designed "denoising first and demosiacking later" scheme can have advantages such as less noise-caused color artifacts and cost-effective implementation. This paper presents a principle component analysis (PCA)-based spatially-adaptive denoising algorithm, which works directly on the CFA data using a supporting window to analyze the local image statistics. By exploiting the spatial and spectral correlations existing in the CFA image, the proposed method can effectively suppress noise while preserving color edges and details. Experiments using both simulated and real CFA images indicate that the proposed scheme outperforms many existing approaches, including those sophisticated demosiacking and denoising schemes, in terms of both objective measurement and visual evaluation.

  8. Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

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

    Keller, Brad M.; Nathan, Diane L.; Wang Yan

    Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., 'FOR PROCESSING') andmore » vendor postprocessed (i.e., 'FOR PRESENTATION'), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which

  9. Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation.

    PubMed

    Keller, Brad M; Nathan, Diane L; Wang, Yan; Zheng, Yuanjie; Gee, James C; Conant, Emily F; Kontos, Despina

    2012-08-01

    The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., "FOR PROCESSING") and vendor postprocessed (i.e., "FOR PRESENTATION"), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a

  10. 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

  11. The Adaptive Optics Lucky Imager: Diffraction limited imaging at visible wavelengths with large ground-based telescopes

    NASA Astrophysics Data System (ADS)

    Crass, Jonathan; Mackay, Craig; King, David; Rebolo-López, Rafael; Labadie, Lucas; Puga, Marta; Oscoz, Alejandro; González Escalera, Victor; Pérez Garrido, Antonio; López, Roberto; Pérez-Prieto, Jorge; Rodríguez-Ramos, Luis; Velasco, Sergio; Villó, Isidro

    2015-01-01

    One of the continuing challenges facing astronomers today is the need to obtain ever higher resolution images of the sky. Whether studying nearby crowded fields or distant objects, with increased resolution comes the ability to probe systems in more detail and advance our understanding of the Universe. Obtaining these high-resolution images at visible wavelengths however has previously been limited to the Hubble Space Telescope (HST) due to atmospheric effects limiting the spatial resolution of ground-based telescopes to a fraction of their potential. With HST now having a finite lifespan, it is prudent to investigate other techniques capable of providing these kind of observations from the ground. Maintaining this capability is one of the goals of the Adaptive Optics Lucky Imager (AOLI).Achieving the highest resolutions requires the largest telescope apertures, however, this comes at the cost of increased atmospheric distortion. To overcome these atmospheric effects, there are two main techniques employed today: adaptive optics (AO) and lucky imaging. These techniques individually are unable to provide diffraction limited imaging in the visible on large ground-based telescopes; AO currently only works at infrared wavelengths while lucky imaging reduces in effectiveness on telescopes greater than 2.5 metres in diameter. The limitations of both techniques can be overcome by combing them together to provide diffraction limited imaging at visible wavelengths on the ground.The Adaptive Optics Lucky Imager is being developed as a European collaboration and combines AO and lucky imaging in a dedicated instrument for the first time. Initially for use on the 4.2 metre William Herschel Telescope, AOLI uses a low-order adaptive optics system to reduce the effects of atmospheric turbulence before imaging with a lucky imaging based science detector. The AO system employs a novel type of wavefront sensor, the non-linear Curvature Wavefront Sensor (nlCWFS) which provides

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

    PubMed Central

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

    2015-01-01

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

  13. 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.

  14. A new interferential multispectral image compression algorithm based on adaptive classification and curve-fitting

    NASA Astrophysics Data System (ADS)

    Wang, Ke-Yan; Li, Yun-Song; Liu, Kai; Wu, Cheng-Ke

    2008-08-01

    A novel compression algorithm for interferential multispectral images based on adaptive classification and curve-fitting is proposed. The image is first partitioned adaptively into major-interference region and minor-interference region. Different approximating functions are then constructed for two kinds of regions respectively. For the major interference region, some typical interferential curves are selected to predict other curves. These typical curves are then processed by curve-fitting method. For the minor interference region, the data of each interferential curve are independently approximated. Finally the approximating errors of two regions are entropy coded. The experimental results show that, compared with JPEG2000, the proposed algorithm not only decreases the average output bit-rate by about 0.2 bit/pixel for lossless compression, but also improves the reconstructed images and reduces the spectral distortion greatly, especially at high bit-rate for lossy compression.

  15. Research on adaptive optics image restoration algorithm based on improved joint maximum a posteriori method

    NASA Astrophysics Data System (ADS)

    Zhang, Lijuan; Li, Yang; Wang, Junnan; Liu, Ying

    2018-03-01

    In this paper, we propose a point spread function (PSF) reconstruction method and joint maximum a posteriori (JMAP) estimation method for the adaptive optics image restoration. Using the JMAP method as the basic principle, we establish the joint log likelihood function of multi-frame adaptive optics (AO) images based on the image Gaussian noise models. To begin with, combining the observed conditions and AO system characteristics, a predicted PSF model for the wavefront phase effect is developed; then, we build up iterative solution formulas of the AO image based on our proposed algorithm, addressing the implementation process of multi-frame AO images joint deconvolution method. We conduct a series of experiments on simulated and real degraded AO images to evaluate our proposed algorithm. Compared with the Wiener iterative blind deconvolution (Wiener-IBD) algorithm and Richardson-Lucy IBD algorithm, our algorithm has better restoration effects including higher peak signal-to-noise ratio ( PSNR) and Laplacian sum ( LS) value than the others. The research results have a certain application values for actual AO image restoration.

  16. Adaptive striping watershed segmentation method for processing microscopic images of overlapping irregular-shaped and multicentre particles.

    PubMed

    Xiao, X; Bai, B; Xu, N; Wu, K

    2015-04-01

    Oversegmentation is a major drawback of the morphological watershed algorithm. Here, we study and reveal that the oversegmentation is not only because of the irregular shapes of the particle images, which people are familiar with, but also because of some particles, such as ellipses, with more than one centre. A new parameter, the striping level, is introduced and the criterion for striping parameter is built to help find the right markers prior to segmentation. An adaptive striping watershed algorithm is established by applying a procedure, called the marker searching algorithm, to find the markers, which can effectively suppress the oversegmentation. The effectiveness of the proposed method is validated by analysing some typical particle images including the images of gold nanorod ensembles. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

  17. Optical Profilometers Using Adaptive Signal Processing

    NASA Technical Reports Server (NTRS)

    Hall, Gregory A.; Youngquist, Robert; Mikhael, Wasfy

    2006-01-01

    A method of adaptive signal processing has been proposed as the basis of a new generation of interferometric optical profilometers for measuring surfaces. The proposed profilometers would be portable, hand-held units. Sizes could be thus reduced because the adaptive-signal-processing method would make it possible to substitute lower-power coherent light sources (e.g., laser diodes) for white light sources and would eliminate the need for most of the optical components of current white-light profilometers. The adaptive-signal-processing method would make it possible to attain scanning ranges of the order of decimeters in the proposed profilometers.

  18. 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.

  19. Experimental Demonstration of Adaptive Infrared Multispectral Imaging Using Plasmonic Filter Array (Postprint)

    DTIC Science & Technology

    2016-10-10

    AFRL-RX-WP-JA-2017-0189 EXPERIMENTAL DEMONSTRATION OF ADAPTIVE INFRARED MULTISPECTRAL IMAGING USING PLASMONIC FILTER ARRAY...March 2016 – 23 May 2016 4. TITLE AND SUBTITLE EXPERIMENTAL DEMONSTRATION OF ADAPTIVE INFRARED MULTISPECTRAL IMAGING USING PLASMONIC FILTER ARRAY...experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios

  20. A new method of SC image processing for confluence estimation.

    PubMed

    Soleimani, Sajjad; Mirzaei, Mohsen; Toncu, Dana-Cristina

    2017-10-01

    Stem cells images are a strong instrument in the estimation of confluency during their culturing for therapeutic processes. Various laboratory conditions, such as lighting, cell container support and image acquisition equipment, effect on the image quality, subsequently on the estimation efficiency. This paper describes an efficient image processing method for cell pattern recognition and morphological analysis of images that were affected by uneven background. The proposed algorithm for enhancing the image is based on coupling a novel image denoising method through BM3D filter with an adaptive thresholding technique for improving the uneven background. This algorithm works well to provide a faster, easier, and more reliable method than manual measurement for the confluency assessment of stem cell cultures. The present scheme proves to be valid for the prediction of the confluency and growth of stem cells at early stages for tissue engineering in reparatory clinical surgery. The method used in this paper is capable of processing the image of the cells, which have already contained various defects due to either personnel mishandling or microscope limitations. Therefore, it provides proper information even out of the worst original images available. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Visual communications and image processing '92; Proceedings of the Meeting, Boston, MA, Nov. 18-20, 1992

    NASA Astrophysics Data System (ADS)

    Maragos, Petros

    The topics discussed at the conference include hierarchical image coding, motion analysis, feature extraction and image restoration, video coding, and morphological and related nonlinear filtering. Attention is also given to vector quantization, morphological image processing, fractals and wavelets, architectures for image and video processing, image segmentation, biomedical image processing, and model-based analysis. Papers are presented on affine models for motion and shape recovery, filters for directly detecting surface orientation in an image, tracking of unresolved targets in infrared imagery using a projection-based method, adaptive-neighborhood image processing, and regularized multichannel restoration of color images using cross-validation. (For individual items see A93-20945 to A93-20951)

  2. Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

    NASA Astrophysics Data System (ADS)

    Tan, Zhen-ya; He, Feng

    2018-04-01

    With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

  3. Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

    PubMed Central

    Keller, Brad M.; Nathan, Diane L.; Wang, Yan; Zheng, Yuanjie; Gee, James C.; Conant, Emily F.; Kontos, Despina

    2012-01-01

    Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., “FOR PROCESSING”) and vendor postprocessed (i.e., “FOR PRESENTATION”), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which

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

    NASA Astrophysics Data System (ADS)

    Rogowska, Jadwiga; Brezinski, Mark E.

    2002-02-01

    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.

  5. Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics.

    PubMed

    Li, Dongming; Sun, Changming; Yang, Jinhua; Liu, Huan; Peng, Jiaqi; Zhang, Lijuan

    2017-04-06

    An adaptive optics (AO) system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.

  6. Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics

    PubMed Central

    Li, Dongming; Sun, Changming; Yang, Jinhua; Liu, Huan; Peng, Jiaqi; Zhang, Lijuan

    2017-01-01

    An adaptive optics (AO) system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods. PMID:28383503

  7. Adaptive compressive ghost imaging based on wavelet trees and sparse representation.

    PubMed

    Yu, Wen-Kai; Li, Ming-Fei; Yao, Xu-Ri; Liu, Xue-Feng; Wu, Ling-An; Zhai, Guang-Jie

    2014-03-24

    Compressed sensing is a theory which can reconstruct an image almost perfectly with only a few measurements by finding its sparsest representation. However, the computation time consumed for large images may be a few hours or more. In this work, we both theoretically and experimentally demonstrate a method that combines the advantages of both adaptive computational ghost imaging and compressed sensing, which we call adaptive compressive ghost imaging, whereby both the reconstruction time and measurements required for any image size can be significantly reduced. The technique can be used to improve the performance of all computational ghost imaging protocols, especially when measuring ultra-weak or noisy signals, and can be extended to imaging applications at any wavelength.

  8. Magnetic resonance image restoration via dictionary learning under spatially adaptive constraints.

    PubMed

    Wang, Shanshan; Xia, Yong; Dong, Pei; Feng, David Dagan; Luo, Jianhua; Huang, Qiu

    2013-01-01

    This paper proposes a spatially adaptive constrained dictionary learning (SAC-DL) algorithm for Rician noise removal in magnitude magnetic resonance (MR) images. This algorithm explores both the strength of dictionary learning to preserve image structures and the robustness of local variance estimation to remove signal-dependent Rician noise. The magnitude image is first separated into a number of partly overlapping image patches. The statistics of each patch are collected and analyzed to obtain a local noise variance. To better adapt to Rician noise, a correction factor is formulated with the local signal-to-noise ratio (SNR). Finally, the trained dictionary is used to denoise each image patch under spatially adaptive constraints. The proposed algorithm has been compared to the popular nonlocal means (NLM) filtering and unbiased NLM (UNLM) algorithm on simulated T1-weighted, T2-weighted and PD-weighted MR images. Our results suggest that the SAC-DL algorithm preserves more image structures while effectively removing the noise than NLM and it is also superior to UNLM at low noise levels.

  9. Design of a high definition imaging (HDI) analysis technique adapted to challenging environments

    NASA Astrophysics Data System (ADS)

    Laurent, Sophie Nathalie

    2005-11-01

    This dissertation describes a new comprehensive, flexible, highly-automated and computationally-robust approach for high definition imaging (HDI), a data acquisition technique for video-rate imaging through a turbulent atmosphere with telescopes not equipped with adaptive optics (AO). The HDI process, when applied to astronomical objects, involves the recording of a large number of images (10 3 -10 5 ) from the Earth and, in post-processing mode, selection of the very best ones to create a "perfect-seeing" diffraction-limited image via a three-step process. First, image registration is performed to find the exact position of the object in each field, using a template similar in size and shape to the target. The next task is to select only higher-quality fields using a criterion based on a measure of the blur in a region of interest around that object. The images are then shifted and added together to create an effective time exposure under ideal observing conditions. The last step's objective is to remove residual distortions in the image caused by the atmosphere and the optical equipment, using a point spread function (PSF), and a technique called "l 1 regularization" that has been adapted to this type of environment. In order to study the tenuous sodium atmospheres around solar system bodies, the three-step HDI procedure is done first in the white light domain (695-950 nm), where the Signal-to-Noise Ratio (SNR) of the images is high, resulting in an image with a sharp limb. Then the known selection and registration results are mapped to the simultaneously recorded spectral data (sodium lines: 589 and 589.6 nm), where the lower-SNR images cannot support independent registration and selection. Science results can then be derived from this spectral study to understand the structure of the atmospheres of moons and planets. This dissertation's contribution to space physics deals with locating the source of escaping sodium from Jupiter's moon lo. The results show, for

  10. An adaptive signal-processing approach to online adaptive tutoring.

    PubMed

    Bergeron, Bryan; Cline, Andrew

    2011-01-01

    Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need for the construction of explicit expert and student models. A key advantage of our method over conventional approaches is a lower barrier to entry for educators who want to develop adaptive online learning materials.

  11. 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.

  12. Large-field-of-view imaging by multi-pupil adaptive optics.

    PubMed

    Park, Jung-Hoon; Kong, Lingjie; Zhou, Yifeng; Cui, Meng

    2017-06-01

    Adaptive optics can correct for optical aberrations. We developed multi-pupil adaptive optics (MPAO), which enables simultaneous wavefront correction over a field of view of 450 × 450 μm 2 and expands the correction area to nine times that of conventional methods. MPAO's ability to perform spatially independent wavefront control further enables 3D nonplanar imaging. We applied MPAO to in vivo structural and functional imaging in the mouse brain.

  13. The Urban Adaptation and Adaptation Process of Urban Migrant Children: A Qualitative Study

    ERIC Educational Resources Information Center

    Liu, Yang; Fang, Xiaoyi; Cai, Rong; Wu, Yang; Zhang, Yaofang

    2009-01-01

    This article employs qualitative research methods to explore the urban adaptation and adaptation processes of Chinese migrant children. Through twenty-one in-depth interviews with migrant children, the researchers discovered: The participant migrant children showed a fairly high level of adaptation to the city; their process of urban adaptation…

  14. Spatio-Chromatic Adaptation via Higher-Order Canonical Correlation Analysis of Natural Images

    PubMed Central

    Gutmann, Michael U.; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

    2014-01-01

    Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation. PMID:24533049

  15. Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.

    PubMed

    Gutmann, Michael U; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

    2014-01-01

    Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation.

  16. Multidimensional deconvolution of optical microscope and ultrasound imaging using adaptive least-mean-square (LMS) inverse filtering

    NASA Astrophysics Data System (ADS)

    Sapia, Mark Angelo

    2000-11-01

    Three-dimensional microscope images typically suffer from reduced resolution due to the effects of convolution, optical aberrations and out-of-focus blurring. Two- dimensional ultrasound images are also degraded by convolutional bluffing and various sources of noise. Speckle noise is a major problem in ultrasound images. In microscopy and ultrasound, various methods of digital filtering have been used to improve image quality. Several methods of deconvolution filtering have been used to improve resolution by reversing the convolutional effects, many of which are based on regularization techniques and non-linear constraints. The technique discussed here is a unique linear filter for deconvolving 3D fluorescence microscopy or 2D ultrasound images. The process is to solve for the filter completely in the spatial-domain using an adaptive algorithm to converge to an optimum solution for de-blurring and resolution improvement. There are two key advantages of using an adaptive solution: (1)it efficiently solves for the filter coefficients by taking into account all sources of noise and degraded resolution at the same time, and (2)achieves near-perfect convergence to the ideal linear deconvolution filter. This linear adaptive technique has other advantages such as avoiding artifacts of frequency-domain transformations and concurrent adaptation to suppress noise. Ultimately, this approach results in better signal-to-noise characteristics with virtually no edge-ringing. Many researchers have not adopted linear techniques because of poor convergence, noise instability and negative valued data in the results. The methods presented here overcome many of these well-documented disadvantages and provide results that clearly out-perform other linear methods and may also out-perform regularization and constrained algorithms. In particular, the adaptive solution is most responsible for overcoming the poor performance associated with linear techniques. This linear adaptive approach to

  17. Adaptive Optics Image Restoration Based on Frame Selection and Multi-frame Blind Deconvolution

    NASA Astrophysics Data System (ADS)

    Tian, Yu; Rao, Chang-hui; Wei, Kai

    Restricted by the observational condition and the hardware, adaptive optics can only make a partial correction of the optical images blurred by atmospheric turbulence. A postprocessing method based on frame selection and multi-frame blind deconvolution is proposed for the restoration of high-resolution adaptive optics images. By frame selection we mean we first make a selection of the degraded (blurred) images for participation in the iterative blind deconvolution calculation, with no need of any a priori knowledge, and with only a positivity constraint. This method has been applied to the restoration of some stellar images observed by the 61-element adaptive optics system installed on the Yunnan Observatory 1.2m telescope. The experimental results indicate that this method can effectively compensate for the residual errors of the adaptive optics system on the image, and the restored image can reach the diffraction-limited quality.

  18. 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.

  19. 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

  20. Live imaging using adaptive optics with fluorescent protein guide-stars

    PubMed Central

    Tao, Xiaodong; Crest, Justin; Kotadia, Shaila; Azucena, Oscar; Chen, Diana C.; Sullivan, William; Kubby, Joel

    2012-01-01

    Spatially and temporally dependent optical aberrations induced by the inhomogeneous refractive index of live samples limit the resolution of live dynamic imaging. We introduce an adaptive optical microscope with a direct wavefront sensing method using a Shack-Hartmann wavefront sensor and fluorescent protein guide-stars for live imaging. The results of imaging Drosophila embryos demonstrate its ability to correct aberrations and achieve near diffraction limited images of medial sections of large Drosophila embryos. GFP-polo labeled centrosomes can be observed clearly after correction but cannot be observed before correction. Four dimensional time lapse images are achieved with the correction of dynamic aberrations. These studies also demonstrate that the GFP-tagged centrosome proteins, Polo and Cnn, serve as excellent biological guide-stars for adaptive optics based microscopy. PMID:22772285

  1. Color Imaging management in film processing

    NASA Astrophysics Data System (ADS)

    Tremeau, Alain; Konik, Hubert; Colantoni, Philippe

    2003-12-01

    The latest research projects in the laboratory LIGIV concerns capture, processing, archiving and display of color images considering the trichromatic nature of the Human Vision System (HSV). Among these projects one addresses digital cinematographic film sequences of high resolution and dynamic range. This project aims to optimize the use of content for the post-production operators and for the end user. The studies presented in this paper address the use of metadata to optimise the consumption of video content on a device of user's choice independent of the nature of the equipment that captured the content. Optimising consumption includes enhancing the quality of image reconstruction on a display. Another part of this project addresses the content-based adaptation of image display. Main focus is on Regions of Interest (ROI) operations, based on the ROI concepts of MPEG-7. The aim of this second part is to characterize and ensure the conditions of display even if display device or display media changes. This requires firstly the definition of a reference color space and the definition of bi-directional color transformations for each peripheral device (camera, display, film recorder, etc.). The complicating factor is that different devices have different color gamuts, depending on the chromaticity of their primaries and the ambient illumination under which they are viewed. To match the displayed image to the aimed appearance, all kind of production metadata (camera specification, camera colour primaries, lighting conditions) should be associated to the film material. Metadata and content build together rich content. The author is assumed to specify conditions as known from digital graphics arts. To control image pre-processing and image post-processing, these specifications should be contained in the film's metadata. The specifications are related to the ICC profiles but need additionally consider mesopic viewing conditions.

  2. Superresolution restoration of an image sequence: adaptive filtering approach.

    PubMed

    Elad, M; Feuer, A

    1999-01-01

    This paper presents a new method based on adaptive filtering theory for superresolution restoration of continuous image sequences. The proposed methodology suggests least squares (LS) estimators which adapt in time, based on adaptive filters, least mean squares (LMS) or recursive least squares (RLS). The adaptation enables the treatment of linear space and time-variant blurring and arbitrary motion, both of them assumed known. The proposed new approach is shown to be of relatively low computational requirements. Simulations demonstrating the superresolution restoration algorithms are presented.

  3. Differential transfer processes in incremental visuomotor adaptation.

    PubMed

    Seidler, Rachel D

    2005-01-01

    Visuomotor adaptive processes were examined by testing transfer of adaptation between similar conditions. Participants made manual aiming movements with a joystick to hit targets on a computer screen, with real-time feedback display of their movement. They adapted to three different rotations of the display in a sequential fashion, with a return to baseline display conditions between rotations. Adaptation was better when participants had prior adaptive experiences. When performance was assessed using direction error (calculated at the time of peak velocity) and initial endpoint error (error before any overt corrective actions), transfer was greater when the final rotation reflected an addition of previously experienced rotations (adaptation order 30 degrees rotation, 15 degrees, 45 degrees) than when it was a subtraction of previously experienced conditions (adaptation order 45 degrees rotation, 15 degrees, 30 degrees). Transfer was equal regardless of adaptation order when performance was assessed with final endpoint error (error following any discrete, corrective actions). These results imply the existence of multiple independent processes in visuomotor adaptation.

  4. Low bit-rate image compression via adaptive down-sampling and constrained least squares upconversion.

    PubMed

    Wu, Xiaolin; Zhang, Xiangjun; Wang, Xiaohan

    2009-03-01

    Recently, many researchers started to challenge a long-standing practice of digital photography: oversampling followed by compression and pursuing more intelligent sparse sampling techniques. In this paper, we propose a practical approach of uniform down sampling in image space and yet making the sampling adaptive by spatially varying, directional low-pass prefiltering. The resulting down-sampled prefiltered image remains a conventional square sample grid, and, thus, it can be compressed and transmitted without any change to current image coding standards and systems. The decoder first decompresses the low-resolution image and then upconverts it to the original resolution in a constrained least squares restoration process, using a 2-D piecewise autoregressive model and the knowledge of directional low-pass prefiltering. The proposed compression approach of collaborative adaptive down-sampling and upconversion (CADU) outperforms JPEG 2000 in PSNR measure at low to medium bit rates and achieves superior visual quality, as well. The superior low bit-rate performance of the CADU approach seems to suggest that oversampling not only wastes hardware resources and energy, and it could be counterproductive to image quality given a tight bit budget.

  5. 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.

  6. Low-level processing for real-time image analysis

    NASA Technical Reports Server (NTRS)

    Eskenazi, R.; Wilf, J. M.

    1979-01-01

    A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

  7. A medical imaging analysis system for trigger finger using an adaptive texture-based active shape model (ATASM) in ultrasound images

    PubMed Central

    Chuang, Bo-I; Kuo, Li-Chieh; Yang, Tai-Hua; Su, Fong-Chin; Jou, I-Ming; Lin, Wei-Jr; Sun, Yung-Nien

    2017-01-01

    Trigger finger has become a prevalent disease that greatly affects occupational activity and daily life. Ultrasound imaging is commonly used for the clinical diagnosis of trigger finger severity. Due to image property variations, traditional methods cannot effectively segment the finger joint’s tendon structure. In this study, an adaptive texture-based active shape model method is used for segmenting the tendon and synovial sheath. Adapted weights are applied in the segmentation process to adjust the contribution of energy terms depending on image characteristics at different positions. The pathology is then determined according to the wavelet and co-occurrence texture features of the segmented tendon area. In the experiments, the segmentation results have fewer errors, with respect to the ground truth, than contours drawn by regular users. The mean values of the absolute segmentation difference of the tendon and synovial sheath are 3.14 and 4.54 pixels, respectively. The average accuracy of pathological determination is 87.14%. The segmentation results are all acceptable in data of both clear and fuzzy boundary cases in 74 images. And the symptom classifications of 42 cases are also a good reference for diagnosis according to the expert clinicians’ opinions. PMID:29077737

  8. Automated identification of cone photoreceptors in adaptive optics retinal images.

    PubMed

    Li, Kaccie Y; Roorda, Austin

    2007-05-01

    In making noninvasive measurements of the human cone mosaic, the task of labeling each individual cone is unavoidable. Manual labeling is a time-consuming process, setting the motivation for the development of an automated method. An automated algorithm for labeling cones in adaptive optics (AO) retinal images is implemented and tested on real data. The optical fiber properties of cones aided the design of the algorithm. Out of 2153 manually labeled cones from six different images, the automated method correctly identified 94.1% of them. The agreement between the automated and the manual labeling methods varied from 92.7% to 96.2% across the six images. Results between the two methods disagreed for 1.2% to 9.1% of the cones. Voronoi analysis of large montages of AO retinal images confirmed the general hexagonal-packing structure of retinal cones as well as the general cone density variability across portions of the retina. The consistency of our measurements demonstrates the reliability and practicality of having an automated solution to this problem.

  9. Image processing pipeline for segmentation and material classification based on multispectral high dynamic range polarimetric images.

    PubMed

    Martínez-Domingo, Miguel Ángel; Valero, Eva M; Hernández-Andrés, Javier; Tominaga, Shoji; Horiuchi, Takahiko; Hirai, Keita

    2017-11-27

    We propose a method for the capture of high dynamic range (HDR), multispectral (MS), polarimetric (Pol) images of indoor scenes using a liquid crystal tunable filter (LCTF). We have included the adaptive exposure estimation (AEE) method to fully automatize the capturing process. We also propose a pre-processing method which can be applied for the registration of HDR images after they are already built as the result of combining different low dynamic range (LDR) images. This method is applied to ensure a correct alignment of the different polarization HDR images for each spectral band. We have focused our efforts in two main applications: object segmentation and classification into metal and dielectric classes. We have simplified the segmentation using mean shift combined with cluster averaging and region merging techniques. We compare the performance of our segmentation with that of Ncut and Watershed methods. For the classification task, we propose to use information not only in the highlight regions but also in their surrounding area, extracted from the degree of linear polarization (DoLP) maps. We present experimental results which proof that the proposed image processing pipeline outperforms previous techniques developed specifically for MSHDRPol image cubes.

  10. GRAPE: a graphical pipeline environment for image analysis in adaptive magnetic resonance imaging.

    PubMed

    Gabr, Refaat E; Tefera, Getaneh B; Allen, William J; Pednekar, Amol S; Narayana, Ponnada A

    2017-03-01

    We present a platform, GRAphical Pipeline Environment (GRAPE), to facilitate the development of patient-adaptive magnetic resonance imaging (MRI) protocols. GRAPE is an open-source project implemented in the Qt C++ framework to enable graphical creation, execution, and debugging of real-time image analysis algorithms integrated with the MRI scanner. The platform provides the tools and infrastructure to design new algorithms, and build and execute an array of image analysis routines, and provides a mechanism to include existing analysis libraries, all within a graphical environment. The application of GRAPE is demonstrated in multiple MRI applications, and the software is described in detail for both the user and the developer. GRAPE was successfully used to implement and execute three applications in MRI of the brain, performed on a 3.0-T MRI scanner: (i) a multi-parametric pipeline for segmenting the brain tissue and detecting lesions in multiple sclerosis (MS), (ii) patient-specific optimization of the 3D fluid-attenuated inversion recovery MRI scan parameters to enhance the contrast of brain lesions in MS, and (iii) an algebraic image method for combining two MR images for improved lesion contrast. GRAPE allows graphical development and execution of image analysis algorithms for inline, real-time, and adaptive MRI applications.

  11. Blurred Star Image Processing for Star Sensors under Dynamic Conditions

    PubMed Central

    Zhang, Weina; Quan, Wei; Guo, Lei

    2012-01-01

    The precision of star point location is significant to identify the star map and to acquire the aircraft attitude for star sensors. Under dynamic conditions, star images are not only corrupted by various noises, but also blurred due to the angular rate of the star sensor. According to different angular rates under dynamic conditions, a novel method is proposed in this article, which includes a denoising method based on adaptive wavelet threshold and a restoration method based on the large angular rate. The adaptive threshold is adopted for denoising the star image when the angular rate is in the dynamic range. Then, the mathematical model of motion blur is deduced so as to restore the blurred star map due to large angular rate. Simulation results validate the effectiveness of the proposed method, which is suitable for blurred star image processing and practical for attitude determination of satellites under dynamic conditions. PMID:22778666

  12. A NDVI assisted remote sensing image adaptive scale segmentation method

    NASA Astrophysics Data System (ADS)

    Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

    2018-03-01

    Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

  13. 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.

  14. Wavefront sensorless adaptive optics optical coherence tomography for in vivo retinal imaging in mice

    PubMed Central

    Jian, Yifan; Xu, Jing; Gradowski, Martin A.; Bonora, Stefano; Zawadzki, Robert J.; Sarunic, Marinko V.

    2014-01-01

    We present wavefront sensorless adaptive optics (WSAO) Fourier domain optical coherence tomography (FD-OCT) for in vivo small animal retinal imaging. WSAO is attractive especially for mouse retinal imaging because it simplifies optical design and eliminates the need for wavefront sensing, which is difficult in the small animal eye. GPU accelerated processing of the OCT data permitted real-time extraction of image quality metrics (intensity) for arbitrarily selected retinal layers to be optimized. Modal control of a commercially available segmented deformable mirror (IrisAO Inc.) provided rapid convergence using a sequential search algorithm. Image quality improvements with WSAO OCT are presented for both pigmented and albino mouse retinal data, acquired in vivo. PMID:24575347

  15. Adaptive optical imaging through complex living plant cells

    NASA Astrophysics Data System (ADS)

    Tamada, Yosuke; Hayano, Yutaka; Murata, Takashi; Oya, Shin; Honma, Yusuke; Kanazawa, Minoru; Miura, Noriaki; Hasebe, Mitsuyasu; Kamei, Yasuhiro; Hattori, Masayuki

    2017-04-01

    Live-cell imaging using fluorescent molecules is now essential for biological researches. However, images of living cells are accompanied with blur, which becomes stronger according to the depth inside the cells and tissues. This image blur is caused by the disturbance on light that goes through optically inhomogeneous living cells and tissues. Here, we show adaptive optics (AO) imaging of living plant cells. AO has been developed in astronomy to correct the disturbance on light caused by atmospheric turbulence. We developed AO microscope effective for the observation of living plant cells with strong disturbance by chloroplasts, and successfully obtained clear images inside plant cells.

  16. Experiment research on inertia-aided adaptive electronic image stabilization of optical stable platform

    NASA Astrophysics Data System (ADS)

    Lu, Xiaodong; Wu, Tianze; Zhou, Jun; Zhao, Bin; Ma, Xiaoyuan; Tang, Xiucheng

    2016-03-01

    An electronic image stabilization method compounded with inertia information, which can compensate the coupling interference caused by the pitch-yaw movement of the optical stable platform system, has been proposed in this paper. Firstly the mechanisms of coning rotation and lever-arm translation of line of sight (LOS) are analyzed during the stabilization process under moving carriers, and the mathematical model which describes the relationship between LOS rotation angle and platform attitude angle are derived. Then the image spin angle caused by coning rotation is estimated by using inertia information. Furthermore, an adaptive block matching method, which based on image edge and angular point, is proposed to smooth the jitter created by the lever-arm translation. This method optimizes the matching process and strategies. Finally, the results of hardware-in-the-loop simulation verified the effectiveness and real-time performance of the proposed method.

  17. 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

  18. 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.

  19. A novel method of the image processing on irregular triangular meshes

    NASA Astrophysics Data System (ADS)

    Vishnyakov, Sergey; Pekhterev, Vitaliy; Sokolova, Elizaveta

    2018-04-01

    The paper describes a novel method of the image processing based on irregular triangular meshes implementation. The triangular mesh is adaptive to the image content, least mean square linear approximation is proposed for the basic interpolation within the triangle. It is proposed to use triangular numbers to simplify using of the local (barycentric) coordinates for the further analysis - triangular element of the initial irregular mesh is to be represented through the set of the four equilateral triangles. This allows to use fast and simple pixels indexing in local coordinates, e.g. "for" or "while" loops for access to the pixels. Moreover, representation proposed allows to use discrete cosine transform of the simple "rectangular" symmetric form without additional pixels reordering (as it is used for shape-adaptive DCT forms). Furthermore, this approach leads to the simple form of the wavelet transform on triangular mesh. The results of the method application are presented. It is shown that advantage of the method proposed is a combination of the flexibility of the image-adaptive irregular meshes with the simple form of the pixel indexing in local triangular coordinates and the using of the common forms of the discrete transforms for triangular meshes. Method described is proposed for the image compression, pattern recognition, image quality improvement, image search and indexing. It also may be used as a part of video coding (intra-frame or inter-frame coding, motion detection).

  20. Sliding window adaptive histogram equalization of intraoral radiographs: effect on image quality.

    PubMed

    Sund, T; Møystad, A

    2006-05-01

    To investigate whether contrast enhancement by non-interactive, sliding window adaptive histogram equalization (SWAHE) can enhance the image quality of intraoral radiographs in the dental clinic. Three dentists read 22 periapical and 12 bitewing storage phosphor (SP) radiographs. For the periapical readings they graded the quality of the examination with regard to visually locating the root apex. For the bitewing readings they registered all occurrences of approximal caries on a confidence scale. Each reading was first done on an unprocessed radiograph ("single-view"), and then re-done with the image processed with SWAHE displayed beside the unprocessed version ("twin-view"). The processing parameters for SWAHE were the same for all the images. For the periapical examinations, twin-view was judged to raise the image quality for 52% of those cases where the single-view quality was below the maximum. For the bitewing radiographs, there was a change of caries classification (both positive and negative) with twin-view in 19% of the cases, but with only a 3% net increase in the total number of caries registrations. For both examinations interobserver variance was unaffected. Non-interactive SWAHE applied to dental SP radiographs produces a supplemental contrast enhanced image which in twin-view reading improves the image quality of periapical examinations. SWAHE also affects caries diagnosis of bitewing images, and further study using a gold standard is warranted.

  1. An automatic segmentation method of a parameter-adaptive PCNN for medical images.

    PubMed

    Lian, Jing; Shi, Bin; Li, Mingcong; Nan, Ziwei; Ma, Yide

    2017-09-01

    Since pre-processing and initial segmentation steps in medical images directly affect the final segmentation results of the regions of interesting, an automatic segmentation method of a parameter-adaptive pulse-coupled neural network is proposed to integrate the above-mentioned two segmentation steps into one. This method has a low computational complexity for different kinds of medical images and has a high segmentation precision. The method comprises four steps. Firstly, an optimal histogram threshold is used to determine the parameter [Formula: see text] for different kinds of images. Secondly, we acquire the parameter [Formula: see text] according to a simplified pulse-coupled neural network (SPCNN). Thirdly, we redefine the parameter V of the SPCNN model by sub-intensity distribution range of firing pixels. Fourthly, we add an offset [Formula: see text] to improve initial segmentation precision. Compared with the state-of-the-art algorithms, the new method achieves a comparable performance by the experimental results from ultrasound images of the gallbladder and gallstones, magnetic resonance images of the left ventricle, and mammogram images of the left and the right breast, presenting the overall metric UM of 0.9845, CM of 0.8142, TM of 0.0726. The algorithm has a great potential to achieve the pre-processing and initial segmentation steps in various medical images. This is a premise for assisting physicians to detect and diagnose clinical cases.

  2. Adaptive image inversion of contrast 3D echocardiography for enabling automated analysis.

    PubMed

    Shaheen, Anjuman; Rajpoot, Kashif

    2015-08-01

    Contrast 3D echocardiography (C3DE) is commonly used to enhance the visual quality of ultrasound images in comparison with non-contrast 3D echocardiography (3DE). Although the image quality in C3DE is perceived to be improved for visual analysis, however it actually deteriorates for the purpose of automatic or semi-automatic analysis due to higher speckle noise and intensity inhomogeneity. Therefore, the LV endocardial feature extraction and segmentation from the C3DE images remains a challenging problem. To address this challenge, this work proposes an adaptive pre-processing method to invert the appearance of C3DE image. The image inversion is based on an image intensity threshold value which is automatically estimated through image histogram analysis. In the inverted appearance, the LV cavity appears dark while the myocardium appears bright thus making it similar in appearance to a 3DE image. Moreover, the resulting inverted image has high contrast and low noise appearance, yielding strong LV endocardium boundary and facilitating feature extraction for segmentation. Our results demonstrate that the inverse appearance of contrast image enables the subsequent LV segmentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Adaptive compressed sensing of remote-sensing imaging based on the sparsity prediction

    NASA Astrophysics Data System (ADS)

    Yang, Senlin; Li, Xilong; Chong, Xin

    2017-10-01

    The conventional compressive sensing works based on the non-adaptive linear projections, and the parameter of its measurement times is usually set empirically. As a result, the quality of image reconstruction is always affected. Firstly, the block-based compressed sensing (BCS) with conventional selection for compressive measurements was given. Then an estimation method for the sparsity of image was proposed based on the two dimensional discrete cosine transform (2D DCT). With an energy threshold given beforehand, the DCT coefficients were processed with both energy normalization and sorting in descending order, and the sparsity of the image can be achieved by the proportion of dominant coefficients. And finally, the simulation result shows that, the method can estimate the sparsity of image effectively, and provides an active basis for the selection of compressive observation times. The result also shows that, since the selection of observation times is based on the sparse degree estimated with the energy threshold provided, the proposed method can ensure the quality of image reconstruction.

  4. Noninvasive imaging of the human rod photoreceptor mosaic using a confocal adaptive optics scanning ophthalmoscope

    PubMed Central

    Dubra, Alfredo; Sulai, Yusufu; Norris, Jennifer L.; Cooper, Robert F.; Dubis, Adam M.; Williams, David R.; Carroll, Joseph

    2011-01-01

    The rod photoreceptors are implicated in a number of devastating retinal diseases. However, routine imaging of these cells has remained elusive, even with the advent of adaptive optics imaging. Here, we present the first in vivo images of the contiguous rod photoreceptor mosaic in nine healthy human subjects. The images were collected with three different confocal adaptive optics scanning ophthalmoscopes at two different institutions, using 680 and 775 nm superluminescent diodes for illumination. Estimates of photoreceptor density and rod:cone ratios in the 5°–15° retinal eccentricity range are consistent with histological findings, confirming our ability to resolve the rod mosaic by averaging multiple registered images, without the need for additional image processing. In one subject, we were able to identify the emergence of the first rods at approximately 190 μm from the foveal center, in agreement with previous histological studies. The rod and cone photoreceptor mosaics appear in focus at different retinal depths, with the rod mosaic best focus (i.e., brightest and sharpest) being at least 10 μm shallower than the cones at retinal eccentricities larger than 8°. This study represents an important step in bringing high-resolution imaging to bear on the study of rod disorders. PMID:21750765

  5. Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images

    PubMed Central

    Zhao, Haiying; Liu, Yong; Xie, Xiaojia; Liao, Yiyi; Liu, Xixi

    2016-01-01

    Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms. PMID:27399704

  6. Investigations in adaptive processing of multispectral data

    NASA Technical Reports Server (NTRS)

    Kriegler, F. J.; Horwitz, H. M.

    1973-01-01

    Adaptive data processing procedures are applied to the problem of classifying objects in a scene scanned by multispectral sensor. These procedures show a performance improvement over standard nonadaptive techniques. Some sources of error in classification are identified and those correctable by adaptive processing are discussed. Experiments in adaptation of signature means by decision-directed methods are described. Some of these methods assume correlation between the trajectories of different signature means; for others this assumption is not made.

  7. Adaptive recovery of motion blur point spread function from differently exposed images

    NASA Astrophysics Data System (ADS)

    Albu, Felix; Florea, Corneliu; Drîmbarean, Alexandru; Zamfir, Adrian

    2010-01-01

    Motion due to digital camera movement during the image capture process is a major factor that degrades the quality of images and many methods for camera motion removal have been developed. Central to all techniques is the correct recovery of what is known as the Point Spread Function (PSF). A very popular technique to estimate the PSF relies on using a pair of gyroscopic sensors to measure the hand motion. However, the errors caused either by the loss of the translational component of the movement or due to the lack of precision in gyro-sensors measurements impede the achievement of a good quality restored image. In order to compensate for this, we propose a method that begins with an estimation of the PSF obtained from 2 gyro sensors and uses a pair of under-exposed image together with the blurred image to adaptively improve it. The luminance of the under-exposed image is equalized with that of the blurred image. An initial estimation of the PSF is generated from the output signal of 2 gyro sensors. The PSF coefficients are updated using 2D-Least Mean Square (LMS) algorithms with a coarse-to-fine approach on a grid of points selected from both images. This refined PSF is used to process the blurred image using known deblurring methods. Our results show that the proposed method leads to superior PSF support and coefficient estimation. Also the quality of the restored image is improved compared to 2 gyro only approach or to blind image de-convolution results.

