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Sample records for adaptive image enhancement

  1. Adaptive enhancement for infrared image using shearlet frame

    NASA Astrophysics Data System (ADS)

    Fan, Zunlin; Bi, Duyan; Gao, Shan; He, Linyuan; Ding, Wenshan

    2016-08-01

    An infrared imaging sensor is sensitive to the variation of imaging environment, which may affect the image quality and blur the edges in an infrared image. Therefore, it is necessary to enhance the infrared image. To improve the image contrast and adaptively enhance image structures, such as edges and details, this paper proposes a novel infrared image enhancement algorithm in the shearlet transform domain. To avoid over-enhancing strong edges and amplifying noise in plateau regions, we linearly enhance the details on the high frequency components based on their structure information, and improve the global image contrast by non-uniform illumination correction on the low frequency component. Then we convert the processed low and high components into the spatial domain to obtain the final enhanced image. Experimental results show that the proposed algorithm could enhance the infrared image details well and produce few noise regions, which is very helpful for target detection and recognition.

  2. An adaptive algorithm for low contrast infrared image enhancement

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

  3. Real-time adaptive video image enhancement

    NASA Astrophysics Data System (ADS)

    Garside, John R.; Harrison, Chris G.

    1999-07-01

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

  4. Adaptive 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.

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

    NASA Astrophysics Data System (ADS)

    Xu, Shaoping; Liu, Xiaoping P.

    2015-03-01

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

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

    PubMed Central

    Yoo, Yoonjong; Im, Jaehyun; Paik, Joonki

    2015-01-01

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

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

    PubMed

    Yoo, Yoonjong; Im, Jaehyun; Paik, Joonki

    2015-01-01

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

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

    SciTech Connect

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

    1994-11-29

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

  9. 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. PMID:27161022

  10. 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

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

    PubMed

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

    2015-01-01

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

  12. Color Enhancement in Endoscopic Images Using Adaptive Sigmoid Function and Space Variant Color Reproduction.

    PubMed

    Imtiaz, Mohammad S; Wahid, Khan A

    2015-01-01

    Modern endoscopes play an important role in diagnosing various gastrointestinal (GI) tract related diseases. The improved visual quality of endoscopic images can provide better diagnosis. This paper presents an efficient color image enhancement method for endoscopic images. It is achieved in two stages: image enhancement at gray level followed by space variant chrominance mapping color reproduction. Image enhancement is achieved by performing adaptive sigmoid function and uniform distribution of sigmoid pixels. Secondly, a space variant chrominance mapping color reproduction is used to generate new chrominance components. The proposed method is used on low contrast color white light images (WLI) to enhance and highlight the vascular and mucosa structures of the GI tract. The method is also used to colorize grayscale narrow band images (NBI) and video frames. The focus value and color enhancement factor show that the enhancement level in the processed image is greatly increased compared to the original endoscopic image. The overall contrast level of the processed image is higher than the original image. The color similarity test has proved that the proposed method does not add any additional color which is not present in the original image. The algorithm has low complexity with an execution speed faster than other related methods. PMID:26089969

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

    PubMed

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

    2016-04-01

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

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

    PubMed

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

    2016-04-01

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

  15. Gas image enhancement based on adaptive time-domain filtering and morphology

    NASA Astrophysics Data System (ADS)

    Zhang, Changxing; Wang, Lingxue; Li, Jiakun; Long, Yunting; Zhang, Bei

    2011-05-01

    The fingerprint region of most gases is within 3 to 14μm. A mid-wave or long-wave infrared thermal imager is therefore commonly applied in gas detection. With further influence of low gas concentration and heterogeneity of infrared focal plane arrays, the image has numerous drawbacks. These include loud noise, weak gas signal, gridding, and dead points, all of which are particularly evident in sequential images. In order to solve these problems, we take into account the characteristics of the leaking gas image and propose an enhancement method based on adaptive time-domain filtering with morphology. The adaptive time-domain filtering which operates on time sequence images is a hybrid method combining the recursive filtering and mean filtering. It segments gas and background according to a selected threshold; removes speckle noise according to the median; and removes background domain using weighted difference image. The morphology method can not only dilate the gas region along the direction of gas diffusion to greatly enhance the visibility of the leakage area, but also effectively remove the noise, and smooth the contour. Finally, the false color is added to the gas domain. Results show that the gas infrared region is effectively enhanced.

  16. Bilateral filtering and adaptive tone-mapping for qualified edge and image enhancement

    NASA Astrophysics Data System (ADS)

    Hu, Kuo-Jui; Chang, Ting-Ting; Lu, Min-Yao; Li, Wu-Jeng; Huang, Jih-Fon

    2009-01-01

    Most of high-contrast images are common with dark and bright area. It is difficult to present the detail on both dark and high light areas on display devices. In order to resolve this problem, we proposed a method of image enhancement to improve this image quality and used bilateral filter to keep the detail. In paper, we applied an appropriate algorithm to process images. At first, we use bilateral filter to separate image. One is large scale image and the other is detail image. Second, we made large scale image which was translated into histogram. In order to make the images divided into three stairs, such as lightness, middle-tone and darkness region. We decided two optimal threshold parameters. Finally, according to three images we use different tone-mapping method to process each stair. The tone-mapping method includes adaptive s-curve and gamma curve algorithms. The experiment results of this study revealed image detail and enhancement. To avoid contour phenomenon is in lightness region.

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

    PubMed Central

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  19. A scale-based forward-and-backward diffusion process for adaptive image enhancement and denoising

    NASA Astrophysics Data System (ADS)

    Wang, Yi; Niu, Ruiqing; Zhang, Liangpei; Wu, Ke; Sahli, Hichem

    2011-12-01

    This work presents a scale-based forward-and-backward diffusion (SFABD) scheme. The main idea of this scheme is to perform local adaptive diffusion using local scale information. To this end, we propose a diffusivity function based on the Minimum Reliable Scale (MRS) of Elder and Zucker (IEEE Trans. Pattern Anal. Mach. Intell. 20(7), 699-716, 1998) to detect the details of local structures. The magnitude of the diffusion coefficient at each pixel is determined by taking into account the local property of the image through the scales. A scale-based variable weight is incorporated into the diffusivity function for balancing the forward and backward diffusion. Furthermore, as numerical scheme, we propose a modification of the Perona-Malik scheme (IEEE Trans. Pattern Anal. Mach. Intell. 12(7), 629-639, 1990) by incorporating edge orientations. The article describes the main principles of our method and illustrates image enhancement results on a set of standard images as well as simulated medical images, together with qualitative and quantitative comparisons with a variety of anisotropic diffusion schemes.

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

    NASA Astrophysics Data System (ADS)

    Panigrahi, Swapnesh; Fade, Julien; Alouini, Mehdi

    2015-10-01

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

  1. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  4. 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

  5. A multiresolution approach to image enhancement via histogram shaping and adaptive Wiener filtering

    NASA Astrophysics Data System (ADS)

    Pace, T.; Manville, D.; Lee, H.; Cloud, G.; Puritz, J.

    2008-04-01

    It is critical in military applications to be able to extract features in imagery that may be of interest to the viewer at any time of the day or night. Infrared (IR) imagery is ideally suited for producing these types of images. However, even under the best of circumstances, the traditional approach of applying a global automatic gain control (AGC) to the digital image may not provide the user with local area details that may be of interest. Processing the imagery locally can enhance additional features and characteristics in the image which provide the viewer with an improved understanding of the scene being observed. This paper describes a multi-resolution pyramid approach for decomposing an image, enhancing its contrast by remapping the histograms to desired pdfs, filtering them and recombining them to create an output image with much more visible detail than the input image. The technique improves the local area image contrast in light and dark areas providing the warfighter with significantly improved situational awareness.

  6. Enhancement of Corneal Visibility in Optical Coherence Tomography Images Using Corneal Adaptive Compensation

    PubMed Central

    Girard, Michaël J. A.; Ang, Marcus; Chung, Cheuk Wang; Farook, Mohamed; Strouthidis, Nick; Mehta, Jod S.; Mari, Jean Martial

    2015-01-01

    Purpose: To improve the contrast of optical coherence tomography (OCT) images of the cornea (post processing). Methods: We have recently developed standard compensation (SC) algorithms to remove light attenuation artifacts. A more recent approach, namely adaptive compensation (AC), further limited noise overamplification within deep tissue regions. AC was shown to work efficiently when all A-scan signals were fully attenuated at high depth. But in many imaging applications (e.g., OCT imaging of the cornea), such an assumption is not satisfied, which can result in strong noise overamplification. A corneal adaptive compensation (CAC) algorithm was therefore developed to overcome such limitation. CAC benefited from local A-scan processing (rather than global as in AC) and its performance was compared with that of SC and AC using Fourier-domain OCT images of four human corneas. Results: CAC provided considerably superior image contrast improvement than SC or AC did, with excellent visibility of the corneal stroma, low noise overamplification, homogeneous signal amplification, and high contrast. Specifically, CAC provided mean interlayer contrasts (a measure of high stromal visibility and low noise) greater than 0.97, while SC and AC provided lower values ranging from 0.38 to 1.00. Conclusion: CAC provided considerable improvement compared with SC and AC by eliminating noise overamplification, while maintaining all benefits of compensation, thus making the corneal endothelium and corneal thickness easily identifiable. Translational Relevance: CAC may find wide applicability in clinical practice and could contribute to improved morphometric and biomechanical understanding of the cornea. PMID:26046005

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    SciTech Connect

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

    2015-12-15

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

  9. Adaptive Image Denoising by Mixture Adaptation.

    PubMed

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

    2016-10-01

    We propose an adaptive learning procedure to learn patch-based image priors for image denoising. The new algorithm, called the expectation-maximization (EM) adaptation, takes a generic prior learned from a generic external database and adapts it to the noisy image to generate a specific prior. Different from existing methods that combine internal and external statistics in ad hoc ways, the proposed algorithm is rigorously derived from a Bayesian hyper-prior perspective. There are two contributions of this paper. First, we provide full derivation of the EM adaptation algorithm and demonstrate methods to improve the computational complexity. Second, in the absence of the latent clean image, we show how EM adaptation can be modified based on pre-filtering. The experimental results show that the proposed adaptation algorithm yields consistently better denoising results than the one without adaptation and is superior to several state-of-the-art algorithms. PMID:27416593

  10. Adaptive color image watermarking algorithm

    NASA Astrophysics Data System (ADS)

    Feng, Gui; Lin, Qiwei

    2008-03-01

    As a major method for intellectual property right protecting, digital watermarking techniques have been widely studied and used. But due to the problems of data amount and color shifted, watermarking techniques on color image was not so widespread studied, although the color image is the principal part for multi-medium usages. Considering the characteristic of Human Visual System (HVS), an adaptive color image watermarking algorithm is proposed in this paper. In this algorithm, HSI color model was adopted both for host and watermark image, the DCT coefficient of intensity component (I) of the host color image was used for watermark date embedding, and while embedding watermark the amount of embedding bit was adaptively changed with the complex degree of the host image. As to the watermark image, preprocessing is applied first, in which the watermark image is decomposed by two layer wavelet transformations. At the same time, for enhancing anti-attack ability and security of the watermarking algorithm, the watermark image was scrambled. According to its significance, some watermark bits were selected and some watermark bits were deleted as to form the actual embedding data. The experimental results show that the proposed watermarking algorithm is robust to several common attacks, and has good perceptual quality at the same time.

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

    PubMed

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

    2016-01-01

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

  12. ShaneAO: an enhanced adaptive optics and IR imaging system for the Lick Observatory 3-meter telescope

    NASA Astrophysics Data System (ADS)

    Kupke, Renate; Gavel, Donald; Roskosi, Constance; Cabak, Gerald; Cowley, David; Dillon, Daren; Gates, Elinor L.; McGurk, Rosalie; Norton, Andrew; Peck, Michael; Ratliff, Christopher; Reinig, Marco

    2012-07-01

    The Lick Observatory 3-meter telescope has a history of serving as a testbed for innovative adaptive optics techniques. In 1996, it became one of the first astronomical observatories to employ laser guide star (LGS) adaptive optics as a facility instrument available to the astronomy community. Work on a second-generation LGS adaptive optics system, ShaneAO, is well underway, with plans to deploy on telescope in 2013. In this paper we discuss key design features and implementation plans for the ShaneAO adaptive optics system. Once again, the Shane 3-m will host a number of new techniques and technologies vital to the development of future adaptive optics systems on larger telescopes. Included is a woofer-tweeter based wavefront correction system incorporating a voice-coil actuated, low spatial and temporal bandwidth, high stroke deformable mirror in conjunction with a high order, high bandwidth MEMs deformable mirror. The existing dye laser, in operation since 1996, will be replaced with a fiber laser recently developed at Lawrence Livermore National Laboratories. The system will also incorporate a high-sensitivity, high bandwidth wavefront sensor camera. Enhanced IR performance will be achieved by replacing the existing PICNIC infrared array with an Hawaii 2RG. The updated ShaneAO system will provide opportunities to test predictive control algorithms for adaptive optics. Capabilities for astronomical spectroscopy, polarimetry, and visible-light adaptive optical astronomy will be supported.

  13. Adaptive wiener image restoration kernel

    DOEpatents

    Yuan, Ding

    2007-06-05

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

  14. Smart Image Enhancement Process

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  15. [Medical image enhancement: Sharpening].

    PubMed

    Kats, L; Vered, M

    2015-04-01

    Most digital imaging systems provide opportunities for image enhancement operations. These are applied to improve the original image and to make the image more appealing visually. One possible means of enhancing digital radiographic image is sharpening. The purpose of sharpening filters is to improve image quality by removing noise or edge enhancement. Sharpening filters may make the radiographic images subjectively more appealing. But during this process, important radiographic features may disappear while artifacts that simulate pathological process might be generated. Therefore, it is of utmost importance for dentists to be familiar with and aware of the use of image enhancement operations, provided by medical digital imaging programs. PMID:26255429

  16. 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.

  17. Countermeasures to Enhance Sensorimotor Adaptability

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  18. Adaptive compression of image data

    NASA Astrophysics Data System (ADS)

    Hludov, Sergei; Schroeter, Claus; Meinel, Christoph

    1998-09-01

    In this paper we will introduce a method of analyzing images, a criterium to differentiate between images, a compression method of medical images in digital form based on the classification of the image bit plane and finally an algorithm for adaptive image compression. The analysis of the image content is based on a valuation of the relative number and absolute values of the wavelet coefficients. A comparison between the original image and the decoded image will be done by a difference criteria calculated by the wavelet coefficients of the original image and the decoded image of the first and second iteration step of the wavelet transformation. This adaptive image compression algorithm is based on a classification of digital images into three classes and followed by the compression of the image by a suitable compression algorithm. Furthermore we will show that applying these classification rules on DICOM-images is a very effective method to do adaptive compression. The image classification algorithm and the image compression algorithms have been implemented in JAVA.

  19. Retinal Imaging: Adaptive Optics

    NASA Astrophysics Data System (ADS)

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

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed

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

    2016-01-01

    Automated analysis of retinal images plays a vital role in the examination, diagnosis, and prognosis of healthy and pathological retinas. Retinal disorders and the associated visual loss can be interpreted via quantitative correlations, based on measurements of photoreceptor loss. Therefore, it is important to develop reliable tools for identification of photoreceptor cells. In this paper, an automated algorithm is proposed, based on the use of the Hessian-Laplacian of Gaussian filter, which allows enhancement and detection of photoreceptor cells. The performance of the proposed technique is evaluated on both synthetic and high-resolution retinal images, in terms of packing density. The results on the synthetic data were compared against ground truth as well as cone counts obtained by the Li and Roorda algorithm. For the synthetic datasets, our method showed an average detection accuracy of 98.8%, compared to 93.9% for the Li and Roorda approach. The packing density estimates calculated on the retinal datasets were validated against manual counts and the results obtained by a proprietary software from Imagine Eyes and the Li and Roorda algorithm. Among the tested methods, the proposed approach showed the closest agreement with manual counting. PMID:26831589

  2. Passive adaptive imaging through turbulence

    NASA Astrophysics Data System (ADS)

    Tofsted, David

    2016-05-01

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

  3. Enhancement of video images.

    PubMed

    Baily, N A; Nachazel, R J

    1980-04-01

    The enhancement of radiographic and fluoroscopic images using simple video analog techniques is described. In each instance, both the degree of enhancement and the features of the image to be enhanced are under the direct control of the radiologist. Noise is suppressed with a sharp cut-off, low-pass filter. Three types of analog circuits are discussed. One provides edge sharpening and contrast enhancement; one allows either black or white suppression, with expansion of the remaining shades of gray; and one provides an exponential response to selectable portions of the input signal. PMID:7360962

  4. Imaging an Adapted Dentoalveolar Complex

    PubMed Central

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

    2012-01-01

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

  5. Local adaptive tone mapping for video enhancement

    NASA Astrophysics Data System (ADS)

    Lachine, Vladimir; Dai, Min (.