  8. Preprocessing of PHERMEX flash radiographic images with Haar and adaptive filtering

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

    Brolley, J.E.

    1978-11-01

    Work on image preparation has continued with the application of high-sequency boosting via Haar filtering. This is useful in developing line or edge structures. Widrow LMS adaptive filtering has also been shown to be useful in developing edge structure in special problems. Shadow effects can be obtained with the latter which may be useful for some problems. Combined Haar and adaptive filtering is illustrated for a PHERMEX image.

  9. 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.

  10. Image processing and recognition for biological images

    PubMed Central

    Uchida, Seiichi

    2013-01-01

    This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. PMID:23560739

  11. Image processing and recognition for biological images.

    PubMed

    Uchida, Seiichi

    2013-05-01

    This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. © 2013 The Author Development, Growth & Differentiation © 2013 Japanese Society of Developmental Biologists.

  12. Image Processing Software

    NASA Technical Reports Server (NTRS)

    1990-01-01

    The Ames digital image velocimetry technology has been incorporated in a commercially available image processing software package that allows motion measurement of images on a PC alone. The software, manufactured by Werner Frei Associates, is IMAGELAB FFT. IMAGELAB FFT is a general purpose image processing system with a variety of other applications, among them image enhancement of fingerprints and use by banks and law enforcement agencies for analysis of videos run during robberies.

  13. An adaptive Fuzzy C-means method utilizing neighboring information for breast tumor segmentation in ultrasound images.

    PubMed

    Feng, Yuan; Dong, Fenglin; Xia, Xiaolong; Hu, Chun-Hong; Fan, Qianmin; Hu, Yanle; Gao, Mingyuan; Mutic, Sasa

    2017-07-01

    Ultrasound (US) imaging has been widely used in breast tumor diagnosis and treatment intervention. Automatic delineation of the tumor is a crucial first step, especially for the computer-aided diagnosis (CAD) and US-guided breast procedure. However, the intrinsic properties of US images such as low contrast and blurry boundaries pose challenges to the automatic segmentation of the breast tumor. Therefore, the purpose of this study is to propose a segmentation algorithm that can contour the breast tumor in US images. To utilize the neighbor information of each pixel, a Hausdorff distance based fuzzy c-means (FCM) method was adopted. The size of the neighbor region was adaptively updated by comparing the mutual information between them. The objective function of the clustering process was updated by a combination of Euclid distance and the adaptively calculated Hausdorff distance. Segmentation results were evaluated by comparing with three experts' manual segmentations. The results were also compared with a kernel-induced distance based FCM with spatial constraints, the method without adaptive region selection, and conventional FCM. Results from segmenting 30 patient images showed the adaptive method had a value of sensitivity, specificity, Jaccard similarity, and Dice coefficient of 93.60 ± 5.33%, 97.83 ± 2.17%, 86.38 ± 5.80%, and 92.58 ± 3.68%, respectively. The region-based metrics of average symmetric surface distance (ASSD), root mean square symmetric distance (RMSD), and maximum symmetric surface distance (MSSD) were 0.03 ± 0.04 mm, 0.04 ± 0.03 mm, and 1.18 ± 1.01 mm, respectively. All the metrics except sensitivity were better than that of the non-adaptive algorithm and the conventional FCM. Only three region-based metrics were better than that of the kernel-induced distance based FCM with spatial constraints. Inclusion of the pixel neighbor information adaptively in segmenting US images improved the segmentation performance. The results demonstrate the

  14. Onboard Image Processing System for Hyperspectral Sensor

    PubMed Central

    Hihara, Hiroki; Moritani, Kotaro; Inoue, Masao; Hoshi, Yoshihiro; Iwasaki, Akira; Takada, Jun; Inada, Hitomi; Suzuki, Makoto; Seki, Taeko; Ichikawa, Satoshi; Tanii, Jun

    2015-01-01

    Onboard image processing systems for a hyperspectral sensor have been developed in order to maximize image data transmission efficiency for large volume and high speed data downlink capacity. Since more than 100 channels are required for hyperspectral sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size and weight of a sensor system. A fast lossless image compression algorithm has been developed, and is implemented in the onboard correction circuitry of sensitivity and linearity of Complementary Metal Oxide Semiconductor (CMOS) sensors in order to maximize the compression ratio. The employed image compression method is based on Fast, Efficient, Lossless Image compression System (FELICS), which is a hierarchical predictive coding method with resolution scaling. To improve FELICS’s performance of image decorrelation and entropy coding, we apply a two-dimensional interpolation prediction and adaptive Golomb-Rice coding. It supports progressive decompression using resolution scaling while still maintaining superior performance measured as speed and complexity. Coding efficiency and compression speed enlarge the effective capacity of signal transmission channels, which lead to reducing onboard hardware by multiplexing sensor signals into a reduced number of compression circuits. The circuitry is embedded into the data formatter of the sensor system without adding size, weight, power consumption, and fabrication cost. PMID:26404281

  15. Evaluation of online/offline image guidance/adaptation approaches for prostate cancer radiation therapy.

    PubMed

    Qin, An; Sun, Ying; Liang, Jian; Yan, Di

    2015-04-01

    To evaluate online/offline image-guided/adaptive treatment techniques for prostate cancer radiation therapy with daily cone-beam CT (CBCT) imaging. Three treatment techniques were evaluated retrospectively using daily pre- and posttreatment CBCT images on 22 prostate cancer patients. Prostate, seminal vesicles (SV), rectal wall, and bladder were delineated on all CBCT images. For each patient, a pretreatment intensity modulated radiation therapy plan with clinical target volume (CTV) = prostate + SV and planning target volume (PTV) = CTV + 3 mm was created. The 3 treatment techniques were as follows: (1) Daily Correction: The pretreatment intensity modulated radiation therapy plan was delivered after online CBCT imaging, and position correction; (2) Online Planning: Daily online inverse plans with 3-mm CTV-to-PTV margin were created using online CBCT images, and delivered; and (3) Hybrid Adaption: Daily Correction plus an offline adaptive inverse planning performed after the first week of treatment. The adaptive plan was delivered for all remaining 15 fractions. Treatment dose for each technique was constructed using the daily posttreatment CBCT images via deformable image registration. Evaluation was performed using treatment dose distribution in target and critical organs. Treatment equivalent uniform dose (EUD) for the CTV was within [85.6%, 100.8%] of the pretreatment planned target EUD for Daily Correction; [98.7%, 103.0%] for Online Planning; and [99.2%, 103.4%] for Hybrid Adaptation. Eighteen percent of the 22 patients in Daily Correction had a target dose deficiency >5%. For rectal wall, the mean ± SD of the normalized EUD was 102.6% ± 2.7% for Daily Correction, 99.9% ± 2.5% for Online Planning, and 100.6% ± 2.1% for Hybrid Adaptation. The mean ± SD of the normalized bladder EUD was 108.7% ± 8.2% for Daily Correction, 92.7% ± 8.6% for Online Planning, and 89.4% ± 10.8% for Hybrid Adaptation. Both Online Planning and Hybrid

  16. Evaluation of Online/Offline Image Guidance/Adaptation Approaches for Prostate Cancer Radiation Therapy

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

    Qin, An; Sun, Ying; Liang, Jian

    Purpose: To evaluate online/offline image-guided/adaptive treatment techniques for prostate cancer radiation therapy with daily cone-beam CT (CBCT) imaging. Methods and Materials: Three treatment techniques were evaluated retrospectively using daily pre- and posttreatment CBCT images on 22 prostate cancer patients. Prostate, seminal vesicles (SV), rectal wall, and bladder were delineated on all CBCT images. For each patient, a pretreatment intensity modulated radiation therapy plan with clinical target volume (CTV) = prostate + SV and planning target volume (PTV) = CTV + 3 mm was created. The 3 treatment techniques were as follows: (1) Daily Correction: The pretreatment intensity modulated radiation therapy plan was delivered after online CBCT imaging, and positionmore » correction; (2) Online Planning: Daily online inverse plans with 3-mm CTV-to-PTV margin were created using online CBCT images, and delivered; and (3) Hybrid Adaption: Daily Correction plus an offline adaptive inverse planning performed after the first week of treatment. The adaptive plan was delivered for all remaining 15 fractions. Treatment dose for each technique was constructed using the daily posttreatment CBCT images via deformable image registration. Evaluation was performed using treatment dose distribution in target and critical organs. Results: Treatment equivalent uniform dose (EUD) for the CTV was within [85.6%, 100.8%] of the pretreatment planned target EUD for Daily Correction; [98.7%, 103.0%] for Online Planning; and [99.2%, 103.4%] for Hybrid Adaptation. Eighteen percent of the 22 patients in Daily Correction had a target dose deficiency >5%. For rectal wall, the mean ± SD of the normalized EUD was 102.6% ± 2.7% for Daily Correction, 99.9% ± 2.5% for Online Planning, and 100.6% ± 2.1% for Hybrid Adaptation. The mean ± SD of the normalized bladder EUD was 108.7% ± 8.2% for Daily Correction, 92.7% ± 8.6% for Online Planning, and 89.4% ± 10.8% for

  17. Personal Computer (PC) based image processing applied to fluid mechanics

    NASA Technical Reports Server (NTRS)

    Cho, Y.-C.; Mclachlan, B. G.

    1987-01-01

    A PC based image processing system was employed to determine the instantaneous velocity field of a two-dimensional unsteady flow. The flow was visualized using a suspension of seeding particles in water, and a laser sheet for illumination. With a finite time exposure, the particle motion was captured on a photograph as a pattern of streaks. The streak pattern was digitized and processed using various imaging operations, including contrast manipulation, noise cleaning, filtering, statistical differencing, and thresholding. Information concerning the velocity was extracted from the enhanced image by measuring the length and orientation of the individual streaks. The fluid velocities deduced from the randomly distributed particle streaks were interpolated to obtain velocities at uniform grid points. For the interpolation a simple convolution technique with an adaptive Gaussian window was used. The results are compared with a numerical prediction by a Navier-Stokes computation.

  18. Blind deconvolution post-processing of images corrected by adaptive optics

    NASA Astrophysics Data System (ADS)

    Christou, Julian C.

    1995-08-01

    Experience with the adaptive optics system at the Starfire Optical Range has shown that the point spread function is non-uniform and varies both spatially and temporally as well as being object dependent. Because of this, the application of a standard linear and non-linear deconvolution algorithms make it difficult to deconvolve out the point spread function. In this paper we demonstrate the application of a blind deconvolution algorithm to adaptive optics compensated data where a separate point spread function is not needed.

  19. Local intensity adaptive image coding

    NASA Technical Reports Server (NTRS)

    Huck, Friedrich O.

    1989-01-01

    The objective of preprocessing for machine vision is to extract intrinsic target properties. The most important properties ordinarily are structure and reflectance. Illumination in space, however, is a significant problem as the extreme range of light intensity, stretching from deep shadow to highly reflective surfaces in direct sunlight, impairs the effectiveness of standard approaches to machine vision. To overcome this critical constraint, an image coding scheme is being investigated which combines local intensity adaptivity, image enhancement, and data compression. It is very effective under the highly variant illumination that can exist within a single frame or field of view, and it is very robust to noise at low illuminations. Some of the theory and salient features of the coding scheme are reviewed. Its performance is characterized in a simulated space application, the research and development activities are described.

  20. 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.

  1. 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

  2. Psychological Adaptation to Alteration of Body Image among Stoma Patients: A Descriptive Study.

    PubMed

    Jayarajah, Umesh; Samarasekera, Dharmabandhu Nandadeva

    2017-01-01

    Creation of an ostomy leads to significant change in the body image of the patient. However, adaptation to this alteration of body image is necessary for rehabilitation following surgery. The objective of this study was to identify the factors that influence adaptation to altered body image. An analytical cross-sectional study was conducted among 41 ostomy patients who were treated at a single tertiary care unit. Body image disturbance questionnaire (BIDQ) was used to assess the perception of body image. Data were analyzed using independent samples t -test (unpaired), Chi-square test, and Spearman's correlation. In our study, the mean BIDQ score was 2.22 (standard deviation ± 0.88). The body image disturbance was significantly associated with younger age ( P < 0.05). The prevalence of body image disturbance was significantly higher among overweight patients ( P < 0.05). Males had a higher BIDQ score than females. Those who had temporary stoma had significantly higher BIDQ score ( P < 0.05). Those who felt depressed or had thoughts of self-harm soon after surgery had significantly high body image disturbance score ( P < 0.05). There was a significant negative correlation with the perception of self-efficacy and body image disturbance ( P < 0.01). There was no significant association between body image disturbance and the diagnosis, type of surgery, or time duration after surgery. Poor adaptation to alteration of body image was associated with younger age, overweight, and temporary stoma. Individuals at risk of poor adaptation should be identified before surgery and counseled before surgery, after surgery, and during follow-up visits.

  3. Adaptive Optics For Imaging Bright Objects Next To Dim Ones

    NASA Technical Reports Server (NTRS)

    Shao, Michael; Yu, Jeffrey W.; Malbet, Fabien

    1996-01-01

    Adaptive optics used in imaging optical systems, according to proposal, to enhance high-dynamic-range images (images of bright objects next to dim objects). Designed to alter wavefronts to correct for effects of scattering of light from small bumps on imaging optics. Original intended application of concept in advanced camera installed on Hubble Space Telescope for imaging of such phenomena as large planets near stars other than Sun. Also applicable to other high-quality telescopes and cameras.

  4. Wavelet-based adaptive thresholding method for image segmentation

    NASA Astrophysics Data System (ADS)

    Chen, Zikuan; Tao, Yang; Chen, Xin; Griffis, Carl

    2001-05-01

    A nonuniform background distribution may cause a global thresholding method to fail to segment objects. One solution is using a local thresholding method that adapts to local surroundings. In this paper, we propose a novel local thresholding method for image segmentation, using multiscale threshold functions obtained by wavelet synthesis with weighted detail coefficients. In particular, the coarse-to- fine synthesis with attenuated detail coefficients produces a threshold function corresponding to a high-frequency- reduced signal. This wavelet-based local thresholding method adapts to both local size and local surroundings, and its implementation can take advantage of the fast wavelet algorithm. We applied this technique to physical contaminant detection for poultry meat inspection using x-ray imaging. Experiments showed that inclusion objects in deboned poultry could be extracted at multiple resolutions despite their irregular sizes and uneven backgrounds.

  5. scikit-image: image processing in Python.

    PubMed

    van der Walt, Stéfan; Schönberger, Johannes L; Nunez-Iglesias, Juan; Boulogne, François; Warner, Joshua D; Yager, Neil; Gouillart, Emmanuelle; Yu, Tony

    2014-01-01

    scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image. More information can be found on the project homepage, http://scikit-image.org.

  6. scikit-image: image processing in Python

    PubMed Central

    Schönberger, Johannes L.; Nunez-Iglesias, Juan; Boulogne, François; Warner, Joshua D.; Yager, Neil; Gouillart, Emmanuelle; Yu, Tony

    2014-01-01

    scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image. More information can be found on the project homepage, http://scikit-image.org. PMID:25024921

  7. Adaptive optical microscope for brain imaging in vivo

    NASA Astrophysics Data System (ADS)

    Wang, Kai

    2017-04-01

    The optical heterogeneity of biological tissue imposes a major limitation to acquire detailed structural and functional information deep in the biological specimens using conventional microscopes. To restore optimal imaging performance, we developed an adaptive optical microscope based on direct wavefront sensing technique. This microscope can reliably measure and correct biological samples induced aberration. We demonstrated its performance and application in structural and functional brain imaging in various animal models, including fruit fly, zebrafish and mouse.

  8. Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

    PubMed Central

    Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

    2018-01-01

    There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

  9. Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

    PubMed

    Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

    2018-02-07

    There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

  10. SU-F-J-57: Effectiveness of Daily CT-Based Three-Dimensional Image Guided and Adaptive Proton Therapy

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

    Moriya, S; National Cancer Center, Kashiwa, Chiba; Tachibana, H

    Purpose: Daily CT-based three-dimensional image-guided and adaptive (CTIGRT-ART) proton therapy system was designed and developed. We also evaluated the effectiveness of the CTIGRT-ART. Methods: Retrospective analysis was performed in three lung cancer patients: Proton treatment planning was performed using CT image datasets acquired by Toshiba Aquilion ONE. Planning target volume and surrounding organs were contoured by a well-trained radiation oncologist. Dose distribution was optimized using 180-deg. and 270-deg. two fields in passive scattering proton therapy. Well commissioned Simplified Monte Carlo algorithm was used as dose calculation engine. Daily consecutive CT image datasets was acquired by an in-room CT (Toshiba Aquilionmore » LB). In our in-house program, two image registrations for bone and tumor were performed to shift the isocenter using treatment CT image dataset. Subsequently, dose recalculation was performed after the shift of the isocenter. When the dose distribution after the tumor registration exhibits change of dosimetric parameter of CTV D90% compared to the initial plan, an additional process of was performed that the range shifter thickness was optimized. Dose distribution with CTV D90% for the bone registration, the tumor registration only and adaptive plan with the tumor registration was compared to the initial plan. Results: In the bone registration, tumor dose coverage was decreased by 16% on average (Maximum: 56%). The tumor registration shows better coverage than the bone registration, however the coverage was also decreased by 9% (Maximum: 22%) The adaptive plan shows similar dose coverage of the tumor (Average: 2%, Maximum: 7%). Conclusion: There is a high possibility that only image registration for bone and tumor may reduce tumor coverage. Thus, our proposed methodology of image guidance and adaptive planning using the range adaptation after tumor registration would be effective for proton therapy. This research is partially

  11. SIproc: an open-source biomedical data processing platform for large hyperspectral images.

    PubMed

    Berisha, Sebastian; Chang, Shengyuan; Saki, Sam; Daeinejad, Davar; He, Ziqi; Mankar, Rupali; Mayerich, David

    2017-04-10

    There has recently been significant interest within the vibrational spectroscopy community to apply quantitative spectroscopic imaging techniques to histology and clinical diagnosis. However, many of the proposed methods require collecting spectroscopic images that have a similar region size and resolution to the corresponding histological images. Since spectroscopic images contain significantly more spectral samples than traditional histology, the resulting data sets can approach hundreds of gigabytes to terabytes in size. This makes them difficult to store and process, and the tools available to researchers for handling large spectroscopic data sets are limited. Fundamental mathematical tools, such as MATLAB, Octave, and SciPy, are extremely powerful but require that the data be stored in fast memory. This memory limitation becomes impractical for even modestly sized histological images, which can be hundreds of gigabytes in size. In this paper, we propose an open-source toolkit designed to perform out-of-core processing of hyperspectral images. By taking advantage of graphical processing unit (GPU) computing combined with adaptive data streaming, our software alleviates common workstation memory limitations while achieving better performance than existing applications.

  12. Adaptive optics scanning laser ophthalmoscopy in fundus imaging, a review and update.

    PubMed

    Zhang, Bing; Li, Ni; Kang, Jie; He, Yi; Chen, Xiao-Ming

    2017-01-01

    Adaptive optics scanning laser ophthalmoscopy (AO-SLO) has been a promising technique in funds imaging with growing popularity. This review firstly gives a brief history of adaptive optics (AO) and AO-SLO. Then it compares AO-SLO with conventional imaging methods (fundus fluorescein angiography, fundus autofluorescence, indocyanine green angiography and optical coherence tomography) and other AO techniques (adaptive optics flood-illumination ophthalmoscopy and adaptive optics optical coherence tomography). Furthermore, an update of current research situation in AO-SLO is made based on different fundus structures as photoreceptors (cones and rods), fundus vessels, retinal pigment epithelium layer, retinal nerve fiber layer, ganglion cell layer and lamina cribrosa. Finally, this review indicates possible research directions of AO-SLO in future.

  13. High-speed adaptive optics line scan confocal retinal imaging for human eye.

    PubMed

    Lu, Jing; Gu, Boyu; Wang, Xiaolin; Zhang, Yuhua

    2017-01-01

    Continuous and rapid eye movement causes significant intraframe distortion in adaptive optics high resolution retinal imaging. To minimize this artifact, we developed a high speed adaptive optics line scan confocal retinal imaging system. A high speed line camera was employed to acquire retinal image and custom adaptive optics was developed to compensate the wave aberration of the human eye's optics. The spatial resolution and signal to noise ratio were assessed in model eye and in living human eye. The improvement of imaging fidelity was estimated by reduction of intra-frame distortion of retinal images acquired in the living human eyes with frame rates at 30 frames/second (FPS), 100 FPS, and 200 FPS. The device produced retinal image with cellular level resolution at 200 FPS with a digitization of 512×512 pixels/frame in the living human eye. Cone photoreceptors in the central fovea and rod photoreceptors near the fovea were resolved in three human subjects in normal chorioretinal health. Compared with retinal images acquired at 30 FPS, the intra-frame distortion in images taken at 200 FPS was reduced by 50.9% to 79.7%. We demonstrated the feasibility of acquiring high resolution retinal images in the living human eye at a speed that minimizes retinal motion artifact. This device may facilitate research involving subjects with nystagmus or unsteady fixation due to central vision loss.

  14. Image registration for daylight adaptive optics.

    PubMed

    Hart, Michael

    2018-03-15

    Daytime use of adaptive optics (AO) at large telescopes is hampered by shot noise from the bright sky background. Wave-front sensing may use a sodium laser guide star observed through a magneto-optical filter to suppress the background, but the laser beacon is not sensitive to overall image motion. To estimate that, laser-guided AO systems generally rely on light from the object itself, collected through the full aperture of the telescope. Daylight sets a lower limit to the brightness of an object that may be tracked at rates sufficient to overcome the image jitter. Below that limit, wave-front correction on the basis of the laser alone will yield an image that is approximately diffraction limited but that moves randomly. I describe an iterative registration algorithm that recovers high-resolution long-exposure images in this regime from a rapid series of short exposures with very low signal-to-noise ratio. The technique takes advantage of the fact that in the photon noise limit there is negligible penalty in taking short exposures, and also that once the images are recorded, it is not necessary, as in the case of an AO tracker loop, to estimate the image motion correctly and quickly on every cycle. The algorithm is likely to find application in space situational awareness, where high-resolution daytime imaging of artificial satellites is important.

  15. 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.

  16. Methods in Astronomical Image Processing

    NASA Astrophysics Data System (ADS)

    Jörsäter, S.

    A Brief Introductory Note History of Astronomical Imaging Astronomical Image Data Images in Various Formats Digitized Image Data Digital Image Data Philosophy of Astronomical Image Processing Properties of Digital Astronomical Images Human Image Processing Astronomical vs. Computer Science Image Processing Basic Tools of Astronomical Image Processing Display Applications Calibration of Intensity Scales Calibration of Length Scales Image Re-shaping Feature Enhancement Noise Suppression Noise and Error Analysis Image Processing Packages: Design of AIPS and MIDAS AIPS MIDAS Reduction of CCD Data Bias Subtraction Clipping Preflash Subtraction Dark Subtraction Flat Fielding Sky Subtraction Extinction Correction Deconvolution Methods Rebinning/Combining Summary and Prospects for the Future

  17. Comparison of adaptive optics scanning light ophthalmoscopic fluorescein angiography and offset pinhole imaging

    PubMed Central

    Chui, Toco Y. P.; Dubow, Michael; Pinhas, Alexander; Shah, Nishit; Gan, Alexander; Weitz, Rishard; Sulai, Yusufu N.; Dubra, Alfredo; Rosen, Richard B.

    2014-01-01

    Recent advances to the adaptive optics scanning light ophthalmoscope (AOSLO) have enabled finer in vivo assessment of the human retinal microvasculature. AOSLO confocal reflectance imaging has been coupled with oral fluorescein angiography (FA), enabling simultaneous acquisition of structural and perfusion images. AOSLO offset pinhole (OP) imaging combined with motion contrast post-processing techniques, are able to create a similar set of structural and perfusion images without the use of exogenous contrast agent. In this study, we evaluate the similarities and differences of the structural and perfusion images obtained by either method, in healthy control subjects and in patients with retinal vasculopathy including hypertensive retinopathy, diabetic retinopathy, and retinal vein occlusion. Our results show that AOSLO OP motion contrast provides perfusion maps comparable to those obtained with AOSLO FA, while AOSLO OP reflectance images provide additional information such as vessel wall fine structure not as readily visible in AOSLO confocal reflectance images. AOSLO OP offers a non-invasive alternative to AOSLO FA without the need for any exogenous contrast agent. PMID:24761299

  18. Image acquisition device of inspection robot based on adaptive rotation regulation of polarizer

    NASA Astrophysics Data System (ADS)

    Dong, Maoqi; Wang, Xingguang; Liang, Tao; Yang, Guoqing; Zhang, Chuangyou; Gao, Faqin

    2017-12-01

    An image processing device of inspection robot with adaptive polarization adjustment is proposed, that the device includes the inspection robot body, the image collecting mechanism, the polarizer and the polarizer automatic actuating device. Where, the image acquisition mechanism is arranged at the front of the inspection robot body for collecting equipment image data in the substation. Polarizer is fixed on the automatic actuating device of polarizer, and installed in front of the image acquisition mechanism, and that the optical axis of the camera vertically goes through the polarizer and the polarizer rotates with the optical axis of the visible camera as the central axis. The simulation results show that the system solves the fuzzy problems of the equipment that are caused by glare, reflection of light and shadow, and the robot can observe details of the running status of electrical equipment. And the full coverage of the substation equipment inspection robot observation target is achieved, which ensures the safe operation of the substation equipment.

  19. IMAGES: An interactive image processing system

    NASA Technical Reports Server (NTRS)

    Jensen, J. R.

    1981-01-01

    The IMAGES interactive image processing system was created specifically for undergraduate remote sensing education in geography. The system is interactive, relatively inexpensive to operate, almost hardware independent, and responsive to numerous users at one time in a time-sharing mode. Most important, it provides a medium whereby theoretical remote sensing principles discussed in lecture may be reinforced in laboratory as students perform computer-assisted image processing. In addition to its use in academic and short course environments, the system has also been used extensively to conduct basic image processing research. The flow of information through the system is discussed including an overview of the programs.

  20. 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.

  1. Self-adaptive relevance feedback based on multilevel image content analysis

    NASA Astrophysics Data System (ADS)

    Gao, Yongying; Zhang, Yujin; Fu, Yu

    2001-01-01

    In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

  2. Self-adaptive relevance feedback based on multilevel image content analysis

    NASA Astrophysics Data System (ADS)

    Gao, Yongying; Zhang, Yujin; Fu, Yu

    2000-12-01

    In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

  3. An adaptive toolkit for image quality evaluation in system performance test of digital breast tomosynthesis

    NASA Astrophysics Data System (ADS)

    Zhang, Guozhi; Petrov, Dimitar; Marshall, Nicholas; Bosmans, Hilde

    2017-03-01

    Digital breast tomosynthesis (DBT) is a relatively new diagnostic imaging modality for women. Currently, various models of DBT systems are available on the market and the number of installations is rapidly increasing. EUREF, the European Reference Organization for Quality Assured Breast Screening and Diagnostic Services, has proposed a preliminary Guideline - protocol for the quality control of the physical and technical aspects of digital breast tomosynthesis systems, with an ultimate aim of providing limiting values guaranteeing proper performance for different applications of DBT. In this work, we introduce an adaptive toolkit developed in accordance with this guideline to facilitate the process of image quality evaluation in DBT performance test. This toolkit implements robust algorithms to quantify various technical parameters of DBT images and provides a convenient user interface in practice. Each test is built into a separate module with configurations set corresponding to the European guideline, which can be easily adapted to different settings and extended with additional tests. This toolkit largely improves the efficiency for image quality evaluation of DBT. It is also going to evolve with the development of protocols in quality control of DBT systems.

  4. Smartphone adapters for digital photomicrography.

    PubMed

    Roy, Somak; Pantanowitz, Liron; Amin, Milon; Seethala, Raja R; Ishtiaque, Ahmed; Yousem, Samuel A; Parwani, Anil V; Cucoranu, Ioan; Hartman, Douglas J

    2014-01-01

    Photomicrographs in Anatomic Pathology provide a means of quickly sharing information from a glass slide for consultation, education, documentation and publication. While static image acquisition historically involved the use of a permanently mounted camera unit on a microscope, such cameras may be expensive, need to be connected to a computer, and often require proprietary software to acquire and process images. Another novel approach for capturing digital microscopic images is to use smartphones coupled with the eyepiece of a microscope. Recently, several smartphone adapters have emerged that allow users to attach mobile phones to the microscope. The aim of this study was to test the utility of these various smartphone adapters. We surveyed the market for adapters to attach smartphones to the ocular lens of a conventional light microscope. Three adapters (Magnifi, Skylight and Snapzoom) were tested. We assessed the designs of these adapters and their effectiveness at acquiring static microscopic digital images. All adapters facilitated the acquisition of digital microscopic images with a smartphone. The optimal adapter was dependent on the type of phone used. The Magnifi adapters for iPhone were incompatible when using a protective case. The Snapzoom adapter was easiest to use with iPhones and other smartphones even with protective cases. Smartphone adapters are inexpensive and easy to use for acquiring digital microscopic images. However, they require some adjustment by the user in order to optimize focus and obtain good quality images. Smartphone microscope adapters provide an economically feasible method of acquiring and sharing digital pathology photomicrographs.

  5. Smartphone adapters for digital photomicrography

    PubMed Central

    Roy, Somak; Pantanowitz, Liron; Amin, Milon; Seethala, Raja R.; Ishtiaque, Ahmed; Yousem, Samuel A.; Parwani, Anil V.; Cucoranu, Ioan; Hartman, Douglas J.

    2014-01-01

    Background: Photomicrographs in Anatomic Pathology provide a means of quickly sharing information from a glass slide for consultation, education, documentation and publication. While static image acquisition historically involved the use of a permanently mounted camera unit on a microscope, such cameras may be expensive, need to be connected to a computer, and often require proprietary software to acquire and process images. Another novel approach for capturing digital microscopic images is to use smartphones coupled with the eyepiece of a microscope. Recently, several smartphone adapters have emerged that allow users to attach mobile phones to the microscope. The aim of this study was to test the utility of these various smartphone adapters. Materials and Methods: We surveyed the market for adapters to attach smartphones to the ocular lens of a conventional light microscope. Three adapters (Magnifi, Skylight and Snapzoom) were tested. We assessed the designs of these adapters and their effectiveness at acquiring static microscopic digital images. Results: All adapters facilitated the acquisition of digital microscopic images with a smartphone. The optimal adapter was dependent on the type of phone used. The Magnifi adapters for iPhone were incompatible when using a protective case. The Snapzoom adapter was easiest to use with iPhones and other smartphones even with protective cases. Conclusions: Smartphone adapters are inexpensive and easy to use for acquiring digital microscopic images. However, they require some adjustment by the user in order to optimize focus and obtain good quality images. Smartphone microscope adapters provide an economically feasible method of acquiring and sharing digital pathology photomicrographs. PMID:25191623

  6. Acquisition of STEM Images by Adaptive Compressive Sensing

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

    Xie, Weiyi; Feng, Qianli; Srinivasan, Ramprakash

    Compressive Sensing (CS) allows a signal to be sparsely measured first and accurately recovered later in software [1]. In scanning transmission electron microscopy (STEM), it is possible to compress an image spatially by reducing the number of measured pixels, which decreases electron dose and increases sensing speed [2,3,4]. The two requirements for CS to work are: (1) sparsity of basis coefficients and (2) incoherence of the sensing system and the representation system. However, when pixels are missing from the image, it is difficult to have an incoherent sensing matrix. Nevertheless, dictionary learning techniques such as Beta-Process Factor Analysis (BPFA) [5]more » are able to simultaneously discover a basis and the sparse coefficients in the case of missing pixels. On top of CS, we would like to apply active learning [6,7] to further reduce the proportion of pixels being measured, while maintaining image reconstruction quality. Suppose we initially sample 10% of random pixels. We wish to select the next 1% of pixels that are most useful in recovering the image. Now, we have 11% of pixels, and we want to decide the next 1% of “most informative” pixels. Active learning methods are online and sequential in nature. Our goal is to adaptively discover the best sensing mask during acquisition using feedback about the structures in the image. In the end, we hope to recover a high quality reconstruction with a dose reduction relative to the non-adaptive (random) sensing scheme. In doing this, we try three metrics applied to the partial reconstructions for selecting the new set of pixels: (1) variance, (2) Kullback-Leibler (KL) divergence using a Radial Basis Function (RBF) kernel, and (3) entropy. Figs. 1 and 2 display the comparison of Peak Signal-to-Noise (PSNR) using these three different active learning methods at different percentages of sampled pixels. At 20% level, all the three active learning methods underperform the original CS without active learning

  7. Improving the scalability of hyperspectral imaging applications on heterogeneous platforms using adaptive run-time data compression

    NASA Astrophysics Data System (ADS)

    Plaza, Antonio; Plaza, Javier; Paz, Abel

    2010-10-01

    Latest generation remote sensing instruments (called hyperspectral imagers) are now able to generate hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. In previous work, we have reported that the scalability of parallel processing algorithms dealing with these high-dimensional data volumes is affected by the amount of data to be exchanged through the communication network of the system. However, large messages are common in hyperspectral imaging applications since processing algorithms are pixel-based, and each pixel vector to be exchanged through the communication network is made up of hundreds of spectral values. Thus, decreasing the amount of data to be exchanged could improve the scalability and parallel performance. In this paper, we propose a new framework based on intelligent utilization of wavelet-based data compression techniques for improving the scalability of a standard hyperspectral image processing chain on heterogeneous networks of workstations. This type of parallel platform is quickly becoming a standard in hyperspectral image processing due to the distributed nature of collected hyperspectral data as well as its flexibility and low cost. Our experimental results indicate that adaptive lossy compression can lead to improvements in the scalability of the hyperspectral processing chain without sacrificing analysis accuracy, even at sub-pixel precision levels.

  8. Adaptive optics scanning laser ophthalmoscopy in fundus imaging, a review and update

    PubMed Central

    Zhang, Bing; Li, Ni; Kang, Jie; He, Yi; Chen, Xiao-Ming

    2017-01-01

    Adaptive optics scanning laser ophthalmoscopy (AO-SLO) has been a promising technique in funds imaging with growing popularity. This review firstly gives a brief history of adaptive optics (AO) and AO-SLO. Then it compares AO-SLO with conventional imaging methods (fundus fluorescein angiography, fundus autofluorescence, indocyanine green angiography and optical coherence tomography) and other AO techniques (adaptive optics flood-illumination ophthalmoscopy and adaptive optics optical coherence tomography). Furthermore, an update of current research situation in AO-SLO is made based on different fundus structures as photoreceptors (cones and rods), fundus vessels, retinal pigment epithelium layer, retinal nerve fiber layer, ganglion cell layer and lamina cribrosa. Finally, this review indicates possible research directions of AO-SLO in future. PMID:29181321

  9. Adaptive Statistical Iterative Reconstruction-V Versus Adaptive Statistical Iterative Reconstruction: Impact on Dose Reduction and Image Quality in Body Computed Tomography.

    PubMed

    Gatti, Marco; Marchisio, Filippo; Fronda, Marco; Rampado, Osvaldo; Faletti, Riccardo; Bergamasco, Laura; Ropolo, Roberto; Fonio, Paolo

    The aim of this study was to evaluate the impact on dose reduction and image quality of the new iterative reconstruction technique: adaptive statistical iterative reconstruction (ASIR-V). Fifty consecutive oncologic patients acted as case controls undergoing during their follow-up a computed tomography scan both with ASIR and ASIR-V. Each study was analyzed in a double-blinded fashion by 2 radiologists. Both quantitative and qualitative analyses of image quality were conducted. Computed tomography scanner radiation output was 38% (29%-45%) lower (P < 0.0001) for the ASIR-V examinations than for the ASIR ones. The quantitative image noise was significantly lower (P < 0.0001) for ASIR-V. Adaptive statistical iterative reconstruction-V had a higher performance for the subjective image noise (P = 0.01 for 5 mm and P = 0.009 for 1.25 mm), the other parameters (image sharpness, diagnostic acceptability, and overall image quality) being similar (P > 0.05). Adaptive statistical iterative reconstruction-V is a new iterative reconstruction technique that has the potential to provide image quality equal to or greater than ASIR, with a dose reduction around 40%.

  10. Adaptive non-local means on local principle neighborhood for noise/artifacts reduction in low-dose CT images.

    PubMed

    Zhang, Yuanke; Lu, Hongbing; Rong, Junyan; Meng, Jing; Shang, Junliang; Ren, Pinghong; Zhang, Junying

    2017-09-01

    Low-dose CT (LDCT) technique can reduce the x-ray radiation exposure to patients at the cost of degraded images with severe noise and artifacts. Non-local means (NLM) filtering has shown its potential in improving LDCT image quality. However, currently most NLM-based approaches employ a weighted average operation directly on all neighbor pixels with a fixed filtering parameter throughout the NLM filtering process, ignoring the non-stationary noise nature of LDCT images. In this paper, an adaptive NLM filtering scheme on local principle neighborhoods (PC-NLM) is proposed for structure-preserving noise/artifacts reduction in LDCT images. Instead of using neighboring patches directly, in the PC-NLM scheme, the principle component analysis (PCA) is first applied on local neighboring patches of the target patch to decompose the local patches into uncorrelated principle components (PCs), then a NLM filtering is used to regularize each PC of the target patch and finally the regularized components is transformed to get the target patch in image domain. Especially, in the NLM scheme, the filtering parameter is estimated adaptively from local noise level of the neighborhood as well as the signal-to-noise ratio (SNR) of the corresponding PC, which guarantees a "weaker" NLM filtering on PCs with higher SNR and a "stronger" filtering on PCs with lower SNR. The PC-NLM procedure is iteratively performed several times for better removal of the noise and artifacts, and an adaptive iteration strategy is developed to reduce the computational load by determining whether a patch should be processed or not in next round of the PC-NLM filtering. The effectiveness of the presented PC-NLM algorithm is validated by experimental phantom studies and clinical studies. The results show that it can achieve promising gain over some state-of-the-art methods in terms of artifact suppression and structure preservation. With the use of PCA on local neighborhoods to extract principal structural

  11. Adaptive ISAR Imaging of Maneuvering Targets Based on a Modified Fourier Transform.

    PubMed

    Wang, Binbin; Xu, Shiyou; Wu, Wenzhen; Hu, Pengjiang; Chen, Zengping

    2018-04-27

    Focusing on the inverse synthetic aperture radar (ISAR) imaging of maneuvering targets, this paper presents a new imaging method which works well when the target's maneuvering is not too severe. After translational motion compensation, we describe the equivalent rotation of maneuvering targets by two variables-the relative chirp rate of the linear frequency modulated (LFM) signal and the Doppler focus shift. The first variable indicates the target's motion status, and the second one represents the possible residual error of the translational motion compensation. With them, a modified Fourier transform matrix is constructed and then used for cross-range compression. Consequently, the imaging of maneuvering is converted into a two-dimensional parameter optimization problem in which a stable and clear ISAR image is guaranteed. A gradient descent optimization scheme is employed to obtain the accurate relative chirp rate and Doppler focus shift. Moreover, we designed an efficient and robust initialization process for the gradient descent method, thus, the well-focused ISAR images of maneuvering targets can be achieved adaptively. Human intervention is not needed, and it is quite convenient for practical ISAR imaging systems. Compared to precedent imaging methods, the new method achieves better imaging quality under reasonable computational cost. Simulation results are provided to validate the effectiveness and advantages of the proposed method.

  12. Adaptive photoacoustic imaging using the Mallart-Fink focusing factor

    NASA Astrophysics Data System (ADS)

    Li, Meng-Lin

    2008-02-01

    Focusing errors caused by sound velocity heterogeneities widen the mainlobe and elevate the sidelobes, thus degrading both spatial and contrast resolutions in photoacoustic imaging. We propose an adaptive array-based photoacoustic imaging technique that uses the Mallart-Fink (MF) focusing factor weighting to reduce the effect of such focusing errors. The definition of the MF focusing factor indicates that the MF focusing factor at the main lobe of the point-spread function is high (close to 1, without speckle noise being present, which is the case in photoacoustic imaging), whereas it is low at the sidelobes. Based on this property, the elevated sidelobes caused by sound velocity heterogeneities in the tissue can be suppressed after being multiplied by the corresponding map of the MF focusing factor on each imaging point; thus the focusing quality can be improved. This technique makes no assumption of sources of focusing errors and directly suppresses the unwanted sidelobe contributions. Numerical experiments with near field phase screen and displaced phase screen models were performed here to verify the proposed adaptive weighting technique. The effect of the signal-to-noise ratio on the MF focusing factor is also discussed.