    2015-03-01

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

  6. Hierarchical image enhancement

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  7. A local adaptive image descriptor

    NASA Astrophysics Data System (ADS)

    Zahid Ishraque, S. M.; Shoyaib, Mohammad; Abdullah-Al-Wadud, M.; Monirul Hoque, Md; Chae, Oksam

    2013-12-01

    The local binary pattern (LBP) is a robust but computationally simple approach in texture analysis. However, LBP performs poorly in the presence of noise and large illumination variation. Thus, a local adaptive image descriptor termed as LAID is introduced in this proposal. It is a ternary pattern and is able to generate persistent codes to represent microtextures in a given image, especially in noisy conditions. It can also generate stable texture codes if the pixel intensities change abruptly due to the illumination changes. Experimental results also show the superiority of the proposed method over other state-of-the-art methods.

  8. Preliminary images from an adaptive imaging system.

    PubMed

    Griffiths, J A; Metaxas, M G; Pani, S; Schulerud, H; Esbrand, C; Royle, G J; Price, B; Rokvic, T; Longo, R; Asimidis, A; Bletsas, E; Cavouras, D; Fant, A; Gasiorek, P; Georgiou, H; Hall, G; Jones, J; Leaver, J; Li, G; Machin, D; Manthos, N; Matheson, J; Noy, M; Ostby, J M; Psomadellis, F; van der Stelt, P F; Theodoridis, S; Triantis, F; Turchetta, R; Venanzi, C; Speller, R D

    2008-06-01

    I-ImaS (Intelligent Imaging Sensors) is a European project aiming to produce real-time adaptive X-ray imaging systems using Monolithic Active Pixel Sensors (MAPS) to create images with maximum diagnostic information within given dose constraints. Initial systems concentrate on mammography and cephalography. In our system, the exposure in each image region is optimised and the beam intensity is a function of tissue thickness and attenuation, and also of local physical and statistical parameters in the image. Using a linear array of detectors, the system will perform on-line analysis of the image during the scan, followed by optimisation of the X-ray intensity to obtain the maximum diagnostic information from the region of interest while minimising exposure of diagnostically less important regions. This paper presents preliminary images obtained with a small area CMOS detector developed for this application. Wedge systems were used to modulate the beam intensity during breast and dental imaging using suitable X-ray spectra. The sensitive imaging area of the sensor is 512 x 32 pixels 32 x 32 microm(2) in size. The sensors' X-ray sensitivity was increased by coupling to a structured CsI(Tl) scintillator. In order to develop the I-ImaS prototype, the on-line data analysis and data acquisition control are based on custom-developed electronics using multiple FPGAs. Images of both breast tissues and jaw samples were acquired and different exposure optimisation algorithms applied. Results are very promising since the average dose has been reduced to around 60% of the dose delivered by conventional imaging systems without decrease in the visibility of details. PMID:18291697

  9. Image enhancement by holography.

    NASA Technical Reports Server (NTRS)

    Stroke, G. W.

    1973-01-01

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

  10. Adaptive WMMR filters for edge enhancement

    NASA Astrophysics Data System (ADS)

    Zhou, Jun; Longbotham, Harold G.

    1993-05-01

    In this paper, an adaptive WMMR filter is introduced, which adaptively changes its window size to accommodate edge width variations. We prove that for any given one dimensional input signal convergence is to fixed points, which are PICO (piecewise constant), by iterative application of the adaptive WMMR filter. An application of the filters to one-D data (non- PICO) and images of printed circuit boards are then provided. Application to images in general is discussed.

  11. Domain adaptation for microscopy imaging.

    PubMed

    Becker, Carlos; Christoudias, C Mario; Fua, Pascal

    2015-05-01

    Electron and light microscopy imaging can now deliver high-quality image stacks of neural structures. However, the amount of human annotation effort required to analyze them remains a major bottleneck. While machine learning algorithms can be used to help automate this process, they require training data, which is time-consuming to obtain manually, especially in image stacks. Furthermore, due to changing experimental conditions, successive stacks often exhibit differences that are severe enough to make it difficult to use a classifier trained for a specific one on another. This means that this tedious annotation process has to be repeated for each new stack. In this paper, we present a domain adaptation algorithm that addresses this issue by effectively leveraging labeled examples across different acquisitions and significantly reducing the annotation requirements. Our approach can handle complex, nonlinear image feature transformations and scales to large microscopy datasets that often involve high-dimensional feature spaces and large 3D data volumes. We evaluate our approach on four challenging electron and light microscopy applications that exhibit very different image modalities and where annotation is very costly. Across all applications we achieve a significant improvement over the state-of-the-art machine learning methods and demonstrate our ability to greatly reduce human annotation effort. PMID:25474809

  12. Adaptive image segmentation by quantization

    NASA Astrophysics Data System (ADS)

    Liu, Hui; Yun, David Y.

    1992-12-01

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

  13. Degraded document image enhancement

    NASA Astrophysics Data System (ADS)

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

    2007-01-01

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

  14. [Enhancement and assessment of the fundus image].

    PubMed

    Chen, Mengmeng; Xiong, Xingliang; Li, Guang; Zhang, Tingting

    2014-10-01

    A new enhancement method is proposed based on the characteristics of fundus images in this paper. Firstly, top-hat transform is utilized to weaken the background. Secondly, contrast limited adaptive histogram equalization (CLAHE) is performed to improve the uneven illumination. Finally, two-dimensional matched filters are designed to further enhance the contrast between blood vessels and background. The algorithm was tested in DIARETDB0 databases and showed good applicability for both normal and pathological fundus images. A new no-reference image quality assessment method was used to evaluate the enhancement methods objectively. The results demonstrated that the proposed method could effectively weaken the background, increase contrast, enhance details in the fundus images and improve the image quality greatly. PMID:25764739

  15. Enhanced image capture through fusion

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

  16. Next generation high resolution adaptive optics fundus imager

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

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

  17. Image enhancement system for mobile displays

    NASA Astrophysics Data System (ADS)

    Parkkinen, Jaana; Nenonen, Petri

    2005-02-01

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

  18. Image Enhancement, Image Quality, and Noise

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  19. Visual enhancement of unmixed multispectral imagery using adaptive smoothing

    USGS Publications Warehouse

    Lemeshewsky, G.P.

    2004-01-01

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

  20. Computer Program Helps Enhance Images

    NASA Technical Reports Server (NTRS)

    Stanfill, Daniel F., IV

    1994-01-01

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

  1. Retinex enhancement of infrared images.

    PubMed

    Li, Ying; He, Renjie; Xu, Guizhi; Hou, Changzhi; Sun, Yunyan; Guo, Lei; Rao, Liyun; Yan, Weili

    2008-01-01

    With the ability of imaging the temperature distribution of body, infrared imaging is promising in diagnostication and prognostication of diseases. However the poor quality of the raw original infrared images prevented applications and one of the essential problems is the low contrast appearance of the imagined object. In this paper, the image enhancement technique based on the Retinex theory is studied, which is a process that automatically retrieve the visual realism to images. The algorithms, including Frackle-McCann algorithm, McCann99 algorithm, single-scale Retinex algorithm, multi-scale Retinex algorithm and multi-scale Retinex algorithm with color restoration, are experienced to the enhancement of infrared images. The entropy measurements along with the visual inspection were compared and results shown the algorithms based on Retinex theory have the ability in enhancing the infrared image. Out of the algorithms compared, MSRCR demonstrated the best performance. PMID:19163132

  2. Camera lens adapter magnifies image

    NASA Technical Reports Server (NTRS)

    Moffitt, F. L.

    1967-01-01

    Polaroid Land camera with an illuminated 7-power magnifier adapted to the lens, photographs weld flaws. The flaws are located by inspection with a 10-power magnifying glass and then photographed with this device, thus providing immediate pictorial data for use in remedial procedures.

  3. Digital Image Enhancement of Indic Historical Manuscripts

    NASA Astrophysics Data System (ADS)

    Shi, Zhixin; Setlur, Srirangaraj; Govindaraju, Venu

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

  4. Analog enhancement of radiographic images

    NASA Technical Reports Server (NTRS)

    Baily, N. A.; Nachazel, R. J.

    1976-01-01

    The paper shows how analog methods for edge sharpening, contrast enhancement, and expansion of the range of gray levels of particular interest are effective for easy on-line application to video viewing of X-ray roentgenograms or to fluoroscopy. The technique for analog enhancement of radiographic images is a modified version of the system designed by Fuchs et al. (1972), whereby an all directional second derivative signal called detail signal is used to produce both vertical and horizontal enhancement of the image. Particular attention is given to noise filtration and contrast enhancement. Numerous radiographs supplement the text.

  5. Image super-resolution based on image adaptive decomposition

    NASA Astrophysics Data System (ADS)

    Xie, Qiwei; Wang, Haiyan; Shen, Lijun; Chen, Xi; Han, Hua

    2011-11-01

    In this paper we propose an image super-resolution algorithm based on Gaussian Mixture Model (GMM) and a new adaptive image decomposition algorithm. The new image decomposition algorithm uses local extreme of image to extract the cartoon and oscillating part of image. In this paper, we first decompose an image into oscillating and piecewise smooth (cartoon) parts, then enlarge the cartoon part with interpolation. Because GMM accurately characterizes the oscillating part, we specify it as the prior distribution and then formulate the image super-resolution problem as a constrained optimization problem to acquire the enlarged texture part and finally we obtain a fine result.

  6. Imaging-Based Treatment Adaptation in Radiation Oncology.

    PubMed

    Troost, Esther G C; Thorwarth, Daniela; Oyen, Wim J G

    2015-12-01

    In many tumor types, significant effort is being put into patient-tailored adaptation of treatment to improve outcome and preferably reduce toxicity. These opportunities first arose with the introduction of modern irradiation techniques (e.g., intensity-modulated radiotherapy) combined with functional imaging for more precise delineation of target volume. On the basis of functional CT, MRI, and PET results, radiation target volumes are altered during the course of treatment, or subvolumes inside the primary tumor are defined to enhance the dosing strategy. Moreover, the probability of complications to normal tissues is predicted using anatomic or functional imaging, such as in the use of CT or PET to predict radiation pneumonitis. Besides focusing, monitoring, and adapting photon therapy for solid tumors, PET also has a role in verifying proton-beam therapy. This article discusses the current state and remaining challenges of imaging-based treatment adaptation in radiation oncology. PMID:26429959

  7. Image space adaptive volume rendering

    NASA Astrophysics Data System (ADS)

    Corcoran, Andrew; Dingliana, John

    2012-01-01

    We present a technique for interactive direct volume rendering which provides adaptive sampling at a reduced memory requirement compared to traditional methods. Our technique exploits frame to frame coherence to quickly generate a two-dimensional importance map of the volume which guides sampling rate optimisation and allows us to provide interactive frame rates for user navigation and transfer function changes. In addition our ray casting shader detects any inconsistencies in our two-dimensional map and corrects them on the fly to ensure correct classification of important areas of the volume.

  8. 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

  9. Image-Specific Prior Adaptation for Denoising.

    PubMed

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

    2015-12-01

    Image priors are essential to many image restoration applications, including denoising, deblurring, and inpainting. Existing methods use either priors from the given image (internal) or priors from a separate collection of images (external). We find through statistical analysis that unifying the internal and external patch priors may yield a better patch prior. We propose a novel prior learning algorithm that combines the strength of both internal and external priors. In particular, we first learn a generic Gaussian mixture model from a collection of training images and then adapt the model to the given image by simultaneously adding additional components and refining the component parameters. We apply this image-specific prior to image denoising. The experimental results show that our approach yields better or competitive denoising results in terms of both the peak signal-to-noise ratio and structural similarity. PMID:26316129

  10. Contrast enhancement of mail piece images

    NASA Astrophysics Data System (ADS)

    Shin, Yong-Chul; Sridhar, Ramalingam; Demjanenko, Victor; Palumbo, Paul W.; Hull, Jonathan J.

    1992-08-01

    A New approach to contrast enhancement of mail piece images is presented. The contrast enhancement is used as a preprocessing step in the real-time address block location (RT-ABL) system. The RT-ABL system processes a stream of mail piece images and locates destination address blocks. Most of the mail pieces (classified into letters) show high contrast between background and foreground. As an extreme case, however, the seasonal greeting cards usually use colored envelopes which results in reduced contrast osured by an error rate by using a linear distributed associative memory (DAM). The DAM is trained to recognize the spectra of three classes of images: with high, medium, and low OCR error rates. The DAM is not forced to make a classification every time. It is allowed to reject as unknown a spectrum presented that does not closely resemble any that has been stored in the DAM. The DAM was fairly accurate with noisy images but conservative (i.e., rejected several text images as unknowns) when there was little ground and foreground degradations without affecting the nondegraded images. This approach provides local enhancement which adapts to local features. In order to simplify the computation of A and (sigma) , dynamic programming technique is used. Implementation details, performance, and the results on test images are presented in this paper.

  11. Adaptive prediction trees for image compression.

    PubMed

    Robinson, John A

    2006-08-01

    This paper presents a complete general-purpose method for still-image compression called adaptive prediction trees. Efficient lossy and lossless compression of photographs, graphics, textual, and mixed images is achieved by ordering the data in a multicomponent binary pyramid, applying an empirically optimized nonlinear predictor, exploiting structural redundancies between color components, then coding with hex-trees and adaptive runlength/Huffman coders. Color palettization and order statistics prefiltering are applied adaptively as appropriate. Over a diverse image test set, the method outperforms standard lossless and lossy alternatives. The competing lossy alternatives use block transforms and wavelets in well-studied configurations. A major result of this paper is that predictive coding is a viable and sometimes preferable alternative to these methods. PMID:16900671

  12. Photographic image enhancement

    NASA Astrophysics Data System (ADS)

    Hite, Gerald E.

    1990-12-01

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

  13. Photographic image enhancement

    NASA Technical Reports Server (NTRS)

    Hite, Gerald E.

    1990-01-01

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

  14. Denoising-enhancing images on elastic manifolds.

    PubMed

    Ratner, Vadim; Zeevi, Yehoshua Y

    2011-08-01

    The conflicting demands for simultaneous low-pass and high-pass processing, required in image denoising and enhancement, still present an outstanding challenge, although a great deal of progress has been made by means of adaptive diffusion-type algorithms. To further advance such processing methods and algorithms, we introduce a family of second-order (in time) partial differential equations. These equations describe the motion of a thin elastic sheet in a damping environment. They are also derived by a variational approach in the context of image processing. The new operator enables better edge preservation in denoising applications by offering an adaptive lowpass filter, which preserves high-frequency components in the pass-band better than the adaptive diffusion filter, while offering slower error propagation across edges. We explore the action of this powerful operator in the context of image processing and exploit for this purpose the wealth of knowledge accumulated in physics and mathematics about the action and behavior of this operator. The resulting methods are further generalized for color and/or texture image processing, by embedding images in multidimensional manifolds. A specific application of the proposed new approach to superresolution is outlined. PMID:21342847

  15. Helium and Enhanced Image of the Sun

    NASA Video Gallery

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

  16. Multiview image sequence enhancement

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  17. A New Adaptive Image Denoising Method

    NASA Astrophysics Data System (ADS)

    Biswas, Mantosh; Om, Hari

    2016-03-01

    In this paper, a new adaptive image denoising method is proposed that follows the soft-thresholding technique. In our method, a new threshold function is also proposed, which is determined by taking the various combinations of noise level, noise-free signal variance, subband size, and decomposition level. It is simple and adaptive as it depends on the data-driven parameters estimation in each subband. The state-of-the-art denoising methods viz. VisuShrink, SureShrink, BayesShrink, WIDNTF and IDTVWT are not able to modify the coefficients in an efficient manner to provide the good quality of image. Our method removes the noise from the noisy image significantly and provides better visual quality of an image.

  18. Adapting overcomplete wavelet models to natural images

    NASA Astrophysics Data System (ADS)

    Sallee, Phil; Olshausen, Bruno A.

    2003-11-01

    Overcomplete wavelet representations have become increasingly popular for their ability to provide highly sparse and robust descriptions of natural signals. We describe a method for incorporating an overcomplete wavelet representation as part of a statistical model of images which includes a sparse prior distribution over the wavelet coefficients. The wavelet basis functions are parameterized by a small set of 2-D functions. These functions are adapted to maximize the average log-likelihood of the model for a large database of natural images. When adapted to natural images, these functions become selective to different spatial orientations, and they achieve a superior degree of sparsity on natural images as compared with traditional wavelet bases. The learned basis is similar to the Steerable Pyramid basis, and yields slightly higher SNR for the same number of active coefficients. Inference with the learned model is demonstrated for applications such as denoising, with results that compare favorably with other methods.

  19. Information-Adaptive Image Encoding and Restoration

    NASA Technical Reports Server (NTRS)

    Park, Stephen K.; Rahman, Zia-ur

    1998-01-01

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

  20. Enhancing astronaut performance using sensorimotor adaptability training.

    PubMed

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

    2015-01-01

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

  1. Enhancing astronaut performance using sensorimotor adaptability training

    PubMed Central

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

    2015-01-01

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

  2. Enhancing retinal images by extracting structural information

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

    High-resolution imaging of the retina has significant importance for science: physics and optics, biology, and medicine. The enhancement of images with poor contrast and the detection of faint structures require objective methods for assessing perceptual image quality. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce a framework for quality assessment based on the degradation of structural information. We implemented a new processing technique on a long sequence of retinal images of subjects with normal vision. We were able to perform a precise shift-and-add at the sub-pixel level in order to resolve the structures of the size of single cells in the living human retina. Last, we quantified the restoration reliability of the distorted images using an improved quality assessment. To that purpose, we used the single image restoration method based on the ergodic principle, which has originated in solar astronomy, to deconvolve aberrations after adaptive optics compensation.

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

    NASA Astrophysics Data System (ADS)

    Jiang, Yuhao; Zachary, Josey

    2016-03-01

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

  4. Enhancement classification of galaxy images

    NASA Astrophysics Data System (ADS)

    Jenkinson, John

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

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

    NASA Astrophysics Data System (ADS)

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

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

  6. Adaptive contrast imaging: transmit frequency optimization

    NASA Astrophysics Data System (ADS)

    Ménigot, Sébastien; Novell, Anthony; Voicu, Iulian; Bouakaz, Ayache; Girault, Jean-Marc

    2010-01-01

    Introduction: Since the introduction of ultrasound (US) contrast imaging, the imaging systems use a fixed emitting frequency. However it is known that the insonified medium is time-varying and therefore an adapted time-varying excitation is expected. We suggest an adaptive imaging technique which selects the optimal transmit frequency that maximizes the acoustic contrast. Two algorithms have been proposed to find an US excitation for which the frequency was optimal with microbubbles. Methods and Materials: Simulations were carried out for encapsulated microbubbles of 2 microns by considering the modified Rayleigh-Plesset equation for 2 MHz transmit frequency and for various pressure levels (20 kPa up to 420kPa). In vitro experiments were carried out using a transducer operating at 2 MHz and using a programmable waveform generator. Contrast agent was then injected into a small container filled with water. Results and discussions: We show through simulations and in vitro experiments that our adaptive imaging technique gives: 1) in case of simulations, a gain of acoustic contrast which can reach 9 dB compared to the traditional technique without optimization and 2) for in vitro experiments, a gain which can reach 18 dB. There is a non negligible discrepancy between simulations and experiments. These differences are certainly due to the fact that our simulations do not take into account the diffraction and nonlinear propagation effects. Further optimizations are underway.

  7. Approach for reconstructing anisoplanatic adaptive optics images.

    PubMed

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

    2007-08-20

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

  8. Adaptive EAGLE dynamic solution adaptation and grid quality enhancement

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  9. Contrast-enhanced refraction imaging

    NASA Astrophysics Data System (ADS)

    Hall, Christopher J.; Rogers, Keith D.; Lewis, Rob A.; Menk, Ralf Hendrik; Arfelli, Fulvia; Siu, Karen K.; Benci, A.; Kitchen, M.; Pillon, Alessandra; Rigon, Luigi; Round, Andrew J.; Hufton, Alan P.; Evans, Andrew; Pinder, Sarah E.; Evans, S.

    2004-01-01

    An attempt has been made, for the first time, to extend the capabilities of diffraction enhanced imaging (DEI) using low concentrations of a contrast agent. A phantom has been constructed to accommodate a systematic series of diluted bromine deoxyuridase (BrDU) samples in liquid form. This was imaged using a conventional DEI arrangement and at a range of energies traversing the Br K-edge. The images were analyzed to provide a quantitative measure of contrast as a function of X-ray energy and (BrDU) concentration. The results indicate that the particular experimental arrangement was not optimized to exploit the potential of this contrast enhancement and several suggestions are discussed to improve this further.

  10. Iterative blind deconvolution of adaptive optics images

    NASA Astrophysics Data System (ADS)

    Liang, Ying; Rao, Changhui; Li, Mei; Geng, Zexun

    2006-04-01

    Adaptive optics (AO) technique has been extensively used for large ground-based optical telescopes to overcome the effect of atmospheric turbulence. But the correction is often partial. An iterative blind deconvolution (IBD) algorithm based on maximum-likelihood (ML) method is proposed to restore the details of the object image corrected by AO. IBD algorithm and the procedure are briefly introduced and the experiment results are presented. The results show that IBD algorithm is efficient for the restoration of some useful high-frequency of the image.

  11. Adaptive Optics Imaging in Laser Pointer Maculopathy.

    PubMed

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

    2016-08-01

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

  12. Comparison of various enhanced radar imaging techniques

    NASA Astrophysics Data System (ADS)

    Gupta, Inder J.; Gandhe, Avinash

    1998-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

  14. Adaptive Flight Control for Aircraft Safety Enhancements

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

  15. CMOS image sensor with contour enhancement

    NASA Astrophysics Data System (ADS)

    Meng, Liya; Lai, Xiaofeng; Chen, Kun; Yuan, Xianghui

    2010-10-01

    Imitating the signal acquisition and processing of vertebrate retina, a CMOS image sensor with bionic pre-processing circuit is designed. Integration of signal-process circuit on-chip can reduce the requirement of bandwidth and precision of the subsequent interface circuit, and simplify the design of the computer-vision system. This signal pre-processing circuit consists of adaptive photoreceptor, spatial filtering resistive network and Op-Amp calculation circuit. The adaptive photoreceptor unit with a dynamic range of approximately 100 dB has a good self-adaptability for the transient changes in light intensity instead of intensity level itself. Spatial low-pass filtering resistive network used to mimic the function of horizontal cell, is composed of the horizontal resistor (HRES) circuit and OTA (Operational Transconductance Amplifier) circuit. HRES circuit, imitating dendrite of the neuron cell, comprises of two series MOS transistors operated in weak inversion region. Appending two diode-connected n-channel transistors to a simple transconductance amplifier forms the OTA Op-Amp circuit, which provides stable bias voltage for the gate of MOS transistors in HRES circuit, while serves as an OTA voltage follower to provide input voltage for the network nodes. The Op-Amp calculation circuit with a simple two-stage Op-Amp achieves the image contour enhancing. By adjusting the bias voltage of the resistive network, the smoothing effect can be tuned to change the effect of image's contour enhancement. Simulations of cell circuit and 16×16 2D circuit array are implemented using CSMC 0.5μm DPTM CMOS process.

  16. Adaptive line enhancers for fast acquisition

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

  17. Bio-inspired color image enhancement

    NASA Astrophysics Data System (ADS)

    Meylan, Laurence; Susstrunk, Sabine

    2004-06-01

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

  18. SAR imaging via iterative adaptive approach and sparse Bayesian learning

    NASA Astrophysics Data System (ADS)

    Xue, Ming; Santiago, Enrique; Sedehi, Matteo; Tan, Xing; Li, Jian

    2009-05-01

    We consider sidelobe reduction and resolution enhancement in synthetic aperture radar (SAR) imaging via an iterative adaptive approach (IAA) and a sparse Bayesian learning (SBL) method. The nonparametric weighted least squares based IAA algorithm is a robust and user parameter-free adaptive approach originally proposed for array processing. We show that it can be used to form enhanced SAR images as well. SBL has been used as a sparse signal recovery algorithm for compressed sensing. It has been shown in the literature that SBL is easy to use and can recover sparse signals more accurately than the l 1 based optimization approaches, which require delicate choice of the user parameter. We consider using a modified expectation maximization (EM) based SBL algorithm, referred to as SBL-1, which is based on a three-stage hierarchical Bayesian model. SBL-1 is not only more accurate than benchmark SBL algorithms, but also converges faster. SBL-1 is used to further enhance the resolution of the SAR images formed by IAA. Both IAA and SBL-1 are shown to be effective, requiring only a limited number of iterations, and have no need for polar-to-Cartesian interpolation of the SAR collected data. This paper characterizes the achievable performance of these two approaches by processing the complex backscatter data from both a sparse case study and a backhoe vehicle in free space with different aperture sizes.

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

    PubMed

    Liu, Guoying; Zhang, Yun; Wang, Aimin

    2015-11-01

    Fuzzy c-means (FCM) clustering with spatial constraints has attracted great attention in the field of image segmentation. However, most of the popular techniques fail to resolve misclassification problems due to the inaccuracy of their spatial models. This paper presents a new unsupervised FCM-based image segmentation method by paying closer attention to the selection of local information. In this method, region-level local information is incorporated into the fuzzy clustering procedure to adaptively control the range and strength of interactive pixels. First, a novel dissimilarity function is established by combining region-based and pixel-based distance functions together, in order to enhance the relationship between pixels which have similar local characteristics. Second, a novel prior probability function is developed by integrating the differences between neighboring regions into the mean template of the fuzzy membership function, which adaptively selects local spatial constraints by a tradeoff weight depending upon whether a pixel belongs to a homogeneous region or not. Through incorporating region-based information into the spatial constraints, the proposed method strengthens the interactions between pixels within the same region and prevents over smoothing across region boundaries. Experimental results over synthetic noise images, natural color images, and synthetic aperture radar images show that the proposed method achieves more accurate segmentation results, compared with five state-of-the-art image segmentation methods. PMID:26186787

  20. 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.

  1. Adaptive Optics Imaging of Solar System Objects

    NASA Technical Reports Server (NTRS)

    Roddier, Francois; Owen, Toby

    1997-01-01

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

  2. Adaptive Optics Retinal Imaging: Emerging Clinical Applications

    PubMed Central

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

    2010-01-01

    The human retina is a uniquely accessible tissue. Tools like scanning laser ophthalmoscopy (SLO) and spectral domain optical coherence tomography (SD-OCT) provide clinicians with remarkably clear pictures of the living retina. While the anterior optics of the eye permit such non-invasive visualization of the retina and associated pathology, these same optics induce significant aberrations that in most cases obviate cellular-resolution imaging. Adaptive optics (AO) imaging systems use active optical elements to compensate for aberrations in the optical path between the object and the camera. Applied to the human eye, AO allows direct visualization of individual rod and cone photoreceptor cells, RPE 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 made possible with AO imaging of the human retina, and discuss applications and future prospects for clinical imaging. PMID:21057346

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

    PubMed

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

    2013-03-01

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

  4. Adaptive optics for directly imaging planetary systems

    NASA Astrophysics Data System (ADS)

    Bailey, Vanessa Perry

    In this dissertation I present the results from five papers (including one in preparation) on giant planets, brown dwarfs, and their environments, as well as on the commissioning and optimization of the Adaptive Optics system for the Large Binocular Telescope Interferometer. The first three Chapters cover direct imaging results on several distantly-orbiting planets and brown dwarf companions. The boundary between giant planets and brown dwarf companions in wide orbits is a blurry one. In Chapter 2, I use 3--5 mum imaging of several brown dwarf companions, combined with mid-infrared photometry for each system to constrain the circum-substellar disks around the brown dwarfs. I then use this information to discuss limits on scattering events versus in situ formation. In Chapters 3 and 4, I present results from an adaptive optics imaging survey for giant planets, where the target stars were selected based on the properties of their circumstellar debris disks. Specifically, we targeted systems with debris disks whose SEDs indicated gaps, clearings, or truncations; these features may possibly be sculpted by planets. I discuss in detail one planet-mass companion discovered as part of this survey, HD 106906 b. At a projected separation of 650 AU and weighing in at 11 Jupiter masses, a companion such as this is not a common outcome of any planet or binary star formation model. In the remaining three Chapters, I discuss pre-commissioning, on-sky results, and planned work on the Large Binocular Telescope Interferometer Adaptive Optics system. Before construction of the LBT AO system was complete, I tested a prototype of LBTI's pyramid wavefront sensor unit at the MMT with synthetically-generated calibration files. I present the methodology and MMT on-sky tests in Chapter 5. In Chapter 6, I present the commissioned performance of LBTIAO. Optical imperfections within LBTI limited the quality of the science images, and I describe a simple method to use the adaptive optics system

  5. Laser Image Contrast Enhancement System

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

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

    PubMed

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

    2015-01-01

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

  8. 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

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

    SciTech Connect

    Druckmueller, M.

    2013-08-15

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

  10. Imaging Radio Galaxies with Adaptive Optics

    NASA Astrophysics Data System (ADS)

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

    2000-12-01

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

  11. Extreme Adaptive Optics Planet Imager: XAOPI

    SciTech Connect

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

    2003-09-17

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

  12. Image enhancement algorithm based on improved lateral inhibition network

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

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

    PubMed

    Lee, Chi-Mei; Bo, Jin

    2016-01-01

    The authors focused on young adults with varying degrees of motor difficulties and examined their adaptability in a visuomotor adaptation task where the visual feedback of participants' movement error was presented with either 1:1 ratio (i.e., regular feedback schedule) or 1:2 ratio (i.e., enhanced feedback schedule). Within-subject design was used with two feedback schedules counter-balanced and separated for 10 days. Results revealed that participants with greater motor difficulties showed less adaptability than those with normal motor abilities in the regular feedback schedule; however, all participants demonstrated similar level of adaptability in the enhanced feedback schedule. The results suggest that error argumentation enhances adaptability in adults with low motor ability. PMID:26672393

  14. Automatic image enhancement based on multi-scale image decomposition

    NASA Astrophysics Data System (ADS)

    Feng, Lu; Wu, Zhuangzhi; Pei, Luo; Long, Xiong

    2014-01-01

    In image processing and computational photography, automatic image enhancement is one of the long-range objectives. Recently the automatic image enhancement methods not only take account of the globe semantics, like correct color hue and brightness imbalances, but also the local content of the image, such as human face and sky of landscape. In this paper we describe a new scheme for automatic image enhancement that considers both global semantics and local content of image. Our automatic image enhancement method employs the multi-scale edge-aware image decomposition approach to detect the underexposure regions and enhance the detail of the salient content. The experiment results demonstrate the effectiveness of our approach compared to existing automatic enhancement methods.

  15. Adaptive Optics Imaging and Spectroscopy of Neptune

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  16. An adaptive PCA fusion method for remote sensing images

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  17. Image enhancement by local histogram stretching

    NASA Astrophysics Data System (ADS)

    Alparslan, E.; Fuatince, Mr.

    1981-05-01

    An image enhancement algorithm that makes use of local histogram stretching is introduced. This algorithm yields considerable improvements in human observation of details in an image, compared to straightforward histogram equalization and a number of other enhancement techniques. The algorithm is especially suitable for producing hard copies of images on electrostatic plotters with limited gray levels, as shown in applications to the Girl's image and a Landsat image.

  18. Enhancement of Electrolaryngeal Speech by Adaptive Filtering.

    ERIC Educational Resources Information Center

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

    1998-01-01

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

  19. Color image enhancement based on HVS and MSRCR

    NASA Astrophysics Data System (ADS)

    Xue, Rong kun; Li, Yu feng

    2015-10-01

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

  20. Infrared image enhancement based on human visual properties

    NASA Astrophysics Data System (ADS)

    Chen, Hongyu; Hui, Bin

    2015-10-01

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

  1. Testing of hardware implementation of infrared image enhancing algorithm

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

  2. Gabor filter based fingerprint image enhancement

    NASA Astrophysics Data System (ADS)

    Wang, Jin-Xiang

    2013-03-01

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

  3. Concurrent enhancement of percolation and synchronization in adaptive networks

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    PubMed

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

    2016-01-01

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

  5. Concurrent enhancement of percolation and synchronization in adaptive networks

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Lachine, Vladimir; Smith, Gregory; Lee, Louie

    2013-02-01

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

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

    NASA Astrophysics Data System (ADS)

    Khawne, Amnach; Hamamoto, Kazuhiko; Chitsobhuk, Orachat

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

  8. JPEG 2000 coding of image data over adaptive refinement grids

    NASA Astrophysics Data System (ADS)

    Gamito, Manuel N.; Dias, Miguel S.