  13. High-speed adaptive optics line scan confocal retinal imaging for human eye

    PubMed Central

    Wang, Xiaolin; Zhang, Yuhua

    2017-01-01

    Purpose Continuous and rapid eye movement causes significant intraframe distortion in adaptive optics high resolution retinal imaging. To minimize this artifact, we developed a high speed adaptive optics line scan confocal retinal imaging system. Methods A high speed line camera was employed to acquire retinal image and custom adaptive optics was developed to compensate the wave aberration of the human eye’s optics. The spatial resolution and signal to noise ratio were assessed in model eye and in living human eye. The improvement of imaging fidelity was estimated by reduction of intra-frame distortion of retinal images acquired in the living human eyes with frame rates at 30 frames/second (FPS), 100 FPS, and 200 FPS. Results The device produced retinal image with cellular level resolution at 200 FPS with a digitization of 512×512 pixels/frame in the living human eye. Cone photoreceptors in the central fovea and rod photoreceptors near the fovea were resolved in three human subjects in normal chorioretinal health. Compared with retinal images acquired at 30 FPS, the intra-frame distortion in images taken at 200 FPS was reduced by 50.9% to 79.7%. Conclusions We demonstrated the feasibility of acquiring high resolution retinal images in the living human eye at a speed that minimizes retinal motion artifact. This device may facilitate research involving subjects with nystagmus or unsteady fixation due to central vision loss. PMID:28257458

  14. Information Processing Techniques Program. Volume II. Communications- Adaptive Internetting

    DTIC Science & Technology

    1977-09-30

    LABORATORY INFORMATION PROCESSING TECHNIQUES PROGRAM VOLUME II: COMMUNICATIONS-ADAPTIVE INTERNETTING I SEMIANNUAL TECHNICAL SUMMARY REPORT TO THE...MASSACHUSETTS ABSTRACT This repori describes work performed on the Communications-Adaptive Internetting program sponsored by the Information ... information processing techniques network speech terminal communicatlons-adaptive internetting 04 links digital voice communications time-varying

  15. 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.

  16. Image pre-processing method for near-wall PIV measurements over moving curved interfaces

    NASA Astrophysics Data System (ADS)

    Jia, L. C.; Zhu, Y. D.; Jia, Y. X.; Yuan, H. J.; Lee, C. B.

    2017-03-01

    PIV measurements near a moving interface are always difficult. This paper presents a PIV image pre-processing method that returns high spatial resolution velocity profiles near the interface. Instead of re-shaping or re-orientating the interrogation windows, interface tracking and an image transformation are used to stretch the particle image strips near a curved interface into rectangles. Then the adaptive structured interrogation windows can be arranged at specified distances from the interface. Synthetic particles are also added into the solid region to minimize interfacial effects and to restrict particles on both sides of the interface. Since a high spatial resolution is only required in high velocity gradient region, adaptive meshing and stretching of the image strips in the normal direction is used to improve the cross-correlation signal-to-noise ratio (SN) by reducing the velocity difference and the particle image distortion within the interrogation window. A two dimensional Gaussian fit is used to compensate for the effects of stretching particle images. The working hypothesis is that fluid motion near the interface is ‘quasi-tangential flow’, which is reasonable in most fluid-structure interaction scenarios. The method was validated against the window deformation iterative multi-grid scheme (WIDIM) using synthetic image pairs with different velocity profiles. The method was tested for boundary layer measurements of a supersonic turbulent boundary layer on a flat plate, near a rotating blade and near a flexible flapping flag. This image pre-processing method provides higher spatial resolution than conventional WIDIM and good robustness for measuring velocity profiles near moving interfaces.

  17. An adaptive management process for forest soil conservation.

    Treesearch

    Michael P. Curran; Douglas G. Maynard; Ronald L. Heninger; Thomas A. Terry; Steven W. Howes; Douglas M. Stone; Thomas Niemann; Richard E. Miller; Robert F. Powers

    2005-01-01

    Soil disturbance guidelines should be based on comparable disturbance categories adapted to specific local soil conditions, validated by monitoring and research. Guidelines, standards, and practices should be continually improved based on an adaptive management process, which is presented in this paper. Core components of this process include: reliable monitoring...

  18. 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.

  19. Image Processing System

    NASA Technical Reports Server (NTRS)

    1986-01-01

    Mallinckrodt Institute of Radiology (MIR) is using a digital image processing system which employs NASA-developed technology. MIR's computer system is the largest radiology system in the world. It is used in diagnostic imaging. Blood vessels are injected with x-ray dye, and the images which are produced indicate whether arteries are hardened or blocked. A computer program developed by Jet Propulsion Laboratory known as Mini-VICAR/IBIS was supplied to MIR by COSMIC. The program provides the basis for developing the computer imaging routines for data processing, contrast enhancement and picture display.

  20. Image Processing Software

    NASA Technical Reports Server (NTRS)

    1992-01-01

    To convert raw data into environmental products, the National Weather Service and other organizations use the Global 9000 image processing system marketed by Global Imaging, Inc. The company's GAE software package is an enhanced version of the TAE, developed by Goddard Space Flight Center to support remote sensing and image processing applications. The system can be operated in three modes and is combined with HP Apollo workstation hardware.

  1. Image Processing

    NASA Technical Reports Server (NTRS)

    1993-01-01

    Electronic Imagery, Inc.'s ImageScale Plus software, developed through a Small Business Innovation Research (SBIR) contract with Kennedy Space Flight Center for use on space shuttle Orbiter in 1991, enables astronauts to conduct image processing, prepare electronic still camera images in orbit, display them and downlink images to ground based scientists for evaluation. Electronic Imagery, Inc.'s ImageCount, a spin-off product of ImageScale Plus, is used to count trees in Florida orange groves. Other applications include x-ray and MRI imagery, textile designs and special effects for movies. As of 1/28/98, company could not be located, therefore contact/product information is no longer valid.

  2. 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.

  3. 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.

  4. Wavefront correction and high-resolution in vivo OCT imaging with an objective integrated multi-actuator adaptive lens

    PubMed Central

    Bonora, Stefano; Jian, Yifan; Zhang, Pengfei; Zam, Azhar; Pugh, Edward N.; Zawadzki, Robert J.; Sarunic, Marinko V.

    2015-01-01

    Adaptive optics is rapidly transforming microscopy and high-resolution ophthalmic imaging. The adaptive elements commonly used to control optical wavefronts are liquid crystal spatial light modulators and deformable mirrors. We introduce a novel Multi-actuator Adaptive Lens that can correct aberrations to high order, and which has the potential to increase the spread of adaptive optics to many new applications by simplifying its integration with existing systems. Our method combines an adaptive lens with an imaged-based optimization control that allows the correction of images to the diffraction limit, and provides a reduction of hardware complexity with respect to existing state-of-the-art adaptive optics systems. The Multi-actuator Adaptive Lens design that we present can correct wavefront aberrations up to the 4th order of the Zernike polynomial characterization. The performance of the Multi-actuator Adaptive Lens is demonstrated in a wide field microscope, using a Shack-Hartmann wavefront sensor for closed loop control. The Multi-actuator Adaptive Lens and image-based wavefront-sensorless control were also integrated into the objective of a Fourier Domain Optical Coherence Tomography system for in vivo imaging of mouse retinal structures. The experimental results demonstrate that the insertion of the Multi-actuator Objective Lens can generate arbitrary wavefronts to correct aberrations down to the diffraction limit, and can be easily integrated into optical systems to improve the quality of aberrated images. PMID:26368169

  5. Wavefront correction and high-resolution in vivo OCT imaging with an objective integrated multi-actuator adaptive lens.

    PubMed

    Bonora, Stefano; Jian, Yifan; Zhang, Pengfei; Zam, Azhar; Pugh, Edward N; Zawadzki, Robert J; Sarunic, Marinko V

    2015-08-24

    Adaptive optics is rapidly transforming microscopy and high-resolution ophthalmic imaging. The adaptive elements commonly used to control optical wavefronts are liquid crystal spatial light modulators and deformable mirrors. We introduce a novel Multi-actuator Adaptive Lens that can correct aberrations to high order, and which has the potential to increase the spread of adaptive optics to many new applications by simplifying its integration with existing systems. Our method combines an adaptive lens with an imaged-based optimization control that allows the correction of images to the diffraction limit, and provides a reduction of hardware complexity with respect to existing state-of-the-art adaptive optics systems. The Multi-actuator Adaptive Lens design that we present can correct wavefront aberrations up to the 4th order of the Zernike polynomial characterization. The performance of the Multi-actuator Adaptive Lens is demonstrated in a wide field microscope, using a Shack-Hartmann wavefront sensor for closed loop control. The Multi-actuator Adaptive Lens and image-based wavefront-sensorless control were also integrated into the objective of a Fourier Domain Optical Coherence Tomography system for in vivo imaging of mouse retinal structures. The experimental results demonstrate that the insertion of the Multi-actuator Objective Lens can generate arbitrary wavefronts to correct aberrations down to the diffraction limit, and can be easily integrated into optical systems to improve the quality of aberrated images.

  6. Cytopathology whole slide images and adaptive tutorials for postgraduate pathology trainees: a randomized crossover trial.

    PubMed

    Van Es, Simone L; Kumar, Rakesh K; Pryor, Wendy M; Salisbury, Elizabeth L; Velan, Gary M

    2015-09-01

    To determine whether cytopathology whole slide images and virtual microscopy adaptive tutorials aid learning by postgraduate trainees, we designed a randomized crossover trial to evaluate the quantitative and qualitative impact of whole slide images and virtual microscopy adaptive tutorials compared with traditional glass slide and textbook methods of learning cytopathology. Forty-three anatomical pathology registrars were recruited from Australia, New Zealand, and Malaysia. Online assessments were used to determine efficacy, whereas user experience and perceptions of efficiency were evaluated using online Likert scales and open-ended questions. Outcomes of online assessments indicated that, with respect to performance, learning with whole slide images and virtual microscopy adaptive tutorials was equivalent to using traditional methods. High-impact learning, efficiency, and equity of learning from virtual microscopy adaptive tutorials were strong themes identified in open-ended responses. Participants raised concern about the lack of z-axis capability in the cytopathology whole slide images, suggesting that delivery of z-stacked whole slide images online may be important for future educational development. In this trial, learning cytopathology with whole slide images and virtual microscopy adaptive tutorials was found to be as effective as and perceived as more efficient than learning from glass slides and textbooks. The use of whole slide images and virtual microscopy adaptive tutorials has the potential to provide equitable access to effective learning from teaching material of consistently high quality. It also has broader implications for continuing professional development and maintenance of competence and quality assurance in specialist practice. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Semi-automated Image Processing for Preclinical Bioluminescent Imaging.

    PubMed

    Slavine, Nikolai V; McColl, Roderick W

    Bioluminescent imaging is a valuable noninvasive technique for investigating tumor dynamics and specific biological molecular events in living animals to better understand the effects of human disease in animal models. The purpose of this study was to develop and test a strategy behind automated methods for bioluminescence image processing from the data acquisition to obtaining 3D images. In order to optimize this procedure a semi-automated image processing approach with multi-modality image handling environment was developed. To identify a bioluminescent source location and strength we used the light flux detected on the surface of the imaged object by CCD cameras. For phantom calibration tests and object surface reconstruction we used MLEM algorithm. For internal bioluminescent sources we used the diffusion approximation with balancing the internal and external intensities on the boundary of the media and then determined an initial order approximation for the photon fluence we subsequently applied a novel iterative deconvolution method to obtain the final reconstruction result. We find that the reconstruction techniques successfully used the depth-dependent light transport approach and semi-automated image processing to provide a realistic 3D model of the lung tumor. Our image processing software can optimize and decrease the time of the volumetric imaging and quantitative assessment. The data obtained from light phantom and lung mouse tumor images demonstrate the utility of the image reconstruction algorithms and semi-automated approach for bioluminescent image processing procedure. We suggest that the developed image processing approach can be applied to preclinical imaging studies: characteristics of tumor growth, identify metastases, and potentially determine the effectiveness of cancer treatment.

  8. Prism adaptation in virtual and natural contexts: Evidence for a flexible adaptive process.

    PubMed

    Veilleux, Louis-Nicolas; Proteau, Luc

    2015-01-01

    Prism exposure when aiming at a visual target in a virtual condition (e.g., when the hand is represented by a video representation) produces no or only small adaptations (after-effects), whereas prism exposure in a natural condition produces large after-effects. Some researchers suggested that this difference may arise from distinct adaptive processes, but other studies suggested a unique process. The present study reconciled these conflicting interpretations. Forty participants were divided into two groups: One group used visual feedback of their hand (natural context), and the other group used computer-generated representational feedback (virtual context). Visual feedback during adaptation was concurrent or terminal. All participants underwent laterally displacing prism perturbation. The results showed that the after-effects were twice as large in the "natural context" than in the "virtual context". No significant differences were observed between the concurrent and terminal feedback conditions. The after-effects generalized to untested targets and workspace. These results suggest that prism adaptation in virtual and natural contexts involves the same process. The smaller after-effects in the virtual context suggest that the depth of adaptation is a function of the degree of convergence between the proprioceptive and visual information that arises from the hand.

  9. Adaptive structured dictionary learning for image fusion based on group-sparse-representation

    NASA Astrophysics Data System (ADS)

    Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

    2018-04-01

    Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.

  10. [A spatial adaptive algorithm for endmember extraction on multispectral remote sensing image].

    PubMed

    Zhu, Chang-Ming; Luo, Jian-Cheng; Shen, Zhan-Feng; Li, Jun-Li; Hu, Xiao-Dong

    2011-10-01

    Due to the problem that the convex cone analysis (CCA) method can only extract limited endmember in multispectral imagery, this paper proposed a new endmember extraction method by spatial adaptive spectral feature analysis in multispectral remote sensing image based on spatial clustering and imagery slice. Firstly, in order to remove spatial and spectral redundancies, the principal component analysis (PCA) algorithm was used for lowering the dimensions of the multispectral data. Secondly, iterative self-organizing data analysis technology algorithm (ISODATA) was used for image cluster through the similarity of the pixel spectral. And then, through clustering post process and litter clusters combination, we divided the whole image data into several blocks (tiles). Lastly, according to the complexity of image blocks' landscape and the feature of the scatter diagrams analysis, the authors can determine the number of endmembers. Then using hourglass algorithm extracts endmembers. Through the endmember extraction experiment on TM multispectral imagery, the experiment result showed that the method can extract endmember spectra form multispectral imagery effectively. What's more, the method resolved the problem of the amount of endmember limitation and improved accuracy of the endmember extraction. The method has provided a new way for multispectral image endmember extraction.

  11. 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).

  12. Adaptive bit plane quadtree-based block truncation coding for image compression

    NASA Astrophysics Data System (ADS)

    Li, Shenda; Wang, Jin; Zhu, Qing

    2018-04-01

    Block truncation coding (BTC) is a fast image compression technique applied in spatial domain. Traditional BTC and its variants mainly focus on reducing computational complexity for low bit rate compression, at the cost of lower quality of decoded images, especially for images with rich texture. To solve this problem, in this paper, a quadtree-based block truncation coding algorithm combined with adaptive bit plane transmission is proposed. First, the direction of edge in each block is detected using Sobel operator. For the block with minimal size, adaptive bit plane is utilized to optimize the BTC, which depends on its MSE loss encoded by absolute moment block truncation coding (AMBTC). Extensive experimental results show that our method gains 0.85 dB PSNR on average compare to some other state-of-the-art BTC variants. So it is desirable for real time image compression applications.

  13. Hyperspectral image processing methods

    USDA-ARS?s Scientific Manuscript database

    Hyperspectral image processing refers to the use of computer algorithms to extract, store and manipulate both spatial and spectral information contained in hyperspectral images across the visible and near-infrared portion of the electromagnetic spectrum. A typical hyperspectral image processing work...

  14. Adaptive and automatic red blood cell counting method based on microscopic hyperspectral imaging technology

    NASA Astrophysics Data System (ADS)

    Liu, Xi; Zhou, Mei; Qiu, Song; Sun, Li; Liu, Hongying; Li, Qingli; Wang, Yiting

    2017-12-01

    Red blood cell counting, as a routine examination, plays an important role in medical diagnoses. Although automated hematology analyzers are widely used, manual microscopic examination by a hematologist or pathologist is still unavoidable, which is time-consuming and error-prone. This paper proposes a full-automatic red blood cell counting method which is based on microscopic hyperspectral imaging of blood smears and combines spatial and spectral information to achieve high precision. The acquired hyperspectral image data of the blood smear in the visible and near-infrared spectral range are firstly preprocessed, and then a quadratic blind linear unmixing algorithm is used to get endmember abundance images. Based on mathematical morphological operation and an adaptive Otsu’s method, a binaryzation process is performed on the abundance images. Finally, the connected component labeling algorithm with magnification-based parameter setting is applied to automatically select the binary images of red blood cell cytoplasm. Experimental results show that the proposed method can perform well and has potential for clinical applications.

  15. Adaptive technique for matching the spectral response in skin lesions' images

    NASA Astrophysics Data System (ADS)

    Pavlova, P.; Borisova, E.; Pavlova, E.; Avramov, L.

    2015-03-01

    The suggested technique is a subsequent stage for data obtaining from diffuse reflectance spectra and images of diseased tissue with a final aim of skin cancer diagnostics. Our previous work allows us to extract patterns for some types of skin cancer, as a ratio between spectra, obtained from healthy and diseased tissue in the range of 380 - 780 nm region. The authenticity of the patterns depends on the tested point into the area of lesion, and the resulting diagnose could also be fixed with some probability. In this work, two adaptations are implemented to localize pixels of the image lesion, where the reflectance spectrum corresponds to pattern. First adapts the standard to the personal patient and second - translates the spectrum white point basis to the relative white point of the image. Since the reflectance spectra and the image pixels are regarding to different white points, a correction of the compared colours is needed. The latest is done using a standard method for chromatic adaptation. The technique follows the steps below: -Calculation the colorimetric XYZ parameters for the initial white point, fixed by reflectance spectrum from healthy tissue; -Calculation the XYZ parameters for the distant white point on the base of image of nondiseased tissue; -Transformation the XYZ parameters for the test-spectrum by obtained matrix; -Finding the RGB values of the XYZ parameters for the test-spectrum according sRGB; Finally, the pixels of the lesion's image, corresponding to colour from the test-spectrum and particular diagnostic pattern are marked with a specific colour.

  16. 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.

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

    PubMed Central

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

    2010-01-01

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

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

    PubMed

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

    2010-04-07

    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 x 20.0 mm dimensions could

  19. ImageJ: Image processing and analysis in Java

    NASA Astrophysics Data System (ADS)

    Rasband, W. S.

    2012-06-01

    ImageJ is a public domain Java image processing program inspired by NIH Image. It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and "raw". It supports "stacks", a series of images that share a single window. It is multithreaded, so time-consuming operations such as image file reading can be performed in parallel with other operations.

  20. Contrast limited adaptive histogram equalization image processing to improve the detection of simulated spiculations in dense mammograms.

    PubMed

    Pisano, E D; Zong, S; Hemminger, B M; DeLuca, M; Johnston, R E; Muller, K; Braeuning, M P; Pizer, S M

    1998-11-01

    The purpose of this project was to determine whether Contrast Limited Adaptive Histogram Equalization (CLAHE) improves detection of simulated spiculations in dense mammograms. Lines simulating the appearance of spiculations, a common marker of malignancy when visualized with masses, were embedded in dense mammograms digitized at 50 micron pixels, 12 bits deep. Film images with no CLAHE applied were compared to film images with nine different combinations of clip levels and region sizes applied. A simulated spiculation was embedded in a background of dense breast tissue, with the orientation of the spiculation varied. The key variables involved in each trial included the orientation of the spiculation, contrast level of the spiculation and the CLAHE settings applied to the image. Combining the 10 CLAHE conditions, 4 contrast levels and 4 orientations gave 160 combinations. The trials were constructed by pairing 160 combinations of key variables with 40 backgrounds. Twenty student observers were asked to detect the orientation of the spiculation in the image. There was a statistically significant improvement in detection performance for spiculations with CLAHE over unenhanced images when the region size was set at 32 with a clip level of 2, and when the region size was set at 32 with a clip level of 4. The selected CLAHE settings should be tested in the clinic with digital mammograms to determine whether detection of spiculations associated with masses detected at mammography can be improved.

  1. Fuzzy image processing in sun sensor

    NASA Technical Reports Server (NTRS)

    Mobasser, S.; Liebe, C. C.; Howard, A.

    2003-01-01

    This paper will describe how the fuzzy image processing is implemented in the instrument. Comparison of the Fuzzy image processing and a more conventional image processing algorithm is provided and shows that the Fuzzy image processing yields better accuracy then conventional image processing.

  2. Utility of adaptive control processing for the interpretation of digital mammograms.

    PubMed

    Jinnouchi, Mikako; Yabuuchi, Hidetake; Kubo, Makoto; Tokunaga, Eriko; Yamamoto, Hidetaka; Honda, Hiroshi

    2016-11-01

    Background Adaptive control processing for mammography (ACM) is a novel program that automatically sets up appropriate image-processing parameters for individual mammograms (MMGs) by analyzing the focal and whole breast histogram. Purpose To investigate whether ACM improves the image contrast of digital MMGs and whether it improves radiologists' diagnostic performance in reading of MMGs. Material and Methods One hundred normal cases for image quality assessment and another 100 cases (50 normal and 50 cancers) for observer performance assessment were enrolled. All mammograms were examined with and without ACM. Five radiologists assessed the intra- and extra-mammary contrast of 100 normal MMGs, and the mean scores of the intra- and extra-mammary contrast were compared between MMGs with and without ACM in both the dense and non-dense group. They classified 100 MMGs into BI-RADS categories 1-5, and were asked to rate the images on a scale of 0 to 100 for the likelihood of the presence of category 3-5 lesions in each breast. Detectability of breast cancer, reading time, and frequency of window adjustment were compared between MMGs with and without ACM. Results ACM improved the intra-mammary contrast in both the dense and non-dense group but degraded extra-mammary contrast in the dense group. There was no significant difference in detectability of breast cancer between MMGs with and without ACM. Frequency of window adjustment without ACM was significantly higher than that with ACM. Reading time without ACM was significantly longer than that with ACM. Conclusion ACM improves the image contrast of MMGs and shortens reading time.

  3. 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

  4. Introducing an on-line adaptive procedure for prostate image guided intensity modulate proton therapy.

    PubMed

    Zhang, M; Westerly, D C; Mackie, T R

    2011-08-07

    With on-line image guidance (IG), prostate shifts relative to the bony anatomy can be corrected by realigning the patient with respect to the treatment fields. In image guided intensity modulated proton therapy (IG-IMPT), because the proton range is more sensitive to the material it travels through, the realignment may introduce large dose variations. This effect is studied in this work and an on-line adaptive procedure is proposed to restore the planned dose to the target. A 2D anthropomorphic phantom was constructed from a real prostate patient's CT image. Two-field laterally opposing spot 3D-modulation and 24-field full arc distal edge tracking (DET) plans were generated with a prescription of 70 Gy to the planning target volume. For the simulated delivery, we considered two types of procedures: the non-adaptive procedure and the on-line adaptive procedure. In the non-adaptive procedure, only patient realignment to match the prostate location in the planning CT was performed. In the on-line adaptive procedure, on top of the patient realignment, the kinetic energy for each individual proton pencil beam was re-determined from the on-line CT image acquired after the realignment and subsequently used for delivery. Dose distributions were re-calculated for individual fractions for different plans and different delivery procedures. The results show, without adaptive, that both the 3D-modulation and the DET plans experienced delivered dose degradation by having large cold or hot spots in the prostate. The DET plan had worse dose degradation than the 3D-modulation plan. The adaptive procedure effectively restored the planned dose distribution in the DET plan, with delivered prostate D(98%), D(50%) and D(2%) values less than 1% from the prescription. In the 3D-modulation plan, in certain cases the adaptive procedure was not effective to reduce the delivered dose degradation and yield similar results as the non-adaptive procedure. In conclusion, based on this 2D phantom

  5. Introducing an on-line adaptive procedure for prostate image guided intensity modulate proton therapy

    NASA Astrophysics Data System (ADS)

    Zhang, M.; Westerly, D. C.; Mackie, T. R.

    2011-08-01

    With on-line image guidance (IG), prostate shifts relative to the bony anatomy can be corrected by realigning the patient with respect to the treatment fields. In image guided intensity modulated proton therapy (IG-IMPT), because the proton range is more sensitive to the material it travels through, the realignment may introduce large dose variations. This effect is studied in this work and an on-line adaptive procedure is proposed to restore the planned dose to the target. A 2D anthropomorphic phantom was constructed from a real prostate patient's CT image. Two-field laterally opposing spot 3D-modulation and 24-field full arc distal edge tracking (DET) plans were generated with a prescription of 70 Gy to the planning target volume. For the simulated delivery, we considered two types of procedures: the non-adaptive procedure and the on-line adaptive procedure. In the non-adaptive procedure, only patient realignment to match the prostate location in the planning CT was performed. In the on-line adaptive procedure, on top of the patient realignment, the kinetic energy for each individual proton pencil beam was re-determined from the on-line CT image acquired after the realignment and subsequently used for delivery. Dose distributions were re-calculated for individual fractions for different plans and different delivery procedures. The results show, without adaptive, that both the 3D-modulation and the DET plans experienced delivered dose degradation by having large cold or hot spots in the prostate. The DET plan had worse dose degradation than the 3D-modulation plan. The adaptive procedure effectively restored the planned dose distribution in the DET plan, with delivered prostate D98%, D50% and D2% values less than 1% from the prescription. In the 3D-modulation plan, in certain cases the adaptive procedure was not effective to reduce the delivered dose degradation and yield similar results as the non-adaptive procedure. In conclusion, based on this 2D phantom study

  6. Adaptive signal processing at NOSC

    NASA Astrophysics Data System (ADS)

    Albert, T. R.

    1992-03-01

    Adaptive signal processing work at the Naval Ocean Systems Center (NOSC) dates back to the late 1960s. It began as an IR/IED project by John McCool, who made use of an adaptive algorithm that had been developed by Professor Bernard Widrow of Stanford University. In 1972, a team lead by McCool built the first hardware implementation of the algorithm that could process in real-time at acoustic bandwidths. Early tests with the two units that were built were extremely successful, and attracted much attention. Sponsors from different commands provided funding to develop hardware for submarine, surface ship, airborne, and other systems. In addition, an effort was initiated to analyze performance and behavior of the algorithm. Most of the hardware development and analysis efforts were active through the 1970s, and a few into the 1980s. One of the original programs continues to this date.

  7. CORDIC-based digital signal processing (DSP) element for adaptive signal processing

    NASA Astrophysics Data System (ADS)

    Bolstad, Gregory D.; Neeld, Kenneth B.

    1995-04-01

    The High Performance Adaptive Weight Computation (HAWC) processing element is a CORDIC based application specific DSP element that, when connected in a linear array, can perform extremely high throughput (100s of GFLOPS) matrix arithmetic operations on linear systems of equations in real time. In particular, it very efficiently performs the numerically intense computation of optimal least squares solutions for large, over-determined linear systems. Most techniques for computing solutions to these types of problems have used either a hard-wired, non-programmable systolic array approach, or more commonly, programmable DSP or microprocessor approaches. The custom logic methods can be efficient, but are generally inflexible. Approaches using multiple programmable generic DSP devices are very flexible, but suffer from poor efficiency and high computation latencies, primarily due to the large number of DSP devices that must be utilized to achieve the necessary arithmetic throughput. The HAWC processor is implemented as a highly optimized systolic array, yet retains some of the flexibility of a programmable data-flow system, allowing efficient implementation of algorithm variations. This provides flexible matrix processing capabilities that are one to three orders of magnitude less expensive and more dense than the current state of the art, and more importantly, allows a realizable solution to matrix processing problems that were previously considered impractical to physically implement. HAWC has direct applications in RADAR, SONAR, communications, and image processing, as well as in many other types of systems.

  8. Novel image processing method study for a label-free optical biosensor

    NASA Astrophysics Data System (ADS)

    Yang, Chenhao; Wei, Li'an; Yang, Rusong; Feng, Ying

    2015-10-01

    Optical biosensor is generally divided into labeled type and label-free type, the former mainly contains fluorescence labeled method and radioactive-labeled method, while fluorescence-labeled method is more mature in the application. The mainly image processing methods of fluorescent-labeled biosensor includes smooth filtering, artificial gridding and constant thresholding. Since some fluorescent molecules may influence the biological reaction, label-free methods have been the main developing direction of optical biosensors nowadays. The using of wider field of view and larger angle of incidence light path which could effectively improve the sensitivity of the label-free biosensor also brought more difficulties in image processing, comparing with the fluorescent-labeled biosensor. Otsu's method is widely applied in machine vision, etc, which choose the threshold to minimize the intraclass variance of the thresholded black and white pixels. It's capacity-constrained with the asymmetrical distribution of images as a global threshold segmentation. In order to solve the irregularity of light intensity on the transducer, we improved the algorithm. In this paper, we present a new image processing algorithm based on a reflectance modulation biosensor platform, which mainly comprises the design of sliding normalization algorithm for image rectification and utilizing the improved otsu's method for image segmentation, in order to implement automatic recognition of target areas. Finally we used adaptive gridding method extracting the target parameters for analysis. Those methods could improve the efficiency of image processing, reduce human intervention, enhance the reliability of experiments and laid the foundation for the realization of high throughput of label-free optical biosensors.

  9. Novel Near-Lossless Compression Algorithm for Medical Sequence Images with Adaptive Block-Based Spatial Prediction.

    PubMed

    Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

    2016-12-01

    To address the low compression efficiency of lossless compression and the low image quality of general near-lossless compression, a novel near-lossless compression algorithm based on adaptive spatial prediction is proposed for medical sequence images for possible diagnostic use in this paper. The proposed method employs adaptive block size-based spatial prediction to predict blocks directly in the spatial domain and Lossless Hadamard Transform before quantization to improve the quality of reconstructed images. The block-based prediction breaks the pixel neighborhood constraint and takes full advantage of the local spatial correlations found in medical images. The adaptive block size guarantees a more rational division of images and the improved use of the local structure. The results indicate that the proposed algorithm can efficiently compress medical images and produces a better peak signal-to-noise ratio (PSNR) under the same pre-defined distortion than other near-lossless methods.

  10. Image-guided adaptive gating of lung cancer radiotherapy: a computer simulation study

    NASA Astrophysics Data System (ADS)

    Aristophanous, Michalis; Rottmann, Joerg; Park, Sang-June; Nishioka, Seiko; Shirato, Hiroki; Berbeco, Ross I.

    2010-08-01

    The purpose of this study is to investigate the effect that image-guided adaptation of the gating window during treatment could have on the residual tumor motion, by simulating different gated radiotherapy techniques. There are three separate components of this simulation: (1) the 'Hokkaido Data', which are previously measured 3D data of lung tumor motion tracks and the corresponding 1D respiratory signals obtained during the entire ungated radiotherapy treatments of eight patients, (2) the respiratory gating protocol at our institution and the imaging performed under that protocol and (3) the actual simulation in which the Hokkaido Data are used to select tumor position information that could have been collected based on the imaging performed under our gating protocol. We simulated treatments with a fixed gating window and a gating window that is updated during treatment. The patient data were divided into different fractions, each with continuous acquisitions longer than 2 min. In accordance to the imaging performed under our gating protocol, we assume that we have tumor position information for the first 15 s of treatment, obtained from kV fluoroscopy, and for the rest of the fractions the tumor position is only available during the beam-on time from MV imaging. The gating window was set according to the information obtained from the first 15 s such that the residual motion was less than 3 mm. For the fixed gating window technique the gate remained the same for the entire treatment, while for the adaptive technique the range of the tumor motion during beam-on time was measured and used to adapt the gating window to keep the residual motion below 3 mm. The algorithm used to adapt the gating window is described. The residual tumor motion inside the gating window was reduced on average by 24% for the patients with regular breathing patterns and the difference was statistically significant (p-value = 0.01). The magnitude of the residual tumor motion depended on the

  11. Visual Communications and Image Processing

    NASA Astrophysics Data System (ADS)

    Hsing, T. Russell

    1987-07-01

    This special issue of Optical Engineering is concerned with visual communications and image processing. The increase in communication of visual information over the past several decades has resulted in many new image processing and visual communication systems being put into service. The growth of this field has been rapid in both commercial and military applications. The objective of this special issue is to intermix advent technology in visual communications and image processing with ideas generated from industry, universities, and users through both invited and contributed papers. The 15 papers of this issue are organized into four different categories: image compression and transmission, image enhancement, image analysis and pattern recognition, and image processing in medical applications.

  12. Accuracy requirements of optical linear algebra processors in adaptive optics imaging systems

    NASA Technical Reports Server (NTRS)

    Downie, John D.

    1990-01-01

    A ground-based adaptive optics imaging telescope system attempts to improve image quality by detecting and correcting for atmospherically induced wavefront aberrations. The required control computations during each cycle will take a finite amount of time. Longer time delays result in larger values of residual wavefront error variance since the atmosphere continues to change during that time. Thus an optical processor may be well-suited for this task. This paper presents a study of the accuracy requirements in a general optical processor that will make it competitive with, or superior to, a conventional digital computer for the adaptive optics application. An optimization of the adaptive optics correction algorithm with respect to an optical processor's degree of accuracy is also briefly discussed.

  13. Adaptive Iterative Dose Reduction Using Three Dimensional Processing (AIDR3D) improves chest CT image quality and reduces radiation exposure.

    PubMed

    Yamashiro, Tsuneo; Miyara, Tetsuhiro; Honda, Osamu; Kamiya, Hisashi; Murata, Kiyoshi; Ohno, Yoshiharu; Tomiyama, Noriyuki; Moriya, Hiroshi; Koyama, Mitsuhiro; Noma, Satoshi; Kamiya, Ayano; Tanaka, Yuko; Murayama, Sadayuki

    2014-01-01

    To assess the advantages of Adaptive Iterative Dose Reduction using Three Dimensional Processing (AIDR3D) for image quality improvement and dose reduction for chest computed tomography (CT). Institutional Review Boards approved this study and informed consent was obtained. Eighty-eight subjects underwent chest CT at five institutions using identical scanners and protocols. During a single visit, each subject was scanned using different tube currents: 240, 120, and 60 mA. Scan data were converted to images using AIDR3D and a conventional reconstruction mode (without AIDR3D). Using a 5-point scale from 1 (non-diagnostic) to 5 (excellent), three blinded observers independently evaluated image quality for three lung zones, four patterns of lung disease (nodule/mass, emphysema, bronchiolitis, and diffuse lung disease), and three mediastinal measurements (small structure visibility, streak artifacts, and shoulder artifacts). Differences in these scores were assessed by Scheffe's test. At each tube current, scans using AIDR3D had higher scores than those without AIDR3D, which were significant for lung zones (p<0.0001) and all mediastinal measurements (p<0.01). For lung diseases, significant improvements with AIDR3D were frequently observed at 120 and 60 mA. Scans with AIDR3D at 120 mA had significantly higher scores than those without AIDR3D at 240 mA for lung zones and mediastinal streak artifacts (p<0.0001), and slightly higher or equal scores for all other measurements. Scans with AIDR3D at 60 mA were also judged superior or equivalent to those without AIDR3D at 120 mA. For chest CT, AIDR3D provides better image quality and can reduce radiation exposure by 50%.

  14. Adaptive Optics Imaging of Solar System Objects

    NASA Technical Reports Server (NTRS)

    Roddier, Francois; Owen, Toby

    1999-01-01

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

  15. Lower-upper-threshold correlation for underwater range-gated imaging self-adaptive enhancement.

    PubMed

    Sun, Liang; Wang, Xinwei; Liu, Xiaoquan; Ren, Pengdao; Lei, Pingshun; He, Jun; Fan, Songtao; Zhou, Yan; Liu, Yuliang

    2016-10-10

    In underwater range-gated imaging (URGI), enhancement of low-brightness and low-contrast images is critical for human observation. Traditional histogram equalizations over-enhance images, with the result of details being lost. To compress over-enhancement, a lower-upper-threshold correlation method is proposed for underwater range-gated imaging self-adaptive enhancement based on double-plateau histogram equalization. The lower threshold determines image details and compresses over-enhancement. It is correlated with the upper threshold. First, the upper threshold is updated by searching for the local maximum in real time, and then the lower threshold is calculated by the upper threshold and the number of nonzero units selected from a filtered histogram. With this method, the backgrounds of underwater images are constrained with enhanced details. Finally, the proof experiments are performed. Peak signal-to-noise-ratio, variance, contrast, and human visual properties are used to evaluate the objective quality of the global and regions of interest images. The evaluation results demonstrate that the proposed method adaptively selects the proper upper and lower thresholds under different conditions. The proposed method contributes to URGI with effective image enhancement for human eyes.

  16. Impact induced damage assessment by means of Lamb wave image processing

    NASA Astrophysics Data System (ADS)

    Kudela, Pawel; Radzienski, Maciej; Ostachowicz, Wieslaw

    2018-03-01

    The aim of this research is an analysis of full wavefield Lamb wave interaction with impact-induced damage at various impact energies in order to find out the limitation of the wavenumber adaptive image filtering method. In other words, the relation between impact energy and damage detectability will be shown. A numerical model based on the time domain spectral element method is used for modeling of Lamb wave propagation and interaction with barely visible impact damage in a carbon-epoxy laminate. Numerical studies are followed by experimental research on the same material with an impact damage induced by various energy and also a Teflon insert simulating delamination. Wavenumber adaptive image filtering and signal processing are used for damage visualization and assessment for both numerical and experimental full wavefield data. It is shown that it is possible to visualize and assess the impact damage location, size and to some extent severity by using the proposed technique.

  17. Standard and reduced radiation dose liver CT images: adaptive statistical iterative reconstruction versus model-based iterative reconstruction-comparison of findings and image quality.

    PubMed

    Shuman, William P; Chan, Keith T; Busey, Janet M; Mitsumori, Lee M; Choi, Eunice; Koprowicz, Kent M; Kanal, Kalpana M

    2014-12-01

    To investigate whether reduced radiation dose liver computed tomography (CT) images reconstructed with model-based iterative reconstruction ( MBIR model-based iterative reconstruction ) might compromise depiction of clinically relevant findings or might have decreased image quality when compared with clinical standard radiation dose CT images reconstructed with adaptive statistical iterative reconstruction ( ASIR adaptive statistical iterative reconstruction ). With institutional review board approval, informed consent, and HIPAA compliance, 50 patients (39 men, 11 women) were prospectively included who underwent liver CT. After a portal venous pass with ASIR adaptive statistical iterative reconstruction images, a 60% reduced radiation dose pass was added with MBIR model-based iterative reconstruction images. One reviewer scored ASIR adaptive statistical iterative reconstruction image quality and marked findings. Two additional independent reviewers noted whether marked findings were present on MBIR model-based iterative reconstruction images and assigned scores for relative conspicuity, spatial resolution, image noise, and image quality. Liver and aorta Hounsfield units and image noise were measured. Volume CT dose index and size-specific dose estimate ( SSDE size-specific dose estimate ) were recorded. Qualitative reviewer scores were summarized. Formal statistical inference for signal-to-noise ratio ( SNR signal-to-noise ratio ), contrast-to-noise ratio ( CNR contrast-to-noise ratio ), volume CT dose index, and SSDE size-specific dose estimate was made (paired t tests), with Bonferroni adjustment. Two independent reviewers identified all 136 ASIR adaptive statistical iterative reconstruction image findings (n = 272) on MBIR model-based iterative reconstruction images, scoring them as equal or better for conspicuity, spatial resolution, and image noise in 94.1% (256 of 272), 96.7% (263 of 272), and 99.3% (270 of 272), respectively. In 50 image sets, two reviewers

  18. Accuracy requirements of optical linear algebra processors in adaptive optics imaging systems.

    PubMed

    Downie, J D; Goodman, J W

    1989-10-15

    A ground-based adaptive optics imaging telescope system attempts to improve image quality by measuring and correcting for atmospherically induced wavefront aberrations. The necessary control computations during each cycle will take a finite amount of time, which adds to the residual error variance since the atmosphere continues to change during that time. Thus an optical processor may be well-suited for this task. This paper investigates this possibility by studying the accuracy requirements in a general optical processor that will make it competitive with, or superior to, a conventional digital computer for adaptive optics use.

  19. Automatic telangiectasia analysis in dermoscopy images using adaptive critic design.

    PubMed

    Cheng, B; Stanley, R J; Stoecker, W V; Hinton, K

    2012-11-01

    Telangiectasia, tiny skin vessels, are important dermoscopy structures used to discriminate basal cell carcinoma (BCC) from benign skin lesions. This research builds off of previously developed image analysis techniques to identify vessels automatically to discriminate benign lesions from BCCs. A biologically inspired reinforcement learning approach is investigated in an adaptive critic design framework to apply action-dependent heuristic dynamic programming (ADHDP) for discrimination based on computed features using different skin lesion contrast variations to promote the discrimination process. Lesion discrimination results for ADHDP are compared with multilayer perception backpropagation artificial neural networks. This study uses a data set of 498 dermoscopy skin lesion images of 263 BCCs and 226 competitive benign images as the input sets. This data set is extended from previous research [Cheng et al., Skin Research and Technology, 2011, 17: 278]. Experimental results yielded a diagnostic accuracy as high as 84.6% using the ADHDP approach, providing an 8.03% improvement over a standard multilayer perception method. We have chosen BCC detection rather than vessel detection as the endpoint. Although vessel detection is inherently easier, BCC detection has potential direct clinical applications. Small BCCs are detectable early by dermoscopy and potentially detectable by the automated methods described in this research. © 2011 John Wiley & Sons A/S.