    2003-06-01

    An extension of the JPEG 2000 standard is presented for non-conventional images resulting from an adaptive subdivision process. Samples, generated through adaptive subdivision, can have different sizes, depending on the amount of subdivision that was locally introduced in each region of the image. The subdivision principle allows each individual sample to be recursively subdivided into sets of four progressively smaller samples. Image datasets generated through adaptive subdivision find application in Computational Physics where simulations of natural processes are often performed over adaptive grids. It is also found that compression gains can be achieved for non-natural imagery, like text or graphics, if they first undergo an adaptive subdivision process. The representation of adaptive subdivision images is performed by first coding the subdivision structure into the JPEG 2000 bitstream, ina lossless manner, followed by the entropy coded and quantized transform coefficients. Due to the irregular distribution of sample sizes across the image, the wavelet transform must be applied on irregular image subsets that are nested across all the resolution levels. Using the conventional JPEG 2000 coding standard, adaptive subdivision images would first have to be upsampled to the smallest sample size in order to attain a uniform resolution. The proposed method for coding adaptive subdivision images is shown to perform better than conventional JPEG 2000 for medium to high bitrates.

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

  10. Design of Pel Adaptive DPCM coding based upon image partition

    NASA Astrophysics Data System (ADS)

    Saitoh, T.; Harashima, H.; Miyakawa, H.

    1982-01-01

    A Pel Adaptive DPCM coding system based on image partition is developed which possesses coding characteristics superior to those of the Block Adaptive DPCM coding system. This method uses multiple DPCM coding loops and nonhierarchical cluster analysis. It is found that the coding performances of the Pel Adaptive DPCM coding method differ depending on the subject images. The Pel Adaptive DPCM designed using these methods is shown to yield a maximum performance advantage of 2.9 dB for the Girl and Couple images and 1.5 dB for the Aerial image, although no advantage was obtained for the moon image. These results show an improvement over the optimally designed Block Adaptive DPCM coding method proposed by Saito et al. (1981).

  11. Nonequilibrium Enhances Adaptation Efficiency of Stochastic Biochemical Systems

    PubMed Central

    Jia, Chen; Qian, Minping

    2016-01-01

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

  12. Nonequilibrium Enhances Adaptation Efficiency of Stochastic Biochemical Systems.

    PubMed

    Jia, Chen; Qian, Minping

    2016-01-01

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

  13. Millimeter-wave sensor image enhancement

    NASA Technical Reports Server (NTRS)

    Wilson, William J.; Suess, Helmut

    1989-01-01

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

  14. Millimeter-wave Sensor Image Enhancement

    NASA Technical Reports Server (NTRS)

    Wilson, William J.; Suess, Helmut

    1988-01-01

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

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

    PubMed

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

    2016-09-01

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

  16. Automatic image equalization and contrast enhancement using Gaussian mixture modeling.

    PubMed

    Celik, Turgay; Tjahjadi, Tardi

    2012-01-01

    In this paper, we propose an adaptive image equalization algorithm that automatically enhances the contrast in an input image. The algorithm uses the Gaussian mixture model to model the image gray-level distribution, and the intersection points of the Gaussian components in the model are used to partition the dynamic range of the image into input gray-level intervals. The contrast equalized image is generated by transforming the pixels' gray levels in each input interval to the appropriate output gray-level interval according to the dominant Gaussian component and the cumulative distribution function of the input interval. To take account of the hypothesis that homogeneous regions in the image represent homogeneous silences (or set of Gaussian components) in the image histogram, the Gaussian components with small variances are weighted with smaller values than the Gaussian components with larger variances, and the gray-level distribution is also used to weight the components in the mapping of the input interval to the output interval. Experimental results show that the proposed algorithm produces better or comparable enhanced images than several state-of-the-art algorithms. Unlike the other algorithms, the proposed algorithm is free of parameter setting for a given dynamic range of the enhanced image and can be applied to a wide range of image types. PMID:21775265

  17. Infrared image enhancement using Cellular Automata

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  18. Testing of infrared image enhancing algorithm in different spectral bands

    NASA Astrophysics Data System (ADS)

    Dulski, R.; Sosnowski, T.; Kastek, M.; Trzaskawka, P.

    2012-06-01

    The paper presents results of testing the infrared image quality enhancing algorithm based on histogram processing. Testing were performed on real images registered in NIR, MWIR, and LWIR spectral bands. Infrared images are a very specific type of information. The perception and interpretation of such image depends not only on radiative properties of observed objects and surrounding scenery. Probably still most important are skills and experience of an observer itself. In practice, the optimal settings of the camera as well as automatic temperature range or contrast control do not guarantee the displayed images are optimal from observer's point of view. The solution to this are algorithms of image quality enhancing based on digital image processing methods. Such algorithms can be implemented inside the camera or applied later, after image registration. They must improve the visibility of low-contrast objects. They should also provide effective dynamic contrast control not only across entire image but also selectively to specific areas in order to maintain optimal visualization of observed scenery. In the paper one histogram equalization algorithm was tested. Adaptive nature of the algorithm should assure significant improvement of the image quality and the same effectiveness of object detection. Another requirement and difficulty is that it should also be effective for any given thermal image and it should not cause a visible image degradation in unpredictable situations. The application of tested algorithm is a promising alternative to a very effective but complex algorithms due to its low complexity and real time operation.

  19. Image enhancement based on gamma map processing

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  20. Vessel contrast enhancement in hyperspectral images

    NASA Astrophysics Data System (ADS)

    Bjorgan, Asgeir; Denstedt, Martin; Milanič, Matija; Paluchowski, Lukasz A.; Randeberg, Lise L.

    2015-03-01

    Imaging of vessel structures can be useful for investigation of endothelial function, angiogenesis and hyper-vascularization. This can be challenging for hyperspectral tissue imaging due to photon scattering and absorption in other parts of the tissue. Real-time processing techniques for enhancement of vessel contrast in hyperspectral tissue images were investigated. Wavelet processing and an inverse diffusion model were employed, and compared to band ratio metrics and statistical methods. A multiscale vesselness filter was applied for further enhancement. The results show that vessel structures in hyperspectral images can be enhanced and characterized using a combination of statistical, numerical and more physics informed models.

  1. Adaptive predictive multiplicative autoregressive model for medical image compression.

    PubMed

    Chen, Z D; Chang, R F; Kuo, W J

    1999-02-01

    In this paper, an adaptive predictive multiplicative autoregressive (APMAR) method is proposed for lossless medical image coding. The adaptive predictor is used for improving the prediction accuracy of encoded image blocks in our proposed method. Each block is first adaptively predicted by one of the seven predictors of the JPEG lossless mode and a local mean predictor. It is clear that the prediction accuracy of an adaptive predictor is better than that of a fixed predictor. Then the residual values are processed by the MAR model with Huffman coding. Comparisons with other methods [MAR, SMAR, adaptive JPEG (AJPEG)] on a series of test images show that our method is suitable for reversible medical image compression. PMID:10232675

  2. Enhancement of galaxy images for improved classification

    NASA Astrophysics Data System (ADS)

    Jenkinson, John; Grigoryan, Artyom M.; Agaian, Sos S.

    2015-03-01

    In this paper, the classification accuracy of galaxy images is demonstrated to be improved by enhancing the galaxy images. Galaxy images often contain faint regions that are of similar intensity to stars and the image background, resulting in data loss during background subtraction and galaxy segmentation. Enhancement darkens these faint regions, enabling them to be distinguished from other objects in the image and the image background, relative to their original intensities. The heap transform is employed for the purpose of enhancement. Segmentation then produces a galaxy image which closely resembles the structure of the original galaxy image, and one that is suitable for further processing and classification. 6 Morphological feature descriptors are applied to the segmented images after a preprocessing stage and used to extract the galaxy image structure for use in training the classifier. The support vector machine learning algorithm performs training and validation of the original and enhanced data, and a comparison between the classification accuracy of each data set is included. Principal component analysis is used to compress the data sets for the purpose of classification visualization and a comparison between the reduced and original feature spaces. Future directions for this research include galaxy image enhancement by various methods, and classification performed with the use of a sparse dictionary. Both future directions are introduced.

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

    PubMed

    Daniel, Ebenezer; Anitha, J

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Biswas, Mantosh; Om, Hari

    2016-03-01

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

  5. Plasma cell adaptation to enhance particle acceleration

    SciTech Connect

    Ragheb, M. S.

    2008-06-15

    A plasma study is performed in order to construct a cell for plasma acceleration purpose. As well, a multicell design is introduced for the injection of beam driver application. The suggested idea is experimentally demonstrated for two plasma cell configuration. The preformed plasma is obtained by a symmetrically driven capacitive audio frequency discharge. It is featured by its moderate pressure of 0.1-0.2 Torr, low consumption power of 130 W maximum, low discharge voltage and frequency up to 950 V and 20 kHz, respectively, and high plasma density from 10{sup 11} to 10{sup 15} cm{sup -3}. The electron temperature obtained by Langmuir double probe varies from 1 up to 16 eV. It is observed that the increases of the discharge voltage and frequency enlarge the plasma parameters to their maximum values. The plasma cell filled with different gases demonstrates that the Ar and He gases manifest the highest ionization efficiency exceeding 100% at 950 V and 20 kHz. The formed plasma is cold; its density is uniform and stable along the positive column for long competitive lifetime. Showing that it follows the conditions to enhance particle acceleration and in conjunction with its periphery devices form a plasma cell that could be extended to serve this purpose. Demonstrating that an injected electron beam into the extended preformed plasma could follow, to long distance, a continuous trajectory of uniform density. Such plasma generated by H{sub 2} or Ar gases is suggested to be used, respectively, for low-density or higher density beam driver.

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

    SciTech Connect

    Chang, Dah-Chung; Wu, Wen-Rong

    1996-12-31

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

  7. Image edge detection based on adaptive lifting scheme

    NASA Astrophysics Data System (ADS)

    Xia, Ping; Xiang, Xuejun; Wan, Junli

    2009-10-01

    Image edge is because the gradation is the result of not continuously, is image's information basic characteristic, is also one of hot topics in image processing. This paper analyzes traditional arithmetic of image edge detection and existing problem, uses adaptive lifting wavelet analysis, adaptive adjusts the predict filter and the update filter according to information's partial characteristic, thus realizes the processing information accurate match; at the same time, improves the wavelet edge detection operator, realizes one kind to be suitable for the adaptive lifting scheme image edge detection's algorithm, and applies this method in the medicine image edge detection. The experiment results show that this paper's algorithm is better than the traditional algorithm effect.

  8. A Real Time Superresolution Image Enhancement Processor

    NASA Astrophysics Data System (ADS)

    Gerwe, D.; Menicucci, P.

    An image processor is discussed that combines many types of image enhancement onto a single compact electronics card. The current enhancements include bad pixel compensation, focal plane array non-uniformity correction, and several stages of contrast enhancement, feature sharpening, superresolution, and image motion stabilization. Though there are certainly better algorithms for particular applications, this mixture of algorithms reliably enables the system to substantially improve image quality for a large variety of sensors, platforms, and imaging geometries. The card design hosted an FPGA and microprocessor facilitated rapid development by allowing many complicated algorithm elements to be quickly coded in C, with the FPGA providing horsepower for simpler but more computationally intensive elements. Examples show the quality improvement gained by compensating for image degradations including camera motion, atmospheric turbulence induced blur, focal plane imperfections, camera pixel density, and noise.

  9. Diffraction enhanced x-ray imaging

    SciTech Connect

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

    1997-09-01

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

  10. Content- and disparity-adaptive stereoscopic image retargeting

    NASA Astrophysics Data System (ADS)

    Yan, Weiqing; Hou, Chunping; Zhou, Yuan; Xiang, Wei

    2016-02-01

    The paper proposes a content- and disparity-adaptive stereoscopic image retargeting. To simultaneously avoid the saliency content and disparity distortion, firstly, we calculate the image saliency region distortion difference, and conclude the factors causing visual distortion. Then, the proposed method via a convex quadratic programming can simultaneously avoid the distortion of the salient region and adjust disparity to a target area, by considering the relationship of the scaling factor of salient region and the disparity scaling factor. The experimental results show that the proposed method is able to successfully adapt the image disparity to the target display screen, while the salient objects remain undistorted in the retargeted stereoscopic image.

  11. Enhanced Video Surveillance (EVS) with speckle imaging

    SciTech Connect

    Carrano, C J

    2004-01-13

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

  12. Adaptive SVD-Based Digital Image Watermarking

    NASA Astrophysics Data System (ADS)

    Shirvanian, Maliheh; Torkamani Azar, Farah

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

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

    PubMed

    Webster, Michael A

    2014-11-01

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

  14. Image Sensors Enhance Camera Technologies

    NASA Technical Reports Server (NTRS)

    2010-01-01

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

  15. Image contrast enhancement using Chebyshev wavelet moments

    NASA Astrophysics Data System (ADS)

    Uchaev, Dm. V.; Uchaev, D. V.; Malinnikov, V. A.

    2015-12-01

    A new algorithm for image contrast enhancement in the Chebyshev moment transform (CMT) domain is introduced. This algorithm is based on a contrast measure that is defined as the ratio of high-frequency to zero-frequency content in the bands of CMT matrix. Our algorithm enables to enhance a large number of high-spatial-frequency coefficients, that are responsible for image details, without severely degrading low-frequency contributions. To enhance high-frequency Chebyshev coefficients we use a multifractal spectrum of scaling exponents (SEs) for Chebyshev wavelet moment (CWM) magnitudes, where CWMs are multiscale realization of Chebyshev moments (CMs). This multifractal spectrum is very well suited to extract meaningful structures on images of natural scenes, because these images have a multifractal character. Experiments with test images show some advantages of the proposed algorithm as compared to other widely used image enhancement algorithms. The main advantage of our algorithm is the following: the algorithm very well highlights image details during image contrast enhancement.

  16. Coherent Image Layout using an Adaptive Visual Vocabulary

    SciTech Connect

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

    2013-03-06

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

  17. 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.

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

    PubMed Central

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

    2013-01-01

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

  19. The research of infrared image enhancement algorithm based on human vision

    NASA Astrophysics Data System (ADS)

    Wang, Chen; Gao, Sili; Tang, Xinyi

    2014-11-01

    Infrared images have their own characteristics: low contrast, great noise, large dynamic range and poor visual effect. The traditional image enhancement algorithms have certain limitations and can't achieve a good visual effect. In order to obtain a good visual effect and improve the target detection and recognition capabilities, the paper studied various enhancement methods. After analyzing the retinex theory, we choose the image enhancement method based on human visual system called retinex to process infrared images. Retinex has been used to enhance the visible light image. To do experiment on infrared image enhancement, multi-scale retinex method gets ideal visual effect. On this basis, we propose an improved multi-scale Retinex (AMSR) method based on adaptive adjustment. This method can adaptively adjust the gray level and contrast of the image, enhance the details, make the weak small targets more conducive to the human eye observation. While, it is impossible to find a method suited for all infrared images with different characteristics. So, we use several traditional image enhancement algorithms to compare with the retinex algorithms. And calculate the objective evaluation factors, including average, standard deviation, entropy and so on. After observation the processing results and analyzing these evaluation factors, the AMSR algorithm is proved having its applicability and superiority. In order to select a suitable infrared image enhancement algorithms, we analyze the applicability of each enhancement methods for infrared image has obvious characteristics, To some extent, the study is significant to the infrared target detection and recognition.

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

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

  1. Hierarchical Segmentation Enhances Diagnostic Imaging

    NASA Technical Reports Server (NTRS)

    2007-01-01

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

  2. Combined terahertz imaging system for enhanced imaging quality

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  3. Towards Adaptive High-Resolution Images Retrieval Schemes

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  4. An enhanced fast scanning algorithm for image segmentation

    NASA Astrophysics Data System (ADS)

    Ismael, Ahmed Naser; Yusof, Yuhanis binti

    2015-12-01

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

  5. 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. PMID:18262881

  6. Adaptive filtering image preprocessing for smart FPA technology

    NASA Astrophysics Data System (ADS)

    Brooks, Geoffrey W.

    1995-05-01

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

  7. Enhancement of Magnetic Resonance Imaging with Metasurfaces.

    PubMed

    Slobozhanyuk, Alexey P; Poddubny, Alexander N; Raaijmakers, Alexander J E; van den Berg, Cornelis A T; Kozachenko, Alexander V; Dubrovina, Irina A; Melchakova, Irina V; Kivshar, Yuri S; Belov, Pavel A

    2016-03-01

    It is revealed that the unique properties of ultrathin metasurface resonators can improve magnetic resonance imaging dramatically. A metasurface formed when an array of metallic wires is placed inside a scanner under the studied object and a substantial enhancement of the radio-frequency magnetic field is achieved by means of subwavelength manipulation with the metasurface, also allowing improved image resolution. PMID:26754827

  8. Digital enhancement of flow field images

    NASA Technical Reports Server (NTRS)

    Kudlinski, Robert A.; Park, Stephen K.

    1988-01-01

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

  9. Three-dimensional region-based adaptive image processing techniques for volume visualization applications

    NASA Astrophysics Data System (ADS)

    de Deus Lopes, Roseli; Zuffo, Marcelo K.; Rangayyan, Rangaraj M.

    1996-04-01

    Recent advances in three-dimensional (3D) imaging techniques have expanded the scope of applications of volume visualization to many areas such as medical imaging, scientific visualization, robotic vision, and virtual reality. Advanced image filtering, enhancement, and analysis techniques are being developed in parallel in the field of digital image processing. Although the fields cited have many aspects in common, it appears that many of the latest developments in image processing are not being applied to the fullest extent possible in visualization. It is common to encounter the use of rather simple and elementary image pre- processing operations being used in visualization and 3D imaging applications. The purpose of this paper is to present an overview of selected topics from recent developments in adaptive image processing and demonstrate or suggest their applications in volume visualization. The techniques include adaptive noise removal; improvement of contrast and visibility of objects; space-variant deblurring and restoration; segmentation-based lossless coding for data compression; and perception-based measures for analysis, enhancement, and rendering. The techniques share the common base of identification of adaptive regions by region growing, which lends them a perceptual basis related to the human visual system. Preliminary results obtained with some of the techniques implemented so far are used to illustrate the concepts involved, and to indicate potential performance capabilities of the methods.

  10. 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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

    Webster, Michael A.

    2014-01-01

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

  13. Noise reduction and image enhancement using a hardware implementation of artificial neural networks

    NASA Astrophysics Data System (ADS)

    David, Robert; Williams, Erin; de Tremiolles, Ghislain; Tannhof, Pascal

    1999-03-01

    In this paper, we present a neural based solution developed for noise reduction and image enhancement using the ZISC, an IBM hardware processor which implements the Restricted Coulomb Energy algorithm and the K-Nearest Neighbor algorithm. Artificial neural networks present the advantages of processing time reduction in comparison with classical models, adaptability, and the weighted property of pattern learning. The goal of the developed application is image enhancement in order to restore old movies (noise reduction, focus correction, etc.), to improve digital television images, or to treat images which require adaptive processing (medical images, spatial images, special effects, etc.). Image results show a quantitative improvement over the noisy image as well as the efficiency of this system. Further enhancements are being examined to improve the output of the system.

  14. Automatic anatomically selective image enhancement in digital chest radiography

    SciTech Connect

    Sezan, M.I. ); Minerbo, G.N. ); Schaetzing, R. )

    1989-06-01

    The authors develop a technique for automatic anatomically selective enhancement of digital chest radiographs. Anatomically selective enhancement is motivated by the desire to simultaneously meet the different enhancement requirements of the lung field and the mediastinum. A recent peak detection algorithm and a set of rules are applied to the image histogram to determine automatically a gray-level threshold between the lung field and mediastinum. The gray-level threshold facilitates anatomically selective gray-scale modification and/or unsharp masking. Further, in an attempt to suppress possible white-band or black-band artifacts due to unsharp masking at sharp edges, local-contrast adaptivity is incorporated into anatomically selective unsharp masking by designing an anatomy-sensitive emphasis parameter which varies asymmetrically with positive and negative values of the local image contrast.

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

    NASA Astrophysics Data System (ADS)

    Kellogg, Robert L.; Escuti, Michael J.

    2007-09-01

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

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

    SciTech Connect

    Ren Deqing; Dou Jiangpei; Zhang Xi; Zhu Yongtian

    2012-07-10

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

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

    NASA Astrophysics Data System (ADS)

    Ai, Ling; Ding, Mingyue; Zhang, Xuming

    2016-03-01

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

  18. In vivo high-resolution retinal imaging using adaptive optics.

    PubMed

    Seyedahmadi, Babak Jian; Vavvas, Demetrios

    2010-01-01

    Retinal imaging with conventional methods is only able to overcome the lowest order of aberration, defocus and astigmatism. The human eye is fraught with higher order of aberrations. Since we are forced to use the human optical system in retinal imaging, the images are degraded. In addition, all of these distortions are constantly changing due to head/eye movement and change in accommodation. Adaptive optics is a promising technology introduced in the field of ophthalmology to measure and compensate for these aberrations. High-resolution obtained by adaptive optics enables us to view and image the retinal photoreceptors, retina pigment epithelium, and identification of cone subclasses in vivo. In this review we will be discussing the basic technology of adaptive optics and hardware requirement in addition to clinical applications of such technology. PMID:21090998

  19. Adaptive entropy coded subband coding of images.

    PubMed

    Kim, Y H; Modestino, J W

    1992-01-01

    The authors describe a design approach, called 2-D entropy-constrained subband coding (ECSBC), based upon recently developed 2-D entropy-constrained vector quantization (ECVQ) schemes. The output indexes of the embedded quantizers are further compressed by use of noiseless entropy coding schemes, such as Huffman or arithmetic codes, resulting in variable-rate outputs. Depending upon the specific configurations of the ECVQ and the ECPVQ over the subbands, many different types of SBC schemes can be derived within the generic 2-D ECSBC framework. Among these, the authors concentrate on three representative types of 2-D ECSBC schemes and provide relative performance evaluations. They also describe an adaptive buffer instrumented version of 2-D ECSBC, called 2-D ECSBC/AEC, for use with fixed-rate channels which completely eliminates buffer overflow/underflow problems. This adaptive scheme achieves performance quite close to the corresponding ideal 2-D ECSBC system. PMID:18296138

  20. Content-adaptive ghost imaging of dynamic scenes.

    PubMed

    Li, Ziwei; Suo, Jinli; Hu, Xuemei; Dai, Qionghai

    2016-04-01

    Limited by long acquisition time of 2D ghost imaging, current ghost imaging systems are so far inapplicable for dynamic scenes. However, it's been demonstrated that nature images are spatiotemporally redundant and the redundancy is scene dependent. Inspired by that, we propose a content-adaptive computational ghost imaging approach to achieve high reconstruction quality under a small number of measurements, and thus achieve ghost imaging of dynamic scenes. To utilize content-adaptive inter-frame redundancy, we put the reconstruction under an iterative reweighted optimization, with non-uniform weight computed from temporal-correlated frame sequences. The proposed approach can achieve dynamic imaging at 16fps with 64×64-pixel resolution. PMID:27137022

  1. An experimental infrared sensor using adaptive coded apertures for enhanced resolution

    NASA Astrophysics Data System (ADS)

    Gordon, Neil T.; de Villiers, Geoffrey D.; Ridley, Kevin D.; Bennett, Charlotte R.; McNie, Mark E.; Proudler, Ian K.; Russell, Lee; Slinger, Christopher W.; Gilholm, Kevin

    2010-08-01

    Adaptive coded aperture imaging (ACAI) has the potential to enhance greatly the performance of sensing systems by allowing sub detector pixel image and tracking resolution. A small experimental system has been set up to allow the practical demonstration of these benefits in the mid infrared, as well as investigating the calibration and stability of the system. The system can also be used to test modeling of similar ACAI systems in the infrared. The demonstrator can use either a set of fixed masks or a novel MOEMS adaptive transmissive spatial light modulator. This paper discusses the design and testing of the system including the development of novel decoding algorithms and some initial imaging results are presented.

  2. Development of a Countermeasure to Enhance Postflight Locomotor Adaptability

    NASA Technical Reports Server (NTRS)

    Bloomberg, Jacob J.

    2006-01-01

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

  3. Tooling Techniques Enhance Medical Imaging

    NASA Technical Reports Server (NTRS)

    2012-01-01

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

  4. 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.

  5. 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. PMID:26417525

  6. On pre-image iterations for speech enhancement.

    PubMed

    Leitner, Christina; Pernkopf, Franz

    2015-01-01

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

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

    SciTech Connect

    Smith, Mark William; Wick, David Victor

    2004-11-01

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

  8. Multiscale image enhancement of chromosome banding patterns

    NASA Astrophysics Data System (ADS)

    Wu, Qiang; Castleman, Kenneth R.

    1996-10-01

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

  9. Enhancing forensic science with spectroscopic imaging

    NASA Astrophysics Data System (ADS)

    Ricci, Camilla; Kazarian, Sergei G.

    2006-09-01

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

  10. Adaptation of web pages and images for mobile applications

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

  11. Adaptive polarimetric image representation for contrast optimization of a polarized beacon through fog

    NASA Astrophysics Data System (ADS)

    Panigrahi, Swapnesh; Fade, Julien; Alouini, Mehdi

    2015-06-01

    We present a contrast-maximizing optimal linear representation of polarimetric images obtained from a snapshot polarimetric camera for enhanced vision of a polarized light source in obscured weather conditions (fog, haze, cloud) over long distances (above 1 km). We quantitatively compare the gain in contrast obtained by different linear representations of the experimental polarimetric images taken during rapidly varying foggy conditions. It is shown that the adaptive image representation that depends on the correlation in background noise fluctuations in the two polarimetric images provides an optimal contrast enhancement over all weather conditions as opposed to a simple difference image which underperforms during low visibility conditions. Finally, we derive the analytic expression of the gain in contrast obtained with this optimal representation and show that the experimental results are in agreement with the assumed correlated Gaussian noise model.

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

    PubMed

    Bamber, J C; Daft, C

    1986-01-01

    Current medical ultrasonic scanning instrumentation permits the display of fine image detail (speckle) which does not transfer useful information but degrades the apparent low contrast resolution in the image. An adaptive two-dimensional filter has been developed which uses local features of image texture to recognize and maximally low-pass filter those parts of the image which correspond to fully developed speckle, while substantially preserving information associated with resolved-object structure. A first implementation of the filter is described which uses the ratio of the local variance and the local mean as the speckle recognition feature. Preliminary results of applying this form of display processing to medical ultrasound images are very encouraging; it appears that the visual perception of features such as small discrete structures, subtle fluctuations in mean echo level and changes in image texture may be enhanced relative to that for unprocessed images. PMID:3510500

  13. Nanoparticles as image enhancing agents for ultrasonography

    NASA Astrophysics Data System (ADS)

    Liu, Jun; Levine, Andrea L.; Mattoon, John S.; Yamaguchi, Mamoru; Lee, Robert J.; Pan, Xueliang; Rosol, Thomas J.

    2006-05-01

    Nanoparticles have drawn great attention as targeted imaging and/or therapeutic agents. The small size of the nanoparticles allows them to target cells that are beyond capillary vasculature, such as cancer cells. We investigated the effect of solid nanoparticles for enhancing ultrasonic grey scale images in tissue phantoms and mouse livers in vivo. Silica nanospheres (100 nm) were dispersed in agarose at 1-2.5% mass concentration and imaged by a high-resolution ultrasound imaging system (transducer centre frequency: 30 MHz). Polystyrene particles of different sizes (500-3000 nm) and concentrations (0.13-0.75% mass) were similarly dispersed in agarose and imaged. Mice were injected intravenously with nanoparticle suspensions in saline. B-mode images of the livers were acquired at different time points after particle injection. An automated computer program was used to quantify the grey scale changes. Ultrasonic reflections were observed from nanoparticle suspensions in agarose gels. The image brightness, i.e., mean grey scale level, increased with particle size and concentration. The mean grey scale of mouse livers also increased following particle administration. These results indicated that it is feasible to use solid nanoparticles as contrast enhancing agents for ultrasonic imaging.

  14. Feature-Linking Model for Image Enhancement.

    PubMed

    Zhan, Kun; Teng, Jicai; Shi, Jinhui; Li, Qiaoqiao; Wang, Mingying

    2016-06-01

    Inspired by gamma-band oscillations and other neurobiological discoveries, neural networks research shifts the emphasis toward temporal coding, which uses explicit times at which spikes occur as an essential dimension in neural representations. We present a feature-linking model (FLM) that uses the timing of spikes to encode information. The first spiking time of FLM is applied to image enhancement, and the processing mechanisms are consistent with the human visual system. The enhancement algorithm achieves boosting the details while preserving the information of the input image. Experiments are conducted to demonstrate the effectiveness of the proposed method. Results show that the proposed method is effective. PMID:26942747

  15. Nanobubbles for enhanced ultrasound imaging of tumors.

    PubMed

    Yin, Tinghui; Wang, Ping; Zheng, Rongqin; Zheng, Bowen; Cheng, Du; Zhang, Xinling; Shuai, Xintao

    2012-01-01

    The fabrication and initial applications of nanobubbles (NBs) have shown promising results in recent years. A small particle size is a basic requirement for ultrasound contrast-enhanced agents that penetrate tumor blood vessel pores to allow for targeted imaging and therapy. However, the nanoscale size of the particles used has the disadvantage of weakening the imaging ability of clinical diagnostic ultrasound. In this work, we fabricated a lipid NBs contrast-enhanced ultrasound agent and evaluated its passive targeting ability in vivo. The results showed that the NBs were small (436.8 ± 5.7 nm), and in vitro ultrasound imaging suggested that the ultrasonic imaging ability is comparable to that of microbubbles (MBs). In vivo experiments confirmed the ability of NBs to passively target tumor tissues. The NBs remained in the tumor area for a longer period because they exhibited enhanced permeability and retention. Direct evidence was obtained by direct observation of red fluorescence-dyed NBs in tumor tissue using confocal laser scanning microscopy. We have demonstrated the ability to fabricate NBs that can be used for the in vivo contrast-enhanced imaging of tumor tissue and that have potential for drug/gene delivery. PMID:22393289

  16. Improvements for Image Compression Using Adaptive Principal Component Extraction (APEX)

    NASA Technical Reports Server (NTRS)

    Ziyad, Nigel A.; Gilmore, Erwin T.; Chouikha, Mohamed F.

    1997-01-01

    The issues of image compression and pattern classification have been a primary focus of researchers among a variety of fields including signal and image processing, pattern recognition, data classification, etc. These issues depend on finding an efficient representation of the source data. In this paper we collate our earlier results where we introduced the application of the. Hilbe.rt scan to a principal component algorithm (PCA) with Adaptive Principal Component Extraction (APEX) neural network model. We apply these technique to medical imaging, particularly image representation and compression. We apply the Hilbert scan to the APEX algorithm to improve results

  17. Adaptive polyphase subband decomposition structures for image compression.

    PubMed

    Gerek, O N; Cetin, A E

    2000-01-01

    Subband decomposition techniques have been extensively used for data coding and analysis. In most filter banks, the goal is to obtain subsampled signals corresponding to different spectral regions of the original data. However, this approach leads to various artifacts in images having spatially varying characteristics, such as images containing text, subtitles, or sharp edges. In this paper, adaptive filter banks with perfect reconstruction property are presented for such images. The filters of the decomposition structure which can be either linear or nonlinear vary according to the nature of the signal. This leads to improved image compression ratios. Simulation examples are presented. PMID:18262904

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

    PubMed

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

    2016-01-10

    The Gemini Planet Imager's adaptive optics (AO) subsystem was designed specifically to facilitate high-contrast imaging. A definitive description of the system's algorithms and technologies as built is given. 564 AO telemetry measurements from the Gemini Planet Imager Exoplanet Survey campaign are analyzed. The modal gain optimizer tracks changes in atmospheric conditions. Science observations show that image quality can be improved with the use of both the spatially filtered wavefront sensor and linear-quadratic-Gaussian control of vibration. The error budget indicates that for all targets and atmospheric conditions AO bandwidth error is the largest term. PMID:26835769

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

    PubMed Central

    Wu, Shibin; Xie, Yaoqin

    2013-01-01

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

  20. Guided Adaptive Image Smoothing via Directional Anisotropic Structure Measurement.

    PubMed

    Zang, Yu; Huang, Hua; Zhang, Lei

    2015-09-01

    Image smoothing prefers a good metric to identify dominant structures from textures adaptive of intensity contrast. In this paper, we drop on a novel directional anisotropic structure measurement (DASM) toward adaptive image smoothing. With observations on psychological perception regarding anisotropy, non-periodicity and local directionality, DASM can well characterize structures and textures independent on their contrast scales. By using such measurement as constraint, we design a guided adaptive image smoothing scheme by improving extrema localization and envelopes construction in a structure-aware manner. Our approach can well suppresses the staircase-like artifacts and blur of structures that appear in previous methods, which better suits structure-preserving image smoothing task. The algorithm is performed on a space-filling curve as the reduced domain, so it is very fast and much easy to implement in practice. We make comprehensive comparisons with previous state-of-the-art methods for a variety of applications. Experimental results demonstrate the merit using our DASM as metric to identify structures, and the effectiveness and efficiency of our adaptive image smoothing approach to produce commendable results. PMID:26357284

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2016-01-01

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

  3. Adaptive deformable image registration of inhomogeneous tissues

    NASA Astrophysics Data System (ADS)

    Ren, Jing

    2015-03-01

    Physics based deformable registration can provide physically consistent image match of deformable soft tissues. In order to help radiologist/surgeons to determine the status of malicious tumors, we often need to accurately align the regions with embedded tumors. This is a very challenging task since the tumor and the surrounding tissues have very different tissue properties such as stiffness and elasticity. In order to address this problem, based on minimum strain energy principle in elasticity theory, we propose to partition the whole region of interest into smaller sub-regions and dynamically adjust weights of vessel segments and bifurcation points in each sub-region in the registration objective function. Our previously proposed fast vessel registration is used as a component in the inner loop. We have validated the proposed method using liver MR images from human subjects. The results show that our method can detect the large registration errors and improve the registration accuracy in the neighborhood of the tumors and guarantee the registration errors to be within acceptable accuracy. The proposed technique has the potential to significantly improve the registration capability and the quality of clinical diagnosis and treatment planning.