  20. Robust and adaptive band-to-band image transform of UAS miniature multi-lens multispectral camera

    NASA Astrophysics Data System (ADS)

    Jhan, Jyun-Ping; Rau, Jiann-Yeou; Haala, Norbert

    2018-03-01

    Utilizing miniature multispectral (MS) or hyperspectral (HS) cameras by mounting them on an Unmanned Aerial System (UAS) has the benefits of convenience and flexibility to collect remote sensing imagery for precision agriculture, vegetation monitoring, and environment investigation applications. Most miniature MS cameras adopt a multi-lens structure to record discrete MS bands of visible and invisible information. The differences in lens distortion, mounting positions, and viewing angles among lenses mean that the acquired original MS images have significant band misregistration errors. We have developed a Robust and Adaptive Band-to-Band Image Transform (RABBIT) method for dealing with the band co-registration of various types of miniature multi-lens multispectral cameras (Mini-MSCs) to obtain band co-registered MS imagery for remote sensing applications. The RABBIT utilizes modified projective transformation (MPT) to transfer the multiple image geometry of a multi-lens imaging system to one sensor geometry, and combines this with a robust and adaptive correction (RAC) procedure to correct several systematic errors and to obtain sub-pixel accuracy. This study applies three state-of-the-art Mini-MSCs to evaluate the RABBIT method's performance, specifically the Tetracam Miniature Multiple Camera Array (MiniMCA), Micasense RedEdge, and Parrot Sequoia. Six MS datasets acquired at different target distances and dates, and locations are also applied to prove its reliability and applicability. Results prove that RABBIT is feasible for different types of Mini-MSCs with accurate, robust, and rapid image processing efficiency.

  1. Adaptive multifocus image fusion using block compressed sensing with smoothed projected Landweber integration in the wavelet domain.

    PubMed

    V S, Unni; Mishra, Deepak; Subrahmanyam, G R K S

    2016-12-01

    The need for image fusion in current image processing systems is increasing mainly due to the increased number and variety of image acquisition techniques. Image fusion is the process of combining substantial information from several sensors using mathematical techniques in order to create a single composite image that will be more comprehensive and thus more useful for a human operator or other computer vision tasks. This paper presents a new approach to multifocus image fusion based on sparse signal representation. Block-based compressive sensing integrated with a projection-driven compressive sensing (CS) recovery that encourages sparsity in the wavelet domain is used as a method to get the focused image from a set of out-of-focus images. Compression is achieved during the image acquisition process using a block compressive sensing method. An adaptive thresholding technique within the smoothed projected Landweber recovery process reconstructs high-resolution focused images from low-dimensional CS measurements of out-of-focus images. Discrete wavelet transform and dual-tree complex wavelet transform are used as the sparsifying basis for the proposed fusion. The main finding lies in the fact that sparsification enables a better selection of the fusion coefficients and hence better fusion. A Laplacian mixture model fit is done in the wavelet domain and estimation of the probability density function (pdf) parameters by expectation maximization leads us to the proper selection of the coefficients of the fused image. Using the proposed method compared with the fusion scheme without employing the projected Landweber (PL) scheme and the other existing CS-based fusion approaches, it is observed that with fewer samples itself, the proposed method outperforms other approaches.

  2. 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

  3. Automated and Adaptable Quantification of Cellular Alignment from Microscopic Images for Tissue Engineering Applications

    PubMed Central

    Xu, Feng; Beyazoglu, Turker; Hefner, Evan; Gurkan, Umut Atakan

    2011-01-01

    Cellular alignment plays a critical role in functional, physical, and biological characteristics of many tissue types, such as muscle, tendon, nerve, and cornea. Current efforts toward regeneration of these tissues include replicating the cellular microenvironment by developing biomaterials that facilitate cellular alignment. To assess the functional effectiveness of the engineered microenvironments, one essential criterion is quantification of cellular alignment. Therefore, there is a need for rapid, accurate, and adaptable methodologies to quantify cellular alignment for tissue engineering applications. To address this need, we developed an automated method, binarization-based extraction of alignment score (BEAS), to determine cell orientation distribution in a wide variety of microscopic images. This method combines a sequenced application of median and band-pass filters, locally adaptive thresholding approaches and image processing techniques. Cellular alignment score is obtained by applying a robust scoring algorithm to the orientation distribution. We validated the BEAS method by comparing the results with the existing approaches reported in literature (i.e., manual, radial fast Fourier transform-radial sum, and gradient based approaches). Validation results indicated that the BEAS method resulted in statistically comparable alignment scores with the manual method (coefficient of determination R2=0.92). Therefore, the BEAS method introduced in this study could enable accurate, convenient, and adaptable evaluation of engineered tissue constructs and biomaterials in terms of cellular alignment and organization. PMID:21370940

  4. Stable image acquisition for mobile image processing applications

    NASA Astrophysics Data System (ADS)

    Henning, Kai-Fabian; Fritze, Alexander; Gillich, Eugen; Mönks, Uwe; Lohweg, Volker

    2015-02-01

    Today, mobile devices (smartphones, tablets, etc.) are widespread and of high importance for their users. Their performance as well as versatility increases over time. This leads to the opportunity to use such devices for more specific tasks like image processing in an industrial context. For the analysis of images requirements like image quality (blur, illumination, etc.) as well as a defined relative position of the object to be inspected are crucial. Since mobile devices are handheld and used in constantly changing environments the challenge is to fulfill these requirements. We present an approach to overcome the obstacles and stabilize the image capturing process such that image analysis becomes significantly improved on mobile devices. Therefore, image processing methods are combined with sensor fusion concepts. The approach consists of three main parts. First, pose estimation methods are used to guide a user moving the device to a defined position. Second, the sensors data and the pose information are combined for relative motion estimation. Finally, the image capturing process is automated. It is triggered depending on the alignment of the device and the object as well as the image quality that can be achieved under consideration of motion and environmental effects.

  5. Use of focus measure operators for characterization of flood illumination adaptive optics ophthalmoscopy image quality

    PubMed Central

    Alonso-Caneiro, David; Sampson, Danuta M.; Chew, Avenell L.; Collins, Michael J.; Chen, Fred K.

    2018-01-01

    Adaptive optics flood illumination ophthalmoscopy (AO-FIO) allows imaging of the cone photoreceptor in the living human retina. However, clinical interpretation of the AO-FIO image remains challenging due to suboptimal quality arising from residual uncorrected wavefront aberrations and rapid eye motion. An objective method of assessing image quality is necessary to determine whether an AO-FIO image is suitable for grading and diagnostic purpose. In this work, we explore the use of focus measure operators as a surrogate measure of AO-FIO image quality. A set of operators are tested on data sets acquired at different focal depths and different retinal locations from healthy volunteers. Our results demonstrate differences in focus measure operator performance in quantifying AO-FIO image quality. Further, we discuss the potential application of the selected focus operators in (i) selection of the best quality AO-FIO image from a series of images collected at the same retinal location and (ii) assessment of longitudinal changes in the diseased retina. Focus function could be incorporated into real-time AO-FIO image processing and provide an initial automated quality assessment during image acquisition or reading center grading. PMID:29552404

  6. Use of focus measure operators for characterization of flood illumination adaptive optics ophthalmoscopy image quality.

    PubMed

    Alonso-Caneiro, David; Sampson, Danuta M; Chew, Avenell L; Collins, Michael J; Chen, Fred K

    2018-02-01

    Adaptive optics flood illumination ophthalmoscopy (AO-FIO) allows imaging of the cone photoreceptor in the living human retina. However, clinical interpretation of the AO-FIO image remains challenging due to suboptimal quality arising from residual uncorrected wavefront aberrations and rapid eye motion. An objective method of assessing image quality is necessary to determine whether an AO-FIO image is suitable for grading and diagnostic purpose. In this work, we explore the use of focus measure operators as a surrogate measure of AO-FIO image quality. A set of operators are tested on data sets acquired at different focal depths and different retinal locations from healthy volunteers. Our results demonstrate differences in focus measure operator performance in quantifying AO-FIO image quality. Further, we discuss the potential application of the selected focus operators in (i) selection of the best quality AO-FIO image from a series of images collected at the same retinal location and (ii) assessment of longitudinal changes in the diseased retina. Focus function could be incorporated into real-time AO-FIO image processing and provide an initial automated quality assessment during image acquisition or reading center grading.

  7. Adaptive constructive processes and the future of memory.

    PubMed

    Schacter, Daniel L

    2012-11-01

    Memory serves critical functions in everyday life but is also prone to error. This article examines adaptive constructive processes, which play a functional role in memory and cognition but can also produce distortions, errors, and illusions. The article describes several types of memory errors that are produced by adaptive constructive processes and focuses in particular on the process of imagining or simulating events that might occur in one's personal future. Simulating future events relies on many of the same cognitive and neural processes as remembering past events, which may help to explain why imagination and memory can be easily confused. The article considers both pitfalls and adaptive aspects of future event simulation in the context of research on planning, prediction, problem solving, mind-wandering, prospective and retrospective memory, coping and positivity bias, and the interconnected set of brain regions known as the default network. PsycINFO Database Record (c) 2012 APA, all rights reserved.

  8. Adaptive coded aperture imaging in the infrared: towards a practical implementation

    NASA Astrophysics Data System (ADS)

    Slinger, Chris W.; Gilholm, Kevin; Gordon, Neil; McNie, Mark; Payne, Doug; Ridley, Kevin; Strens, Malcolm; Todd, Mike; De Villiers, Geoff; Watson, Philip; Wilson, Rebecca; Dyer, Gavin; Eismann, Mike; Meola, Joe; Rogers, Stanley

    2008-08-01

    An earlier paper [1] discussed the merits of adaptive coded apertures for use as lensless imaging systems in the thermal infrared and visible. It was shown how diffractive (rather than the more conventional geometric) coding could be used, and that 2D intensity measurements from multiple mask patterns could be combined and decoded to yield enhanced imagery. Initial experimental results in the visible band were presented. Unfortunately, radiosity calculations, also presented in that paper, indicated that the signal to noise performance of systems using this approach was likely to be compromised, especially in the infrared. This paper will discuss how such limitations can be overcome, and some of the tradeoffs involved. Experimental results showing tracking and imaging performance of these modified, diffractive, adaptive coded aperture systems in the visible and infrared will be presented. The subpixel imaging and tracking performance is compared to that of conventional imaging systems and shown to be superior. System size, weight and cost calculations indicate that the coded aperture approach, employing novel photonic MOEMS micro-shutter architectures, has significant merits for a given level of performance in the MWIR when compared to more conventional imaging approaches.

  9. Optoelectronic imaging of speckle using image processing method

    NASA Astrophysics Data System (ADS)

    Wang, Jinjiang; Wang, Pengfei

    2018-01-01

    A detailed image processing of laser speckle interferometry is proposed as an example for the course of postgraduate student. Several image processing methods were used together for dealing with optoelectronic imaging system, such as the partial differential equations (PDEs) are used to reduce the effect of noise, the thresholding segmentation also based on heat equation with PDEs, the central line is extracted based on image skeleton, and the branch is removed automatically, the phase level is calculated by spline interpolation method, and the fringe phase can be unwrapped. Finally, the imaging processing method was used to automatically measure the bubble in rubber with negative pressure which could be used in the tire detection.

  10. Regionally adaptive histogram equalization of the chest.

    PubMed

    Sherrier, R H; Johnson, G A

    1987-01-01

    Advances in the area of digital chest radiography have resulted in the acquisition of high-quality images of the human chest. With these advances, there arises a genuine need for image processing algorithms specific to the chest, in order to fully exploit this digital technology. We have implemented the well-known technique of histogram equalization, noting the problems encountered when it is adapted to chest images. These problems have been successfully solved with our regionally adaptive histogram equalization method. With this technique histograms are calculated locally and then modified according to both the mean pixel value of that region as well as certain characteristics of the cumulative distribution function. This process, which has allowed certain regions of the chest radiograph to be enhanced differentially, may also have broader implications for other image processing tasks.

  11. Image processing for cryogenic transmission electron microscopy of symmetry-mismatched complexes.

    PubMed

    Huiskonen, Juha T

    2018-02-08

    Cryogenic transmission electron microscopy (cryo-TEM) is a high-resolution biological imaging method, whereby biological samples, such as purified proteins, macromolecular complexes, viral particles, organelles and cells, are embedded in vitreous ice preserving their native structures. Due to sensitivity of biological materials to the electron beam of the microscope, only relatively low electron doses can be applied during imaging. As a result, the signal arising from the structure of interest is overpowered by noise in the images. To increase the signal-to-noise ratio, different image processing-based strategies that aim at coherent averaging of signal have been devised. In such strategies, images are generally assumed to arise from multiple identical copies of the structure. Prior to averaging, the images must be grouped according to the view of the structure they represent and images representing the same view must be simultaneously aligned relatively to each other. For computational reconstruction of the three-dimensional structure, images must contain different views of the original structure. Structures with multiple symmetry-related substructures are advantageous in averaging approaches because each image provides multiple views of the substructures. However, the symmetry assumption may be valid for only parts of the structure, leading to incoherent averaging of the other parts. Several image processing approaches have been adapted to tackle symmetry-mismatched substructures with increasing success. Such structures are ubiquitous in nature and further computational method development is needed to understanding their biological functions. ©2018 The Author(s).

  12. Automated Coronal Loop Identification Using Digital Image Processing Techniques

    NASA Technical Reports Server (NTRS)

    Lee, Jong K.; Gary, G. Allen; Newman, Timothy S.

    2003-01-01

    The results of a master thesis project on a study of computer algorithms for automatic identification of optical-thin, 3-dimensional solar coronal loop centers from extreme ultraviolet and X-ray 2-dimensional images will be presented. These center splines are proxies of associated magnetic field lines. The project is pattern recognition problems in which there are no unique shapes or edges and in which photon and detector noise heavily influence the images. The study explores extraction techniques using: (1) linear feature recognition of local patterns (related to the inertia-tensor concept), (2) parametric space via the Hough transform, and (3) topological adaptive contours (snakes) that constrains curvature and continuity as possible candidates for digital loop detection schemes. We have developed synthesized images for the coronal loops to test the various loop identification algorithms. Since the topology of these solar features is dominated by the magnetic field structure, a first-order magnetic field approximation using multiple dipoles provides a priori information in the identification process. Results from both synthesized and solar images will be presented.

  13. Architectures and algorithms for digital image processing; Proceedings of the Meeting, Cannes, France, December 5, 6, 1985

    NASA Technical Reports Server (NTRS)

    Duff, Michael J. B. (Editor); Siegel, Howard J. (Editor); Corbett, Francis J. (Editor)

    1986-01-01

    The conference presents papers on the architectures, algorithms, and applications of image processing. Particular attention is given to a very large scale integration system for image reconstruction from projections, a prebuffer algorithm for instant display of volume data, and an adaptive image sequence filtering scheme based on motion detection. Papers are also presented on a simple, direct practical method of sensing local motion and analyzing local optical flow, image matching techniques, and an automated biological dosimetry system.

  14. High contrast imaging through adaptive transmittance control in the focal plane

    NASA Astrophysics Data System (ADS)

    Dhadwal, Harbans S.; Rastegar, Jahangir; Feng, Dake

    2016-05-01

    High contrast imaging, in the presence of a bright background, is a challenging problem encountered in diverse applications ranging from the daily chore of driving into a sun-drenched scene to in vivo use of biomedical imaging in various types of keyhole surgeries. Imaging in the presence of bright sources saturates the vision system, resulting in loss of scene fidelity, corresponding to low image contrast and reduced resolution. The problem is exacerbated in retro-reflective imaging systems where the light sources illuminating the object are unavoidably strong, typically masking the object features. This manuscript presents a novel theoretical framework, based on nonlinear analysis and adaptive focal plane transmittance, to selectively remove object domain sources of background light from the image plane, resulting in local and global increases in image contrast. The background signal can either be of a global specular nature, giving rise to parallel illumination from the entire object surface or can be represented by a mosaic of randomly orientated, small specular surfaces. The latter is more representative of real world practical imaging systems. Thus, the background signal comprises of groups of oblique rays corresponding to distributions of the mosaic surfaces. Through the imaging system, light from group of like surfaces, converges to a localized spot in the focal plane of the lens and then diverges to cast a localized bright spot in the image plane. Thus, transmittance of a spatial light modulator, positioned in the focal plane, can be adaptively controlled to block a particular source of background light. Consequently, the image plane intensity is entirely due to the object features. Experimental image data is presented to verify the efficacy of the methodology.

  15. Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction.

    PubMed

    Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

    2018-06-01

    To improve the compression rates for lossless compression of medical images, an efficient algorithm, based on irregular segmentation and region-based prediction, is proposed in this paper. Considering that the first step of a region-based compression algorithm is segmentation, this paper proposes a hybrid method by combining geometry-adaptive partitioning and quadtree partitioning to achieve adaptive irregular segmentation for medical images. Then, least square (LS)-based predictors are adaptively designed for each region (regular subblock or irregular subregion). The proposed adaptive algorithm not only exploits spatial correlation between pixels but it utilizes local structure similarity, resulting in efficient compression performance. Experimental results show that the average compression performance of the proposed algorithm is 10.48, 4.86, 3.58, and 0.10% better than that of JPEG 2000, CALIC, EDP, and JPEG-LS, respectively. Graphical abstract ᅟ.

  16. Adaptive optics fundus images of cone photoreceptors in the macula of patients with retinitis pigmentosa.

    PubMed

    Tojo, Naoki; Nakamura, Tomoko; Fuchizawa, Chiharu; Oiwake, Toshihiko; Hayashi, Atsushi

    2013-01-01

    The purpose of this study was to examine cone photoreceptors in the macula of patients with retinitis pigmentosa using an adaptive optics fundus camera and to investigate any correlations between cone photoreceptor density and findings on optical coherence tomography and fundus autofluorescence. We examined two patients with typical retinitis pigmentosa who underwent ophthalmological examination, including measurement of visual acuity, and gathering of electroretinographic, optical coherence tomographic, fundus autofluorescent, and adaptive optics fundus images. The cone photoreceptors in the adaptive optics images of the two patients with retinitis pigmentosa and five healthy subjects were analyzed. An abnormal parafoveal ring of high-density fundus autofluorescence was observed in the macula in both patients. The border of the ring corresponded to the border of the external limiting membrane and the inner segment and outer segment line in the optical coherence tomographic images. Cone photoreceptors at the abnormal parafoveal ring were blurred and decreased in the adaptive optics images. The blurred area corresponded to the abnormal parafoveal ring in the fundus autofluorescence images. Cone densities were low at the blurred areas and at the nasal and temporal retina along a line from the fovea compared with those of healthy controls. The results for cone spacing and Voronoi domains in the macula corresponded with those for the cone densities. Cone densities were heavily decreased in the macula, especially at the parafoveal ring on high-density fundus autofluorescence in both patients with retinitis pigmentosa. Adaptive optics images enabled us to observe in vivo changes in the cone photoreceptors of patients with retinitis pigmentosa, which corresponded to changes in the optical coherence tomographic and fundus autofluorescence images.

  17. Molecular PET imaging for biology-guided adaptive radiotherapy of head and neck cancer.

    PubMed

    Hoeben, Bianca A W; Bussink, Johan; Troost, Esther G C; Oyen, Wim J G; Kaanders, Johannes H A M

    2013-10-01

    Integration of molecular imaging PET techniques into therapy selection strategies and radiation treatment planning for head and neck squamous cell carcinoma (HNSCC) can serve several purposes. First, pre-treatment assessments can steer decisions about radiotherapy modifications or combinations with other modalities. Second, biology-based objective functions can be introduced to the radiation treatment planning process by co-registration of molecular imaging with planning computed tomography (CT) scans. Thus, customized heterogeneous dose distributions can be generated with escalated doses to tumor areas where radiotherapy resistance mechanisms are most prevalent. Third, monitoring of temporal and spatial variations in these radiotherapy resistance mechanisms early during the course of treatment can discriminate responders from non-responders. With such information available shortly after the start of treatment, modifications can be implemented or the radiation treatment plan can be adapted tailing the biological response pattern. Currently, these strategies are in various phases of clinical testing, mostly in single-center studies. Further validation in multicenter set-up is needed. Ultimately, this should result in availability for routine clinical practice requiring stable production and accessibility of tracers, reproducibility and standardization of imaging and analysis methods, as well as general availability of knowledge and expertise. Small studies employing adaptive radiotherapy based on functional dynamics and early response mechanisms demonstrate promising results. In this context, we focus this review on the widely used PET tracer (18)F-FDG and PET tracers depicting hypoxia and proliferation; two well-known radiation resistance mechanisms.

  18. Efficient visibility-driven medical image visualisation via adaptive binned visibility histogram.

    PubMed

    Jung, Younhyun; Kim, Jinman; Kumar, Ashnil; Feng, David Dagan; Fulham, Michael

    2016-07-01

    'Visibility' is a fundamental optical property that represents the observable, by users, proportion of the voxels in a volume during interactive volume rendering. The manipulation of this 'visibility' improves the volume rendering processes; for instance by ensuring the visibility of regions of interest (ROIs) or by guiding the identification of an optimal rendering view-point. The construction of visibility histograms (VHs), which represent the distribution of all the visibility of all voxels in the rendered volume, enables users to explore the volume with real-time feedback about occlusion patterns among spatially related structures during volume rendering manipulations. Volume rendered medical images have been a primary beneficiary of VH given the need to ensure that specific ROIs are visible relative to the surrounding structures, e.g. the visualisation of tumours that may otherwise be occluded by neighbouring structures. VH construction and its subsequent manipulations, however, are computationally expensive due to the histogram binning of the visibilities. This limits the real-time application of VH to medical images that have large intensity ranges and volume dimensions and require a large number of histogram bins. In this study, we introduce an efficient adaptive binned visibility histogram (AB-VH) in which a smaller number of histogram bins are used to represent the visibility distribution of the full VH. We adaptively bin medical images by using a cluster analysis algorithm that groups the voxels according to their intensity similarities into a smaller subset of bins while preserving the distribution of the intensity range of the original images. We increase efficiency by exploiting the parallel computation and multiple render targets (MRT) extension of the modern graphical processing units (GPUs) and this enables efficient computation of the histogram. We show the application of our method to single-modality computed tomography (CT), magnetic resonance

  19. Adaptive Optics Imaging Survey of Luminous Infrared Galaxies

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

    Laag, E A; Canalizo, G; van Breugel, W

    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 twomore » 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.« less

  20. Video image processing

    NASA Technical Reports Server (NTRS)

    Murray, N. D.

    1985-01-01

    Current technology projections indicate a lack of availability of special purpose computing for Space Station applications. Potential functions for video image special purpose processing are being investigated, such as smoothing, enhancement, restoration and filtering, data compression, feature extraction, object detection and identification, pixel interpolation/extrapolation, spectral estimation and factorization, and vision synthesis. Also, architectural approaches are being identified and a conceptual design generated. Computationally simple algorithms will be research and their image/vision effectiveness determined. Suitable algorithms will be implimented into an overall architectural approach that will provide image/vision processing at video rates that are flexible, selectable, and programmable. Information is given in the form of charts, diagrams and outlines.

  1. Face Adaptation Effects: Reviewing the Impact of Adapting Information, Time, and Transfer

    PubMed Central

    Strobach, Tilo; Carbon, Claus-Christian

    2013-01-01

    The ability to adapt is essential to live and survive in an ever-changing environment such as the human ecosystem. Here we review the literature on adaptation effects of face stimuli to give an overview of existing findings in this area, highlight gaps in its research literature, initiate new directions in face adaptation research, and help to design future adaptation studies. Furthermore, this review should lead to better understanding of the processing characteristics as well as the mental representations of face-relevant information. The review systematizes studies at a behavioral level in respect of a framework which includes three dimensions representing the major characteristics of studies in this field of research. These dimensions comprise (1) the specificity of adapting face information, e.g., identity, gender, or age aspects of the material to be adapted to (2) aspects of timing (e.g., the sustainability of adaptation effects) and (3) transfer relations between face images presented during adaptation and adaptation tests (e.g., images of the same or different identities). The review concludes with options for how to combine findings across different dimensions to demonstrate the relevance of our framework for future studies. PMID:23760550

  2. [Imaging center - optimization of the imaging process].

    PubMed

    Busch, H-P

    2013-04-01

    Hospitals around the world are under increasing pressure to optimize the economic efficiency of treatment processes. Imaging is responsible for a great part of the success but also of the costs of treatment. In routine work an excessive supply of imaging methods leads to an "as well as" strategy up to the limit of the capacity without critical reflection. Exams that have no predictable influence on the clinical outcome are an unjustified burden for the patient. They are useless and threaten the financial situation and existence of the hospital. In recent years the focus of process optimization was exclusively on the quality and efficiency of performed single examinations. In the future critical discussion of the effectiveness of single exams in relation to the clinical outcome will be more important. Unnecessary exams can be avoided, only if in addition to the optimization of single exams (efficiency) there is an optimization strategy for the total imaging process (efficiency and effectiveness). This requires a new definition of processes (Imaging Pathway), new structures for organization (Imaging Center) and a new kind of thinking on the part of the medical staff. Motivation has to be changed from gratification of performed exams to gratification of process quality (medical quality, service quality, economics), including the avoidance of additional (unnecessary) exams. © Georg Thieme Verlag KG Stuttgart · New York.

  3. 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.

  4. Fuzzy intelligent quality monitoring model for X-ray image processing.

    PubMed

    Khalatbari, Azadeh; Jenab, Kouroush

    2009-01-01

    Today's imaging diagnosis needs to adapt modern techniques of quality engineering to maintain and improve its accuracy and reliability in health care system. One of the main factors that influences diagnostic accuracy of plain film X-ray on detecting pathology is the level of film exposure. If the level of film exposure is not adequate, a normal body structure may be interpretated as pathology and vice versa. This not only influences the patient management but also has an impact on health care cost and patient's quality of life. Therefore, providing an accurate and high quality image is the first step toward an excellent patient management in any health care system. In this paper, we study these techniques and also present a fuzzy intelligent quality monitoring model, which can be used to keep variables from degrading the image quality. The variables derived from chemical activity, cleaning procedures, maintenance, and monitoring may not be sensed, measured, or calculated precisely due to uncertain situations. Therefore, the gamma-level fuzzy Bayesian model for quality monitoring of an image processing is proposed. In order to apply the Bayesian concept, the fuzzy quality characteristics are assumed as fuzzy random variables. Using the fuzzy quality characteristics, the newly developed model calculates the degradation risk for image processing. A numerical example is also presented to demonstrate the application of the model.

  5. ADAPTIVE OPTICS IMAGING OF FOVEAL SPARING IN GEOGRAPHIC ATROPHY SECONDARY TO AGE-RELATED MACULAR DEGENERATION.

    PubMed

    Querques, Giuseppe; Kamami-Levy, Cynthia; Georges, Anouk; Pedinielli, Alexandre; Capuano, Vittorio; Blanco-Garavito, Rocio; Poulon, Fanny; Souied, Eric H

    2016-02-01

    To describe adaptive optics (AO) imaging of foveal sparing in geographic atrophy (GA) secondary to age-related macular degeneration. Flood-illumination AO infrared (IR) fundus images were obtained in four consecutive patients with GA using an AO retinal camera (rtx1; Imagine Eyes). Adaptive optics IR images were overlaid with confocal scanning laser ophthalmoscope near-IR autofluorescence images to allow direct correlation of en face AO features with areas of foveal sparing. Adaptive optics appearance of GA and foveal sparing, preservation of functional photoreceptors, and cone densities in areas of foveal sparing were investigated. In 5 eyes of 4 patients (all female; mean age 74.2 ± 11.9 years), a total of 5 images, sized 4° × 4°, of foveal sparing visualized on confocal scanning laser ophthalmoscope near-IR autofluorescence were investigated by AO imaging. En face AO images revealed GA as regions of inhomogeneous hyperreflectivity with irregularly dispersed hyporeflective clumps. By direct comparison with adjacent regions of GA, foveal sparing appeared as well-demarcated areas of reduced reflectivity with less hyporeflective clumps (mean 14.2 vs. 3.2; P = 0.03). Of note, in these areas, en face AO IR images revealed cone photoreceptors as hyperreflective dots over the background reflectivity (mean cone density 3,271 ± 1,109 cones per square millimeter). Microperimetry demonstrated residual function in areas of foveal sparing detected by confocal scanning laser ophthalmoscope near-IR autofluorescence. Adaptive optics allows the appreciation of differences in reflectivity between regions of GA and foveal sparing. Preservation of functional cone photoreceptors was demonstrated on en face AO IR images in areas of foveal sparing detected by confocal scanning laser ophthalmoscope near-IR autofluorescence.

  6. Apple Image Processing Educator

    NASA Technical Reports Server (NTRS)

    Gunther, F. J.

    1981-01-01

    A software system design is proposed and demonstrated with pilot-project software. The system permits the Apple II microcomputer to be used for personalized computer-assisted instruction in the digital image processing of LANDSAT images. The programs provide data input, menu selection, graphic and hard-copy displays, and both general and detailed instructions. The pilot-project results are considered to be successful indicators of the capabilities and limits of microcomputers for digital image processing education.

  7. Image Processing Using a Parallel Architecture.

    DTIC Science & Technology

    1987-12-01

    ENG/87D-25 Abstract This study developed a set o± low level image processing tools on a parallel computer that allows concurrent processing of images...environment, the set of tools offers a significant reduction in the time required to perform some commonly used image processing operations. vI IMAGE...step toward developing these systems, a structured set of image processing tools was implemented using a parallel computer. More important than

  8. A photoacoustic imaging reconstruction method based on directional total variation with adaptive directivity.

    PubMed

    Wang, Jin; Zhang, Chen; Wang, Yuanyuan

    2017-05-30

    In photoacoustic tomography (PAT), total variation (TV) based iteration algorithm is reported to have a good performance in PAT image reconstruction. However, classical TV based algorithm fails to preserve the edges and texture details of the image because it is not sensitive to the direction of the image. Therefore, it is of great significance to develop a new PAT reconstruction algorithm to effectively solve the drawback of TV. In this paper, a directional total variation with adaptive directivity (DDTV) model-based PAT image reconstruction algorithm, which weightedly sums the image gradients based on the spatially varying directivity pattern of the image is proposed to overcome the shortcomings of TV. The orientation field of the image is adaptively estimated through a gradient-based approach. The image gradients are weighted at every pixel based on both its anisotropic direction and another parameter, which evaluates the estimated orientation field reliability. An efficient algorithm is derived to solve the iteration problem associated with DDTV and possessing directivity of the image adaptively updated for each iteration step. Several texture images with various directivity patterns are chosen as the phantoms for the numerical simulations. The 180-, 90- and 30-view circular scans are conducted. Results obtained show that the DDTV-based PAT reconstructed algorithm outperforms the filtered back-projection method (FBP) and TV algorithms in the quality of reconstructed images with the peak signal-to-noise rations (PSNR) exceeding those of TV and FBP by about 10 and 18 dB, respectively, for all cases. The Shepp-Logan phantom is studied with further discussion of multimode scanning, convergence speed, robustness and universality aspects. In-vitro experiments are performed for both the sparse-view circular scanning and linear scanning. The results further prove the effectiveness of the DDTV, which shows better results than that of the TV with sharper image edges and

  9. Highly undersampled MR image reconstruction using an improved dual-dictionary learning method with self-adaptive dictionaries.

    PubMed

    Li, Jiansen; Song, Ying; Zhu, Zhen; Zhao, Jun

    2017-05-01

    Dual-dictionary learning (Dual-DL) method utilizes both a low-resolution dictionary and a high-resolution dictionary, which are co-trained for sparse coding and image updating, respectively. It can effectively exploit a priori knowledge regarding the typical structures, specific features, and local details of training sets images. The prior knowledge helps to improve the reconstruction quality greatly. This method has been successfully applied in magnetic resonance (MR) image reconstruction. However, it relies heavily on the training sets, and dictionaries are fixed and nonadaptive. In this research, we improve Dual-DL by using self-adaptive dictionaries. The low- and high-resolution dictionaries are updated correspondingly along with the image updating stage to ensure their self-adaptivity. The updated dictionaries incorporate both the prior information of the training sets and the test image directly. Both dictionaries feature improved adaptability. Experimental results demonstrate that the proposed method can efficiently and significantly improve the quality and robustness of MR image reconstruction.

  10. Adaptive single-pixel imaging with aggregated sampling and continuous differential measurements

    NASA Astrophysics Data System (ADS)

    Huo, Yaoran; He, Hongjie; Chen, Fan; Tai, Heng-Ming

    2018-06-01

    This paper proposes an adaptive compressive imaging technique with one single-pixel detector and single arm. The aggregated sampling (AS) method enables the reduction of resolutions of the reconstructed images. It aims to reduce the time and space consumption. The target image with a resolution up to 1024 × 1024 can be reconstructed successfully at the 20% sampling rate. The continuous differential measurement (CDM) method combined with a ratio factor of significant coefficient (RFSC) improves the imaging quality. Moreover, RFSC reduces the human intervention in parameter setting. This technique enhances the practicability of single-pixel imaging with the benefits from less time and space consumption, better imaging quality and less human intervention.

  11. Single cell imaging of the chick retina with adaptive optics.

    PubMed

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

    2011-10-01

    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. The New England College of Optometry (NECO) AO fundus camera was modified to allow high resolution in vivo imaging on two 6-week-old White Leghorn chicks (Gallus gallus domesticus)-labeled chick A and chick B. Multiple, adjacent images, each with a 2.5(o) 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. In both chicks, cone photoreceptors were clearly visible at all retinal locations imaged. Cone densities measured at 36(o) nasal-12(o) superior retina from the pecten tip for chick A and 40(o) nasal-12(o) superior retina for chick B were 21,714 ± 543 and 26,105 ± 653 cones/mm(2) 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/mm(2). 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.

  12. High-resolution retinal imaging through open-loop adaptive optics

    NASA Astrophysics Data System (ADS)

    Li, Chao; Xia, Mingliang; Li, Dayu; Mu, Quanquan; Xuan, Li

    2010-07-01

    Using the liquid crystal spatial light modulator (LC-SLM) as the wavefront corrector, an open-loop adaptive optics (AO) system for fundus imaging in vivo is constructed. Compared with the LC-SLM closed-loop AO system, the light energy efficiency is increased by a factor of 2, which is helpful for the safety of fundus illumination in vivo. In our experiment, the subjective accommodation method is used to precorrect the defocus aberration, and three subjects with different myopia 0, -3, and -5 D are tested. Although the residual wavefront error after correction cannot to detected, the fundus images adequately demonstrate that the imaging system reaches the resolution of a single photoreceptor cell through the open-loop correction. Without dilating and cyclopleging the eye, the continuous imaging for 8 s is recorded for one of the subjects.

  13. Amplitude image processing by diffractive optics.

    PubMed

    Cagigal, Manuel P; Valle, Pedro J; Canales, V F

    2016-02-22

    In contrast to the standard digital image processing, which operates over the detected image intensity, we propose to perform amplitude image processing. Amplitude processing, like low pass or high pass filtering, is carried out using diffractive optics elements (DOE) since it allows to operate over the field complex amplitude before it has been detected. We show the procedure for designing the DOE that corresponds to each operation. Furthermore, we accomplish an analysis of amplitude image processing performances. In particular, a DOE Laplacian filter is applied to simulated astronomical images for detecting two stars one Airy ring apart. We also check by numerical simulations that the use of a Laplacian amplitude filter produces less noisy images than the standard digital image processing.

  14. Method of Improved Fuzzy Contrast Combined Adaptive Threshold in NSCT for Medical Image Enhancement

    PubMed Central

    Yang, Jie; Kasabov, Nikola

    2017-01-01

    Noises and artifacts are introduced to medical images due to acquisition techniques and systems. This interference leads to low contrast and distortion in images, which not only impacts the effectiveness of the medical image but also seriously affects the clinical diagnoses. This paper proposes an algorithm for medical image enhancement based on the nonsubsampled contourlet transform (NSCT), which combines adaptive threshold and an improved fuzzy set. First, the original image is decomposed into the NSCT domain with a low-frequency subband and several high-frequency subbands. Then, a linear transformation is adopted for the coefficients of the low-frequency component. An adaptive threshold method is used for the removal of high-frequency image noise. Finally, the improved fuzzy set is used to enhance the global contrast and the Laplace operator is used to enhance the details of the medical images. Experiments and simulation results show that the proposed method is superior to existing methods of image noise removal, improves the contrast of the image significantly, and obtains a better visual effect. PMID:28744464

  15. Combining image-processing and image compression schemes

    NASA Technical Reports Server (NTRS)

    Greenspan, H.; Lee, M.-C.

    1995-01-01

    An investigation into the combining of image-processing schemes, specifically an image enhancement scheme, with existing compression schemes is discussed. Results are presented on the pyramid coding scheme, the subband coding scheme, and progressive transmission. Encouraging results are demonstrated for the combination of image enhancement and pyramid image coding schemes, especially at low bit rates. Adding the enhancement scheme to progressive image transmission allows enhanced visual perception at low resolutions. In addition, further progressing of the transmitted images, such as edge detection schemes, can gain from the added image resolution via the enhancement.

  16. Long-term imaging of mouse embryos using adaptive harmonic generation microscopy

    NASA Astrophysics Data System (ADS)

    Thayil, Anisha; Watanabe, Tomoko; Jesacher, Alexander; Wilson, Tony; Srinivas, Shankar; Booth, Martin

    2011-04-01

    We present a detailed description of an adaptive harmonic generation (HG) microscope and culture techniques that permit long-term, three-dimensional imaging of mouse embryos. HG signal from both pre- and postimplantation stage (0.5-5.5 day-old) mouse embryos are fully characterized. The second HG images reveal central spindles during cytokinesis whereas third HG images show several features, such as lipid droplets, nucleoli, and plasma membranes. The embryos are found to develop normally during one-day-long discontinuous HG imaging, permitting the observation of several dynamic events, such as morula compaction and blastocyst formation.

  17. Deep neural network-based domain adaptation for classification of remote sensing images

    NASA Astrophysics Data System (ADS)

    Ma, Li; Song, Jiazhen

    2017-10-01

    We investigate the effectiveness of deep neural network for cross-domain classification of remote sensing images in this paper. In the network, class centroid alignment is utilized as a domain adaptation strategy, making the network able to transfer knowledge from the source domain to target domain on a per-class basis. Since predicted labels of target data should be used to estimate the centroid of each class, we use overall centroid alignment as a coarse domain adaptation method to improve the estimation accuracy. In addition, rectified linear unit is used as the activation function to produce sparse features, which may improve the separation capability. The proposed network can provide both aligned features and an adaptive classifier, as well as obtain label-free classification of target domain data. The experimental results using Hyperion, NCALM, and WorldView-2 remote sensing images demonstrated the effectiveness of the proposed approach.

  18. Adaptive Constructive Processes and the Future of Memory

    ERIC Educational Resources Information Center

    Schacter, Daniel L.

    2012-01-01

    Memory serves critical functions in everyday life but is also prone to error. This article examines adaptive constructive processes, which play a functional role in memory and cognition but can also produce distortions, errors, and illusions. The article describes several types of memory errors that are produced by adaptive constructive processes…

  19. Process- and controller-adaptations determine the physiological effects of cold acclimation.

    PubMed

    Werner, Jürgen

    2008-09-01

    Experimental results on physiological effects of cold adaptation seem confusing and apparently incompatible with one another. This paper will explain that a substantial part of such a variety of results may be deduced from a common functional concept. A core/shell treatment ("model") of the thermoregulatory system is used with mean body temperature as the controlled variable. Adaptation, as a higher control level, is introduced into the system. Due to persistent stressors, either the (heat transfer) process or the controller properties (parameters) are adjusted (or both). It is convenient to call the one "process adaptation" and the other "controller adaptation". The most commonly demonstrated effect of autonomic cold acclimation is a change in the controller threshold. The analysis shows that this necessarily means a lowering of body temperature because of a lowered metabolic rate. This explains experimental results on both Europeans in the climatic chamber and Australian Aborigines in a natural environment. Exclusive autonomic process adaptation occurs in the form of a better insulation. The analysis explains why the post-adaptive steady-state can only be achieved, if the controller system reduces metabolism and why in spite of this the new state is inevitably characterized by a rise in body temperature. If both process and controller adaptations are simultaneously present, there may be not any change of body temperature at all, e.g., as demonstrated in animal experiments. Whether this kind of adaptation delivers a decrease, an increase or no change of mean body temperature, depends on the proportion of process and controller adaptation.

  20. Image processing mini manual

    NASA Technical Reports Server (NTRS)

    Matthews, Christine G.; Posenau, Mary-Anne; Leonard, Desiree M.; Avis, Elizabeth L.; Debure, Kelly R.; Stacy, Kathryn; Vonofenheim, Bill

    1992-01-01

    The intent is to provide an introduction to the image processing capabilities available at the Langley Research Center (LaRC) Central Scientific Computing Complex (CSCC). Various image processing software components are described. Information is given concerning the use of these components in the Data Visualization and Animation Laboratory at LaRC.