  4. 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

  5. Local adaptive filtering of images corrupted by nonstationary noise

    NASA Astrophysics Data System (ADS)

    Lukin, Vladimir V.; Fevralev, Dmitriy V.; Ponomarenko, Nikolay N.; Pogrebnyak, Oleksiy B.; Egiazarian, Karen O.; Astola, Jaakko T.

    2009-02-01

    In various practical situations of remote sensing image processing it is assumed that noise is nonstationary and no a priory information on noise dependence on local mean or about local properties of noise statistics is available. It is shown that in such situations it is difficult to find a proper filter for effective image processing, i.e., for noise removal with simultaneous edge/detail preservation. To deal with such images, a local adaptive filter based on discrete cosine transform in overlapping blocks is proposed. A threshold is set locally based on a noise standard deviation estimate obtained for each block. Several other operations to improve performance of the locally adaptive filter are proposed and studied. The designed filter effectiveness is demonstrated for simulated data as well as for real life radar remote sensing and marine polarimetric radar images.

  6. Techniques for radar imaging using a wideband adaptive array

    NASA Astrophysics Data System (ADS)

    Curry, Mark Andrew

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

  7. Multistatic adaptive microwave imaging for early breast cancer detection.

    PubMed

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

    2006-08-01

    We propose a new multistatic adaptive microwave imaging (MAMI) method for early breast cancer detection. MAMI is a two-stage robust Capon beamforming (RCB) based image formation algorithm. MAMI exhibits higher resolution, lower sidelobes, and better noise and interference rejection capabilities than the existing approaches. The effectiveness of using MAMI for breast cancer detection is demonstrated via a simulated 3-D breast model and several numerical examples. PMID:16916099

  8. IR CMOS: infrared enhanced silicon imaging

    NASA Astrophysics Data System (ADS)

    Pralle, M. U.; Carey, J. E.; Haddad, Homayoon; Vineis, C.; Sickler, J.; Li, X.; Jiang, J.; Sahebi, F.; Palsule, C.; McKee, J.

    2013-06-01

    SiOnyx has developed visible and infrared CMOS image sensors leveraging a proprietary ultrafast laser semiconductor process technology. This technology demonstrates 10 fold improvements in infrared sensitivity over incumbent imaging technology while maintaining complete compatibility with standard CMOS image sensor process flows. Furthermore, these sensitivity enhancements are achieved on a focal plane with state of the art noise performance of 2 electrons/pixel. By capturing light in the visible regime as well as infrared light from the night glow, this sensor technology provides imaging in daytime through twilight and into nighttime conditions. The measured 10x quantum efficiency at the critical 1064 nm laser node enables see spot imaging capabilities in a variety of ambient conditions. The spectral sensitivity is from 400 to 1200 nm.

  9. Polarization imaging with enhanced spatial resolution

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  10. Resolution enhancement in medical ultrasound imaging

    PubMed Central

    Ploquin, Marie; Basarab, Adrian; Kouamé, Denis

    2015-01-01

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

  11. Stochastic processes, estimation theory and image enhancement

    NASA Technical Reports Server (NTRS)

    Assefi, T.

    1978-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

  13. 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).

  14. eXtreme Adaptive Optics Planet Imager: Overview and status

    SciTech Connect

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

    2004-08-18

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

  15. Colored adaptive compressed imaging with a single photodiode.

    PubMed

    Yan, Yiyun; Dai, Huidong; Liu, Xingjiong; He, Weiji; Chen, Qian; Gu, Guohua

    2016-05-10

    Computational ghost imaging is commonly used to reconstruct grayscale images. Currently, however, there is little research aimed at reconstructing color images. In this paper, we theoretically and experimentally demonstrate a colored adaptive compressed imaging method. Benefiting from imaging in YUV color space, the proposed method adequately exploits the sparsity of the U, V components in the wavelet domain, the interdependence between luminance and chrominance, and human visual characteristics. The simulation and experimental results show that our method greatly reduces the measurements required and offers better image quality compared to recovering the red (R), green (G), and blue (B) components separately in RGB color space. As the application of a single photodiode increases, our method shows great potential in many fields. PMID:27168280

  16. High-resolution adaptive imaging with a single photodiode

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  17. High-resolution adaptive imaging with a single photodiode

    PubMed Central

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

    2015-01-01

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

  18. How we perform delayed enhancement imaging.

    PubMed

    Kim, Raymond J; Shah, Dipan J; Judd, Robert M

    2003-07-01

    Recently, numerous studies have demonstrated the effectiveness of a segmented inversion recovery fast gradient echo (seg IR-FGE) sequence for differentiating injured from normal myocardium. This technique for delayed enhancement imaging has been shown to be effective in identifying the presence and extent of myocardial infarction, as well as predicting improvement in contractile function after coronary revascularization. In this article we outline the procedure of delayed enhancement imaging performed at our center, describe the seg IR-FGE sequence in more detail, including our process for choosing sequence settings, review our process of image interpretation, and highlight potential pitfalls (and techniques to overcome them) that we have encountered in our experience with performing the technique in over 1500 patients. PMID:12882082

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

    SciTech Connect

    Gibbard, S; Marchis, F

    2002-12-20

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

  20. An adaptive algorithm for motion compensated color image coding

    NASA Technical Reports Server (NTRS)

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

    1987-01-01

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

  1. Image enhancement based on edge boosting algorithm

    NASA Astrophysics Data System (ADS)

    Ngernplubpla, Jaturon; Chitsobhuk, Orachat

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  3. 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

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

    PubMed

    Liu, Changgeng; Kim, Myung K

    2015-01-01

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

  5. Digital adaptive optics line-scanning confocal imaging system

    NASA Astrophysics Data System (ADS)

    Liu, Changgeng; Kim, Myung K.

    2015-11-01

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

  6. Nanoparticle-dispersed metamaterial sensors for adaptive coded aperture imaging applications

    NASA Astrophysics Data System (ADS)

    Nehmetallah, Georges; Banerjee, Partha; Aylo, Rola; Rogers, Stanley

    2011-09-01

    We propose tunable single-layer and multi-layer (periodic and with defect) structures comprising nanoparticle dispersed metamaterials in suitable hosts, including adaptive coded aperture constructs, for possible Adaptive Coded Aperture Imaging (ACAI) applications such as in microbolometry, pressure/temperature sensors, and directed energy transfer, over a wide frequency range, from visible to terahertz. These structures are easy to fabricate, are low-cost and tunable, and offer enhanced functionality, such as perfect absorption (in the case of bolometry) and low cross-talk (for sensors). Properties of the nanoparticle dispersed metamaterial are determined using effective medium theory.

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

    PubMed

    Gur, M Berke; Niezrecki, Christopher

    2011-04-01

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

  8. 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. PMID:18255433

  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. 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

  11. Image registration for DSA quality enhancement.

    PubMed

    Buzug, T M; Weese, J

    1998-01-01

    A generalized framework for histogram-based similarity measures is presented and applied to the image-enhancement task in digital subtraction angiography (DSA). The class of differentiable, strictly convex weighting functions is identified as suitable weightings of histograms for measuring the degree of clustering that goes along with registration. With respect to computation time, the energy similarity measure is the function of choice for the registration of mask and contrast image prior to subtraction. The robustness of the energy measure is studied for geometrical image distortions like rotation and scaling. Additionally, it is investigated how the histogram binning and inhomogeneous motion inside the templates influence the quality of the similarity measure. Finally, the registration success for the automated procedure is compared with the manually shift-corrected image pair of the head. PMID:9719851

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

    NASA Astrophysics Data System (ADS)

    Sellahewa, Harin; Jassim, Sabah A.

    2009-05-01

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

  13. Adaptive spectral imager for space-based sensing

    NASA Astrophysics Data System (ADS)

    Vujkovic-Cvijin, Pajo; Goldstein, Neil; Fox, Marsha J.; Higbee, Shawn D.; Becker, Latika S.; Ooi, Teng K.

    2006-05-01

    Optical sensors aboard space vehicles designated to perform seeker functions need to generate multispectral images in the mid-wave infrared (MWIR) and long-wave infrared (LWIR) spectral regions in order to investigate and classify man-made space objects, and to distinguish them relative to the interfering scene clutter. The spectral imager part of the sensor collects spectral signatures of the observed objects in order to extract information on surface emissivity and target temperature, both important parameters for object-discrimination algorithms. The Adaptive Spectral Imager described in this paper fulfills two functions simultaneously: one output produces instantaneous two-dimensional polychromatic imagery for object acquisition and tracking, while the other output produces multispectral images for object discrimination and classification. The spectral and temporal resolution of the data produced by the spectral imager are adjustable in real time, making it possible to achieve optimum tradeoff between different sensing functions to match dynamic monitoring requirements during a mission. The system has high optical collection efficiency, with output data rates limited only by the readout speed of the detector array. The instrument has no macro-scale moving parts, and can be built in a robust, small-volume and lightweight package, suitable for integration with space vehicles. The technology is also applicable to multispectral imaging applications in diverse areas such as surveillance, agriculture, process control, and biomedical imaging, and can be adapted for use in any spectral domain from the ultraviolet (UV) to the LWIR region.

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

    NASA Astrophysics Data System (ADS)

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

    2005-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Technical Reports Server (NTRS)

    Shlien, S.; Goodenough, D.

    1974-01-01

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

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

    PubMed Central

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

    2015-01-01

    We use our previously developed adaptive optics (AO) scanning laser ophthalmoscope (SLO)/ optical coherence tomography (OCT) instrument to investigate its capability for imaging retinal vasculature. The system records SLO and OCT images simultaneously with a pixel to pixel correspondence which allows a direct comparison between those imaging modalities. Different field of views ranging from 0.8°x0.8° up to 4°x4° are supported by the instrument. In addition a dynamic focus scheme was developed for the AO-SLO/OCT system in order to maintain the high transverse resolution throughout imaging depth. The active axial eye tracking that is implemented in the OCT channel allows time resolved measurements of the retinal vasculature in the en-face imaging plane. Vessel walls and structures that we believe correspond to individual erythrocytes could be visualized with the system. PMID:25909024

  19. Enhancement of fluoroscopic images with varying contrast.

    PubMed

    Ozanian, T O; Phillips, R

    2001-04-01

    A heuristic algorithm for enhancement of fluoroscopic images of varying contrast is proposed. The new technique aims at identifying a suitable type of enhancement for different locations in an image. The estimation relies on simple preliminary classification of image parts into one of the following types: uniform, sharp (with sufficient contrast), detail-containing (structure present) and unknown (for the cases where it is difficult to make a decision). Different smoothing techniques are applied locally in the different types of image parts. For those parts that are classified as detail-containing, probable object boundaries are identified and local sharpening is carried out to increase the contrast at these places. The adopted approach attempts to improve the quality of an image by reducing available noise and simultaneously increasing the contrast at probable object boundaries without increasing the overall dynamic range. In addition, it allows noise to be cleaned, that at some locations is stronger than the fine structure at other locations, whilst preserving the details. PMID:11223147

  20. Interpretation techniques. [image enhancement and pattern recognition

    NASA Technical Reports Server (NTRS)

    Dragg, J. L.

    1974-01-01

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

  1. Raster image adaptation for mobile devices using profiles

    NASA Astrophysics Data System (ADS)

    Rosenbaum, René; Hamann, Bernd

    2012-02-01

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

  2. 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.

  3. Image fusion for dynamic contrast enhanced magnetic resonance imaging

    PubMed Central

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

    2004-01-01

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

  4. Image Enhancement with Polymer Grid Triode Arrays

    NASA Astrophysics Data System (ADS)

    Heeger, Alan J.; Heeger, David J.; Langan, John; Yang, Yang

    1995-12-01

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

  5. Appropriate Contrast Enhancement Measures for Brain and Breast Cancer Images

    PubMed Central

    Gupta, Suneet; Porwal, Rabins

    2016-01-01

    Medical imaging systems often produce images that require enhancement, such as improving the image contrast as they are poor in contrast. Therefore, they must be enhanced before they are examined by medical professionals. This is necessary for proper diagnosis and subsequent treatment. We do have various enhancement algorithms which enhance the medical images to different extents. We also have various quantitative metrics or measures which evaluate the quality of an image. This paper suggests the most appropriate measures for two of the medical images, namely, brain cancer images and breast cancer images. PMID:27127497

  6. 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.

  7. Enhanced high-speed coherent diffraction imaging

    NASA Astrophysics Data System (ADS)

    Potier, Jonathan; Fricker, Sebastien; Idir, Mourad

    2011-03-01

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

  8. Range Imaging for Underwater Vision Enhancement

    SciTech Connect

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

    1999-04-19

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

  9. Enhancing the Imaging Experience for Pediatric Patients.

    PubMed

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

    2016-01-01

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

  10. Design of adaptive objective lens for ultrabroad near infrared imaging

    NASA Astrophysics Data System (ADS)

    Lan, Gongpu; Li, Guoqiang

    2016-03-01

    We present a compound adaptive objective lens in which a water-filled membrane lens is inserted into a front group (one lens) and a back group (two lenses). This adaptive objective lens works in the ultrabroad near infrared waveband (760nm ~ 920nm) with the volume scan of > 1mm3 and the resolution of 2.8 μm (calculated at the wavelength of 840 nm). The focal range is 19.5mm ~ 20.5mm and the numerical number is 0.196. The size of the adaptive lens is 10mm (diameter) × 17mm (length). This kind of lens can be widely used in three-dimensional (3D) volume biomedical imaging instruments, such as confocal microscope, optical coherence tomography (OCT), two photon microscope, etc.

  11. Depth image enhancement using perceptual texture priors

    NASA Astrophysics Data System (ADS)

    Bang, Duhyeon; Shim, Hyunjung

    2015-03-01

    A depth camera is widely used in various applications because it provides a depth image of the scene in real time. However, due to the limited power consumption, the depth camera presents severe noises, incapable of providing the high quality 3D data. Although the smoothness prior is often employed to subside the depth noise, it discards the geometric details so to degrade the distance resolution and hinder achieving the realism in 3D contents. In this paper, we propose a perceptual-based depth image enhancement technique that automatically recovers the depth details of various textures, using a statistical framework inspired by human mechanism of perceiving surface details by texture priors. We construct the database composed of the high quality normals. Based on the recent studies in human visual perception (HVP), we select the pattern density as a primary feature to classify textures. Upon the classification results, we match and substitute the noisy input normals with high quality normals in the database. As a result, our method provides the high quality depth image preserving the surface details. We expect that our work is effective to enhance the details of depth image from 3D sensors and to provide a high-fidelity virtual reality experience.

  12. Adaptive polymer lens for rapid zoom shortwave infrared imaging applications

    NASA Astrophysics Data System (ADS)

    Santiago, Freddie; Bagwell, Brett E.; Pinon, Victor; Krishna, Sanjay

    2014-12-01

    This work demonstrates the use of adaptive polymer lenses (APLs) for short-wavelength infrared (SWIR) applications. First, we present a push-button adaptive optical zoom system for variable magnification with a SWIR focal plane array. We then present a push-button, variable divergence, SWIR laser system for pointing and illumination. Last, we outline a system that combines the two: an SWIR adaptive zoom coupled with an APL-enhanced designator/illuminator. The result would allow a user to toggle between different fields of view (magnification), while optimizing illumination (beam divergence) for each field of view. This could be critical for situational awareness and target identification/designation in tactical applications.

  13. Teaching People and Machines to Enhance Images

    NASA Astrophysics Data System (ADS)

    Berthouzoz, Floraine Sara Martianne

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

  14. Adaptive memory: enhanced location memory after survival processing.

    PubMed

    Nairne, James S; Vanarsdall, Joshua E; Pandeirada, Josefa N S; Blunt, Janell R

    2012-03-01

    Two experiments investigated whether survival processing enhances memory for location. From an adaptive perspective, remembering that food has been located in a particular area, or that potential predators are likely to be found in a given territory, should increase the chances of subsequent survival. Participants were shown pictures of food or animals located at various positions on a computer screen. The task was to rate the ease of collecting the food or capturing the animals relative to a central fixation point. Surprise retention tests revealed that people remembered the locations of the items better when the collection or capturing task was described as relevant to survival. These data extend the generality of survival processing advantages to a new domain (location memory) by means of a task that does not involve rating the relevance of words to a scenario. PMID:22004268

  15. Enhancing topology adaptation in information-sharing social networks

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  16. Adaptation and the color statistics of natural images.

    PubMed

    Webster, M A; Mollon, J D

    1997-12-01

    Color perception depends profoundly on adaptation processes that adjust sensitivity in response to the prevailing pattern of stimulation. We examined how color sensitivity and appearance might be influenced by adaptation to the color distributions characteristic of natural images. Color distributions were measured for natural scenes by sampling an array of locations within each scene with a spectroradiometer, or by recording each scene with a digital camera successively through 31 interference filters. The images were used to reconstruct the L, M and S cone excitation at each spatial location, and the contrasts along three post-receptoral axes [L + M, L - M or S - (L + M)]. Individual scenes varied substantially in their mean chromaticity and luminance, in the principal color-luminance axes of their distributions, and in the range of contrasts in their distributions. Chromatic contrasts were biased along a relatively narrow range of bluish to yellowish-green angles, lying roughly between the S - (L + M) axis (which was more characteristic of scenes with lush vegetation and little sky) and a unique blue-yellow axis (which was more typical of arid scenes). For many scenes L - M and S - (L + M) signals were highly correlated, with weaker correlations between luminance and chromaticity. We use a two-stage model (von Kries scaling followed by decorrelation) to show how the appearance of colors may be altered by light adaptation to the mean of the distributions and by contrast adaptation to the contrast range and principal axes of the distributions; and we show that such adjustments are qualitatively consistent with empirical measurements of asymmetric color matches obtained after adaptation to successive random samples drawn from natural distributions of chromaticities and lightnesses. Such adaptation effects define the natural range of operating states of the visual system. PMID:9425544

  17. Despeckling algorithm on ultrasonic image using adaptive block-based singular value decomposition

    NASA Astrophysics Data System (ADS)

    Sae-Bae, Napa; Udomhunsakul, Somkait

    2008-03-01

    Speckle noise reduction is an important technique to enhance the quality of ultrasonic image. In this paper, a despeckling algorithm based on an adaptive block-based singular value decomposition filtering (BSVD) applied on ultrasonic images is presented. Instead of applying BSVD directly to ultrasonic image, we propose to apply BSVD on the noisy edge image version obtained from the difference between the logarithmic transformations of the original image and blur image version of its. The recovered image is performed by combining the speckle noise-free edge image with blur image version of its. Finally, exponential transformation is applied in order to get the reconstructed image. To evaluate our algorithm compared with well-know algorithms such as Lee filter, Kuan filter, Homomorphic Wiener filter, median filter and wavelet soft thresholding, four image quality measurements, which are Mean Square Error (MSE), Signal to MSE (S/MSE), Edge preservation (β), and Correlation measurement (ρ), are used. From the results, it clearly shows that the proposed algorithm outperforms other methods in terms of quantitative and subjective assessments.

  18. Adaptive registration of diffusion tensor images on lie groups

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  19. Adaptive registration of diffusion tensor images on lie groups

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  20. Multiwavelength adaptive optical fundus camera and continuous retinal imaging

    NASA Astrophysics Data System (ADS)

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

    2009-08-01

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

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

    PubMed

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

    2015-06-01

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

  2. 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

  3. Research on Medical Image Enhancement Algorithm Based on GSM Model for Wavelet Coefficients

    NASA Astrophysics Data System (ADS)

    Wang, Lei; Jiang, Nian-de; Ning, Xing

    For the complexity and application diversity of medical CT image, this article presents a medical CT Image enhancing algorithm based on Gaussian Scale Mixture Model for wavelet coefficient in the study of wavelet multi-scale analysis. The noisy image is firstly denoised in auto-adapted Wiener filter. Secondly, through the qualitative analysis and classification of wavelet coefficients for the signal and noise, the wavelet's approximate distribution and statistical characteristics are described, combining GSM(Gaussian scale mixture) model for wavelet coefficient in this paper. It is shown that this algorithm can improve the denoised result and enhanced the medical CT image obviously.

  4. 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. PMID:26235517

  5. Lidar imaging with on-the-fly adaptable spatial resolution

    NASA Astrophysics Data System (ADS)

    Riu, J.; Royo, S.

    2013-10-01

    We present our work in the design and construction of a novel type of lidar device capable of measuring 3D range images with an spatial resolution which can be reconfigured through an on-the-fly configuration approach, adjustable by software and on the image area, and which can reach the 2Mpixel value. A double-patented novel concept of scanning system enables to change dynamically the image resolution depending on external information provided by the image captured in a previous cycle or on other sensors like greyscale or hyperspectral 2D imagers. A prototype of an imaging lidar system which can modify its spatial resolution on demand from one image to the next according to the target nature and state has been developed, and indoor and outdoor sample images showing its performance are presented. Applications in object detection, tracking and identification through a real-time adaptable scanning system for each situation and target behaviour are currently being pursued in different areas.

  6. Brief Communication: Contrast-stretching- and histogram-smoothness-based synthetic aperture radar image enhancement for flood map generation

    NASA Astrophysics Data System (ADS)

    Nazir, F.; Riaz, M. M.; Ghafoor, A.; Arif, F.

    2015-02-01

    Synthetic-aperture-radar-image-based flood map generation is usually a challenging task (due to degraded contrast). A three-step approach (based on adaptive histogram clipping, histogram remapping and smoothing) is proposed for generation of a more visualized flood map image. The pre- and post-flood images are adaptively histogram equalized. The hidden details in difference image are enhanced using contrast-based enhancement and histogram smoothing. A fast-ready flood map is then generated using equalized pre-, post- and difference images. Results (evaluated using different data sets) show significance of the proposed technique.

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

    NASA Astrophysics Data System (ADS)

    Verma, Harish Kumar; Pal, Sandeep

    2016-06-01

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

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

    PubMed Central

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

    2015-01-01

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

  9. Despeckling of medical ultrasound images using data and rate adaptive lossy compression.

    PubMed

    Gupta, Nikhil; Swamy, M N S; Plotkin, Eugene

    2005-06-01

    A novel technique for despeckling the medical ultrasound images using lossy compression is presented. The logarithm of the input image is first transformed to the multiscale wavelet domain. It is then shown that the subband coefficients of the log-transformed ultrasound image can be successfully modeled using the generalized Laplacian distribution. Based on this modeling, a simple adaptation of the zero-zone and reconstruction levels of the uniform threshold quantizer is proposed in order to achieve simultaneous despeckling and quantization. This adaptation is based on: (1) an estimate of the corrupting speckle noise level in the image; (2) the estimated statistics of the noise-free subband coefficients; and (3) the required compression rate. The Laplacian distribution is considered as a special case of the generalized Laplacian distribution and its efficacy is demonstrated for the problem under consideration. Context-based classification is also applied to the noisy coefficients to enhance the performance of the subband coder. Simulation results using a contrast detail phantom image and several real ultrasound images are presented. To validate the performance of the proposed scheme, comparison with two two-stage schemes, wherein the speckled image is first filtered and then compressed using the state-of-the-art JPEG2000 encoder, is presented. Experimental results show that the proposed scheme works better, both in terms of the signal to noise ratio and the visual quality. PMID:15957598

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

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

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

    PubMed Central

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

    2015-01-01

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

  12. Enhancing retinal images by nonlinear registration

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  13. 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.

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

    PubMed

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

    2004-06-01

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

  15. 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.

  16. Compressive adaptive ghost imaging via sharing mechanism and fellow relationship.

    PubMed

    Huo, Yaoran; He, Hongjie; Chen, Fan

    2016-04-20

    For lower sampling rate and better imaging quality, a compressive adaptive ghost imaging is proposed by adopting the sharing mechanism and fellow relationship in the wavelet tree. The sharing mechanisms, including intrascale and interscale sharing mechanisms, and fellow relationship are excavated from the wavelet tree and utilized for sampling. The shared coefficients, which are part of the approximation subband, are localized according to the parent coefficients and sampled based on the interscale sharing mechanism and fellow relationship. The sampling rate can be reduced owing to the fact that some shared coefficients can be calculated by adopting the parent coefficients and the sampled sum of shared coefficients. According to the shared coefficients and parent coefficients, the proposed method predicts the positions of significant coefficients and samples them based on the intrascale sharing mechanism. The ghost image, reconstructed by the significant coefficients and the coarse image at the given largest scale, achieves better quality because the significant coefficients contain more detailed information. The simulations demonstrate that the proposed method improves the imaging quality at the same sampling rate and also achieves a lower sampling rate for the same imaging quality for different types of target object images in noise-free and noisy environments. PMID:27140111

  17. Multimodal Medical Image Fusion by Adaptive Manifold Filter.

    PubMed

    Geng, Peng; Liu, Shuaiqi; Zhuang, Shanna

    2015-01-01

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

  18. Adaptive SPECT imaging with crossed-slit apertures

    PubMed Central

    Durko, Heather L.; Furenlid, Lars R.

    2015-01-01

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

  19. 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. PMID:22163859

  20. The iterative adaptive approach in medical ultrasound imaging.

    PubMed

    Jensen, Are Charles; Austeng, Andreas

    2014-10-01

    Many medical ultrasound imaging systems are based on sweeping the image plane with a set of narrow beams. Usually, the returning echo from each of these beams is used to form one or a few azimuthal image samples. We model, for each radial distance, jointly the full azimuthal scanline. The model consists of the amplitudes of a set of densely placed potential reflectors (or scatterers), cf. sparse signal representation. To fit the model, we apply the iterative adaptive approach (IAA) on data formed by a sequenced time delay and phase shift. The performance of the IAA in combination with our time-delayed and phase-shifted data are studied on both simulated data of scenes consisting of point targets and hollow cyst-like structures, and recorded ultrasound phantom data from a specially adapted commercially available scanner. The results show that the proposed IAA is more capable of resolving point targets and gives better defined and more geometrically correct cyst-like structures in speckle images compared with the conventional delay-and-sum (DAS) approach. Compared with a Capon beamformer, the IAA showed an improved rendering of cyst-like structures and a similar point-target resolvability. Unlike the Capon beamformer, the IAA has no user parameters and seems unaffected by signal cancellation. The disadvantage of the IAA is a high computational load. PMID:25265177

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

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

    PubMed

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

    2014-03-21

    This paper introduces a new image denoising, fusion and enhancement framework for combining and optimal visualization of x-ray attenuation contrast (AC), differential phase contrast (DPC) and dark-field contrast (DFC) images retrieved from x-ray Talbot-Lau grating interferometry. The new image fusion framework comprises three steps: (i) denoising each input image (AC, DPC and DFC) through adaptive Wiener filtering, (ii) performing a two-step image fusion process based on the shift-invariant wavelet transform, i.e. first fusing the AC with the DPC image and then fusing the resulting image with the DFC image, and finally (iii) enhancing the fused image to obtain a final image using adaptive histogram equalization, adaptive sharpening and contrast optimization. Application examples are presented for two biological objects (a human tooth and a cherry) and the proposed method is compared to two recently published AC/DPC/DFC image processing techniques. In conclusion, the new framework for the processing of AC, DPC and DFC allows the most relevant features of all three images to be combined in one image while reducing the noise and enhancing adaptively the relevant image features. The newly developed framework may be used in technical and medical applications. PMID:24584079

  3. Computer techniques used for some enhancements of ERTS images

    NASA Technical Reports Server (NTRS)

    Billingsley, F. C.; Goetz, A. F. H.

    1973-01-01

    The JPL VICAR image processing system has been used for the enhancement of images received from the ERTS for the Arizona geology mapping experiment. This system contains flexible capabilities for reading and repairing MSS digital tape images, for geometric corrections and interpicture registration, for various enhancements and analyses of the data, and for display of the images in black and white and color.

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

    PubMed

    Zeng, Hui; Kang, Xiangui

    2016-03-01

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

  5. Enhancement of document images from cameras

    NASA Astrophysics Data System (ADS)

    Taylor, Michael J.; Dance, Christopher R.

    1998-04-01

    As digital cameras become cheaper and more powerful, driven by the consumer digital photography market, we anticipate significant value in extending their utility as a general office peripheral by adding a paper scanning capability. The main technical challenges in realizing this new scanning interface are insufficient resolution, blur and lighting variations. We have developed an efficient technique for the recovery of text from digital camera images, which simultaneously treats these three problems, unlike other local thresholding algorithms which do not cope with blur and resolution enhancement. The technique first performs deblurring by deconvolution, and then resolution enhancement by linear interpolation. We compare the performance of a threshold derived from the local mean and variance of all pixel values within a neighborhood with a threshold derived from the local mean of just those pixels with high gradient. We assess performance using OCR error scores.

  6. Image enhancement with polymer grid triode arrays

    SciTech Connect

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

    1995-12-08

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

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

    PubMed

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

    2014-12-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    SciTech Connect

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

    2015-05-15

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

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-09-01

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

  12. Breast image feature learning with adaptive deconvolutional networks

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

  13. Adaptive tracking of maneuvering targets based on IR image data

    NASA Astrophysics Data System (ADS)

    Maybeck, Peter S.

    1989-06-01

    The capability of tracking dynamic targets from forward looking infrared (FLIR) measurements was improved substantially by replacing standard correlation trackers with adaptive extended Kalman filters or enhanced correlator/Kalman filter combinations. A tracker able to handle multiple hot-spot targets, in which digital and/or optical signal processing is employed on the FLIR data to identify the underlying target shape is investigated. Furthermore, multiple model adaptive filtering is investigated as a means of changing the field-of-view as well as the tracker bandwidth when target acceleration can vary over a wide range. Enhancements are developed and analyzed: (1) allowing some of the elemental filters within the adaptive algorithm to have rectangular fields-of-view and to be tuned for target dynamics that are harsher in one direction than others; (2) considering both Gauss-Markov acceleration models and constant turn-rate models for target dynamics; and (3) devising an initial target acquisition algorithm to remove important biases in the estimated target template to be used within the tracker. The performance potential of such a tracking algorithm is shown to be substantial.

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

    NASA Astrophysics Data System (ADS)

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

    2010-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

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

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

    NASA Technical Reports Server (NTRS)

    Gonzalez, R. C.

    1974-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2006-06-01

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

  19. A charge-adaptive nanosystem for prolonged and enhanced in vivo antibiotic delivery.

    PubMed

    Chu, Liping; Gao, Honglin; Cheng, Tangjian; Zhang, Yumin; Liu, Jinjian; Huang, Fan; Yang, Cuihong; Shi, Linqi; Liu, Jianfeng

    2016-05-01

    Herein we report on a charge-adaptive nanosystem for prolonged and enhanced in vivo antibiotic delivery. The nanocarrier achieves acid-dependent charge conversion, thus prolonging the circulation time and enhancing antibiotic accumulation in subcutaneous inflammation models. PMID:27077219

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  1. Classification in medical images using adaptive metric k-NN

    NASA Astrophysics Data System (ADS)

    Chen, C.; Chernoff, K.; Karemore, G.; Lo, P.; Nielsen, M.; Lauze, F.