  1. Multilevel processes and cultural adaptation: Examples from past and present small-scale societies.

    PubMed

    Reyes-García, V; Balbo, A L; Gomez-Baggethun, E; Gueze, M; Mesoudi, A; Richerson, P; Rubio-Campillo, X; Ruiz-Mallén, I; Shennan, S

    2016-12-01

    Cultural adaptation has become central in the context of accelerated global change with authors increasingly acknowledging the importance of understanding multilevel processes that operate as adaptation takes place. We explore the importance of multilevel processes in explaining cultural adaptation by describing how processes leading to cultural (mis)adaptation are linked through a complex nested hierarchy, where the lower levels combine into new units with new organizations, functions, and emergent properties or collective behaviours. After a brief review of the concept of "cultural adaptation" from the perspective of cultural evolutionary theory and resilience theory, the core of the paper is constructed around the exploration of multilevel processes occurring at the temporal, spatial, social and political scales. We do so by examining small-scale societies' case studies. In each section, we discuss the importance of the selected scale for understanding cultural adaptation and then present an example that illustrates how multilevel processes in the selected scale help explain observed patterns in the cultural adaptive process. We end the paper discussing the potential of modelling and computer simulation for studying multilevel processes in cultural adaptation.

  2. 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

  3. Processing of NiTi Reinforced Adaptive Solder for Electronic Packaging

    DTIC Science & Technology

    2004-03-01

    NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS PROCESSING OF NITI REINFORCED ADAPTIVE SOLDER FOR ELECTRONIC PACKAGING...March 2004 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE: Processing of NiTi Reinforced Adaptive Solder for Electronic...reports in the development a process to fabricate solder joints with a fine distribution of shape memory alloys (SMA) NiTi particulates. The

  4. Astronomical Image Processing with Hadoop

    NASA Astrophysics Data System (ADS)

    Wiley, K.; Connolly, A.; Krughoff, S.; Gardner, J.; Balazinska, M.; Howe, B.; Kwon, Y.; Bu, Y.

    2011-07-01

    In the coming decade astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. With a requirement that these images be analyzed in real time to identify moving sources such as potentially hazardous asteroids or transient objects such as supernovae, these data streams present many computational challenges. In the commercial world, new techniques that utilize cloud computing have been developed to handle massive data streams. In this paper we describe how cloud computing, and in particular the map-reduce paradigm, can be used in astronomical data processing. We will focus on our experience implementing a scalable image-processing pipeline for the SDSS database using Hadoop (http://hadoop.apache.org). This multi-terabyte imaging dataset approximates future surveys such as those which will be conducted with the LSST. Our pipeline performs image coaddition in which multiple partially overlapping images are registered, integrated and stitched into a single overarching image. We will first present our initial implementation, then describe several critical optimizations that have enabled us to achieve high performance, and finally describe how we are incorporating a large in-house existing image processing library into our Hadoop system. The optimizations involve prefiltering of the input to remove irrelevant images from consideration, grouping individual FITS files into larger, more efficient indexed files, and a hybrid system in which a relational database is used to determine the input images relevant to the task. The incorporation of an existing image processing library, written in C++, presented difficult challenges since Hadoop is programmed primarily in Java. We will describe how we achieved this integration and the sophisticated image processing routines that were made feasible as a result. We will end by briefly describing the longer term goals of our work, namely detection and classification

  5. Multiscale Image Processing of Solar Image Data

    NASA Astrophysics Data System (ADS)

    Young, C.; Myers, D. C.

    2001-12-01

    It is often said that the blessing and curse of solar physics is too much data. Solar missions such as Yohkoh, SOHO and TRACE have shown us the Sun with amazing clarity but have also increased the amount of highly complex data. We have improved our view of the Sun yet we have not improved our analysis techniques. The standard techniques used for analysis of solar images generally consist of observing the evolution of features in a sequence of byte scaled images or a sequence of byte scaled difference images. The determination of features and structures in the images are done qualitatively by the observer. There is little quantitative and objective analysis done with these images. Many advances in image processing techniques have occured in the past decade. Many of these methods are possibly suited for solar image analysis. Multiscale/Multiresolution methods are perhaps the most promising. These methods have been used to formulate the human ability to view and comprehend phenomena on different scales. So these techniques could be used to quantitify the imaging processing done by the observers eyes and brains. In this work we present several applications of multiscale techniques applied to solar image data. Specifically, we discuss uses of the wavelet, curvelet, and related transforms to define a multiresolution support for EIT, LASCO and TRACE images.

  6. Personal computer (PC) based image processing applied to fluid mechanics research

    NASA Technical Reports Server (NTRS)

    Cho, Y.-C.; Mclachlan, B. G.

    1987-01-01

    A PC based image processing system was employed to determine the instantaneous velocity field of a two-dimensional unsteady flow. The flow was visualized using a suspension of seeding particles in water, and a laser sheet for illumination. With a finite time exposure, the particle motion was captured on a photograph as a pattern of streaks. The streak pattern was digitized and processsed using various imaging operations, including contrast manipulation, noise cleaning, filtering, statistical differencing, and thresholding. Information concerning the velocity was extracted from the enhanced image by measuring the length and orientation of the individual streaks. The fluid velocities deduced from the randomly distributed particle streaks were interpolated to obtain velocities at uniform grid points. For the interpolation a simple convolution technique with an adaptive Gaussian window was used. The results are compared with a numerical prediction by a Navier-Stokes commputation.

  7. Bayesian nonparametric adaptive control using Gaussian processes.

    PubMed

    Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A

    2015-03-01

    Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.

  8. Adaptive polarization image fusion based on regional energy dynamic weighted average

    NASA Astrophysics Data System (ADS)

    Zhao, Yong-Qiang; Pan, Quan; Zhang, Hong-Cai

    2005-11-01

    According to the principle of polarization imaging and the relation between Stokes parameters and the degree of linear polarization, there are much redundant and complementary information in polarized images. Since man-made objects and natural objects can be easily distinguished in images of degree of linear polarization and images of Stokes parameters contain rich detailed information of the scene, the clutters in the images can be removed efficiently while the detailed information can be maintained by combining these images. An algorithm of adaptive polarization image fusion based on regional energy dynamic weighted average is proposed in this paper to combine these images. Through an experiment and simulations, most clutters are removed by this algorithm. The fusion method is used for different light conditions in simulation, and the influence of lighting conditions on the fusion results is analyzed.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  10. Adaptive automation of human-machine system information-processing functions.

    PubMed

    Kaber, David B; Wright, Melanie C; Prinzel, Lawrence J; Clamann, Michael P

    2005-01-01

    The goal of this research was to describe the ability of human operators to interact with adaptive automation (AA) applied to various stages of complex systems information processing, defined in a model of human-automation interaction. Forty participants operated a simulation of an air traffic control task. Automated assistance was adaptively applied to information acquisition, information analysis, decision making, and action implementation aspects of the task based on operator workload states, which were measured using a secondary task. The differential effects of the forms of automation were determined and compared with a manual control condition. Results of two 20-min trials of AA or manual control revealed a significant effect of the type of automation on performance, particularly during manual control periods as part of the adaptive conditions. Humans appear to better adapt to AA applied to sensory and psychomotor information-processing functions (action implementation) than to AA applied to cognitive functions (information analysis and decision making), and AA is superior to completely manual control. Potential applications of this research include the design of automation to support air traffic controller information processing.

  11. A design of real time image capturing and processing system using Texas Instrument's processor

    NASA Astrophysics Data System (ADS)

    Wee, Toon-Joo; Chaisorn, Lekha; Rahardja, Susanto; Gan, Woon-Seng

    2007-09-01

    In this work, we developed and implemented an image capturing and processing system that equipped with capability of capturing images from an input video in real time. The input video can be a video from a PC, video camcorder or DVD player. We developed two modes of operation in the system. In the first mode, an input image from the PC is processed on the processing board (development platform with a digital signal processor) and is displayed on the PC. In the second mode, current captured image from the video camcorder (or from DVD player) is processed on the board but is displayed on the LCD monitor. The major difference between our system and other existing conventional systems is that image-processing functions are performed on the board instead of the PC (so that the functions can be used for further developments on the board). The user can control the operations of the board through the Graphic User Interface (GUI) provided on the PC. In order to have a smooth image data transfer between the PC and the board, we employed Real Time Data Transfer (RTDX TM) technology to create a link between them. For image processing functions, we developed three main groups of function: (1) Point Processing; (2) Filtering and; (3) 'Others'. Point Processing includes rotation, negation and mirroring. Filter category provides median, adaptive, smooth and sharpen filtering in the time domain. In 'Others' category, auto-contrast adjustment, edge detection, segmentation and sepia color are provided, these functions either add effect on the image or enhance the image. We have developed and implemented our system using C/C# programming language on TMS320DM642 (or DM642) board from Texas Instruments (TI). The system was showcased in College of Engineering (CoE) exhibition 2006 at Nanyang Technological University (NTU) and have more than 40 users tried our system. It is demonstrated that our system is adequate for real time image capturing. Our system can be used or applied for

  12. Performance evaluation of spatial compounding in the presence of aberration and adaptive imaging

    NASA Astrophysics Data System (ADS)

    Dahl, Jeremy J.; Guenther, Drake; Trahey, Gregg E.

    2003-05-01

    Spatial compounding has been used for years to reduce speckle in ultrasonic images and to resolve anatomical features hidden behind the grainy appearance of speckle. Adaptive imaging restores image contrast and resolution by compensating for beamforming errors caused by tissue-induced phase errors. Spatial compounding represents a form of incoherent imaging, whereas adaptive imaging attempts to maintain a coherent, diffraction-limited aperture in the presence of aberration. Using a Siemens Antares scanner, we acquired single channel RF data on a commercially available 1-D probe. Individual channel RF data was acquired on a cyst phantom in the presence of a near field electronic phase screen. Simulated data was also acquired for both a 1-D and a custom built 8x96, 1.75-D probe (Tetrad Corp.). The data was compounded using a receive spatial compounding algorithm; a widely used algorithm because it takes advantage of parallel beamforming to avoid reductions in frame rate. Phase correction was also performed by using a least mean squares algorithm to estimate the arrival time errors. We present simulation and experimental data comparing the performance of spatial compounding to phase correction in contrast and resolution tasks. We evaluate spatial compounding and phase correction, and combinations of the two methods, under varying aperture sizes, aperture overlaps, and aberrator strength to examine the optimum configuration and conditions in which spatial compounding will provide a similar or better result than adaptive imaging. We find that, in general, phase correction is hindered at high aberration strengths and spatial frequencies, whereas spatial compounding is helped by these aberrators.

  13. Adaptation as process: the future of Darwinism and the legacy of Theodosius Dobzhansky.

    PubMed

    Depew, David J

    2011-03-01

    Conceptions of adaptation have varied in the history of genetic Darwinism depending on whether what is taken to be focal is the process of adaptation, adapted states of populations, or discrete adaptations in individual organisms. I argue that Theodosius Dobzhansky's view of adaptation as a dynamical process contrasts with so-called "adaptationist" views of natural selection figured as "design-without-a-designer" of relatively discrete, enumerable adaptations. Correlated with these respectively process and product oriented approaches to adaptive natural selection are divergent pictures of organisms themselves as developmental wholes or as "bundles" of adaptations. While even process versions of genetical Darwinism are insufficiently sensitive to the fact much of the variation on which adaptive selection works consists of changes in the timing, rate, or location of ontogenetic events, I argue that articulations of the Modern Synthesis influenced by Dobzhansky are more easily reconciled with the recent shift to evolutionary developmentalism than are versions that make discrete adaptations central. Copyright © 2010 Elsevier Ltd. All rights reserved.

  14. Integration and Evaluation of Microscope Adapter for the Ultra-Compact Imaging Spectrometer

    NASA Astrophysics Data System (ADS)

    Smith-Dryden, S. D.; Blaney, D. L.; Van Gorp, B.; Mouroulis, P.; Green, R. O.; Sellar, R. G.; Rodriguez, J.; Wilson, D.

    2012-12-01

    Petrologic, diagenetic, impact and weathering processes often happen at scales that are not observable from orbit. On Earth, one of the most common things that a scientist does when trying to understand detailed geologic history is to create a thin section of the rock and study the mineralogy and texture. Unfortunately, sample preparation and manipulation with advanced instrumentation may be a resource intensive proposition (e.g. time, power, complexity) in-situ. Getting detailed mineralogy and textural information without sample preparation is highly desirable. Visible to short wavelength microimaging spectroscopy has the potential to provide this information without sample preparation. Wavelengths between 500-2600 nm are sensitive to a wide range of minerals including mafic, carbonates, clays, and sulfates. The Ultra-Compact Imaging Spectrometer (UCIS) has been developed as a low mass (<2.0 kg), low power (~5.2 W) Offner spectrometer, ideal for use on Mars rover or other in-situ platforms. The UCIS instrument with its HgCdTe detector provides a spectral resolution of 10 nm with a range of 500-2600 nm, in addition to a 30 degree field of view and a 1.35 mrad instantaneous field of view. (Van Gorp et al. 2011). To explore applications of this technology for microscale investigations, an f/10 microimaging adapter has been designed and integrated to allow imaging of samples. The spatial coverage of the instrument is 2.56 cm with sampling of 67.5 microns (380 spatial pixels). Because the adapter is slow relative to the UCIS detector, strong sample illumination is required. Light from the lamp box was directed through optical fiber bundles, and directed onto the sample at a high angle of incidence to provide dark field imaging. For data collection, a mineral sample is mounted on the microscope adapter and scanned by the detector as it is moved horizontally via actuator. Data from the instrument is stored as a xyz cube end product with one spectral and two spatial

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

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

    Paganelli, Chiara; Peroni, Marta; Baroni, Guido

    2013-11-15

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

  16. A novel speckle pattern—Adaptive digital image correlation approach with robust strain calculation

    NASA Astrophysics Data System (ADS)

    Cofaru, Corneliu; Philips, Wilfried; Van Paepegem, Wim

    2012-02-01

    Digital image correlation (DIC) has seen widespread acceptance and usage as a non-contact method for the determination of full-field displacements and strains in experimental mechanics. The advances of imaging hardware in the last decades led to high resolution and speed cameras being more affordable than in the past making large amounts of data image available for typical DIC experimental scenarios. The work presented in this paper is aimed at maximizing both the accuracy and speed of DIC methods when employed with such images. A low-level framework for speckle image partitioning which replaces regularly shaped blocks with image-adaptive cells in the displacement calculation is introduced. The Newton-Raphson DIC method is modified to use the image pixels of the cells and to perform adaptive regularization to increase the spatial consistency of the displacements. Furthermore, a novel robust framework for strain calculation based also on the Newton-Raphson algorithm is introduced. The proposed methods are evaluated in five experimental scenarios, out of which four use numerically deformed images and one uses real experimental data. Results indicate that, as the desired strain density increases, significant computational gains can be obtained while maintaining or improving accuracy and rigid-body rotation sensitivity.

  17. Adaptive removal of background and white space from document images using seam categorization

    NASA Astrophysics Data System (ADS)

    Fillion, Claude; Fan, Zhigang; Monga, Vishal

    2011-03-01

    Document images are obtained regularly by rasterization of document content and as scans of printed documents. Resizing via background and white space removal is often desired for better consumption of these images, whether on displays or in print. While white space and background are easy to identify in images, existing methods such as naïve removal and content aware resizing (seam carving) each have limitations that can lead to undesirable artifacts, such as uneven spacing between lines of text or poor arrangement of content. An adaptive method based on image content is hence needed. In this paper we propose an adaptive method to intelligently remove white space and background content from document images. Document images are different from pictorial images in structure. They typically contain objects (text letters, pictures and graphics) separated by uniform background, which include both white paper space and other uniform color background. Pixels in uniform background regions are excellent candidates for deletion if resizing is required, as they introduce less change in document content and style, compared with deletion of object pixels. We propose a background deletion method that exploits both local and global context. The method aims to retain the document structural information and image quality.

  18. Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications

    PubMed Central

    Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

    2017-01-01

    Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC. PMID:29280970

  19. Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications.

    PubMed

    Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

    2017-12-27

    Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.

  20. Wavefront sensorless adaptive optics OCT with the DONE algorithm for in vivo human retinal imaging [Invited].

    PubMed

    Verstraete, Hans R G W; Heisler, Morgan; Ju, Myeong Jin; Wahl, Daniel; Bliek, Laurens; Kalkman, Jeroen; Bonora, Stefano; Jian, Yifan; Verhaegen, Michel; Sarunic, Marinko V

    2017-04-01

    In this report, which is an international collaboration of OCT, adaptive optics, and control research, we demonstrate the Data-based Online Nonlinear Extremum-seeker (DONE) algorithm to guide the image based optimization for wavefront sensorless adaptive optics (WFSL-AO) OCT for in vivo human retinal imaging. The ocular aberrations were corrected using a multi-actuator adaptive lens after linearization of the hysteresis in the piezoelectric actuators. The DONE algorithm succeeded in drastically improving image quality and the OCT signal intensity, up to a factor seven, while achieving a computational time of 1 ms per iteration, making it applicable for many high speed applications. We demonstrate the correction of five aberrations using 70 iterations of the DONE algorithm performed over 2.8 s of continuous volumetric OCT acquisition. Data acquired from an imaging phantom and in vivo from human research volunteers are presented.

  1. Fast Image Restoration for Spatially Varying Defocus Blur of Imaging Sensor

    PubMed Central

    Cheong, Hejin; Chae, Eunjung; Lee, Eunsung; Jo, Gwanghyun; Paik, Joonki

    2015-01-01

    This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive image restoration by selecting the optimal restoration filter according to the estimated blur parameters. Each restoration filter is implemented in the form of a combination of multiple FIR filters, which guarantees the fast image restoration without the need of iterative or recursive processing. Experimental results show that the proposed method outperforms existing space-invariant restoration methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed to a wide area of image restoration applications, such as mobile imaging devices, robot vision, and satellite image processing. PMID:25569760

  2. A 176×144 148dB adaptive tone-mapping imager

    NASA Astrophysics Data System (ADS)

    Vargas-Sierra, S.; Liñán-Cembrano, G.; Rodríguez-Vázquez, A.

    2012-03-01

    This paper presents a 176x144 (QCIF) HDR image sensor where visual information is simultaneously captured and adaptively compressed by means of an in-pixel tone mapping scheme. The tone mapping curve (TMC) is calculated from the histogram of a Time Stamp image captured in the previous frame, which serves as a probability indicator of the distribution of illuminations within the present frame. The chip produces 7-bit/pixel images that can map illuminations from 311μlux to 55.3 klux in a single frame in a way that each pixel decides when to stop observing photocurrent integration -with extreme values captured at 8s and 2.34μs respectively. Pixels size is 33x33μm2, which includes a 3x3μm2 Nwell- Psubstrate photodiode and an autozeroing technique for establishing the reset voltage, which cancels most of the offset contributions created by the analog processing circuitry. Dark signal (10.8 mV/s ) effects in the final image are attenuated by an automatic programming of the DAC top voltage. Measured characteristics are Sensitivity 5.79 V/lux.s , FWC 12.2ke-, Conversion Factor 129(e-/DN), and Read Noise 25e-. The chip has been designed in the 0.35μm OPTO technology from Austriamicrosystems (AMS). Due to the focal plane operation, this architecture is especially well suited to be implemented in a 3D (vertical stacking) technology using per-pixel TSVs.

  3. High Tech Aids Low Vision: A Review of Image Processing for the Visually Impaired.

    PubMed

    Moshtael, Howard; Aslam, Tariq; Underwood, Ian; Dhillon, Baljean

    2015-08-01

    Recent advances in digital image processing provide promising methods for maximizing the residual vision of the visually impaired. This paper seeks to introduce this field to the readership and describe its current state as found in the literature. A systematic search revealed 37 studies that measure the value of image processing techniques for subjects with low vision. The techniques used are categorized according to their effect and the principal findings are summarized. The majority of participants preferred enhanced images over the original for a wide range of enhancement types. Adapting the contrast and spatial frequency content often improved performance at object recognition and reading speed, as did techniques that attenuate the image background and a technique that induced jitter. A lack of consistency in preference and performance measures was found, as well as a lack of independent studies. Nevertheless, the promising results should encourage further research in order to allow their widespread use in low-vision aids.

  4. Improving the quality of reconstructed X-ray CT images of polymer gel dosimeters: zero-scan coupled with adaptive mean filtering.

    PubMed

    Kakakhel, M B; Jirasek, A; Johnston, H; Kairn, T; Trapp, J V

    2017-03-01

    This study evaluated the feasibility of combining the 'zero-scan' (ZS) X-ray computed tomography (CT) based polymer gel dosimeter (PGD) readout with adaptive mean (AM) filtering for improving the signal to noise ratio (SNR), and to compare these results with available average scan (AS) X-ray CT readout techniques. NIPAM PGD were manufactured, irradiated with 6 MV photons, CT imaged and processed in Matlab. AM filter for two iterations, with 3 × 3 and 5 × 5 pixels (kernel size), was used in two scenarios (a) the CT images were subjected to AM filtering (pre-processing) and these were further employed to generate AS and ZS gel images, and (b) the AS and ZS images were first reconstructed from the CT images and then AM filtering was carried out (post-processing). SNR was computed in an ROI of 30 × 30 for different pre and post processing cases. Results showed that the ZS technique combined with AM filtering resulted in improved SNR. Using the previously-recommended 25 images for reconstruction the ZS pre-processed protocol can give an increase of 44% and 80% in SNR for 3 × 3 and 5 × 5 kernel sizes respectively. However, post processing using both techniques and filter sizes introduced blur and a reduction in the spatial resolution. Based on this work, it is possible to recommend that the ZS method may be combined with pre-processed AM filtering using appropriate kernel size, to produce a large increase in the SNR of the reconstructed PGD images.

  5. Novel Multistatic Adaptive Microwave Imaging Methods for Early Breast Cancer Detection

    NASA Astrophysics Data System (ADS)

    Xie, Yao; Guo, Bin; Li, Jian; Stoica, Petre

    2006-12-01

    Multistatic adaptive microwave imaging (MAMI) methods are presented and compared for early breast cancer detection. Due to the significant contrast between the dielectric properties of normal and malignant breast tissues, developing microwave imaging techniques for early breast cancer detection has attracted much interest lately. MAMI is one of the microwave imaging modalities and employs multiple antennas that take turns to transmit ultra-wideband (UWB) pulses while all antennas are used to receive the reflected signals. MAMI can be considered as a special case of the multi-input multi-output (MIMO) radar with the multiple transmitted waveforms being either UWB pulses or zeros. Since the UWB pulses transmitted by different antennas are displaced in time, the multiple transmitted waveforms are orthogonal to each other. The challenge to microwave imaging is to improve resolution and suppress strong interferences caused by the breast skin, nipple, and so forth. The MAMI methods we investigate herein utilize the data-adaptive robust Capon beamformer (RCB) to achieve high resolution and interference suppression. We will demonstrate the effectiveness of our proposed methods for breast cancer detection via numerical examples with data simulated using the finite-difference time-domain method based on a 3D realistic breast model.

  6. Image sensor system with bio-inspired efficient coding and adaptation.

    PubMed

    Okuno, Hirotsugu; Yagi, Tetsuya

    2012-08-01

    We designed and implemented an image sensor system equipped with three bio-inspired coding and adaptation strategies: logarithmic transform, local average subtraction, and feedback gain control. The system comprises a field-programmable gate array (FPGA), a resistive network, and active pixel sensors (APS), whose light intensity-voltage characteristics are controllable. The system employs multiple time-varying reset voltage signals for APS in order to realize multiple logarithmic intensity-voltage characteristics, which are controlled so that the entropy of the output image is maximized. The system also employs local average subtraction and gain control in order to obtain images with an appropriate contrast. The local average is calculated by the resistive network instantaneously. The designed system was successfully used to obtain appropriate images of objects that were subjected to large changes in illumination.

  7. Online Magnetic Resonance Image Guided Adaptive Radiation Therapy: First Clinical Applications

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

    Acharya, Sahaja; Fischer-Valuck, Benjamin W.; Kashani, Rojano

    Purpose: To demonstrate the feasibility of online adaptive magnetic resonance (MR) image guided radiation therapy (MR-IGRT) through reporting of our initial clinical experience and workflow considerations. Methods and Materials: The first clinically deployed online adaptive MR-IGRT system consisted of a split 0.35T MR scanner straddling a ring gantry with 3 multileaf collimator-equipped {sup 60}Co heads. The unit is supported by a Monte Carlo–based treatment planning system that allows real-time adaptive planning with the patient on the table. All patients undergo computed tomography and MR imaging (MRI) simulation for initial treatment planning. A volumetric MRI scan is acquired for each patient atmore » the daily treatment setup. Deformable registration is performed using the planning computed tomography data set, which allows for the transfer of the initial contours and the electron density map to the daily MRI scan. The deformed electron density map is then used to recalculate the original plan on the daily MRI scan for physician evaluation. Recontouring and plan reoptimization are performed when required, and patient-specific quality assurance (QA) is performed using an independent in-house software system. Results: The first online adaptive MR-IGRT treatments consisted of 5 patients with abdominopelvic malignancies. The clinical setting included neoadjuvant colorectal (n=3), unresectable gastric (n=1), and unresectable pheochromocytoma (n=1). Recontouring and reoptimization were deemed necessary for 3 of 5 patients, and the initial plan was deemed sufficient for 2 of the 5 patients. The reasons for plan adaptation included tumor progression or regression and a change in small bowel anatomy. In a subsequently expanded cohort of 170 fractions (20 patients), 52 fractions (30.6%) were reoptimized online, and 92 fractions (54.1%) were treated with an online-adapted or previously adapted plan. The median time for recontouring, reoptimization, and QA was 26

  8. Adapting clinical practice guidelines for diabetic retinopathy in Kenya: process and outputs.

    PubMed

    Mwangi, Nyawira; Gachago, Muchai; Gichangi, Michael; Gichuhi, Stephen; Githeko, Kibata; Jalango, Atieno; Karimurio, Jefitha; Kibachio, Joseph; Muthami, Lawrence; Ngugi, Nancy; Nduri, Carmichael; Nyaga, Patrick; Nyamori, Joseph; Zindamoyen, Alain Nazaire Mbongo; Bascaran, Covadonga; Foster, Allen

    2018-06-15

    The use of clinical practice guidelines envisages augmenting quality and best practice in clinical outcomes. Generic guidelines that are not adapted for local use often fail to produce these outcomes. Adaptation is a systematic and rigorous process that should maintain the quality and validity of the guideline, while making it more usable by the targeted users. Diverse skills are required for the task of adaptation. Although adapting a guideline is not a guarantee that it will be implemented, adaptation may improve acceptance and adherence to its recommendations. We describe the process used to adapt clinical guidelines for diabetic retinopathy in Kenya, using validated tools and manuals. A technical working group consisting of volunteers provided leadership. The process was intensive and required more time than anticipated. Flexibility in the process and concurrent health system activities contributed to the success of the adaptation. The outputs from the adaptation include the guidelines in different formats, point of care instruments, as well as tools for training, monitoring, quality assurance and patient education. Guideline adaptation is applicable and feasible at the national level in Kenya. However, it is labor- and time -intensive. It presents a valuable opportunity to develop several additional outputs that are useful at the point of care.

  9. Wavefront sensorless adaptive optics OCT with the DONE algorithm for in vivo human retinal imaging [Invited

    PubMed Central

    Verstraete, Hans R. G. W.; Heisler, Morgan; Ju, Myeong Jin; Wahl, Daniel; Bliek, Laurens; Kalkman, Jeroen; Bonora, Stefano; Jian, Yifan; Verhaegen, Michel; Sarunic, Marinko V.

    2017-01-01

    In this report, which is an international collaboration of OCT, adaptive optics, and control research, we demonstrate the Data-based Online Nonlinear Extremum-seeker (DONE) algorithm to guide the image based optimization for wavefront sensorless adaptive optics (WFSL-AO) OCT for in vivo human retinal imaging. The ocular aberrations were corrected using a multi-actuator adaptive lens after linearization of the hysteresis in the piezoelectric actuators. The DONE algorithm succeeded in drastically improving image quality and the OCT signal intensity, up to a factor seven, while achieving a computational time of 1 ms per iteration, making it applicable for many high speed applications. We demonstrate the correction of five aberrations using 70 iterations of the DONE algorithm performed over 2.8 s of continuous volumetric OCT acquisition. Data acquired from an imaging phantom and in vivo from human research volunteers are presented. PMID:28736670

  10. A Feedfordward Adaptive Controller to Reduce the Imaging Time of Large-Sized Biological Samples with a SPM-Based Multiprobe Station

    PubMed Central

    Otero, Jorge; Guerrero, Hector; Gonzalez, Laura; Puig-Vidal, Manel

    2012-01-01

    The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on bang-bang and adaptive controls. The controls are based in the difference between the maximum speeds that can be used for imaging depending on the flatness of the sample zone. Topographic images of Escherichia coli bacteria samples were acquired using the implemented controllers. Results show that to go faster in the flat zones, rather than using a constant scanning speed for the whole image, speeds up the imaging process of large samples by up to a 4× factor. PMID:22368491

  11. High-Resolution Adaptive Optics Retinal Imaging of Cellular Structure in Choroideremia

    PubMed Central

    Morgan, Jessica I. W.; Han, Grace; Klinman, Eva; Maguire, William M.; Chung, Daniel C.; Maguire, Albert M.; Bennett, Jean

    2014-01-01

    Purpose. We characterized retinal structure in patients and carriers of choroideremia using adaptive optics and other high resolution modalities. Methods. A total of 57 patients and 18 carriers of choroideremia were imaged using adaptive optics scanning light ophthalmoscopy (AOSLO), optical coherence tomography (OCT), autofluorescence (AF), and scanning light ophthalmoscopy (SLO). Cone density was measured in 59 eyes of 34 patients where the full cone mosaic was observed. Results. The SLO imaging revealed scalloped edges of RPE atrophy and large choroidal vessels. The AF imaging showed hypo-AF in areas of degeneration, while central AF remained present. OCT images showed outer retinal tubulations and thinned RPE/interdigitation layers. The AOSLO imaging revealed the cone mosaic in central relatively intact retina, and cone density was either reduced or normal at 0.5 mm eccentricity. The border of RPE atrophy showed abrupt loss of the cone mosaic at the same location. The AF imaging in comparison with AOSLO showed RPE health may be compromised before cone degeneration. Other disease features, including visualization of choroidal vessels, hyper-reflective clumps of cones, and unique retinal findings, were tabulated to show the frequency of occurrence and model disease progression. Conclusions. The data support the RPE being one primary site of degeneration in patients with choroideremia. Photoreceptors also may degenerate independently. High resolution imaging, particularly AOSLO in combination with OCT, allows single cell analysis of disease in choroideremia. These modalities promise to be useful in monitoring disease progression, and in documenting the efficacy of gene and cell-based therapies for choroideremia and other diseases as these therapies emerge. (ClinicalTrials.gov number, NCT01866371.) PMID:25190651

  12. High-resolution adaptive optics retinal imaging of cellular structure in choroideremia.

    PubMed

    Morgan, Jessica I W; Han, Grace; Klinman, Eva; Maguire, William M; Chung, Daniel C; Maguire, Albert M; Bennett, Jean

    2014-09-04

    We characterized retinal structure in patients and carriers of choroideremia using adaptive optics and other high resolution modalities. A total of 57 patients and 18 carriers of choroideremia were imaged using adaptive optics scanning light ophthalmoscopy (AOSLO), optical coherence tomography (OCT), autofluorescence (AF), and scanning light ophthalmoscopy (SLO). Cone density was measured in 59 eyes of 34 patients where the full cone mosaic was observed. The SLO imaging revealed scalloped edges of RPE atrophy and large choroidal vessels. The AF imaging showed hypo-AF in areas of degeneration, while central AF remained present. OCT images showed outer retinal tubulations and thinned RPE/interdigitation layers. The AOSLO imaging revealed the cone mosaic in central relatively intact retina, and cone density was either reduced or normal at 0.5 mm eccentricity. The border of RPE atrophy showed abrupt loss of the cone mosaic at the same location. The AF imaging in comparison with AOSLO showed RPE health may be compromised before cone degeneration. Other disease features, including visualization of choroidal vessels, hyper-reflective clumps of cones, and unique retinal findings, were tabulated to show the frequency of occurrence and model disease progression. The data support the RPE being one primary site of degeneration in patients with choroideremia. Photoreceptors also may degenerate independently. High resolution imaging, particularly AOSLO in combination with OCT, allows single cell analysis of disease in choroideremia. These modalities promise to be useful in monitoring disease progression, and in documenting the efficacy of gene and cell-based therapies for choroideremia and other diseases as these therapies emerge. (ClinicalTrials.gov number, NCT01866371.). Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

  13. An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization

    NASA Astrophysics Data System (ADS)

    Li, Shuo; Jin, Weiqi; Li, Li; Li, Yiyang

    2018-05-01

    Infrared thermal images can reflect the thermal-radiation distribution of a particular scene. However, the contrast of the infrared images is usually low. Hence, it is generally necessary to enhance the contrast of infrared images in advance to facilitate subsequent recognition and analysis. Based on the adaptive double plateaus histogram equalization, this paper presents an improved contrast enhancement algorithm for infrared thermal images. In the proposed algorithm, the normalized coefficient of variation of the histogram, which characterizes the level of contrast enhancement, is introduced as feedback information to adjust the upper and lower plateau thresholds. The experiments on actual infrared images show that compared to the three typical contrast-enhancement algorithms, the proposed algorithm has better scene adaptability and yields better contrast-enhancement results for infrared images with more dark areas or a higher dynamic range. Hence, it has high application value in contrast enhancement, dynamic range compression, and digital detail enhancement for infrared thermal images.

  14. Retinal axial focusing and multi-layer imaging with a liquid crystal adaptive optics camera

    NASA Astrophysics Data System (ADS)

    Liu, Rui-Xue; Zheng, Xian-Liang; Li, Da-Yu; Xia, Ming-Liang; Hu, Li-Fa; Cao, Zhao-Liang; Mu, Quan-Quan; Xuan, Li

    2014-09-01

    With the help of adaptive optics (AO) technology, cellular level imaging of living human retina can be achieved. Aiming to reduce distressing feelings and to avoid potential drug induced diseases, we attempted to image retina with dilated pupil and froze accommodation without drugs. An optimized liquid crystal adaptive optics camera was adopted for retinal imaging. A novel eye stared system was used for stimulating accommodation and fixating imaging area. Illumination sources and imaging camera kept linkage for focusing and imaging different layers. Four subjects with diverse degree of myopia were imaged. Based on the optical properties of the human eye, the eye stared system reduced the defocus to less than the typical ocular depth of focus. In this way, the illumination light can be projected on certain retina layer precisely. Since that the defocus had been compensated by the eye stared system, the adopted 512 × 512 liquid crystal spatial light modulator (LC-SLM) corrector provided the crucial spatial fidelity to fully compensate high-order aberrations. The Strehl ratio of a subject with -8 diopter myopia was improved to 0.78, which was nearly close to diffraction-limited imaging. By finely adjusting the axial displacement of illumination sources and imaging camera, cone photoreceptors, blood vessels and nerve fiber layer were clearly imaged successfully.

  15. Automatic Near-Real-Time Image Processing Chain for Very High Resolution Optical Satellite Data

    NASA Astrophysics Data System (ADS)

    Ostir, K.; Cotar, K.; Marsetic, A.; Pehani, P.; Perse, M.; Zaksek, K.; Zaletelj, J.; Rodic, T.

    2015-04-01

    In response to the increasing need for automatic and fast satellite image processing SPACE-SI has developed and implemented a fully automatic image processing chain STORM that performs all processing steps from sensor-corrected optical images (level 1) to web-delivered map-ready images and products without operator's intervention. Initial development was tailored to high resolution RapidEye images, and all crucial and most challenging parts of the planned full processing chain were developed: module for automatic image orthorectification based on a physical sensor model and supported by the algorithm for automatic detection of ground control points (GCPs); atmospheric correction module, topographic corrections module that combines physical approach with Minnaert method and utilizing anisotropic illumination model; and modules for high level products generation. Various parts of the chain were implemented also for WorldView-2, THEOS, Pleiades, SPOT 6, Landsat 5-8, and PROBA-V. Support of full-frame sensor currently in development by SPACE-SI is in plan. The proposed paper focuses on the adaptation of the STORM processing chain to very high resolution multispectral images. The development concentrated on the sub-module for automatic detection of GCPs. The initially implemented two-step algorithm that worked only with rasterized vector roads and delivered GCPs with sub-pixel accuracy for the RapidEye images, was improved with the introduction of a third step: super-fine positioning of each GCP based on a reference raster chip. The added step exploits the high spatial resolution of the reference raster to improve the final matching results and to achieve pixel accuracy also on very high resolution optical satellite data.

  16. SU-E-J-42: Motion Adaptive Image Filter for Low Dose X-Ray Fluoroscopy in the Real-Time Tumor-Tracking Radiotherapy System.

    PubMed

    Miyamoto, N; Ishikawa, M; Sutherland, K; Suzuki, R; Matsuura, T; Takao, S; Toramatsu, C; Nihongi, H; Shimizu, S; Onimaru, R; Umegaki, K; Shirato, H

    2012-06-01

    In the real-time tumor-tracking radiotherapy system, fiducial markers are detected by X-ray fluoroscopy. The fluoroscopic parameters should be optimized as low as possible in order to reduce unnecessary imaging dose. However, the fiducial markers could not be recognized due to effect of statistical noise in low dose imaging. Image processing is envisioned to be a solution to improve image quality and to maintain tracking accuracy. In this study, a recursive image filter adapted to target motion is proposed. A fluoroscopy system was used for the experiment. A spherical gold marker was used as a fiducial marker. About 450 fluoroscopic images of the marker were recorded. In order to mimic respiratory motion of the marker, the images were shifted sequentially. The tube voltage, current and exposure duration were fixed at 65 kV, 50 mA and 2.5 msec as low dose imaging condition, respectively. The tube current was 100 mA as high dose imaging. A pattern recognition score (PRS) ranging from 0 to 100 and image registration error were investigated by performing template pattern matching to each sequential image. The results with and without image processing were compared. In low dose imaging, theimage registration error and the PRS without the image processing were 2.15±1.21 pixel and 46.67±6.40, respectively. Those with the image processing were 1.48±0.82 pixel and 67.80±4.51, respectively. There was nosignificant difference in the image registration error and the PRS between the results of low dose imaging with the image processing and that of high dose imaging without the image processing. The results showed that the recursive filter was effective in order to maintain marker tracking stability and accuracy in low dose fluoroscopy. © 2012 American Association of Physicists in Medicine.

  17. Multilevel processes and cultural adaptation: Examples from past and present small-scale societies

    PubMed Central

    Reyes-García, V.; Balbo, A. L.; Gomez-Baggethun, E.; Gueze, M.; Mesoudi, A.; Richerson, P.; Rubio-Campillo, X.; Ruiz-Mallén, I.; Shennan, S.

    2016-01-01

    Cultural adaptation has become central in the context of accelerated global change with authors increasingly acknowledging the importance of understanding multilevel processes that operate as adaptation takes place. We explore the importance of multilevel processes in explaining cultural adaptation by describing how processes leading to cultural (mis)adaptation are linked through a complex nested hierarchy, where the lower levels combine into new units with new organizations, functions, and emergent properties or collective behaviours. After a brief review of the concept of “cultural adaptation” from the perspective of cultural evolutionary theory and resilience theory, the core of the paper is constructed around the exploration of multilevel processes occurring at the temporal, spatial, social and political scales. We do so by examining small-scale societies’ case studies. In each section, we discuss the importance of the selected scale for understanding cultural adaptation and then present an example that illustrates how multilevel processes in the selected scale help explain observed patterns in the cultural adaptive process. We end the paper discussing the potential of modelling and computer simulation for studying multilevel processes in cultural adaptation. PMID:27774109

  18. Defect Detection of Steel Surfaces with Global Adaptive Percentile Thresholding of Gradient Image

    NASA Astrophysics Data System (ADS)

    Neogi, Nirbhar; Mohanta, Dusmanta K.; Dutta, Pranab K.

    2017-12-01

    Steel strips are used extensively for white goods, auto bodies and other purposes where surface defects are not acceptable. On-line surface inspection systems can effectively detect and classify defects and help in taking corrective actions. For detection of defects use of gradients is very popular in highlighting and subsequently segmenting areas of interest in a surface inspection system. Most of the time, segmentation by a fixed value threshold leads to unsatisfactory results. As defects can be both very small and large in size, segmentation of a gradient image based on percentile thresholding can lead to inadequate or excessive segmentation of defective regions. A global adaptive percentile thresholding of gradient image has been formulated for blister defect and water-deposit (a pseudo defect) in steel strips. The developed method adaptively changes the percentile value used for thresholding depending on the number of pixels above some specific values of gray level of the gradient image. The method is able to segment defective regions selectively preserving the characteristics of defects irrespective of the size of the defects. The developed method performs better than Otsu method of thresholding and an adaptive thresholding method based on local properties.

  19. Image processing of aerodynamic data

    NASA Technical Reports Server (NTRS)

    Faulcon, N. D.

    1985-01-01

    The use of digital image processing techniques in analyzing and evaluating aerodynamic data is discussed. An image processing system that converts images derived from digital data or from transparent film into black and white, full color, or false color pictures is described. Applications to black and white images of a model wing with a NACA 64-210 section in simulated rain and to computed low properties for transonic flow past a NACA 0012 airfoil are presented. Image processing techniques are used to visualize the variations of water film thicknesses on the wing model and to illustrate the contours of computed Mach numbers for the flow past the NACA 0012 airfoil. Since the computed data for the NACA 0012 airfoil are available only at discrete spatial locations, an interpolation method is used to provide values of the Mach number over the entire field.

  20. 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.

  1. A novel data processing technique for image reconstruction of penumbral imaging

    NASA Astrophysics Data System (ADS)

    Xie, Hongwei; Li, Hongyun; Xu, Zeping; Song, Guzhou; Zhang, Faqiang; Zhou, Lin

    2011-06-01

    CT image reconstruction technique was applied to the data processing of the penumbral imaging. Compared with other traditional processing techniques for penumbral coded pinhole image such as Wiener, Lucy-Richardson and blind technique, this approach is brand new. In this method, the coded aperture processing method was used for the first time independent to the point spread function of the image diagnostic system. In this way, the technical obstacles was overcome in the traditional coded pinhole image processing caused by the uncertainty of point spread function of the image diagnostic system. Then based on the theoretical study, the simulation of penumbral imaging and image reconstruction was carried out to provide fairly good results. While in the visible light experiment, the point source of light was used to irradiate a 5mm×5mm object after diffuse scattering and volume scattering. The penumbral imaging was made with aperture size of ~20mm. Finally, the CT image reconstruction technique was used for image reconstruction to provide a fairly good reconstruction result.

  2. Associative architecture for image processing

    NASA Astrophysics Data System (ADS)

    Adar, Rutie; Akerib, Avidan

    1997-09-01

    This article presents a new generation in parallel processing architecture for real-time image processing. The approach is implemented in a real time image processor chip, called the XiumTM-2, based on combining a fully associative array which provides the parallel engine with a serial RISC core on the same die. The architecture is fully programmable and can be programmed to implement a wide range of color image processing, computer vision and media processing functions in real time. The associative part of the chip is based on patented pending methodology of Associative Computing Ltd. (ACL), which condenses 2048 associative processors, each of 128 'intelligent' bits. Each bit can be a processing bit or a memory bit. At only 33 MHz and 0.6 micron manufacturing technology process, the chip has a computational power of 3 billion ALU operations per second and 66 billion string search operations per second. The fully programmable nature of the XiumTM-2 chip enables developers to use ACL tools to write their own proprietary algorithms combined with existing image processing and analysis functions from ACL's extended set of libraries.

  3. High-performance image processing architecture

    NASA Astrophysics Data System (ADS)

    Coffield, Patrick C.

    1992-04-01

    The proposed architecture is a logical design specifically for image processing and other related computations. The design is a hybrid electro-optical concept consisting of three tightly coupled components: a spatial configuration processor (the optical analog portion), a weighting processor (digital), and an accumulation processor (digital). The systolic flow of data and image processing operations are directed by a control buffer and pipelined to each of the three processing components. The image processing operations are defined by an image algebra developed by the University of Florida. The algebra is capable of describing all common image-to-image transformations. The merit of this architectural design is how elegantly it handles the natural decomposition of algebraic functions into spatially distributed, point-wise operations. The effect of this particular decomposition allows convolution type operations to be computed strictly as a function of the number of elements in the template (mask, filter, etc.) instead of the number of picture elements in the image. Thus, a substantial increase in throughput is realized. The logical architecture may take any number of physical forms. While a hybrid electro-optical implementation is of primary interest, the benefits and design issues of an all digital implementation are also discussed. The potential utility of this architectural design lies in its ability to control all the arithmetic and logic operations of the image algebra's generalized matrix product. This is the most powerful fundamental formulation in the algebra, thus allowing a wide range of applications.

  4. Behavioral training promotes multiple adaptive processes following acute hearing loss.

    PubMed

    Keating, Peter; Rosenior-Patten, Onayomi; Dahmen, Johannes C; Bell, Olivia; King, Andrew J

    2016-03-23

    The brain possesses a remarkable capacity to compensate for changes in inputs resulting from a range of sensory impairments. Developmental studies of sound localization have shown that adaptation to asymmetric hearing loss can be achieved either by reinterpreting altered spatial cues or by relying more on those cues that remain intact. Adaptation to monaural deprivation in adulthood is also possible, but appears to lack such flexibility. Here we show, however, that appropriate behavioral training enables monaurally-deprived adult humans to exploit both of these adaptive processes. Moreover, cortical recordings in ferrets reared with asymmetric hearing loss suggest that these forms of plasticity have distinct neural substrates. An ability to adapt to asymmetric hearing loss using multiple adaptive processes is therefore shared by different species and may persist throughout the lifespan. This highlights the fundamental flexibility of neural systems, and may also point toward novel therapeutic strategies for treating sensory disorders.

  5. Integration of digital signal processing technologies with pulsed electron paramagnetic resonance imaging

    PubMed Central

    Pursley, Randall H.; Salem, Ghadi; Devasahayam, Nallathamby; Subramanian, Sankaran; Koscielniak, Janusz; Krishna, Murali C.; Pohida, Thomas J.

    2006-01-01

    The integration of modern data acquisition and digital signal processing (DSP) technologies with Fourier transform electron paramagnetic resonance (FT-EPR) imaging at radiofrequencies (RF) is described. The FT-EPR system operates at a Larmor frequency (Lf) of 300 MHz to facilitate in vivo studies. This relatively low frequency Lf, in conjunction with our ~10 MHz signal bandwidth, enables the use of direct free induction decay time-locked subsampling (TLSS). This particular technique provides advantages by eliminating the traditional analog intermediate frequency downconversion stage along with the corresponding noise sources. TLSS also results in manageable sample rates that facilitate the design of DSP-based data acquisition and image processing platforms. More specifically, we utilize a high-speed field programmable gate array (FPGA) and a DSP processor to perform advanced real-time signal and image processing. The migration to a DSP-based configuration offers the benefits of improved EPR system performance, as well as increased adaptability to various EPR system configurations (i.e., software configurable systems instead of hardware reconfigurations). The required modifications to the FT-EPR system design are described, with focus on the addition of DSP technologies including the application-specific hardware, software, and firmware developed for the FPGA and DSP processor. The first results of using real-time DSP technologies in conjunction with direct detection bandpass sampling to implement EPR imaging at RF frequencies are presented. PMID:16243552

  6. Transmission mode adaptive beamforming for planar phased arrays and its application to 3D ultrasonic transcranial imaging

    NASA Astrophysics Data System (ADS)

    Shapoori, Kiyanoosh; Sadler, Jeffrey; Wydra, Adrian; Malyarenko, Eugene; Sinclair, Anthony; Maev, Roman G.

    2013-03-01

    A new adaptive beamforming method for accurately focusing ultrasound behind highly scattering layers of human skull and its application to 3D transcranial imaging via small-aperture planar phased arrays are reported. Due to its undulating, inhomogeneous, porous, and highly attenuative structure, human skull bone severely distorts ultrasonic beams produced by conventional focusing methods in both imaging and therapeutic applications. Strong acoustical mismatch between the skull and brain tissues, in addition to the skull's undulating topology across the active area of a planar ultrasonic probe, could cause multiple reflections and unpredictable refraction during beamforming and imaging processes. Such effects could significantly deflect the probe's beam from the intended focal point. Presented here is a theoretical basis and simulation results of an adaptive beamforming method that compensates for the latter effects in transmission mode, accompanied by experimental verification. The probe is a custom-designed 2 MHz, 256-element matrix array with 0.45 mm element size and 0.1mm kerf. Through its small footprint, it is possible to accurately measure the profile of the skull segment in contact with the probe and feed the results into our ray tracing program. The latter calculates the new time delay patterns adapted to the geometrical and acoustical properties of the skull phantom segment in contact with the probe. The time delay patterns correct for the refraction at the skull-brain boundary and bring the distorted beam back to its intended focus. The algorithms were implemented on the ultrasound open-platform ULA-OP (developed at the University of Florence).

  7. White Light Schlieren Optics Using Bacteriorhodopsin as an Adaptive Image Grid

    NASA Technical Reports Server (NTRS)

    Peale, Robert; Ruffin, Boh; Donahue, Jeff; Barrett, Carolyn

    1996-01-01

    A Schlieren apparatus using a bacteriorhodopsin film as an adaptive image grid with white light illumination is demonstrated for the first time. The time dependent spectral properties of the film are characterized. Potential applications include a single-ended Schlieren system for leak detection.

  8. Blocking reduction of Landsat Thematic Mapper JPEG browse images using optimal PSNR estimated spectra adaptive postfiltering

    NASA Technical Reports Server (NTRS)

    Linares, Irving; Mersereau, Russell M.; Smith, Mark J. T.

    1994-01-01

    Two representative sample images of Band 4 of the Landsat Thematic Mapper are compressed with the JPEG algorithm at 8:1, 16:1 and 24:1 Compression Ratios for experimental browsing purposes. We then apply the Optimal PSNR Estimated Spectra Adaptive Postfiltering (ESAP) algorithm to reduce the DCT blocking distortion. ESAP reduces the blocking distortion while preserving most of the image's edge information by adaptively postfiltering the decoded image using the block's spectral information already obtainable from each block's DCT coefficients. The algorithm iteratively applied a one dimensional log-sigmoid weighting function to the separable interpolated local block estimated spectra of the decoded image until it converges to the optimal PSNR with respect to the original using a 2-D steepest ascent search. Convergence is obtained in a few iterations for integer parameters. The optimal logsig parameters are transmitted to the decoder as a negligible byte of overhead data. A unique maxima is guaranteed due to the 2-D asymptotic exponential overshoot shape of the surface generated by the algorithm. ESAP is based on a DFT analysis of the DCT basis functions. It is implemented with pixel-by-pixel spatially adaptive separable FIR postfilters. PSNR objective improvements between 0.4 to 0.8 dB are shown together with their corresponding optimal PSNR adaptive postfiltered images.

  9. APPLEPIPS /Apple Personal Image Processing System/ - An interactive digital image processing system for the Apple II microcomputer

    NASA Technical Reports Server (NTRS)

    Masuoka, E.; Rose, J.; Quattromani, M.

    1981-01-01

    Recent developments related to microprocessor-based personal computers have made low-cost digital image processing systems a reality. Image analysis systems built around these microcomputers provide color image displays for images as large as 256 by 240 pixels in sixteen colors. Descriptive statistics can be computed for portions of an image, and supervised image classification can be obtained. The systems support Basic, Fortran, Pascal, and assembler language. A description is provided of a system which is representative of the new microprocessor-based image processing systems currently on the market. While small systems may never be truly independent of larger mainframes, because they lack 9-track tape drives, the independent processing power of the microcomputers will help alleviate some of the turn-around time problems associated with image analysis and display on the larger multiuser systems.

  10. Image processing in forensic pathology.

    PubMed

    Oliver, W R

    1998-03-01

    Image processing applications in forensic pathology are becoming increasingly important. This article introduces basic concepts in image processing as applied to problems in forensic pathology in a non-mathematical context. Discussions of contrast enhancement, digital encoding, compression, deblurring, and other topics are presented.

  11. High-speed adaptive optics for imaging of the living human eye

    PubMed Central

    Yu, Yongxin; Zhang, Tianjiao; Meadway, Alexander; Wang, Xiaolin; Zhang, Yuhua

    2015-01-01

    The discovery of high frequency temporal fluctuation of human ocular wave aberration dictates the necessity of high speed adaptive optics (AO) correction for high resolution retinal imaging. We present a high speed AO system for an experimental adaptive optics scanning laser ophthalmoscope (AOSLO). We developed a custom high speed Shack-Hartmann wavefront sensor and maximized the wavefront detection speed based upon a trade-off among the wavefront spatial sampling density, the dynamic range, and the measurement sensitivity. We examined the temporal dynamic property of the ocular wavefront under the AOSLO imaging condition and improved the dual-thread AO control strategy. The high speed AO can be operated with a closed-loop frequency up to 110 Hz. Experiment results demonstrated that the high speed AO system can provide improved compensation for the wave aberration up to 30 Hz in the living human eye. PMID:26368408

  12. An approach to analyze the breast tissues in infrared images using nonlinear adaptive level sets and Riesz transform features.

    PubMed

    Prabha, S; Suganthi, S S; Sujatha, C M

    2015-01-01

    Breast thermography is a potential imaging method for the early detection of breast cancer. The pathological conditions can be determined by measuring temperature variations in the abnormal breast regions. Accurate delineation of breast tissues is reported as a challenging task due to inherent limitations of infrared images such as low contrast, low signal to noise ratio and absence of clear edges. Segmentation technique is attempted to delineate the breast tissues by detecting proper lower breast boundaries and inframammary folds. Characteristic features are extracted to analyze the asymmetrical thermal variations in normal and abnormal breast tissues. An automated analysis of thermal variations of breast tissues is attempted using nonlinear adaptive level sets and Riesz transform. Breast thermal images are initially subjected to Stein's unbiased risk estimate based orthonormal wavelet denoising. These denoised images are enhanced using contrast-limited adaptive histogram equalization method. The breast tissues are then segmented using non-linear adaptive level set method. The phase map of enhanced image is integrated into the level set framework for final boundary estimation. The segmented results are validated against the corresponding ground truth images using overlap and regional similarity metrics. The segmented images are further processed with Riesz transform and structural texture features are derived from the transformed coefficients to analyze pathological conditions of breast tissues. Results show that the estimated average signal to noise ratio of denoised images and average sharpness of enhanced images are improved by 38% and 6% respectively. The interscale consideration adopted in the denoising algorithm is able to improve signal to noise ratio by preserving edges. The proposed segmentation framework could delineate the breast tissues with high degree of correlation (97%) between the segmented and ground truth areas. Also, the average segmentation

  13. Policy Implementation as a Loosely-Coupled Organizational Adaptation Process.

    ERIC Educational Resources Information Center

    Peterson, Vance T.

    Policy implementation in organizations has been described in the literature as a process of adaptation. A study was performed to investigate three basic linkages specified in the traditional rational adaptation paradigm during the implementation of a new budget structure in a multicampus community college district. Loose coupling between elements…

  14. Introduction to computer image processing

    NASA Technical Reports Server (NTRS)

    Moik, J. G.

    1973-01-01

    Theoretical backgrounds and digital techniques for a class of image processing problems are presented. Image formation in the context of linear system theory, image evaluation, noise characteristics, mathematical operations on image and their implementation are discussed. Various techniques for image restoration and image enhancement are presented. Methods for object extraction and the problem of pictorial pattern recognition and classification are discussed.

  15. Blind Bayesian restoration of adaptive optics telescope images using generalized Gaussian Markov random field models

    NASA Astrophysics Data System (ADS)

    Jeffs, Brian D.; Christou, Julian C.

    1998-09-01

    This paper addresses post processing for resolution enhancement of sequences of short exposure adaptive optics (AO) images of space objects. The unknown residual blur is removed using Bayesian maximum a posteriori blind image restoration techniques. In the problem formulation, both the true image and the unknown blur psf's are represented by the flexible generalized Gaussian Markov random field (GGMRF) model. The GGMRF probability density function provides a natural mechanism for expressing available prior information about the image and blur. Incorporating such prior knowledge in the deconvolution optimization is crucial for the success of blind restoration algorithms. For example, space objects often contain sharp edge boundaries and geometric structures, while the residual blur psf in the corresponding partially corrected AO image is spectrally band limited, and exhibits while the residual blur psf in the corresponding partially corrected AO image is spectrally band limited, and exhibits smoothed, random , texture-like features on a peaked central core. By properly choosing parameters, GGMRF models can accurately represent both the blur psf and the object, and serve to regularize the deconvolution problem. These two GGMRF models also serve as discriminator functions to separate blur and object in the solution. Algorithm performance is demonstrated with examples from synthetic AO images. Results indicate significant resolution enhancement when applied to partially corrected AO images. An efficient computational algorithm is described.

  16. A novel smartphone ophthalmic imaging adapter: User feasibility studies in Hyderabad, India

    PubMed Central

    Ludwig, Cassie A; Murthy, Somasheila I; Pappuru, Rajeev R; Jais, Alexandre; Myung, David J; Chang, Robert T

    2016-01-01

    Aim of Study: To evaluate the ability of ancillary health staff to use a novel smartphone imaging adapter system (EyeGo, now known as Paxos Scope) to capture images of sufficient quality to exclude emergent eye findings. Secondary aims were to assess user and patient experiences during image acquisition, interuser reproducibility, and subjective image quality. Materials and Methods: The system captures images using a macro lens and an indirect ophthalmoscopy lens coupled with an iPhone 5S. We conducted a prospective cohort study of 229 consecutive patients presenting to L. V. Prasad Eye Institute, Hyderabad, India. Primary outcome measure was mean photographic quality (FOTO-ED study 1–5 scale, 5 best). 210 patients and eight users completed surveys assessing comfort and ease of use. For 46 patients, two users imaged the same patient's eyes sequentially. For 182 patients, photos taken with the EyeGo system were compared to images taken by existing clinic cameras: a BX 900 slit-lamp with a Canon EOS 40D Digital Camera and an FF 450 plus Fundus Camera with VISUPAC™ Digital Imaging System. Images were graded post hoc by a reviewer blinded to diagnosis. Results: Nine users acquired 719 useable images and 253 videos of 229 patients. Mean image quality was ≥ 4.0/5.0 (able to exclude subtle findings) for all users. 8/8 users and 189/210 patients surveyed were comfortable with the EyeGo device on a 5-point Likert scale. For 21 patients imaged with the anterior adapter by two users, a weighted κ of 0.597 (95% confidence interval: 0.389–0.806) indicated moderate reproducibility. High level of agreement between EyeGo and existing clinic cameras (92.6% anterior, 84.4% posterior) was found. Conclusion: The novel, ophthalmic imaging system is easily learned by ancillary eye care providers, well tolerated by patients, and captures high-quality images of eye findings. PMID:27146928

  17. PET imaging in adaptive radiotherapy of prostate tumors.

    PubMed

    Beuthien-Baumann, Bettina; Koerber, Stefan A

    2018-06-04

    The integration of data from positron-emission-tomography, combined with computed tomography as PET/CT or combined with magnet resonance imaging as PET/MRI, into radiation treatment planning of prostate cancer is gaining higher impact with the development of more sensitive and specific radioligands. The classic PET-tracer for prostate cancer imaging are [11C]choline and [11C]acetate, which are currently outperformed by ligands binding to the prostate-specific- membrane-antigen (PSMA). [68Ga]PSMA-11, which is the most frequently applied tracer, has shown to detect lymph node metastases, local recurrences, distant metastases and intraprostatic foci with high sensitivity, even at relatively low PSA levels. The results from PET-imaging may influence radiotherapeutic (RT) management at different stages of the disease i.e. during primary staging or biochemical recurrence, when the detection of distant metastases may alter the curative treatment concept into a palliative approach. On the other hand, the clinical target volume could be adapted by visualizing lymph node metastases at locations, which might not have been suspicious on morphologic imaging alone. The treatment plan might contain a boost to the dominant intraprostatic lesion, which could be delineated by a combination of PET-tracer uptake and multiparametric MRI. Therefore, PSMA-PET imaging is well suited for being integrated into prostate radiation planning. However, further prospective trials evaluating the impact on oncological outcome are indicated.

  18. 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

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

    PubMed

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

    2016-08-01

    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. 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. 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. 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.

  20. Image processing for optical mapping.

    PubMed

    Ravindran, Prabu; Gupta, Aditya

    2015-01-01

    Optical Mapping is an established single-molecule, whole-genome analysis system, which has been used to gain a comprehensive understanding of genomic structure and to study structural variation of complex genomes. A critical component of Optical Mapping system is the image processing module, which extracts single molecule restriction maps from image datasets of immobilized, restriction digested and fluorescently stained large DNA molecules. In this review, we describe robust and efficient image processing techniques to process these massive datasets and extract accurate restriction maps in the presence of noise, ambiguity and confounding artifacts. We also highlight a few applications of the Optical Mapping system.

  1. PSYCHOSOCIAL INTERVENTION EFFECTS ON ADAPTATION, DISEASE COURSE AND BIOBEHAVIORAL PROCESSES IN CANCER

    PubMed Central

    Antoni, Michael H.

    2012-01-01

    A diagnosis of cancer and subsequent treatments place demands on psychological adaptation. Behavioral research suggests the importance of cognitive, behavioral, and social factors in facilitating adaptation during active treatment and throughout cancer survivorship, which forms the rationale for the use of many psychosocial interventions in cancer patients. This cancer experience may also affect physiological adaptation systems (e.g., neuroendocrine) in parallel with psychological adaptation changes (negative affect). Changes in adaptation may alter tumor growth-promoting processes (increased angiogenesis, migration and invasion, and inflammation) and tumor defense processes (decreased cellular immunity) relevant for cancer progression and the quality of life of cancer patients. Some evidence suggests that psychosocial intervention can improve psychological and physiological adaptation indicators in cancer patients. However, less is known about whether these interventions can influence tumor activity and tumor growth-promoting processes and whether changes in these processes could explain the psychosocial intervention effects on recurrence and survival documented to date. Documenting that psychosocial interventions can modulate molecular activities (e.g., transcriptional indicators of cell signaling) that govern tumor promoting and tumor defense processes on the one hand, and clinical disease course on the other is a key challenge for biobehavioral oncology research. This mini-review will summarize current knowledge on psychological and physiological adaptation processes affected throughout the stress of the cancer experience, and the effects of psychosocial interventions on psychological adaptation, cancer disease progression, and changes in stress-related biobehavioral processes that may mediate intervention effects on clinical cancer outcomes. Very recent intervention work in breast cancer will be used to illuminate emerging trends in molecular probes of

  2. Psychosocial intervention effects on adaptation, disease course and biobehavioral processes in cancer.

    PubMed

    Antoni, Michael H

    2013-03-01

    A diagnosis of cancer and subsequent treatments place demands on psychological adaptation. Behavioral research suggests the importance of cognitive, behavioral, and social factors in facilitating adaptation during active treatment and throughout cancer survivorship, which forms the rationale for the use of many psychosocial interventions in cancer patients. This cancer experience may also affect physiological adaptation systems (e.g., neuroendocrine) in parallel with psychological adaptation changes (negative affect). Changes in adaptation may alter tumor growth-promoting processes (increased angiogenesis, migration and invasion, and inflammation) and tumor defense processes (decreased cellular immunity) relevant for cancer progression and the quality of life of cancer patients. Some evidence suggests that psychosocial intervention can improve psychological and physiological adaptation indicators in cancer patients. However, less is known about whether these interventions can influence tumor activity and tumor growth-promoting processes and whether changes in these processes could explain the psychosocial intervention effects on recurrence and survival documented to date. Documenting that psychosocial interventions can modulate molecular activities (e.g., transcriptional indicators of cell signaling) that govern tumor promoting and tumor defense processes on the one hand, and clinical disease course on the other is a key challenge for biobehavioral oncology research. This mini-review will summarize current knowledge on psychological and physiological adaptation processes affected throughout the stress of the cancer experience, and the effects of psychosocial interventions on psychological adaptation, cancer disease progression, and changes in stress-related biobehavioral processes that may mediate intervention effects on clinical cancer outcomes. Very recent intervention work in breast cancer will be used to illuminate emerging trends in molecular probes of

  3. Remote Sensing Image Quality Assessment Experiment with Post-Processing

    NASA Astrophysics Data System (ADS)

    Jiang, W.; Chen, S.; Wang, X.; Huang, Q.; Shi, H.; Man, Y.

    2018-04-01

    This paper briefly describes the post-processing influence assessment experiment, the experiment includes three steps: the physical simulation, image processing, and image quality assessment. The physical simulation models sampled imaging system in laboratory, the imaging system parameters are tested, the digital image serving as image processing input are produced by this imaging system with the same imaging system parameters. The gathered optical sampled images with the tested imaging parameters are processed by 3 digital image processes, including calibration pre-processing, lossy compression with different compression ratio and image post-processing with different core. Image quality assessment method used is just noticeable difference (JND) subject assessment based on ISO20462, through subject assessment of the gathered and processing images, the influence of different imaging parameters and post-processing to image quality can be found. The six JND subject assessment experimental data can be validated each other. Main conclusions include: image post-processing can improve image quality; image post-processing can improve image quality even with lossy compression, image quality with higher compression ratio improves less than lower ratio; with our image post-processing method, image quality is better, when camera MTF being within a small range.

  4. Image processing based detection of lung cancer on CT scan images

    NASA Astrophysics Data System (ADS)

    Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi

    2017-10-01

    In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.

  5. Image quality and dose differences caused by vendor-specific image processing of neonatal radiographs.

    PubMed

    Sensakovic, William F; O'Dell, M Cody; Letter, Haley; Kohler, Nathan; Rop, Baiywo; Cook, Jane; Logsdon, Gregory; Varich, Laura

    2016-10-01

    Image processing plays an important role in optimizing image quality and radiation dose in projection radiography. Unfortunately commercial algorithms are black boxes that are often left at or near vendor default settings rather than being optimized. We hypothesize that different commercial image-processing systems, when left at or near default settings, create significant differences in image quality. We further hypothesize that image-quality differences can be exploited to produce images of equivalent quality but lower radiation dose. We used a portable radiography system to acquire images on a neonatal chest phantom and recorded the entrance surface air kerma (ESAK). We applied two image-processing systems (Optima XR220amx, by GE Healthcare, Waukesha, WI; and MUSICA(2) by Agfa HealthCare, Mortsel, Belgium) to the images. Seven observers (attending pediatric radiologists and radiology residents) independently assessed image quality using two methods: rating and matching. Image-quality ratings were independently assessed by each observer on a 10-point scale. Matching consisted of each observer matching GE-processed images and Agfa-processed images with equivalent image quality. A total of 210 rating tasks and 42 matching tasks were performed and effective dose was estimated. Median Agfa-processed image-quality ratings were higher than GE-processed ratings. Non-diagnostic ratings were seen over a wider range of doses for GE-processed images than for Agfa-processed images. During matching tasks, observers matched image quality between GE-processed images and Agfa-processed images acquired at a lower effective dose (11 ± 9 μSv; P < 0.0001). Image-processing methods significantly impact perceived image quality. These image-quality differences can be exploited to alter protocols and produce images of equivalent image quality but lower doses. Those purchasing projection radiography systems or third-party image-processing software should be aware that image

  6. Cultural adaptation process for international dissemination of the strengthening families program.

    PubMed

    Kumpfer, Karol L; Pinyuchon, Methinin; Teixeira de Melo, Ana; Whiteside, Henry O

    2008-06-01

    The Strengthening Families Program (SFP) is an evidence-based family skills training intervention developed and found efficacious for substance abuse prevention by U.S researchers in the 1980s. In the 1990s, a cultural adaptation process was developed to transport SFP for effectiveness trials with diverse populations (African, Hispanic, Asian, Pacific Islander, and Native American). Since 2003, SFP has been culturally adapted for use in 17 countries. This article reviews the SFP theory and research and a recommended cultural adaptation process. Challenges in international dissemination of evidence-based programs (EBPs) are discussed based on the results of U.N. and U.S. governmental initiatives to transport EBP family interventions to developing countries. The technology transfer and quality assurance system are described, including the language translation and cultural adaptation process for materials development, staff training, and on-site and online Web-based supervision and technical assistance and evaluation services to assure quality implementation and process evaluation feedback for improvements.

  7. Retinal image quality and visual stimuli processing by simulation of partial eye cataract

    NASA Astrophysics Data System (ADS)

    Ozolinsh, Maris; Danilenko, Olga; Zavjalova, Varvara

    2016-10-01

    Visual stimuli were demonstrated on a 4.3'' mobile phone screen inside a "Virtual Reality" adapter that allowed separation of the left and right eye visual fields. Contrast of the retina image thus can be controlled by the image on the phone screen and parallel to that at appropriate geometry by the AC voltage applied to scattering PDLC cell inside the adapter. Such optical pathway separation allows to demonstrate to both eyes spatially variant images, that after visual binocular fusion acquire their characteristic indications. As visual stimuli we used grey and different color (two opponent components to vision - red-green in L*a*b* color space) spatially periodical stimuli for left and right eyes; and with spatial content that by addition or subtraction resulted as clockwise or counter clockwise slanted Gabor gratings. We performed computer modeling with numerical addition or subtraction of signals similar to processing in brain via stimuli input decomposition in luminance and color opponency components. It revealed the dependence of the perception psychophysical equilibrium point between clockwise or counter clockwise perception of summation on one eye image contrast and color saturation, and on the strength of the retinal aftereffects. Existence of a psychophysical equilibrium point in perception of summation is only in the presence of a prior adaptation to a slanted periodical grating and at the appropriate slant orientation of adaptation grating and/or at appropriate spatial grating pattern phase according to grating nods. Actual observer perception experiments when one eye images were deteriorated by simulated cataract approved the shift of mentioned psychophysical equilibrium point on the degree of artificial cataract. We analyzed also the mobile devices stimuli emission spectra paying attention to areas sensitive to macula pigments absorption spectral maxima and blue areas where the intense irradiation can cause in abnormalities in periodic melatonin

  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. © Wiley Periodicals, Inc.

  9. Adaptive windowing in contrast-enhanced intravascular ultrasound imaging

    PubMed Central

    Lindsey, Brooks D.; Martin, K. Heath; Jiang, Xiaoning; Dayton, Paul A.

    2016-01-01

    Intravascular ultrasound (IVUS) is one of the most commonly-used interventional imaging techniques and has seen recent innovations which attempt to characterize the risk posed by atherosclerotic plaques. One such development is the use of microbubble contrast agents to image vasa vasorum, fine vessels which supply oxygen and nutrients to the walls of coronary arteries and typically have diameters less than 200 µm. The degree of vasa vasorum neovascularization within plaques is positively correlated with plaque vulnerability. Having recently presented a prototype dual-frequency transducer for contrast agent-specific intravascular imaging, here we describe signal processing approaches based on minimum variance (MV) beamforming and the phase coherence factor (PCF) for improving the spatial resolution and contrast-to-tissue ratio (CTR) in IVUS imaging. These approaches are examined through simulations, phantom studies, ex vivo studies in porcine arteries, and in vivo studies in chicken embryos. In phantom studies, PCF processing improved CTR by a mean of 4.2 dB, while combined MV and PCF processing improved spatial resolution by 41.7%. Improvements of 2.2 dB in CTR and 37.2% in resolution were observed in vivo. Applying these processing strategies can enhance image quality in conventional B-mode IVUS or in contrast-enhanced IVUS, where signal-to-noise ratio is relatively low and resolution is at a premium. PMID:27161022

  10. Adaptive windowing in contrast-enhanced intravascular ultrasound imaging.

    PubMed

    Lindsey, Brooks D; Martin, K Heath; Jiang, Xiaoning; Dayton, Paul A

    2016-08-01

    Intravascular ultrasound (IVUS) is one of the most commonly-used interventional imaging techniques and has seen recent innovations which attempt to characterize the risk posed by atherosclerotic plaques. One such development is the use of microbubble contrast agents to image vasa vasorum, fine vessels which supply oxygen and nutrients to the walls of coronary arteries and typically have diameters less than 200μm. The degree of vasa vasorum neovascularization within plaques is positively correlated with plaque vulnerability. Having recently presented a prototype dual-frequency transducer for contrast agent-specific intravascular imaging, here we describe signal processing approaches based on minimum variance (MV) beamforming and the phase coherence factor (PCF) for improving the spatial resolution and contrast-to-tissue ratio (CTR) in IVUS imaging. These approaches are examined through simulations, phantom studies, ex vivo studies in porcine arteries, and in vivo studies in chicken embryos. In phantom studies, PCF processing improved CTR by a mean of 4.2dB, while combined MV and PCF processing improved spatial resolution by 41.7%. Improvements of 2.2dB in CTR and 37.2% in resolution were observed in vivo. Applying these processing strategies can enhance image quality in conventional B-mode IVUS or in contrast-enhanced IVUS, where signal-to-noise ratio is relatively low and resolution is at a premium. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Adaptation to recent conflict in the classical color-word Stroop-task mainly involves facilitation of processing of task-relevant information.

    PubMed

    Purmann, Sascha; Pollmann, Stefan

    2015-01-01

    To process information selectively and to continuously fine-tune selectivity of information processing are important abilities for successful goal-directed behavior. One phenomenon thought to represent this fine-tuning are conflict adaptation effects in interference tasks, i.e., reduction of interference after an incompatible trial and when incompatible trials are frequent. The neurocognitive mechanisms of these effects are currently only partly understood and results from brainimaging studies so far are mixed. In our study we validate and extend recent findings by examining adaption to recent conflict in the classical Stroop task using functional magnetic resonance imaging. Consistent with previous research we found increased activity in a fronto-parietal network comprising the medial prefrontal cortex, ventro-lateral prefrontal cortex, and posterior parietal cortex when contrasting incompatible with compatible trials. These areas have been associated with attentional processes and might reflect increased cognitive conflict and resolution thereof during incompatible trials. While carefully controlling for non-attentional sequential effects we found smaller Stroop interference after an incompatible trial (conflict adaptation effect). These behavioral conflict adaptation effects were accompanied by changes in activity in visual color-selective areas (V4, V4α), while there was no modulation by previous trial compatibility in a visual word-selective area (VWFA). Our results provide further evidence for the notion, that adaptation to recent conflict seems to be based mainly on enhancement of processing of the task-relevant information.

  12. [The role adaptation process of the executive director of nursing department].

    PubMed

    Kang, Sung-Ye; Park, Kwang-Ok; Kim, Jong-Kyung

    2010-12-01

    The purpose of this study was to identify the role adaptation process experienced by executive directors of nursing department of general hospitals. Data were collected from 9 executive nursing directors though in-depth interviews about their experiences. The main question was "How do you describe your experience of the process of role adaptation as an executive nursing director?" Qualitative data from field and transcribed notes were analyzed using Strauss & Corbin's grounded theory methodology. The core category of experience of the process of role adaptation as an executive nursing director was identified as "entering the center with pushing and pulling". The participants used five interactional strategies;'maintaining modest attitudes','inquiring about trends of popular feeling','making each person a faithful follower','collecting & displaying power','leading with initiative'. The consequences of role adaptation in executive nursing directors were'coexisting with others','immersing in one's new role with dedication', and'having capacity for high tolerance'. The types of role adaptations of executive directors in nursing department were friendly type, propulsive type, accommodating type. The results of this study produced useful information for executive nursing directors on designing a self-managerial program to enhance role adaptation based on interactional strategies.

  13. Spot restoration for GPR image post-processing

    DOEpatents

    Paglieroni, David W; Beer, N. Reginald

    2014-05-20

    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.

  14. A novel ship CFAR detection algorithm based on adaptive parameter enhancement and wake-aided detection in SAR images

    NASA Astrophysics Data System (ADS)

    Meng, Siqi; Ren, Kan; Lu, Dongming; Gu, Guohua; Chen, Qian; Lu, Guojun

    2018-03-01

    Synthetic aperture radar (SAR) is an indispensable and useful method for marine monitoring. With the increase of SAR sensors, high resolution images can be acquired and contain more target structure information, such as more spatial details etc. This paper presents a novel adaptive parameter transform (APT) domain constant false alarm rate (CFAR) to highlight targets. The whole method is based on the APT domain value. Firstly, the image is mapped to the new transform domain by the algorithm. Secondly, the false candidate target pixels are screened out by the CFAR detector to highlight the target ships. Thirdly, the ship pixels are replaced by the homogeneous sea pixels. And then, the enhanced image is processed by Niblack algorithm to obtain the wake binary image. Finally, normalized Hough transform (NHT) is used to detect wakes in the binary image, as a verification of the presence of the ships. Experiments on real SAR images validate that the proposed transform does enhance the target structure and improve the contrast of the image. The algorithm has a good performance in the ship and ship wake detection.

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

    PubMed Central

    Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart

    2011-01-01

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

  16. Parallel processing considerations for image recognition tasks

    NASA Astrophysics Data System (ADS)

    Simske, Steven J.

    2011-01-01

    Many image recognition tasks are well-suited to parallel processing. The most obvious example is that many imaging tasks require the analysis of multiple images. From this standpoint, then, parallel processing need be no more complicated than assigning individual images to individual processors. However, there are three less trivial categories of parallel processing that will be considered in this paper: parallel processing (1) by task; (2) by image region; and (3) by meta-algorithm. Parallel processing by task allows the assignment of multiple workflows-as diverse as optical character recognition [OCR], document classification and barcode reading-to parallel pipelines. This can substantially decrease time to completion for the document tasks. For this approach, each parallel pipeline is generally performing a different task. Parallel processing by image region allows a larger imaging task to be sub-divided into a set of parallel pipelines, each performing the same task but on a different data set. This type of image analysis is readily addressed by a map-reduce approach. Examples include document skew detection and multiple face detection and tracking. Finally, parallel processing by meta-algorithm allows different algorithms to be deployed on the same image simultaneously. This approach may result in improved accuracy.

  17. Initial phantom study comparing image quality in computed tomography using adaptive statistical iterative reconstruction and new adaptive statistical iterative reconstruction v.

    PubMed

    Lim, Kyungjae; Kwon, Heejin; Cho, Jinhan; Oh, Jongyoung; Yoon, Seongkuk; Kang, Myungjin; Ha, Dongho; Lee, Jinhwa; Kang, Eunju

    2015-01-01

    The purpose of this study was to assess the image quality of a novel advanced iterative reconstruction (IR) method called as "adaptive statistical IR V" (ASIR-V) by comparing the image noise, contrast-to-noise ratio (CNR), and spatial resolution from those of filtered back projection (FBP) and adaptive statistical IR (ASIR) on computed tomography (CT) phantom image. We performed CT scans at 5 different tube currents (50, 70, 100, 150, and 200 mA) using 3 types of CT phantoms. Scanned images were subsequently reconstructed in 7 different scan settings, such as FBP, and 3 levels of ASIR and ASIR-V (30%, 50%, and 70%). The image noise was measured in the first study using body phantom. The CNR was measured in the second study using contrast phantom and the spatial resolutions were measured in the third study using a high-resolution phantom. We compared the image noise, CNR, and spatial resolution among the 7 reconstructed image scan settings to determine whether noise reduction, high CNR, and high spatial resolution could be achieved at ASIR-V. At quantitative analysis of the first and second studies, it showed that the images reconstructed using ASIR-V had reduced image noise and improved CNR compared with those of FBP and ASIR (P < 0.001). At qualitative analysis of the third study, it also showed that the images reconstructed using ASIR-V had significantly improved spatial resolution than those of FBP and ASIR (P < 0.001). Our phantom studies showed that ASIR-V provides a significant reduction in image noise and a significant improvement in CNR as well as spatial resolution. Therefore, this technique has the potential to reduce the radiation dose further without compromising image quality.

  18. Integrated adaptive optics optical coherence tomography and adaptive optics scanning laser ophthalmoscope system for simultaneous cellular resolution in vivo retinal imaging

    PubMed Central

    Zawadzki, Robert J.; Jones, Steven M.; Pilli, Suman; Balderas-Mata, Sandra; Kim, Dae Yu; Olivier, Scot S.; Werner, John S.

    2011-01-01

    We describe an ultrahigh-resolution (UHR) retinal imaging system that combines adaptive optics Fourier-domain optical coherence tomography (AO-OCT) with an adaptive optics scanning laser ophthalmoscope (AO-SLO) to allow simultaneous data acquisition by the two modalities. The AO-SLO subsystem was integrated into the previously described AO-UHR OCT instrument with minimal changes to the latter. This was done in order to ensure optimal performance and image quality of the AO- UHR OCT. In this design both imaging modalities share most of the optical components including a common AO-subsystem and vertical scanner. One of the benefits of combining Fd-OCT with SLO includes automatic co-registration between two acquisition channels for direct comparison between retinal structures imaged by both modalities (e.g., photoreceptor mosaics or microvasculature maps). Because of differences in the detection scheme of the two systems, this dual imaging modality instrument can provide insight into retinal morphology and potentially function, that could not be accessed easily by a single system. In this paper we describe details of the components and parameters of the combined instrument, including incorporation of a novel membrane magnetic deformable mirror with increased stroke and actuator count used as a single wavefront corrector. We also discuss laser safety calculations for this multimodal system. Finally, retinal images acquired in vivo with this system are presented. PMID:21698028

  19. Hyperspectral imaging for food processing automation

    NASA Astrophysics Data System (ADS)

    Park, Bosoon; Lawrence, Kurt C.; Windham, William R.; Smith, Doug P.; Feldner, Peggy W.

    2002-11-01

    This paper presents the research results that demonstrates hyperspectral imaging could be used effectively for detecting feces (from duodenum, ceca, and colon) and ingesta on the surface of poultry carcasses, and potential application for real-time, on-line processing of poultry for automatic safety inspection. The hyperspectral imaging system included a line scan camera with prism-grating-prism spectrograph, fiber optic line lighting, motorized lens control, and hyperspectral image processing software. Hyperspectral image processing algorithms, specifically band ratio of dual-wavelength (565/517) images and thresholding were effective on the identification of fecal and ingesta contamination of poultry carcasses. A multispectral imaging system including a common aperture camera with three optical trim filters (515.4 nm with 8.6- nm FWHM), 566.4 nm with 8.8-nm FWHM, and 631 nm with 10.2-nm FWHM), which were selected and validated by a hyperspectral imaging system, was developed for a real-time, on-line application. A total image processing time required to perform the current multispectral images captured by a common aperture camera was approximately 251 msec or 3.99 frames/sec. A preliminary test shows that the accuracy of real-time multispectral imaging system to detect feces and ingesta on corn/soybean fed poultry carcasses was 96%. However, many false positive spots that cause system errors were also detected.

  20. Adaptive mesh optimization and nonrigid motion recovery based image registration for wide-field-of-view ultrasound imaging.

    PubMed

    Tan, Chaowei; Wang, Bo; Liu, Paul; Liu, Dong

    2008-01-01

    Wide field of view (WFOV) imaging mode obtains an ultrasound image over an area much larger than the real time window normally available. As the probe is moved over the region of interest, new image frames are combined with prior frames to form a panorama image. Image registration techniques are used to recover the probe motion, eliminating the need for a position sensor. Speckle patterns, which are inherent in ultrasound imaging, change, or become decorrelated, as the scan plane moves, so we pre-smooth the image to reduce the effects of speckle in registration, as well as reducing effects from thermal noise. Because we wish to track the movement of features such as structural boundaries, we use an adaptive mesh over the entire smoothed image to home in on areas with feature. Motion estimation using blocks centered at the individual mesh nodes generates a field of motion vectors. After angular correction of motion vectors, we model the overall movement between frames as a nonrigid deformation. The polygon filling algorithm for precise, persistence-based spatial compounding constructs the final speckle reduced WFOV image.

  1. Coping and adaptation process during puerperium

    PubMed Central

    Muñoz de Rodríguez, Lucy; Ruiz de Cárdenas, Carmen Helena

    2012-01-01

    Introduction: The puerperium is a stage that produces changes and adaptations in women, couples and family. Effective coping, during this stage, depends on the relationship between the demands of stressful or difficult situations and the recourses that the puerperal individual has. Roy (2004), in her Middle Range Theory about the Coping and Adaptation Processing, defines Coping as the ''behavioral and cognitive efforts that a person makes to meet the environment demands''. For the puerperal individual, the correct coping is necessary to maintain her physical and mental well being, especially against situations that can be stressful like breastfeeding and return to work. According to Lazarus and Folkman (1986), a resource for coping is to have someone who receives emotional support, informative and / or tangible. Objective: To review the issue of women coping and adaptation during the puerperium stage and the strategies that enhance this adaptation. Methods: search and selection of database articles: Cochrane, Medline, Ovid, ProQuest, Scielo, and Blackwell Synergy. Other sources: unpublished documents by Roy, published books on Roy´s Model, Websites from of international health organizations. Results: the need to recognize the puerperium as a stage that requires comprehensive care is evident, where nurses must be protagonist with the care offered to women and their families, considering the specific demands of this situation and recourses that promote effective coping and the family, education and health services. PMID:24893059

  2. MO-G-17A-05: PET Image Deblurring Using Adaptive Dictionary Learning

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

    Valiollahzadeh, S; Clark, J; Mawlawi, O

    2014-06-15

    Purpose: The aim of this work is to deblur PET images while suppressing Poisson noise effects using adaptive dictionary learning (DL) techniques. Methods: The model that relates a blurred and noisy PET image to the desired image is described as a linear transform y=Hm+n where m is the desired image, H is a blur kernel, n is Poisson noise and y is the blurred image. The approach we follow to recover m involves the sparse representation of y over a learned dictionary, since the image has lots of repeated patterns, edges, textures and smooth regions. The recovery is based onmore » an optimization of a cost function having four major terms: adaptive dictionary learning term, sparsity term, regularization term, and MLEM Poisson noise estimation term. The optimization is solved by a variable splitting method that introduces additional variables. We simulated a 128×128 Hoffman brain PET image (baseline) with varying kernel types and sizes (Gaussian 9×9, σ=5.4mm; Uniform 5×5, σ=2.9mm) with additive Poisson noise (Blurred). Image recovery was performed once when the kernel type was included in the model optimization and once with the model blinded to kernel type. The recovered image was compared to the baseline as well as another recovery algorithm PIDSPLIT+ (Setzer et. al.) by calculating PSNR (Peak SNR) and normalized average differences in pixel intensities (NADPI) of line profiles across the images. Results: For known kernel types, the PSNR of the Gaussian (Uniform) was 28.73 (25.1) and 25.18 (23.4) for DL and PIDSPLIT+ respectively. For blinded deblurring the PSNRs were 25.32 and 22.86 for DL and PIDSPLIT+ respectively. NADPI between baseline and DL, and baseline and blurred for the Gaussian kernel was 2.5 and 10.8 respectively. Conclusion: PET image deblurring using dictionary learning seems to be a good approach to restore image resolution in presence of Poisson noise. GE Health Care.« less

  3. Automated Adaptive Brightness in Wireless Capsule Endoscopy Using Image Segmentation and Sigmoid Function.

    PubMed

    Shrestha, Ravi; Mohammed, Shahed K; Hasan, Md Mehedi; Zhang, Xuechao; Wahid, Khan A

    2016-08-01

    Wireless capsule endoscopy (WCE) plays an important role in the diagnosis of gastrointestinal (GI) diseases by capturing images of human small intestine. Accurate diagnosis of endoscopic images depends heavily on the quality of captured images. Along with image and frame rate, brightness of the image is an important parameter that influences the image quality which leads to the design of an efficient illumination system. Such design involves the choice and placement of proper light source and its ability to illuminate GI surface with proper brightness. Light emitting diodes (LEDs) are normally used as sources where modulated pulses are used to control LED's brightness. In practice, instances like under- and over-illumination are very common in WCE, where the former provides dark images and the later provides bright images with high power consumption. In this paper, we propose a low-power and efficient illumination system that is based on an automated brightness algorithm. The scheme is adaptive in nature, i.e., the brightness level is controlled automatically in real-time while the images are being captured. The captured images are segmented into four equal regions and the brightness level of each region is calculated. Then an adaptive sigmoid function is used to find the optimized brightness level and accordingly a new value of duty cycle of the modulated pulse is generated to capture future images. The algorithm is fully implemented in a capsule prototype and tested with endoscopic images. Commercial capsules like Pillcam and Mirocam were also used in the experiment. The results show that the proposed algorithm works well in controlling the brightness level accordingly to the environmental condition, and as a result, good quality images are captured with an average of 40% brightness level that saves power consumption of the capsule.

  4. A 3D image sensor with adaptable charge subtraction scheme for background light suppression

    NASA Astrophysics Data System (ADS)

    Shin, Jungsoon; Kang, Byongmin; Lee, Keechang; Kim, James D. K.

    2013-02-01

    We present a 3D ToF (Time-of-Flight) image sensor with adaptive charge subtraction scheme for background light suppression. The proposed sensor can alternately capture high resolution color image and high quality depth map in each frame. In depth-mode, the sensor requires enough integration time for accurate depth acquisition, but saturation will occur in high background light illumination. We propose to divide the integration time into N sub-integration times adaptively. In each sub-integration time, our sensor captures an image without saturation and subtracts the charge to prevent the pixel from the saturation. In addition, the subtraction results are cumulated N times obtaining a final result image without background illumination at full integration time. Experimental results with our own ToF sensor show high background suppression performance. We also propose in-pixel storage and column-level subtraction circuit for chiplevel implementation of the proposed method. We believe the proposed scheme will enable 3D sensors to be used in out-door environment.

  5. Cone photoreceptor definition on adaptive optics retinal imaging

    PubMed Central

    Muthiah, Manickam Nick; Gias, Carlos; Chen, Fred Kuanfu; Zhong, Joe; McClelland, Zoe; Sallo, Ferenc B; Peto, Tunde; Coffey, Peter J; da Cruz, Lyndon

    2014-01-01

    Aims To quantitatively analyse cone photoreceptor matrices on images captured on an adaptive optics (AO) camera and assess their correlation to well-established parameters in the retinal histology literature. Methods High resolution retinal images were acquired from 10 healthy subjects, aged 20–35 years old, using an AO camera (rtx1, Imagine Eyes, France). Left eye images were captured at 5° of retinal eccentricity, temporal to the fovea for consistency. In three subjects, images were also acquired at 0, 2, 3, 5 and 7° retinal eccentricities. Cone photoreceptor density was calculated following manual and automated counting. Inter-photoreceptor distance was also calculated. Voronoi domain and power spectrum analyses were performed for all images. Results At 5° eccentricity, the cone density (cones/mm2 mean±SD) was 15.3±1.4×103 (automated) and 13.9±1.0×103 (manual) and the mean inter-photoreceptor distance was 8.6±0.4 μm. Cone density decreased and inter-photoreceptor distance increased with increasing retinal eccentricity from 2 to 7°. A regular hexagonal cone photoreceptor mosaic pattern was seen at 2, 3 and 5° of retinal eccentricity. Conclusions Imaging data acquired from the AO camera match cone density, intercone distance and show the known features of cone photoreceptor distribution in the pericentral retina as reported by histology, namely, decreasing density values from 2 to 7° of eccentricity and the hexagonal packing arrangement. This confirms that AO flood imaging provides reliable estimates of pericentral cone photoreceptor distribution in normal subjects. PMID:24729030

  6. Tracking features in retinal images of adaptive optics confocal scanning laser ophthalmoscope using KLT-SIFT algorithm

    PubMed Central

    Li, Hao; Lu, Jing; Shi, Guohua; Zhang, Yudong

    2010-01-01

    With the use of adaptive optics (AO), high-resolution microscopic imaging of living human retina in the single cell level has been achieved. In an adaptive optics confocal scanning laser ophthalmoscope (AOSLO) system, with a small field size (about 1 degree, 280 μm), the motion of the eye severely affects the stabilization of the real-time video images and results in significant distortions of the retina images. In this paper, Scale-Invariant Feature Transform (SIFT) is used to abstract stable point features from the retina images. Kanade-Lucas-Tomasi(KLT) algorithm is applied to track the features. With the tracked features, the image distortion in each frame is removed by the second-order polynomial transformation, and 10 successive frames are co-added to enhance the image quality. Features of special interest in an image can also be selected manually and tracked by KLT. A point on a cone is selected manually, and the cone is tracked from frame to frame. PMID:21258443

  7. Differential morphology and image processing.

    PubMed

    Maragos, P

    1996-01-01

    Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

  8. Adaptive neuro-heuristic hybrid model for fruit peel defects detection.

    PubMed

    Woźniak, Marcin; Połap, Dawid

    2018-02-01

    Fusion of machine learning methods benefits in decision support systems. A composition of approaches gives a possibility to use the most efficient features composed into one solution. In this article we would like to present an approach to the development of adaptive method based on fusion of proposed novel neural architecture and heuristic search into one co-working solution. We propose a developed neural network architecture that adapts to processed input co-working with heuristic method used to precisely detect areas of interest. Input images are first decomposed into segments. This is to make processing easier, since in smaller images (decomposed segments) developed Adaptive Artificial Neural Network (AANN) processes less information what makes numerical calculations more precise. For each segment a descriptor vector is composed to be presented to the proposed AANN architecture. Evaluation is run adaptively, where the developed AANN adapts to inputs and their features by composed architecture. After evaluation, selected segments are forwarded to heuristic search, which detects areas of interest. As a result the system returns the image with pixels located over peel damages. Presented experimental research results on the developed solution are discussed and compared with other commonly used methods to validate the efficacy and the impact of the proposed fusion in the system structure and training process on classification results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Selections from 2017: Image Processing with AstroImageJ

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2017-12-01

    Editors note:In these last two weeks of 2017, well be looking at a few selections that we havent yet discussed on AAS Nova from among the most-downloaded paperspublished in AAS journals this year. The usual posting schedule will resume in January.AstroImageJ: Image Processing and Photometric Extraction for Ultra-Precise Astronomical Light CurvesPublished January2017The AIJ image display. A wide range of astronomy specific image display options and image analysis tools are available from the menus, quick access icons, and interactive histogram. [Collins et al. 2017]Main takeaway:AstroImageJ is a new integrated software package presented in a publication led byKaren Collins(Vanderbilt University,Fisk University, andUniversity of Louisville). Itenables new users even at the level of undergraduate student, high school student, or amateur astronomer to quickly start processing, modeling, and plotting astronomical image data.Why its interesting:Science doesnt just happen the momenta telescope captures a picture of a distantobject. Instead, astronomical images must firstbe carefully processed to clean up thedata, and this data must then be systematically analyzed to learn about the objects within it. AstroImageJ as a GUI-driven, easily installed, public-domain tool is a uniquelyaccessible tool for thisprocessing and analysis, allowing even non-specialist users to explore and visualizeastronomical data.Some features ofAstroImageJ:(as reported by Astrobites)Image calibration:generate master flat, dark, and bias framesImage arithmetic:combineimages viasubtraction, addition, division, multiplication, etc.Stack editing:easily perform operations on a series of imagesImage stabilization and image alignment featuresPrecise coordinate converters:calculate Heliocentric and Barycentric Julian DatesWCS coordinates:determine precisely where atelescope was pointed for an image by PlateSolving using Astronomy.netMacro and plugin support:write your own macrosMulti-aperture photometry

  10. Automated Coronal Loop Identification using Digital Image Processing Techniques

    NASA Astrophysics Data System (ADS)

    Lee, J. K.; Gary, G. A.; Newman, T. S.

    2003-05-01

    The results of a Master's thesis study of computer algorithms for automatic extraction and identification (i.e., collectively, "detection") of optically-thin, 3-dimensional, (solar) coronal-loop center "lines" from extreme ultraviolet and X-ray 2-dimensional images will be presented. The center lines, which can be considered to be splines, are proxies of magnetic field lines. Detecting the loops is challenging because there are no unique shapes, the loop edges are often indistinct, and because photon and detector noise heavily influence the images. Three techniques for detecting the projected magnetic field lines have been considered and will be described in the presentation. The three techniques used are (i) linear feature recognition of local patterns (related to the inertia-tensor concept), (ii) parametric space inferences via the Hough transform, and (iii) topological adaptive contours (snakes) that constrain curvature and continuity. Since coronal loop topology is dominated by the magnetic field structure, a first-order magnetic field approximation using multiple dipoles provides a priori information that has also been incorporated into the detection process. Synthesized images have been generated to benchmark the suitability of the three techniques, and the performance of the three techniques on both synthesized and solar images will be presented and numerically evaluated in the presentation. The process of automatic detection of coronal loops is important in the reconstruction of the coronal magnetic field where the derived magnetic field lines provide a boundary condition for magnetic models ( cf. , Gary (2001, Solar Phys., 203, 71) and Wiegelmann & Neukirch (2002, Solar Phys., 208, 233)). . This work was supported by NASA's Office of Space Science - Solar and Heliospheric Physics Supporting Research and Technology Program.

  11. 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,

  12. Software for MR image overlay guided needle insertions: the clinical translation process

    NASA Astrophysics Data System (ADS)

    Ungi, Tamas; U-Thainual, Paweena; Fritz, Jan; Iordachita, Iulian I.; Flammang, Aaron J.; Carrino, John A.; Fichtinger, Gabor

    2013-03-01

    PURPOSE: Needle guidance software using augmented reality image overlay was translated from the experimental phase to support preclinical and clinical studies. Major functional and structural changes were needed to meet clinical requirements. We present the process applied to fulfill these requirements, and selected features that may be applied in the translational phase of other image-guided surgical navigation systems. METHODS: We used an agile software development process for rapid adaptation to unforeseen clinical requests. The process is based on iterations of operating room test sessions, feedback discussions, and software development sprints. The open-source application framework of 3D Slicer and the NA-MIC kit provided sufficient flexibility and stable software foundations for this work. RESULTS: All requirements were addressed in a process with 19 operating room test iterations. Most features developed in this phase were related to workflow simplification and operator feedback. CONCLUSION: Efficient and affordable modifications were facilitated by an open source application framework and frequent clinical feedback sessions. Results of cadaver experiments show that software requirements were successfully solved after a limited number of operating room tests.

  13. Sensory Processing Subtypes in Autism: Association with Adaptive Behavior

    ERIC Educational Resources Information Center

    Lane, Alison E.; Young, Robyn L.; Baker, Amy E. Z.; Angley, Manya T.

    2010-01-01

    Children with autism are frequently observed to experience difficulties in sensory processing. This study examined specific patterns of sensory processing in 54 children with autistic disorder and their association with adaptive behavior. Model-based cluster analysis revealed three distinct sensory processing subtypes in autism. These subtypes…

  14. Research on the liquid crystal adaptive optics system for human retinal imaging

    NASA Astrophysics Data System (ADS)

    Zhang, Lei; Tong, Shoufeng; Song, Yansong; Zhao, Xin

    2013-12-01

    The blood vessels only in Human eye retinal can be observed directly. Many diseases that are not obvious in their early symptom can be diagnosed through observing the changes of distal micro blood vessel. In order to obtain the high resolution human retinal images,an adaptive optical system for correcting the aberration of the human eye was designed by using the Shack-Hartmann wavefront sensor and the Liquid Crystal Spatial Light Modulator(LCLSM) .For a subject eye with 8m-1 (8D)myopia, the wavefront error is reduced to 0.084 λ PV and 0.12 λRMS after adaptive optics(AO) correction ,which has reached diffraction limit.The results show that the LCLSM based AO system has the ability of correcting the aberration of the human eye efficiently,and making the blurred photoreceptor cell to clearly image on a CCD camera.

  15. A new approach to pre-processing digital image for wavelet-based watermark

    NASA Astrophysics Data System (ADS)

    Agreste, Santa; Andaloro, Guido

    2008-11-01

    The growth of the Internet has increased the phenomenon of digital piracy, in multimedia objects, like software, image, video, audio and text. Therefore it is strategic to individualize and to develop methods and numerical algorithms, which are stable and have low computational cost, that will allow us to find a solution to these problems. We describe a digital watermarking algorithm for color image protection and authenticity: robust, not blind, and wavelet-based. The use of Discrete Wavelet Transform is motivated by good time-frequency features and a good match with Human Visual System directives. These two combined elements are important for building an invisible and robust watermark. Moreover our algorithm can work with any image, thanks to the step of pre-processing of the image that includes resize techniques that adapt to the size of the original image for Wavelet transform. The watermark signal is calculated in correlation with the image features and statistic properties. In the detection step we apply a re-synchronization between the original and watermarked image according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has been shown to be resistant against geometric, filtering, and StirMark attacks with a low rate of false alarm.

  16. Negotiating uncertainty: the transitional process of adapting to life with HIV.

    PubMed

    Perrett, Stephanie E; Biley, Francis C

    2013-01-01

    Glaser's (1978) grounded-theory method was used to investigate the transitional process of adapting to life with HIV. Semistructured interviews took place with 8 male HIV-infected participants recruited from a clinic in South Wales, United Kingdom. Data analysis used open, substantive, and theoretical coding. Adapting to a life with HIV infection emerged as a process of adapting to uncertainty with "negotiating uncertainty" as a core concept. Seven subcategories represented movements between bipolar opposites labeled "anticipating hopelessness" and "regaining optimism." This work progresses the theoretical concepts of transitions, uncertainty, and adaptation in relation to the HIV experience. Copyright © 2013 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

  17. WE-G-BRF-09: Force- and Image-Adaptive Strategies for Robotised Placement of 4D Ultrasound Probes

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

    Kuhlemann, I; Graduate School for Computing in Life Science, University of Luebeck, Luebeck; Bruder, R

    2014-06-15

    Purpose: To allow continuous acquisition of high quality 4D ultrasound images for non-invasive live tracking of tumours for IGRT, image- and force-adaptive strategies for robotised placement of 4D ultrasound probes are developed and evaluated. Methods: The developed robotised ultrasound system is based on a 6-axes industrial robot (adept Viper s850) carrying a 4D ultrasound transducer with a mounted force-torque sensor. The force-adaptive placement strategies include probe position control using artificial potential fields and contact pressure regulation by a PD controller strategy. The basis for live target tracking is a continuous minimum contact pressure to ensure good image quality and highmore » patient comfort. This contact pressure can be significantly disturbed by respiratory movements and has to be compensated. All measurements were performed on human subjects under realistic conditions. When performing cardiac ultrasound, rib- and lung shadows are a common source of interference and can disrupt the tracking. To ensure continuous tracking, these artefacts had to be detected to automatically realign the probe. The detection is realised by multiple algorithms based on entropy calculations as well as a determination of the image quality. Results: Through active contact pressure regulation it was possible to reduce the variance of the contact pressure by 89.79% despite respiratory motion of the chest. The results regarding the image processing clearly demonstrate the feasibility to detect image artefacts like rib shadows in real-time. Conclusion: In all cases, it was possible to stabilise the image quality by active contact pressure control and automatically detected image artefacts. This fact enables the possibility to compensate for such interferences by realigning the probe and thus continuously optimising the ultrasound images. This is a huge step towards fully automated transducer positioning and opens the possibility for stable target tracking in

  18. [Role adaptation process of elementary school health teachers: establishing their own positions].

    PubMed

    Lee, Jeong Hee; Lee, Byoung Sook

    2014-06-01

    The purpose of this study was to explore and identify patterns from the phenomenon of the role adaptation process in elementary school health teachers and finally, suggest a model to describe the process. Grounded theory methodology and focus group interviews were used. Data were collected from 24 participants of four focus groups. The questions used were about their experience of role adaptation including situational contexts and interactional coping strategies. Transcribed data and field notes were analyzed with continuous comparative analysis. The core category was 'establishing their own positions', an interactional coping strategy. The phenomenon identified by participants was confusion and wandering in their role performance. Influencing contexts were unclear beliefs for their role as health teachers and non-supportive job environments. The result of the adaptation process was consolidation of their positions. Pride as health teachers and social recognition and supports intervened to produce that result. The process had three stages; entry, growth, and maturity. The role adaptation process of elementary school health teachers can be explained as establishing, strengthening and consolidating their own positions. Results of this study can be used as fundamental information for developing programs to support the role adaptation of health teachers.

  19. Ultrahigh-speed ultrahigh-resolution adaptive optics: optical coherence tomography system for in-vivo small animal retinal imaging

    NASA Astrophysics Data System (ADS)

    Jian, Yifan; Xu, Jing; Zawadzki, Robert J.; Sarunic, Marinko V.

    2013-03-01

    Small animal models of human retinal diseases are a critical component of vision research. In this report, we present an ultrahigh-resolution ultrahigh-speed adaptive optics optical coherence tomography (AO-OCT) system for small animal retinal imaging (mouse, fish, etc.). We adapted our imaging system to different types of small animals in accordance with the optical properties of their eyes. Results of AO-OCT images of small animal retinas acquired with AO correction are presented. Cellular structures including nerve fiber bundles, capillary networks and detailed double-cone photoreceptors are visualized.

  20. MAD Adaptive Optics Imaging of High-luminosity Quasars: A Pilot Project

    NASA Astrophysics Data System (ADS)

    Liuzzo, E.; Falomo, R.; Paiano, S.; Treves, A.; Uslenghi, M.; Arcidiacono, C.; Baruffolo, A.; Diolaiti, E.; Farinato, J.; Lombini, M.; Moretti, A.; Ragazzoni, R.; Brast, R.; Donaldson, R.; Kolb, J.; Marchetti, E.; Tordo, S.

    2016-08-01

    We present near-IR images of five luminous quasars at z ˜ 2 and one at z ˜ 4 obtained with an experimental adaptive optics (AO) instrument at the European Southern Observatory Very Large Telescope. The observations are part of a program aimed at demonstrating the capabilities of multi-conjugated adaptive optics imaging combined with the use of natural guide stars for high spatial resolution studies on large telescopes. The observations were mostly obtained under poor seeing conditions but in two cases. In spite of these nonoptimal conditions, the resulting images of point sources have cores of FWHM ˜ 0.2 arcsec. We are able to characterize the host galaxy properties for two sources and set stringent upper limits to the galaxy luminosity for the others. We also report on the expected capabilities for investigating the host galaxies of distant quasars with AO systems coupled with future Extremely Large Telescopes. Detailed simulations show that it will be possible to characterize compact (2-3 kpc) quasar host galaxies for quasi-stellar objects at z = 2 with nucleus K-magnitude spanning from 15 to 20 (corresponding to absolute magnitude -31 to -26) and host galaxies that are 4 mag fainter than their nuclei.

  1. MAD ADAPTIVE OPTICS IMAGING OF HIGH-LUMINOSITY QUASARS: A PILOT PROJECT

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

    Liuzzo, E.; Falomo, R.; Paiano, S.

    2016-08-01

    We present near-IR images of five luminous quasars at z ∼ 2 and one at z ∼ 4 obtained with an experimental adaptive optics (AO) instrument at the European Southern Observatory Very Large Telescope. The observations are part of a program aimed at demonstrating the capabilities of multi-conjugated adaptive optics imaging combined with the use of natural guide stars for high spatial resolution studies on large telescopes. The observations were mostly obtained under poor seeing conditions but in two cases. In spite of these nonoptimal conditions, the resulting images of point sources have cores of FWHM ∼ 0.2 arcsec. Wemore » are able to characterize the host galaxy properties for two sources and set stringent upper limits to the galaxy luminosity for the others. We also report on the expected capabilities for investigating the host galaxies of distant quasars with AO systems coupled with future Extremely Large Telescopes. Detailed simulations show that it will be possible to characterize compact (2–3 kpc) quasar host galaxies for quasi-stellar objects at z = 2 with nucleus K -magnitude spanning from 15 to 20 (corresponding to absolute magnitude −31 to −26) and host galaxies that are 4 mag fainter than their nuclei.« less

  2. Predictive images of postoperative levator resection outcome using image processing software.

    PubMed

    Mawatari, Yuki; Fukushima, Mikiko

    2016-01-01

    This study aims to evaluate the efficacy of processed images to predict postoperative appearance following levator resection. Analysis involved 109 eyes from 65 patients with blepharoptosis who underwent advancement of levator aponeurosis and Müller's muscle complex (levator resection). Predictive images were prepared from preoperative photographs using the image processing software (Adobe Photoshop ® ). Images of selected eyes were digitally enlarged in an appropriate manner and shown to patients prior to surgery. Approximately 1 month postoperatively, we surveyed our patients using questionnaires. Fifty-six patients (89.2%) were satisfied with their postoperative appearances, and 55 patients (84.8%) positively responded to the usefulness of processed images to predict postoperative appearance. Showing processed images that predict postoperative appearance to patients prior to blepharoptosis surgery can be useful for those patients concerned with their postoperative appearance. This approach may serve as a useful tool to simulate blepharoptosis surgery.

  3. 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.

  4. Similarities in error processing establish a link between saccade prediction at baseline and adaptation performance.

    PubMed

    Wong, Aaron L; Shelhamer, Mark

    2014-05-01

    Adaptive processes are crucial in maintaining the accuracy of body movements and rely on error storage and processing mechanisms. Although classically studied with adaptation paradigms, evidence of these ongoing error-correction mechanisms should also be detectable in other movements. Despite this connection, current adaptation models are challenged when forecasting adaptation ability with measures of baseline behavior. On the other hand, we have previously identified an error-correction process present in a particular form of baseline behavior, the generation of predictive saccades. This process exhibits long-term intertrial correlations that decay gradually (as a power law) and are best characterized with the tools of fractal time series analysis. Since this baseline task and adaptation both involve error storage and processing, we sought to find a link between the intertrial correlations of the error-correction process in predictive saccades and the ability of subjects to alter their saccade amplitudes during an adaptation task. Here we find just such a relationship: the stronger the intertrial correlations during prediction, the more rapid the acquisition of adaptation. This reinforces the links found previously between prediction and adaptation in motor control and suggests that current adaptation models are inadequate to capture the complete dynamics of these error-correction processes. A better understanding of the similarities in error processing between prediction and adaptation might provide the means to forecast adaptation ability with a baseline task. This would have many potential uses in physical therapy and the general design of paradigms of motor adaptation. Copyright © 2014 the American Physiological Society.

  5. Image Processing for Cameras with Fiber Bundle Image Relay

    DTIC Science & Technology

    length. Optical fiber bundles have been used to couple between this focal surface and planar image sensors . However, such fiber-coupled imaging systems...coupled to six discrete CMOS focal planes. We characterize the locally space-variant system impulse response at various stages: monocentric lens image...vignetting, and stitch together the image data from discrete sensors into a single panorama. We compare processed images from the prototype to those taken with

  6. Receptoral and postreceptoral visual processes in recovery from chromatic adaptation.

    PubMed Central

    Jameson, D; Hurvich, L M; Varner, F D

    1979-01-01

    The time course of recovery from chromatic adaptation in human vision was tracked by determining the wavelength of light that appears uniquely yellow (neither red nor green) both before and after exposure to yellowish green and yellowish red adapting lights. Recovery is complete within 5 min after steady light exposure. After exposure to the alternating repeated sequence 10-sec light/10-sec dark, the initial magnitude of the aftereffect is reduced but recovery is retarded. The results are interpreted in terms of two processes located at different levels in the hierarchical organization of the visual system. One is a change in the balance of cone receptor sensitivities; the second is a shift in the equilibrium baseline between opposite-signed responses of the red/green channel at the opponent-process neural level. The baseline-shift mechanism is effective in the condition in which repeated input signals originating at the receptors are of sufficient strength to activate the system effectively. Hence, this process is revealed in the alternating adaptation condition when the receptors undergo partial recovery after each light exposure, but receptor adaptation during continued steady light exposure effectively protects the subsequent neural systems from continued strong activation. PMID:288087

  7. A self-adaptive algorithm for traffic sign detection in motion image based on color and shape features

    NASA Astrophysics Data System (ADS)

    Zhang, Ka; Sheng, Yehua; Gong, Zhijun; Ye, Chun; Li, Yongqiang; Liang, Cheng

    2007-06-01

    As an important sub-system in intelligent transportation system (ITS), the detection and recognition of traffic signs from mobile images is becoming one of the hot spots in the international research field of ITS. Considering the problem of traffic sign automatic detection in motion images, a new self-adaptive algorithm for traffic sign detection based on color and shape features is proposed in this paper. Firstly, global statistical color features of different images are computed based on statistics theory. Secondly, some self-adaptive thresholds and special segmentation rules for image segmentation are designed according to these global color features. Then, for red, yellow and blue traffic signs, the color image is segmented to three binary images by these thresholds and rules. Thirdly, if the number of white pixels in the segmented binary image exceeds the filtering threshold, the binary image should be further filtered. Fourthly, the method of gray-value projection is used to confirm top, bottom, left and right boundaries for candidate regions of traffic signs in the segmented binary image. Lastly, if the shape feature of candidate region satisfies the need of real traffic sign, this candidate region is confirmed as the detected traffic sign region. The new algorithm is applied to actual motion images of natural scenes taken by a CCD camera of the mobile photogrammetry system in Nanjing at different time. The experimental results show that the algorithm is not only simple, robust and more adaptive to natural scene images, but also reliable and high-speed on real traffic sign detection.

  8. Predictive images of postoperative levator resection outcome using image processing software

    PubMed Central

    Mawatari, Yuki; Fukushima, Mikiko

    2016-01-01

    Purpose This study aims to evaluate the efficacy of processed images to predict postoperative appearance following levator resection. Methods Analysis involved 109 eyes from 65 patients with blepharoptosis who underwent advancement of levator aponeurosis and Müller’s muscle complex (levator resection). Predictive images were prepared from preoperative photographs using the image processing software (Adobe Photoshop®). Images of selected eyes were digitally enlarged in an appropriate manner and shown to patients prior to surgery. Results Approximately 1 month postoperatively, we surveyed our patients using questionnaires. Fifty-six patients (89.2%) were satisfied with their postoperative appearances, and 55 patients (84.8%) positively responded to the usefulness of processed images to predict postoperative appearance. Conclusion Showing processed images that predict postoperative appearance to patients prior to blepharoptosis surgery can be useful for those patients concerned with their postoperative appearance. This approach may serve as a useful tool to simulate blepharoptosis surgery. PMID:27757008

  9. Experimental Demonstration of Adaptive Infrared Multispectral Imaging using Plasmonic Filter Array.

    PubMed

    Jang, Woo-Yong; Ku, Zahyun; Jeon, Jiyeon; Kim, Jun Oh; Lee, Sang Jun; Park, James; Noyola, Michael J; Urbas, Augustine

    2016-10-10

    In our previous theoretical study, we performed target detection using a plasmonic sensor array incorporating the data-processing technique termed "algorithmic spectrometry". We achieved the reconstruction of a target spectrum by extracting intensity at multiple wavelengths with high resolution from the image data obtained from the plasmonic array. The ultimate goal is to develop a full-scale focal plane array with a plasmonic opto-coupler in order to move towards the next generation of versatile infrared cameras. To this end, and as an intermediate step, this paper reports the experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios. Each plasmonic filter was designed using periodic circular holes perforated through a gold layer, and an enhanced target detection strategy was proposed to refine the original spectrometry concept for spatial and spectral computation of the data measured from the plasmonic array. Both the spectrum of blackbody radiation and a metal ring object at multiple wavelengths were successfully reconstructed using the weighted superposition of plasmonic output images as specified in the proposed detection strategy. In addition, plasmonic filter arrays were theoretically tested on a target at extremely high temperature as a challenging scenario for the detection scheme.

  10. Experimental Demonstration of Adaptive Infrared Multispectral Imaging using Plasmonic Filter Array

    PubMed Central

    Jang, Woo-Yong; Ku, Zahyun; Jeon, Jiyeon; Kim, Jun Oh; Lee, Sang Jun; Park, James; Noyola, Michael J.; Urbas, Augustine

    2016-01-01

    In our previous theoretical study, we performed target detection using a plasmonic sensor array incorporating the data-processing technique termed “algorithmic spectrometry”. We achieved the reconstruction of a target spectrum by extracting intensity at multiple wavelengths with high resolution from the image data obtained from the plasmonic array. The ultimate goal is to develop a full-scale focal plane array with a plasmonic opto-coupler in order to move towards the next generation of versatile infrared cameras. To this end, and as an intermediate step, this paper reports the experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios. Each plasmonic filter was designed using periodic circular holes perforated through a gold layer, and an enhanced target detection strategy was proposed to refine the original spectrometry concept for spatial and spectral computation of the data measured from the plasmonic array. Both the spectrum of blackbody radiation and a metal ring object at multiple wavelengths were successfully reconstructed using the weighted superposition of plasmonic output images as specified in the proposed detection strategy. In addition, plasmonic filter arrays were theoretically tested on a target at extremely high temperature as a challenging scenario for the detection scheme. PMID:27721506

  11. In vivo imaging of human retinal microvasculature using adaptive optics scanning light ophthalmoscope fluorescein angiography

    PubMed Central

    Pinhas, Alexander; Dubow, Michael; Shah, Nishit; Chui, Toco Y.; Scoles, Drew; Sulai, Yusufu N.; Weitz, Rishard; Walsh, Joseph B.; Carroll, Joseph; Dubra, Alfredo; Rosen, Richard B.

    2013-01-01

    The adaptive optics scanning light ophthalmoscope (AOSLO) allows visualization of microscopic structures of the human retina in vivo. In this work, we demonstrate its application in combination with oral and intravenous (IV) fluorescein angiography (FA) to the in vivo visualization of the human retinal microvasculature. Ten healthy subjects ages 20 to 38 years were imaged using oral (7 and/or 20 mg/kg) and/or IV (500 mg) fluorescein. In agreement with current literature, there were no adverse effects among the patients receiving oral fluorescein while one patient receiving IV fluorescein experienced some nausea and heaving. We determined that all retinal capillary beds can be imaged using clinically accepted fluorescein dosages and safe light levels according to the ANSI Z136.1-2000 maximum permissible exposure. As expected, the 20 mg/kg oral dose showed higher image intensity for a longer period of time than did the 7 mg/kg oral and the 500 mg IV doses. The increased resolution of AOSLO FA, compared to conventional FA, offers great opportunity for studying physiological and pathological vascular processes. PMID:24009994

  12. Cone photoreceptor definition on adaptive optics retinal imaging.

    PubMed

    Muthiah, Manickam Nick; Gias, Carlos; Chen, Fred Kuanfu; Zhong, Joe; McClelland, Zoe; Sallo, Ferenc B; Peto, Tunde; Coffey, Peter J; da Cruz, Lyndon

    2014-08-01

    To quantitatively analyse cone photoreceptor matrices on images captured on an adaptive optics (AO) camera and assess their correlation to well-established parameters in the retinal histology literature. High resolution retinal images were acquired from 10 healthy subjects, aged 20-35 years old, using an AO camera (rtx1, Imagine Eyes, France). Left eye images were captured at 5° of retinal eccentricity, temporal to the fovea for consistency. In three subjects, images were also acquired at 0, 2, 3, 5 and 7° retinal eccentricities. Cone photoreceptor density was calculated following manual and automated counting. Inter-photoreceptor distance was also calculated. Voronoi domain and power spectrum analyses were performed for all images. At 5° eccentricity, the cone density (cones/mm(2) mean±SD) was 15.3±1.4×10(3) (automated) and 13.9±1.0×10(3) (manual) and the mean inter-photoreceptor distance was 8.6±0.4 μm. Cone density decreased and inter-photoreceptor distance increased with increasing retinal eccentricity from 2 to 7°. A regular hexagonal cone photoreceptor mosaic pattern was seen at 2, 3 and 5° of retinal eccentricity. Imaging data acquired from the AO camera match cone density, intercone distance and show the known features of cone photoreceptor distribution in the pericentral retina as reported by histology, namely, decreasing density values from 2 to 7° of eccentricity and the hexagonal packing arrangement. This confirms that AO flood imaging provides reliable estimates of pericentral cone photoreceptor distribution in normal subjects. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  13. Analysis of microvascular perfusion with multi-dimensional complete ensemble empirical mode decomposition with adaptive noise algorithm: Processing of laser speckle contrast images recorded in healthy subjects, at rest and during acetylcholine stimulation.

    PubMed

    Humeau-Heurtier, Anne; Marche, Pauline; Dubois, Severine; Mahe, Guillaume

    2015-01-01

    Laser speckle contrast imaging (LSCI) is a full-field imaging modality to monitor microvascular blood flow. It is able to give images with high temporal and spatial resolutions. However, when the skin is studied, the interpretation of the bidimensional data may be difficult. This is why an averaging of the perfusion values in regions of interest is often performed and the result is followed in time, reducing the data to monodimensional time series. In order to avoid such a procedure (that leads to a loss of the spatial resolution), we propose to extract patterns from LSCI data and to compare these patterns for two physiological states in healthy subjects: at rest and at the peak of acetylcholine-induced perfusion peak. For this purpose, the recent multi-dimensional complete ensemble empirical mode decomposition with adaptive noise (MCEEMDAN) algorithm is applied to LSCI data. The results show that the intrinsic mode functions and residue given by MCEEMDAN show different patterns for the two physiological states. The images, as bidimensional data, can therefore be processed to reveal microvascular perfusion patterns, hidden in the images themselves. This work is therefore a feasibility study before analyzing data in patients with microvascular dysfunctions.

  14. Process perspective on image quality evaluation

    NASA Astrophysics Data System (ADS)

    Leisti, Tuomas; Halonen, Raisa; Kokkonen, Anna; Weckman, Hanna; Mettänen, Marja; Lensu, Lasse; Ritala, Risto; Oittinen, Pirkko; Nyman, Göte

    2008-01-01

    The psychological complexity of multivariate image quality evaluation makes it difficult to develop general image quality metrics. Quality evaluation includes several mental processes and ignoring these processes and the use of a few test images can lead to biased results. By using a qualitative/quantitative (Interpretation Based Quality, IBQ) methodology, we examined the process of pair-wise comparison in a setting, where the quality of the images printed by laser printer on different paper grades was evaluated. Test image consisted of a picture of a table covered with several objects. Three other images were also used, photographs of a woman, cityscape and countryside. In addition to the pair-wise comparisons, observers (N=10) were interviewed about the subjective quality attributes they used in making their quality decisions. An examination of the individual pair-wise comparisons revealed serious inconsistencies in observers' evaluations on the test image content, but not on other contexts. The qualitative analysis showed that this inconsistency was due to the observers' focus of attention. The lack of easily recognizable context in the test image may have contributed to this inconsistency. To obtain reliable knowledge of the effect of image context or attention on subjective image quality, a qualitative methodology is needed.

  15. Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

    PubMed

    Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

    2014-05-01

    In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

  16. Digital processing of radiographic images

    NASA Technical Reports Server (NTRS)

    Bond, A. D.; Ramapriyan, H. K.

    1973-01-01

    Some techniques are presented and the software documentation for the digital enhancement of radiographs. Both image handling and image processing operations are considered. The image handling operations dealt with are: (1) conversion of format of data from packed to unpacked and vice versa; (2) automatic extraction of image data arrays; (3) transposition and 90 deg rotations of large data arrays; (4) translation of data arrays for registration; and (5) reduction of the dimensions of data arrays by integral factors. Both the frequency and the spatial domain approaches are presented for the design and implementation of the image processing operation. It is shown that spatial domain recursive implementation of filters is much faster than nonrecursive implementations using fast fourier transforms (FFT) for the cases of interest in this work. The recursive implementation of a class of matched filters for enhancing image signal to noise ratio is described. Test patterns are used to illustrate the filtering operations. The application of the techniques to radiographic images of metallic structures is demonstrated through several examples.

  17. High-performance image processing on the desktop

    NASA Astrophysics Data System (ADS)

    Jordan, Stephen D.

    1996-04-01

    The suitability of computers to the task of medical image visualization for the purposes of primary diagnosis and treatment planning depends on three factors: speed, image quality, and price. To be widely accepted the technology must increase the efficiency of the diagnostic and planning processes. This requires processing and displaying medical images of various modalities in real-time, with accuracy and clarity, on an affordable system. Our approach to meeting this challenge began with market research to understand customer image processing needs. These needs were translated into system-level requirements, which in turn were used to determine which image processing functions should be implemented in hardware. The result is a computer architecture for 2D image processing that is both high-speed and cost-effective. The architectural solution is based on the high-performance PA-RISC workstation with an HCRX graphics accelerator. The image processing enhancements are incorporated into the image visualization accelerator (IVX) which attaches to the HCRX graphics subsystem. The IVX includes a custom VLSI chip which has a programmable convolver, a window/level mapper, and an interpolator supporting nearest-neighbor, bi-linear, and bi-cubic modes. This combination of features can be used to enable simultaneous convolution, pan, zoom, rotate, and window/level control into 1 k by 1 k by 16-bit medical images at 40 frames/second.

  18. Uncertainty during pain anticipation: the adaptive value of preparatory processes.

    PubMed

    Seidel, Eva-Maria; Pfabigan, Daniela M; Hahn, Andreas; Sladky, Ronald; Grahl, Arvina; Paul, Katharina; Kraus, Christoph; Küblböck, Martin; Kranz, Georg S; Hummer, Allan; Lanzenberger, Rupert; Windischberger, Christian; Lamm, Claus

    2015-02-01

    Anticipatory processes prepare the organism for upcoming experiences. The aim of this study was to investigate neural responses related to anticipation and processing of painful stimuli occurring with different levels of uncertainty. Twenty-five participants (13 females) took part in an electroencephalography and functional magnetic resonance imaging (fMRI) experiment at separate times. A visual cue announced the occurrence of an electrical painful or nonpainful stimulus, delivered with certainty or uncertainty (50% chance), at some point during the following 15 s. During the first 2 s of the anticipation phase, a strong effect of uncertainty was reflected in a pronounced frontal stimulus-preceding negativity (SPN) and increased fMRI activation in higher visual processing areas. In the last 2 s before stimulus delivery, we observed stimulus-specific preparatory processes indicated by a centroparietal SPN and posterior insula activation that was most pronounced for the certain pain condition. Uncertain anticipation was associated with attentional control processes. During stimulation, the results revealed that unexpected painful stimuli produced the strongest activation in the affective pain processing network and a more pronounced offset-P2. Our results reflect that during early anticipation uncertainty is strongly associated with affective mechanisms and seems to be a more salient event compared to certain anticipation. During the last 2 s before stimulation, attentional control mechanisms are initiated related to the increased salience of uncertainty. Furthermore, stimulus-specific preparatory mechanisms during certain anticipation also shaped the response to stimulation, underlining the adaptive value of stimulus-targeted preparatory activity which is less likely when facing an uncertain event. © 2014 Wiley Periodicals, Inc.

  19. FITS Liberator: Image processing software

    NASA Astrophysics Data System (ADS)

    Lindberg Christensen, Lars; Nielsen, Lars Holm; Nielsen, Kaspar K.; Johansen, Teis; Hurt, Robert; de Martin, David

    2012-06-01

    The ESA/ESO/NASA FITS Liberator makes it possible to process and edit astronomical science data in the FITS format to produce stunning images of the universe. Formerly a plugin for Adobe Photoshop, the current version of FITS Liberator is a stand-alone application and no longer requires Photoshop. This image processing software makes it possible to create color images using raw observations from a range of telescopes; the FITS Liberator continues to support the FITS and PDS formats, preferred by astronomers and planetary scientists respectively, which enables data to be processed from a wide range of telescopes and planetary probes, including ESO's Very Large Telescope, the NASA/ESA Hubble Space Telescope, NASA's Spitzer Space Telescope, ESA's XMM-Newton Telescope and Cassini-Huygens or Mars Reconnaissance Orbiter.

  20. VIP: Vortex Image Processing Package for High-contrast Direct Imaging

    NASA Astrophysics Data System (ADS)

    Gomez Gonzalez, Carlos Alberto; Wertz, Olivier; Absil, Olivier; Christiaens, Valentin; Defrère, Denis; Mawet, Dimitri; Milli, Julien; Absil, Pierre-Antoine; Van Droogenbroeck, Marc; Cantalloube, Faustine; Hinz, Philip M.; Skemer, Andrew J.; Karlsson, Mikael; Surdej, Jean

    2017-07-01

    We present the Vortex Image Processing (VIP) library, a python package dedicated to astronomical high-contrast imaging. Our package relies on the extensive python stack of scientific libraries and aims to provide a flexible framework for high-contrast data and image processing. In this paper, we describe the capabilities of VIP related to processing image sequences acquired using the angular differential imaging (ADI) observing technique. VIP implements functionalities for building high-contrast data processing pipelines, encompassing pre- and post-processing algorithms, potential source position and flux estimation, and sensitivity curve generation. Among the reference point-spread function subtraction techniques for ADI post-processing, VIP includes several flavors of principal component analysis (PCA) based algorithms, such as annular PCA and incremental PCA algorithms capable of processing big datacubes (of several gigabytes) on a computer with limited memory. Also, we present a novel ADI algorithm based on non-negative matrix factorization, which comes from the same family of low-rank matrix approximations as PCA and provides fairly similar results. We showcase the ADI capabilities of the VIP library using a deep sequence on HR 8799 taken with the LBTI/LMIRCam and its recently commissioned L-band vortex coronagraph. Using VIP, we investigated the presence of additional companions around HR 8799 and did not find any significant additional point source beyond the four known planets. VIP is available at http://github.com/vortex-exoplanet/VIP and is accompanied with Jupyter notebook tutorials illustrating the main functionalities of the library.

  1. A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

    PubMed

    Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M

    2011-09-01

    Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics

  2. An analysis of neural receptive field plasticity by point process adaptive filtering

    PubMed Central

    Brown, Emery N.; Nguyen, David P.; Frank, Loren M.; Wilson, Matthew A.; Solo, Victor

    2001-01-01

    Neural receptive fields are plastic: with experience, neurons in many brain regions change their spiking responses to relevant stimuli. Analysis of receptive field plasticity from experimental measurements is crucial for understanding how neural systems adapt their representations of relevant biological information. Current analysis methods using histogram estimates of spike rate functions in nonoverlapping temporal windows do not track the evolution of receptive field plasticity on a fine time scale. Adaptive signal processing is an established engineering paradigm for estimating time-varying system parameters from experimental measurements. We present an adaptive filter algorithm for tracking neural receptive field plasticity based on point process models of spike train activity. We derive an instantaneous steepest descent algorithm by using as the criterion function the instantaneous log likelihood of a point process spike train model. We apply the point process adaptive filter algorithm in a study of spatial (place) receptive field properties of simulated and actual spike train data from rat CA1 hippocampal neurons. A stability analysis of the algorithm is sketched in the Appendix. The adaptive algorithm can update the place field parameter estimates on a millisecond time scale. It reliably tracked the migration, changes in scale, and changes in maximum firing rate characteristic of hippocampal place fields in a rat running on a linear track. Point process adaptive filtering offers an analytic method for studying the dynamics of neural receptive fields. PMID:11593043

  3. Quantitative image processing in fluid mechanics

    NASA Technical Reports Server (NTRS)

    Hesselink, Lambertus; Helman, James; Ning, Paul

    1992-01-01

    The current status of digital image processing in fluid flow research is reviewed. In particular, attention is given to a comprehensive approach to the extraction of quantitative data from multivariate databases and examples of recent developments. The discussion covers numerical simulations and experiments, data processing, generation and dissemination of knowledge, traditional image processing, hybrid processing, fluid flow vector field topology, and isosurface analysis using Marching Cubes.

  4. Real-time optical image processing techniques

    NASA Technical Reports Server (NTRS)

    Liu, Hua-Kuang

    1988-01-01

    Nonlinear real-time optical processing on spatial pulse frequency modulation has been pursued through the analysis, design, and fabrication of pulse frequency modulated halftone screens and the modification of micro-channel spatial light modulators (MSLMs). Micro-channel spatial light modulators are modified via the Fabry-Perot method to achieve the high gamma operation required for non-linear operation. Real-time nonlinear processing was performed using the halftone screen and MSLM. The experiments showed the effectiveness of the thresholding and also showed the needs of higher SBP for image processing. The Hughes LCLV has been characterized and found to yield high gamma (about 1.7) when operated in low frequency and low bias mode. Cascading of two LCLVs should also provide enough gamma for nonlinear processing. In this case, the SBP of the LCLV is sufficient but the uniformity of the LCLV needs improvement. These include image correlation, computer generation of holograms, pseudo-color image encoding for image enhancement, and associative-retrieval in neural processing. The discovery of the only known optical method for dynamic range compression of an input image in real-time by using GaAs photorefractive crystals is reported. Finally, a new architecture for non-linear multiple sensory, neural processing has been suggested.

  5. Adaptive Optics Images of the Galactic Center: Using Empirical Noise-maps to Optimize Image Analysis

    NASA Astrophysics Data System (ADS)

    Albers, Saundra; Witzel, Gunther; Meyer, Leo; Sitarski, Breann; Boehle, Anna; Ghez, Andrea M.

    2015-01-01

    Adaptive Optics images are one of the most important tools in studying our Galactic Center. In-depth knowledge of the noise characteristics is crucial to optimally analyze this data. Empirical noise estimates - often represented by a constant value for the entire image - can be greatly improved by computing the local detector properties and photon noise contributions pixel by pixel. To comprehensively determine the noise, we create a noise model for each image using the three main contributors—photon noise of stellar sources, sky noise, and dark noise. We propagate the uncertainties through all reduction steps and analyze the resulting map using Starfinder. The estimation of local noise properties helps to eliminate fake detections while improving the detection limit of fainter sources. We predict that a rigorous understanding of noise allows a more robust investigation of the stellar dynamics in the center of our Galaxy.

  6. Optimal processing for gel electrophoresis images: Applying Monte Carlo Tree Search in GelApp.

    PubMed

    Nguyen, Phi-Vu; Ghezal, Ali; Hsueh, Ya-Chih; Boudier, Thomas; Gan, Samuel Ken-En; Lee, Hwee Kuan

    2016-08-01

    In biomedical research, gel band size estimation in electrophoresis analysis is a routine process. To facilitate and automate this process, numerous software have been released, notably the GelApp mobile app. However, the band detection accuracy is limited due to a band detection algorithm that cannot adapt to the variations in input images. To address this, we used the Monte Carlo Tree Search with Upper Confidence Bound (MCTS-UCB) method to efficiently search for optimal image processing pipelines for the band detection task, thereby improving the segmentation algorithm. Incorporating this into GelApp, we report a significant enhancement of gel band detection accuracy by 55.9 ± 2.0% for protein polyacrylamide gels, and 35.9 ± 2.5% for DNA SYBR green agarose gels. This implementation is a proof-of-concept in demonstrating MCTS-UCB as a strategy to optimize general image segmentation. The improved version of GelApp-GelApp 2.0-is freely available on both Google Play Store (for Android platform), and Apple App Store (for iOS platform). © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Adaptive Processing Experiment (APE) Phase II

    DTIC Science & Technology

    1976-05-01

    P*T*~--- - ~ q ~ IPY , U.S. DEPARTMENT OF COMMERCE National Technical Information Service t AD/A-027 071 ADAPTIVE PROCESSING EXPERIMENT (APE...4 newsletter service covering the most recentik" research findings in 25 areas of industrial, The weekly w•Nsletter series will keep you...and professional informa- wish. Please request NTIS-PR-186/PCN for tion service provided by NTIS in the Weekly more information. Government Abstracts

  8. 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

  9. Adaptive foveated single-pixel imaging with dynamic supersampling

    PubMed Central

    Phillips, David B.; Sun, Ming-Jie; Taylor, Jonathan M.; Edgar, Matthew P.; Barnett, Stephen M.; Gibson, Graham M.; Padgett, Miles J.

    2017-01-01

    In contrast to conventional multipixel cameras, single-pixel cameras capture images using a single detector that measures the correlations between the scene and a set of patterns. However, these systems typically exhibit low frame rates, because to fully sample a scene in this way requires at least the same number of correlation measurements as the number of pixels in the reconstructed image. To mitigate this, a range of compressive sensing techniques have been developed which use a priori knowledge to reconstruct images from an undersampled measurement set. Here, we take a different approach and adopt a strategy inspired by the foveated vision found in the animal kingdom—a framework that exploits the spatiotemporal redundancy of many dynamic scenes. In our system, a high-resolution foveal region tracks motion within the scene, yet unlike a simple zoom, every frame delivers new spatial information from across the entire field of view. This strategy rapidly records the detail of quickly changing features in the scene while simultaneously accumulating detail of more slowly evolving regions over several consecutive frames. This architecture provides video streams in which both the resolution and exposure time spatially vary and adapt dynamically in response to the evolution of the scene. The degree of local frame rate enhancement is scene-dependent, but here, we demonstrate a factor of 4, thereby helping to mitigate one of the main drawbacks of single-pixel imaging techniques. The methods described here complement existing compressive sensing approaches and may be applied to enhance computational imagers that rely on sequential correlation measurements. PMID:28439538

  10. Dynamic deformation image de-blurring and image processing for digital imaging correlation measurement

    NASA Astrophysics Data System (ADS)

    Guo, X.; Li, Y.; Suo, T.; Liu, H.; Zhang, C.

    2017-11-01

    This paper proposes a method for de-blurring of images captured in the dynamic deformation of materials. De-blurring is achieved based on the dynamic-based approach, which is used to estimate the Point Spread Function (PSF) during the camera exposure window. The deconvolution process involving iterative matrix calculations of pixels, is then performed on the GPU to decrease the time cost. Compared to the Gauss method and the Lucy-Richardson method, it has the best result of the image restoration. The proposed method has been evaluated by using the Hopkinson bar loading system. In comparison to the blurry image, the proposed method has successfully restored the image. It is also demonstrated from image processing applications that the de-blurring method can improve the accuracy and the stability of the digital imaging correlation measurement.

  11. Positive-negative corresponding normalized ghost imaging based on an adaptive threshold

    NASA Astrophysics Data System (ADS)

    Li, G. L.; Zhao, Y.; Yang, Z. H.; Liu, X.

    2016-11-01

    Ghost imaging (GI) technology has attracted increasing attention as a new imaging technique in recent years. However, the signal-to-noise ratio (SNR) of GI with pseudo-thermal light needs to be improved before it meets engineering application demands. We therefore propose a new scheme called positive-negative correspondence normalized GI based on an adaptive threshold (PCNGI-AT) to achieve a good performance with less amount of data. In this work, we use both the advantages of normalized GI (NGI) and positive-negative correspondence GI (P-NCGI). The correctness and feasibility of the scheme were proved in theory before we designed an adaptive threshold selection method, in which the parameter of object signal selection conditions is replaced by the normalizing value. The simulation and experimental results reveal that the SNR of the proposed scheme is better than that of time-correspondence differential GI (TCDGI), avoiding the calculation of the matrix of correlation and reducing the amount of data used. The method proposed will make GI far more practical in engineering applications.

  12. Implementation and image processing of a multi-focusing bionic compound eye

    NASA Astrophysics Data System (ADS)

    Wang, Xin; Guo, Yongcai; Luo, Jiasai

    2018-01-01

    In this paper, a new BCE with multi-focusing microlens array (MLA) was proposed. The BCE consist of detachable micro-hole array (MHA), multi-focusing MLA and spherical substrate, thus allowing it to have a large FOV without crosstalk and stray light. The MHA was fabricated by the precision machining and the parameters of the microlens varied depend on the aperture of micro-hole, through which the implementation of the multi-focusing MLA was realized under the negative pressure. Without the pattern transfer and substrate reshaping, the whole fabrication method was capable of accomplishing within several minutes by using microinjection technology. Furthermore, the method is cost-effective and easy for operation, thus providing a feasible method for the mass production of the BCE. The corresponding image processing was used to realize the image stitching for the sub-image of each single microlens, which offering an integral image in large FOV. The image stitching was implemented through the overlap between the adjacent sub-images and the feature points between the adjacent sub-images were captured by the Harris point detection. By using the adaptive non-maximal suppression, numerous potential mismatching points were eliminated and the algorithm efficiency was proved effectively. Following this, the random sample consensus (RANSAC) was used for feature points matching, by which the relation of projection transformation of the image is obtained. The implementation of the accurate image matching was then realized after the smooth transition by weighted average method. Experimental results indicate that the image-stitching algorithm can be applied for the curved BCE in large field.

  13. Adaptive thresholding algorithm based on SAR images and wind data to segment oil spills along the northwest coast of the Iberian Peninsula.

    PubMed

    Mera, David; Cotos, José M; Varela-Pet, José; Garcia-Pineda, Oscar

    2012-10-01

    Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean's surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time. Copyright © 2012 Elsevier Ltd. All rights reserved.

  14. Thermodynamic Costs of Information Processing in Sensory Adaptation

    PubMed Central

    Sartori, Pablo; Granger, Léo; Lee, Chiu Fan; Horowitz, Jordan M.

    2014-01-01

    Biological sensory systems react to changes in their surroundings. They are characterized by fast response and slow adaptation to varying environmental cues. Insofar as sensory adaptive systems map environmental changes to changes of their internal degrees of freedom, they can be regarded as computational devices manipulating information. Landauer established that information is ultimately physical, and its manipulation subject to the entropic and energetic bounds of thermodynamics. Thus the fundamental costs of biological sensory adaptation can be elucidated by tracking how the information the system has about its environment is altered. These bounds are particularly relevant for small organisms, which unlike everyday computers, operate at very low energies. In this paper, we establish a general framework for the thermodynamics of information processing in sensing. With it, we quantify how during sensory adaptation information about the past is erased, while information about the present is gathered. This process produces entropy larger than the amount of old information erased and has an energetic cost bounded by the amount of new information written to memory. We apply these principles to the E. coli's chemotaxis pathway during binary ligand concentration changes. In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum. Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response. PMID:25503948

  15. A Novel Approach for Adaptive Signal Processing

    NASA Technical Reports Server (NTRS)

    Chen, Ya-Chin; Juang, Jer-Nan

    1998-01-01

    Adaptive linear predictors have been used extensively in practice in a wide variety of forms. In the main, their theoretical development is based upon the assumption of stationarity of the signals involved, particularly with respect to the second order statistics. On this basis, the well-known normal equations can be formulated. If high- order statistical stationarity is assumed, then the equivalent normal equations involve high-order signal moments. In either case, the cross moments (second or higher) are needed. This renders the adaptive prediction procedure non-blind. A novel procedure for blind adaptive prediction has been proposed and considerable implementation has been made in our contributions in the past year. The approach is based upon a suitable interpretation of blind equalization methods that satisfy the constant modulus property and offers significant deviations from the standard prediction methods. These blind adaptive algorithms are derived by formulating Lagrange equivalents from mechanisms of constrained optimization. In this report, other new update algorithms are derived from the fundamental concepts of advanced system identification to carry out the proposed blind adaptive prediction. The results of the work can be extended to a number of control-related problems, such as disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. The applications implemented are speech processing, such as coding and synthesis. Simulations are included to verify the novel modelling method.

  16. A Demons algorithm for image registration with locally adaptive regularization.

    PubMed

    Cahill, Nathan D; Noble, J Alison; Hawkes, David J

    2009-01-01

    Thirion's Demons is a popular algorithm for nonrigid image registration because of its linear computational complexity and ease of implementation. It approximately solves the diffusion registration problem by successively estimating force vectors that drive the deformation toward alignment and smoothing the force vectors by Gaussian convolution. In this article, we show how the Demons algorithm can be generalized to allow image-driven locally adaptive regularization in a manner that preserves both the linear complexity and ease of implementation of the original Demons algorithm. We show that the proposed algorithm exhibits lower target registration error and requires less computational effort than the original Demons algorithm on the registration of serial chest CT scans of patients with lung nodules.

  17. Research on pre-processing of QR Code

    NASA Astrophysics Data System (ADS)

    Sun, Haixing; Xia, Haojie; Dong, Ning

    2013-10-01

    QR code encodes many kinds of information because of its advantages: large storage capacity, high reliability, full arrange of utter-high-speed reading, small printing size and high-efficient representation of Chinese characters, etc. In order to obtain the clearer binarization image from complex background, and improve the recognition rate of QR code, this paper researches on pre-processing methods of QR code (Quick Response Code), and shows algorithms and results of image pre-processing for QR code recognition. Improve the conventional method by changing the Souvola's adaptive text recognition method. Additionally, introduce the QR code Extraction which adapts to different image size, flexible image correction approach, and improve the efficiency and accuracy of QR code image processing.

  18. Recasting Transfer as a Socio-Personal Process of Adaptable Learning

    ERIC Educational Resources Information Center

    Billett, Stephen

    2013-01-01

    Transfer is usually cast as an educational, rather than learning, problem. Yet, seeking to adapt what individuals know from one circumstance to another is a process more helpfully associated with learning, than a hybrid one called transfer. Adaptability comprises individuals construing what they experience, then aligning and reconciling with what…

  19. Computers in Public Schools: Changing the Image with Image Processing.

    ERIC Educational Resources Information Center

    Raphael, Jacqueline; Greenberg, Richard

    1995-01-01

    The kinds of educational technologies selected can make the difference between uninspired, rote computer use and challenging learning experiences. University of Arizona's Image Processing for Teaching Project has worked with over 1,000 teachers to develop image-processing techniques that provide students with exciting, open-ended opportunities for…

  20. Visual Communications And Image Processing

    NASA Astrophysics Data System (ADS)

    Hsing, T. Russell; Tzou, Kou-Hu

    1989-07-01

    This special issue on Visual Communications and Image Processing contains 14 papers that cover a wide spectrum in this fast growing area. For the past few decades, researchers and scientists have devoted their efforts to these fields. Through this long-lasting devotion, we witness today the growing popularity of low-bit-rate video as a convenient tool for visual communication. We also see the integration of high-quality video into broadband digital networks. Today, with more sophisticated processing, clearer and sharper pictures are being restored from blurring and noise. Also, thanks to the advances in digital image processing, even a PC-based system can be built to recognize highly complicated Chinese characters at the speed of 300 characters per minute. This special issue can be viewed as a milestone of visual communications and image processing on its journey to eternity. It presents some overviews on advanced topics as well as some new development in specific subjects.

  1. Acute Solar Retinopathy Imaged With Adaptive Optics, Optical Coherence Tomography Angiography, and En Face Optical Coherence Tomography.

    PubMed

    Wu, Chris Y; Jansen, Michael E; Andrade, Jorge; Chui, Toco Y P; Do, Anna T; Rosen, Richard B; Deobhakta, Avnish

    2018-01-01

    Solar retinopathy is a rare form of retinal injury that occurs after direct sungazing. To enhance understanding of the structural changes that occur in solar retinopathy by obtaining high-resolution in vivo en face images. Case report of a young adult woman who presented to the New York Eye and Ear Infirmary with symptoms of acute solar retinopathy after viewing the solar eclipse on August 21, 2017. Results of comprehensive ophthalmic examination and images obtained by fundus photography, microperimetry, spectral-domain optical coherence tomography (OCT), adaptive optics scanning light ophthalmoscopy, OCT angiography, and en face OCT. The patient was examined after viewing the solar eclipse. Visual acuity was 20/20 OD and 20/25 OS. The patient was left-eye dominant. Spectral-domain OCT images were consistent with mild and severe acute solar retinopathy in the right and left eye, respectively. Microperimetry was normal in the right eye but showed paracentral decreased retinal sensitivity in the left eye with a central absolute scotoma. Adaptive optics images of the right eye showed a small region of nonwaveguiding photoreceptors, while images of the left eye showed a large area of abnormal and nonwaveguiding photoreceptors. Optical coherence tomography angiography images were normal in both eyes. En face OCT images of the right eye showed a small circular hyperreflective area, with central hyporeflectivity in the outer retina of the right eye. The left eye showed a hyperreflective lesion that intensified in area from inner to middle retina and became mostly hyporeflective in the outer retina. The shape of the lesion on adaptive optics and en face OCT images of the left eye corresponded to the shape of the scotoma drawn by the patient on Amsler grid. Acute solar retinopathy can present with foveal cone photoreceptor mosaic disturbances on adaptive optics scanning light ophthalmoscopy imaging. Corresponding reflectivity changes can be seen on en face OCT, especially

  2. BreakingNews: Article Annotation by Image and Text Processing.

    PubMed

    Ramisa, Arnau; Yan, Fei; Moreno-Noguer, Francesc; Mikolajczyk, Krystian

    2018-05-01

    Building upon recent Deep Neural Network architectures, current approaches lying in the intersection of Computer Vision and Natural Language Processing have achieved unprecedented breakthroughs in tasks like automatic captioning or image retrieval. Most of these learning methods, though, rely on large training sets of images associated with human annotations that specifically describe the visual content. In this paper we propose to go a step further and explore the more complex cases where textual descriptions are loosely related to the images. We focus on the particular domain of news articles in which the textual content often expresses connotative and ambiguous relations that are only suggested but not directly inferred from images. We introduce an adaptive CNN architecture that shares most of the structure for multiple tasks including source detection, article illustration and geolocation of articles. Deep Canonical Correlation Analysis is deployed for article illustration, and a new loss function based on Great Circle Distance is proposed for geolocation. Furthermore, we present BreakingNews, a novel dataset with approximately 100K news articles including images, text and captions, and enriched with heterogeneous meta-data (such as GPS coordinates and user comments). We show this dataset to be appropriate to explore all aforementioned problems, for which we provide a baseline performance using various Deep Learning architectures, and different representations of the textual and visual features. We report very promising results and bring to light several limitations of current state-of-the-art in this kind of domain, which we hope will help spur progress in the field.

  3. Data Processing of LAPAN-A3 Thermal Imager

    NASA Astrophysics Data System (ADS)

    Hartono, R.; Hakim, P. R.; Syafrudin, AH

    2018-04-01

    As an experimental microsatellite, LAPAN-A3/IPB satellite has an experimental thermal imager, which is called as micro-bolometer, to observe earth surface temperature for horizon observation. The imager data is transmitted from satellite to ground station by S-band video analog signal transmission, and then processed by ground station to become sequence of 8-bit enhanced and contrasted images. Data processing of LAPAN-A3/IPB thermal imager is more difficult than visual digital camera, especially for mosaic and classification purpose. This research aims to describe simple mosaic and classification process of LAPAN-A3/IPB thermal imager based on several videos data produced by the imager. The results show that stitching using Adobe Photoshop produces excellent result but can only process small area, while manual approach using ImageJ software can produce a good result but need a lot of works and time consuming. The mosaic process using image cross-correlation by Matlab offers alternative solution, which can process significantly bigger area in significantly shorter time processing. However, the quality produced is not as good as mosaic images of the other two methods. The simple classifying process that has been done shows that the thermal image can classify three distinct objects, i.e.: clouds, sea, and land surface. However, the algorithm fail to classify any other object which might be caused by distortions in the images. All of these results can be used as reference for development of thermal imager in LAPAN-A4 satellite.

  4. On adaptive robustness approach to Anti-Jam signal processing

    NASA Astrophysics Data System (ADS)

    Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

    An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

  5. Adaptive Memory: Evaluating Alternative Forms of Fitness-Relevant Processing in the Survival Processing Paradigm

    PubMed Central

    Sandry, Joshua; Trafimow, David; Marks, Michael J.; Rice, Stephen

    2013-01-01

    Memory may have evolved to preserve information processed in terms of its fitness-relevance. Based on the assumption that the human mind comprises different fitness-relevant adaptive mechanisms contributing to survival and reproductive success, we compared alternative fitness-relevant processing scenarios with survival processing. Participants rated words for relevancy to fitness-relevant and control conditions followed by a delay and surprise recall test (Experiment 1a). Participants recalled more words processed for their relevance to a survival situation. We replicated these findings in an online study (Experiment 2) and a study using revised fitness-relevant scenarios (Experiment 3). Across all experiments, we did not find a mnemonic benefit for alternative fitness-relevant processing scenarios, questioning assumptions associated with an evolutionary account of remembering. Based on these results, fitness-relevance seems to be too wide-ranging of a construct to account for the memory findings associated with survival processing. We propose that memory may be hierarchically sensitive to fitness-relevant processing instructions. We encourage future researchers to investigate the underlying mechanisms responsible for survival processing effects and work toward developing a taxonomy of adaptive memory. PMID:23585858

  6. Halftoning processing on a JPEG-compressed image

    NASA Astrophysics Data System (ADS)

    Sibade, Cedric; Barizien, Stephane; Akil, Mohamed; Perroton, Laurent

    2003-12-01

    Digital image processing algorithms are usually designed for the raw format, that is on an uncompressed representation of the image. Therefore prior to transforming or processing a compressed format, decompression is applied; then, the result of the processing application is finally re-compressed for further transfer or storage. The change of data representation is resource-consuming in terms of computation, time and memory usage. In the wide format printing industry, this problem becomes an important issue: e.g. a 1 m2 input color image, scanned at 600 dpi exceeds 1.6 GB in its raw representation. However, some image processing algorithms can be performed in the compressed-domain, by applying an equivalent operation on the compressed format. This paper is presenting an innovative application of the halftoning processing operation by screening, to be applied on JPEG-compressed image. This compressed-domain transform is performed by computing the threshold operation of the screening algorithm in the DCT domain. This algorithm is illustrated by examples for different halftone masks. A pre-sharpening operation, applied on a JPEG-compressed low quality image is also described; it allows to de-noise and to enhance the contours of this image.

  7. Phase in Optical Image Processing

    NASA Astrophysics Data System (ADS)

    Naughton, Thomas J.

    2010-04-01

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

  8. Adaptive time-sequential binary sensing for high dynamic range imaging

    NASA Astrophysics Data System (ADS)

    Hu, Chenhui; Lu, Yue M.

    2012-06-01

    We present a novel image sensor for high dynamic range imaging. The sensor performs an adaptive one-bit quantization at each pixel, with the pixel output switched from 0 to 1 only if the number of photons reaching that pixel is greater than or equal to a quantization threshold. With an oracle knowledge of the incident light intensity, one can pick an optimal threshold (for that light intensity) and the corresponding Fisher information contained in the output sequence follows closely that of an ideal unquantized sensor over a wide range of intensity values. This observation suggests the potential gains one may achieve by adaptively updating the quantization thresholds. As the main contribution of this work, we propose a time-sequential threshold-updating rule that asymptotically approaches the performance of the oracle scheme. With every threshold mapped to a number of ordered states, the dynamics of the proposed scheme can be modeled as a parametric Markov chain. We show that the frequencies of different thresholds converge to a steady-state distribution that is concentrated around the optimal choice. Moreover, numerical experiments show that the theoretical performance measures (Fisher information and Craḿer-Rao bounds) can be achieved by a maximum likelihood estimator, which is guaranteed to find globally optimal solution due to the concavity of the log-likelihood functions. Compared with conventional image sensors and the strategy that utilizes a constant single-photon threshold considered in previous work, the proposed scheme attains orders of magnitude improvement in terms of sensor dynamic ranges.

  9. Water surface capturing by image processing

    USDA-ARS?s Scientific Manuscript database

    An alternative means of measuring the water surface interface during laboratory experiments is processing a series of sequentially captured images. Image processing can provide a continuous, non-intrusive record of the water surface profile whose accuracy is not dependent on water depth. More trad...

  10. Mechanisms for Rapid Adaptive Control of Motion Processing in Macaque Visual Cortex.

    PubMed

    McLelland, Douglas; Baker, Pamela M; Ahmed, Bashir; Kohn, Adam; Bair, Wyeth

    2015-07-15

    A key feature of neural networks is their ability to rapidly adjust their function, including signal gain and temporal dynamics, in response to changes in sensory inputs. These adjustments are thought to be important for optimizing the sensitivity of the system, yet their mechanisms remain poorly understood. We studied adaptive changes in temporal integration in direction-selective cells in macaque primary visual cortex, where specific hypotheses have been proposed to account for rapid adaptation. By independently stimulating direction-specific channels, we found that the control of temporal integration of motion at one direction was independent of motion signals driven at the orthogonal direction. We also found that individual neurons can simultaneously support two different profiles of temporal integration for motion in orthogonal directions. These findings rule out a broad range of adaptive mechanisms as being key to the control of temporal integration, including untuned normalization and nonlinearities of spike generation and somatic adaptation in the recorded direction-selective cells. Such mechanisms are too broadly tuned, or occur too far downstream, to explain the channel-specific and multiplexed temporal integration that we observe in single neurons. Instead, we are compelled to conclude that parallel processing pathways are involved, and we demonstrate one such circuit using a computer model. This solution allows processing in different direction/orientation channels to be separately optimized and is sensible given that, under typical motion conditions (e.g., translation or looming), speed on the retina is a function of the orientation of image components. Many neurons in visual cortex are understood in terms of their spatial and temporal receptive fields. It is now known that the spatiotemporal integration underlying visual responses is not fixed but depends on the visual input. For example, neurons that respond selectively to motion direction integrate

  11. Images of photoreceptors in living primate eyes using adaptive optics two-photon ophthalmoscopy

    PubMed Central

    Hunter, Jennifer J.; Masella, Benjamin; Dubra, Alfredo; Sharma, Robin; Yin, Lu; Merigan, William H.; Palczewska, Grazyna; Palczewski, Krzysztof; Williams, David R.

    2011-01-01

    In vivo two-photon imaging through the pupil of the primate eye has the potential to become a useful tool for functional imaging of the retina. Two-photon excited fluorescence images of the macaque cone mosaic were obtained using a fluorescence adaptive optics scanning laser ophthalmoscope, overcoming the challenges of a low numerical aperture, imperfect optics of the eye, high required light levels, and eye motion. Although the specific fluorophores are as yet unknown, strong in vivo intrinsic fluorescence allowed images of the cone mosaic. Imaging intact ex vivo retina revealed that the strongest two-photon excited fluorescence signal comes from the cone inner segments. The fluorescence response increased following light stimulation, which could provide a functional measure of the effects of light on photoreceptors. PMID:21326644

  12. Eliminating "Hotspots" in Digital Image Processing

    NASA Technical Reports Server (NTRS)

    Salomon, P. M.

    1984-01-01

    Signals from defective picture elements rejected. Image processing program for use with charge-coupled device (CCD) or other mosaic imager augmented with algorithm that compensates for common type of electronic defect. Algorithm prevents false interpretation of "hotspots". Used for robotics, image enhancement, image analysis and digital television.

  13. How Digital Image Processing Became Really Easy

    NASA Astrophysics Data System (ADS)

    Cannon, Michael

    1988-02-01

    In the early and mid-1970s, digital image processing was the subject of intense university and corporate research. The research lay along two lines: (1) developing mathematical techniques for improving the appearance of or analyzing the contents of images represented in digital form, and (2) creating cost-effective hardware to carry out these techniques. The research has been very effective, as evidenced by the continued decline of image processing as a research topic, and the rapid increase of commercial companies to market digital image processing software and hardware.

  14. Image-plane processing of visual information

    NASA Technical Reports Server (NTRS)

    Huck, F. O.; Fales, C. L.; Park, S. K.; Samms, R. W.

    1984-01-01

    Shannon's theory of information is used to optimize the optical design of sensor-array imaging systems which use neighborhood image-plane signal processing for enhancing edges and compressing dynamic range during image formation. The resultant edge-enhancement, or band-pass-filter, response is found to be very similar to that of human vision. Comparisons of traits in human vision with results from information theory suggest that: (1) Image-plane processing, like preprocessing in human vision, can improve visual information acquisition for pattern recognition when resolving power, sensitivity, and dynamic range are constrained. Improvements include reduced sensitivity to changes in lighter levels, reduced signal dynamic range, reduced data transmission and processing, and reduced aliasing and photosensor noise degradation. (2) Information content can be an appropriate figure of merit for optimizing the optical design of imaging systems when visual information is acquired for pattern recognition. The design trade-offs involve spatial response, sensitivity, and sampling interval.

  15. Multiscale image processing and antiscatter grids in digital radiography.

    PubMed

    Lo, Winnie Y; Hornof, William J; Zwingenberger, Allison L; Robertson, Ian D

    2009-01-01

    Scatter radiation is a source of noise and results in decreased signal-to-noise ratio and thus decreased image quality in digital radiography. We determined subjectively whether a digitally processed image made without a grid would be of similar quality to an image made with a grid but without image processing. Additionally the effects of exposure dose and of a using a grid with digital radiography on overall image quality were studied. Thoracic and abdominal radiographs of five dogs of various sizes were made. Four acquisition techniques were included (1) with a grid, standard exposure dose, digital image processing; (2) without a grid, standard exposure dose, digital image processing; (3) without a grid, half the exposure dose, digital image processing; and (4) with a grid, standard exposure dose, no digital image processing (to mimic a film-screen radiograph). Full-size radiographs as well as magnified images of specific anatomic regions were generated. Nine reviewers rated the overall image quality subjectively using a five-point scale. All digitally processed radiographs had higher overall scores than nondigitally processed radiographs regardless of patient size, exposure dose, or use of a grid. The images made at half the exposure dose had a slightly lower quality than those made at full dose, but this was only statistically significant in magnified images. Using a grid with digital image processing led to a slight but statistically significant increase in overall quality when compared with digitally processed images made without a grid but whether this increase in quality is clinically significant is unknown.

  16. Adaptive suppression of power line interference in ultra-low field magnetic resonance imaging in an unshielded environment

    NASA Astrophysics Data System (ADS)

    Huang, Xiaolei; Dong, Hui; Qiu, Yang; Li, Bo; Tao, Quan; Zhang, Yi; Krause, Hans-Joachim; Offenhäusser, Andreas; Xie, Xiaoming

    2018-01-01

    Power-line harmonic interference and fixed-frequency noise peaks may cause stripe-artifacts in ultra-low field (ULF) magnetic resonance imaging (MRI) in an unshielded environment and in a conductively shielded room. In this paper we describe an adaptive suppression method to eliminate these artifacts in MRI images. This technique utilizes spatial correlation of the interference from different positions, and is realized by subtracting the outputs of the reference channel(s) from those of the signal channel(s) using wavelet analysis and the least squares method. The adaptive suppression method is first implemented to remove the image artifacts in simulation. We then experimentally demonstrate the feasibility of this technique by adding three orthogonal superconducting quantum interference device (SQUID) magnetometers as reference channels to compensate the output of one 2nd-order gradiometer. The experimental results show great improvement in the imaging quality in both 1D and 2D MRI images at two common imaging frequencies, 1.3 kHz and 4.8 kHz. At both frequencies, the effective compensation bandwidth is as high as 2 kHz. Furthermore, we examine the longitudinal relaxation times of the same sample before and after compensation, and show that the MRI properties of the sample did not change after applying adaptive suppression. This technique can effectively increase the imaging bandwidth and be applied to ULF MRI detected by either SQUIDs or Faraday coil in both an unshielded environment and a conductively shielded room.

  17. A multiresolution processing method for contrast enhancement in portal imaging.

    PubMed

    Gonzalez-Lopez, Antonio

    2018-06-18

    Portal images have a unique feature among the imaging modalities used in radiotherapy: they provide direct visualization of the irradiated volumes. However, contrast and spatial resolution are strongly limited due to the high energy of the radiation sources. Because of this, imaging modalities using x-ray energy beams have gained importance in the verification of patient positioning, replacing portal imaging. The purpose of this work was to develop a method for the enhancement of local contrast in portal images. The method operates in the subbands of a wavelet decomposition of the image, re-scaling them in such a way that coefficients in the high and medium resolution subbands are amplified, an approach totally different of those operating on the image histogram, widely used nowadays. Portal images of an anthropomorphic phantom were acquired in an electronic portal imaging device (EPID). Then, different re-scaling strategies were investigated, studying the effects of the scaling parameters on the enhanced images. Also, the effect of using different types of transforms was studied. Finally, the implemented methods were combined with histogram equalization methods like the contrast limited adaptive histogram equalization (CLAHE), and these combinations were compared. Uniform amplification of the detail subbands shows the best results in contrast enhancement. On the other hand, linear re-escalation of the high resolution subbands increases the visibility of fine detail of the images, at the expense of an increase in noise levels. Also, since processing is applied only to detail subbands, not to the approximation, the mean gray level of the image is minimally modified and no further display adjustments are required. It is shown that re-escalation of the detail subbands of portal images can be used as an efficient method for the enhancement of both, the local contrast and the resolution of these images. © 2018 Institute of

  18. Adaptive optics retinal imaging in the living mouse eye

    PubMed Central

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

    2012-01-01

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

  19. PCB Fault Detection Using Image Processing

    NASA Astrophysics Data System (ADS)

    Nayak, Jithendra P. R.; Anitha, K.; Parameshachari, B. D., Dr.; Banu, Reshma, Dr.; Rashmi, P.

    2017-08-01

    The importance of the Printed Circuit Board inspection process has been magnified by requirements of the modern manufacturing environment where delivery of 100% defect free PCBs is the expectation. To meet such expectations, identifying various defects and their types becomes the first step. In this PCB inspection system the inspection algorithm mainly focuses on the defect detection using the natural images. Many practical issues like tilt of the images, bad light conditions, height at which images are taken etc. are to be considered to ensure good quality of the image which can then be used for defect detection. Printed circuit board (PCB) fabrication is a multidisciplinary process, and etching is the most critical part in the PCB manufacturing process. The main objective of Etching process is to remove the exposed unwanted copper other than the required circuit pattern. In order to minimize scrap caused by the wrongly etched PCB panel, inspection has to be done in early stage. However, all of the inspections are done after the etching process where any defective PCB found is no longer useful and is simply thrown away. Since etching process costs 0% of the entire PCB fabrication, it is uneconomical to simply discard the defective PCBs. In this paper a method to identify the defects in natural PCB images and associated practical issues are addressed using Software tools and some of the major types of single layer PCB defects are Pattern Cut, Pin hole, Pattern Short, Nick etc., Therefore the defects should be identified before the etching process so that the PCB would be reprocessed. In the present approach expected to improve the efficiency of the system in detecting the defects even in low quality images

  20. 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