    2010-03-01

    The performance of the k-nearest neighborhoods (k-NN) classifier is highly dependent on the distance metric used to identify the k nearest neighbors of the query points. The standard Euclidean distance is commonly used in practice. This paper investigates the performance of k-NN classifier with respect to different adaptive metrics in the context of medical imaging. We propose using adaptive metrics such that the structure of the data is better described, introducing some unsupervised learning knowledge in k-NN. We investigated four different metrics are estimated: a theoretical metric based on the assumption that images are drawn from Brownian Image Model (BIM), the normalized metric based on variance of the data, the empirical metric is based on the empirical covariance matrix of the unlabeled data, and an optimized metric obtained by minimizing the classification error. The spectral structure of the empirical covariance also leads to Principal Component Analysis (PCA) performed on it which results the subspace metrics. The metrics are evaluated on two data sets: lateral X-rays of the lumbar aortic/spine region, where we use k-NN for performing abdominal aorta calcification detection; and mammograms, where we use k-NN for breast cancer risk assessment. The results show that appropriate choice of metric can improve classification.

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

    PubMed

    Liu, Kui; Tan, Jieqing; Ai, Liefu

    2016-01-01

    To eliminate the staircasing effect for total variation filter and synchronously avoid the edges blurring for fourth-order PDE filter, a hybrid regularizers-based adaptive anisotropic diffusion is proposed for image denoising. In the proposed model, the [Formula: see text]-norm is considered as the fidelity term and the regularization term is composed of a total variation regularization and a fourth-order filter. The two filters can be adaptively selected according to the diffusion function. When the pixels locate at the edges, the total variation filter is selected to filter the image, which can preserve the edges. When the pixels belong to the flat regions, the fourth-order filter is adopted to smooth the image, which can eliminate the staircase artifacts. In addition, the split Bregman and relaxation approach are employed in our numerical algorithm to speed up the computation. Experimental results demonstrate that our proposed model outperforms the state-of-the-art models cited in the paper in both the qualitative and quantitative evaluations. PMID:27047730

  3. Novel image detail enhancement technology for high dynamic range infrared detector

    NASA Astrophysics Data System (ADS)

    Liu, Ning; Zhu, Caigao

    2014-11-01

    In this paper, we propose a novel image detail enhancement technology which is well solved the problem of how to suppress the noise and enhance the detail at the same time of the infrared image. This technology is based on the layer separation idea. In nowadays, this idea is studied by many researchers, and many detail enhancement algorithms have been come up through this idea such as the bilateral filter for detail enhancement. According to our research, these algorithms although have the advantages of enhancing the detail without enhancing the noise, they also have the disadvantages of massive calculation, low speed and the worst is the gradient flipping effect which cause the enhanced image distorted. Our solution is based on the Guided Image Filter (GIF) to deal the separated detail layer of an image. The gradient flipping effect will be greatly suppressed with the priority that the GIF is a linear filter. Which means that the processed image will become much closer to the original image. We determine an adaptive weighting coefficient as the filter kernel. After that, we compress the base component into the display range by our modified histogram projection and enhance the detail component using the gain mask of the filter weighting coefficient. At last, we recombine the two parts and quantize the result to 8-bit domain. Experimental verification and detailed realization have been provided in this paper. We also have done significant comparison between our method and the proposed algorithm to show the superiority of our algorithm.

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

    SciTech Connect

    Karmakar, Sanjit; Shih, Yanhua

    2010-03-15

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

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

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

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

    PubMed

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

    2014-11-21

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

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

    PubMed Central

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

    2014-01-01

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

  8. Teaching People and Machines to Enhance Images

    NASA Astrophysics Data System (ADS)

    Berthouzoz, Floraine Sara Martianne

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

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

    NASA Astrophysics Data System (ADS)

    Yang, Hansheng; Rao, Xuejun; Zhang, Yudong

    2007-11-01

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

  10. Robust image registration using adaptive coherent point drift method

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Zhang, Qiong; Maldague, Xavier

    2016-01-01

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

  12. Digitally enhanced GLORIA images for petroleum exploration

    SciTech Connect

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

    1990-05-01

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

  13. Adaptive regularized scheme for remote sensing image fusion

    NASA Astrophysics Data System (ADS)

    Tang, Sizhang; Shen, Chaomin; Zhang, Guixu

    2016-06-01

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

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

    PubMed

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

    2016-08-10

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

  15. 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

  16. Enhanced Processing and Analysis of Cassini SAR Images of Titan

    NASA Astrophysics Data System (ADS)

    Lucas, A.; Aharonson, O.; Hayes, A. G.; Deledalle, C. A.; Kirk, R. L.

    2011-12-01

    SAR images suffer from speckle noise, which hinders interpretation and quantitative analysis. We have adapted a non-local algorithm for de-noising images using an appropriate multiplicative noise model [1] for analysis of Cassini SAR images. We illustrate some examples here that demonstrate the improvement of landform interpretation by focusing on transport processes at Titan's surface. Interpretation of the geomorphic features is facilitated (Figure 1); including revealing details of the channels incised into the terrain, shoreline morphology, and contrast variations in the dark, liquid covered areas. The latter are suggestive of sub-marine channels and gradients in the bathymetry. Furthermore, substantial quantitative improvements are possible. We show that a derived Digital Elevation Model from radargrammetry [2] using the de-noised images is obtained with a greater number of matching points (up to 80%) and a better correlation (59% of the pixels give a good correlation in the de-noised data compared with 18% in the original SAR image). An elevation hypsogram of our enhanced DEM shows evidence that fluvial and/or lacustrine processes have affected the topographic distribution substantially. Dune wavelengths and interdune extents are more precisely measured. Finally, radarclinometry technics applied to our new data are more accurate in dunes and mountainous regions. [1] Deledalle C-A., et al., 2009, Weighted maximum likelihood denoising with iterative and probabilistic patch-based weights, Telecom Paris. [2] Kirk, R.L., et al., 2007, First stereoscopic radar images of Titan, Lunar Planet. Sci., XXXVIII, Abstract #1427, Lunar and Planetary Institute, Houston

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

    PubMed

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

    2015-08-01

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

  18. Fourier transform digital holographic adaptive optics imaging system

    PubMed Central

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

    2013-01-01

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

  19. 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.

  20. Liquid-Crystal Light Valve Enhances Edges In Images

    NASA Technical Reports Server (NTRS)

    Chao, Tien-Hsin; Liu, Hua-Kuang

    1991-01-01

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

  1. Automatic image enhancement by artificial bee colony algorithm

    NASA Astrophysics Data System (ADS)

    Yimit, Adiljan; Hagihara, Yoshihiro; Miyoshi, Tasuku; Hagihara, Yukari

    2013-03-01

    With regard to the improvement of image quality, image enhancement is an important process to assist human with better perception. This paper presents an automatic image enhancement method based on Artificial Bee Colony (ABC) algorithm. In this method, ABC algorithm is applied to find the optimum parameters of a transformation function, which is used in the enhancement by utilizing the local and global information of the image. In order to solve the optimization problem by ABC algorithm, an objective criterion in terms of the entropy and edge information is introduced to measure the image quality to make the enhancement as an automatic process. Several images are utilized in experiments to make a comparison with other enhancement methods, which are genetic algorithm-based and particle swarm optimization algorithm-based image enhancement methods.

  2. Image Analysis, Modeling, Enhancement, Restoration, Feature Extraction and Their Applications in Nondestructive Evaluation and Radio Astronomy.

    NASA Astrophysics Data System (ADS)

    Zheng, Yi.

    The principal topic of this dissertation is the development and application of signal and image processing to Nondestructive Evaluation (NDE) and radio astronomy. The dissertation consists of nine papers published or submitted for publication. Each of them has a specific and unique topic related to signal processing or image processing in NDE or radio astronomy. Those topics are listed in the following. (1) Time series analysis and modeling of Very Large Array (VLA) phase data. (2) Image analysis, feature extraction and various applied enhancement methods for industrial NDE X-ray radiographic images. (3) Enhancing NDE radiographic X-ray images by adaptive regional Kalman filtering. (4) Robotic image segmentation, modeling, and restoration with a rule based expert system. (5) Industrial NDE radiographic X-ray image modeling and Kalman filtering considering signal-dependent colored noise. (6) Computational study of Kalman filtering VLA phase data and its computational performance on a supercomputer. (7) A practical and fast maximum entropy deconvolution method for de-blurring industrial NDE X-ray and infrared images. (8) Local feature enhancement of synthetic radio images by adaptive Kalman filtering. (9) A new technique for correcting phase data of a synthetic -aperture antenna array.

  3. Comparison of enhanced flat EEG image via distinct fuzzification

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  4. Shape Adaptive, Robust Iris Feature Extraction from Noisy Iris Images

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Wang, Yanwei; Roberts, William; Li, Jian

    2005-05-01

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

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

    PubMed

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

    2013-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Aiazzi, Bruno; Alparone, Luciano; Baronti, Stefano

    2003-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  9. Adaptive Optics Imaging Survey of Luminous Infrared Galaxies

    SciTech Connect

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

    2006-03-13

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

  10. 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.

  11. Adaptive optics scanning laser ophthalmoscope imaging: technology update

    PubMed Central

    Merino, David; Loza-Alvarez, Pablo

    2016-01-01

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

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

    PubMed

    Merino, David; Loza-Alvarez, Pablo

    2016-01-01

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

  13. Adaptive filtering of radar images for autofocus applications

    NASA Technical Reports Server (NTRS)

    Stiles, J. A.; Frost, V. S.; Gardner, J. S.; Eland, D. R.; Shanmugam, K. S.; Holtzman, J. C.

    1981-01-01

    Autofocus techniques are being designed at the Jet Propulsion Laboratory to automatically choose the filter parameters (i.e., the focus) for the digital synthetic aperture radar correlator; currently, processing relies upon interaction with a human operator who uses his subjective assessment of the quality of the processed SAR data. Algorithms were devised applying image cross-correlation to aid in the choice of filter parameters, but this method also has its drawbacks in that the cross-correlation result may not be readily interpretable. Enhanced performance of the cross-correlation techniques of JPL was hypothesized given that the images to be cross-correlated were first filtered to improve the signal-to-noise ratio for the pair of scenes. The results of experiments are described and images are shown.

  14. An adaptive controller for enhancing operator performance during teleoperation

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Deng, Wankai; Deng, He; Cheng, Lifang

    2015-12-01

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  18. 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.

  19. Enhancing Student Motivation and Learning within Adaptive Tutors

    ERIC Educational Resources Information Center

    Ostrow, Korinn S.

    2015-01-01

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

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

    SciTech Connect

    Ren, Juan; Zou, Qingze

    2014-07-15

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

  1. 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.

  2. Image processing for flight crew enhanced situation awareness

    NASA Technical Reports Server (NTRS)

    Roberts, Barry

    1993-01-01

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

  3. Fast-adaptive near-lossless image compression

    NASA Astrophysics Data System (ADS)

    He, Kejing

    2016-05-01

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

  4. Adaptive Optics Retinal Imaging – Clinical Opportunities and Challenges

    PubMed Central

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

    2014-01-01

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

  5. EUV imaging experiment of an adaptive optics telescope

    NASA Astrophysics Data System (ADS)

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

    2009-08-01

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

  6. Binary adaptive semi-global matching based on image edges

    NASA Astrophysics Data System (ADS)

    Hu, Han; Rzhanov, Yuri; Hatcher, Philip J.; Bergeron, R. D.

    2015-07-01

    Image-based modeling and rendering is currently one of the most challenging topics in Computer Vision and Photogrammetry. The key issue here is building a set of dense correspondence points between two images, namely dense matching or stereo matching. Among all dense matching algorithms, Semi-Global Matching (SGM) is arguably one of the most promising algorithms for real-time stereo vision. Compared with global matching algorithms, SGM aggregates matching cost from several (eight or sixteen) directions rather than only the epipolar line using Dynamic Programming (DP). Thus, SGM eliminates the classical "streaking problem" and greatly improves its accuracy and efficiency. In this paper, we aim at further improvement of SGM accuracy without increasing the computational cost. We propose setting the penalty parameters adaptively according to image edges extracted by edge detectors. We have carried out experiments on the standard Middlebury stereo dataset and evaluated the performance of our modified method with the ground truth. The results have shown a noticeable accuracy improvement compared with the results using fixed penalty parameters while the runtime computational cost was not increased.

  7. ADAPTIVE OPTICS IMAGES OF KEPLER OBJECTS OF INTEREST

    SciTech Connect

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

    2012-08-15

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

  8. 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

  9. 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

    2010-04-01

    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 x 20.0 mm dimensions could

  10. Enhancing Functional Performance using Sensorimotor Adaptability Training Programs

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Gillespie, Alan R.

    1992-01-01

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

  12. Image restoration of the open-loop adaptive optics retinal imaging system based on optical transfer function analysis

    NASA Astrophysics Data System (ADS)

    Yu, Lei; Qi, Yue; Li, Dayu; Xia, Mingliang; Xuan, Li

    2013-07-01

    The residual aberrations of the adaptive optics retinal imaging system will decrease the quality of the retinal images. To overcome this obstacle, we found that the optical transfer function (OTF) of the adaptive optics retinal imaging system can be described as the Levy stable distribution. Then a new method is introduced to estimate the OTF of the open-loop adaptive optics system, based on analyzing the residual aberrations of the open-loop adaptive optics system in the residual aberrations measuring mode. At last, the estimated OTF is applied to restore the retinal images of the open-loop adaptive optics retinal imaging system. The contrast and resolution of the restored image is significantly improved with the Laplacian sum (LS) from 0.0785 to 0.1480 and gray mean grads (GMG) from 0.0165 to 0.0306.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Song, Qiong; Wang, Yuehuan; Bai, Kun

    2016-07-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  18. Microstructure of subretinal drusenoid deposits revealed by adaptive optics imaging.

    PubMed

    Meadway, Alexander; Wang, Xiaolin; Curcio, Christine A; Zhang, Yuhua

    2014-03-01

    Subretinal drusenoid deposits (SDD), a recently recognized lesion associated with progression of age-related macular degeneration, were imaged with adaptive optics scanning laser ophthalmoscopy (AO-SLO) and optical coherence tomography (AO-OCT). AO-SLO revealed a distinct en face structure of stage 3 SDD, showing a hyporeflective annulus surrounded reflective core packed with hyperreflective dots bearing a superficial similarity to the photoreceptors in the unaffected retina. However, AO-OCT suggested that the speckled appearance over the SDD rendered by AO-SLO was the lesion material itself, rather than photoreceptors. AO-OCT assists proper interpretation and understanding of the SDD structure and the lesions' impact on surrounding photoreceptors produced by AO-SLO and vice versa. PMID:24688808

  19. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

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

    PubMed

    Li, Minghui; Hayward, Gordon

    2012-01-01

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

  3. Images on the Internet: Enhanced User Access.

    ERIC Educational Resources Information Center

    Cox, Jennifer; Taleb, Mohamed

    1994-01-01

    Gives practical tips on how to retrieve and view images from Internet databases, with a description of image file formats and the requirements for viewing and decompression software. A list of nine image databases and a brief description of the University of Arizona library's digital image project are provided. (Contains four references.) (KRN)

  4. CT imaging of enhanced oil recovery experiments

    SciTech Connect

    Gall, B.L.

    1992-12-01

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

  5. CT imaging of enhanced oil recovery experiments

    SciTech Connect

    Gall, B.L.

    1992-12-01

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

  6. An enhanced MIML algorithm for natural scene image classification

    NASA Astrophysics Data System (ADS)

    Wu, Wei; Zhang, Hui; Yang, Suyan

    2015-12-01

    The multi-instance multi-label (MIML) learning is a learning framework where each example is described by a bag of instances and corresponding to a set of labels. In some studies, the algorithms are applied to natural scene image classification and have achieved satisfied performance. We design a MIML algorithm based on RBF neural network for the natural scene image classification. In the framework, we compare classification accuracy based on the existing definitions of bag distance: maximum Hausdorff, minimum Hausdorff and average Hausdorff. Although the accuracy of average Hausdorff bag distance is the highest, we find average Hausdorff bag distance to weaken the role of the minimum distance between the instances in the two bags. So we redefine the average Hausdorff bag distance by introducing an adaptive adjustment coefficient, and it can change according to the minimum distance between the instances in the two bags. Finally, the experimental results show that the enhanced algorithm has a better result than the original algorithm.

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

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

    SciTech Connect

    CAMERON, STEWART M.

    2001-10-01

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

  9. Image enhancement by adjusting the contrast of spatial frequencies

    NASA Astrophysics Data System (ADS)

    Yang, Ching-Chung

    2008-02-01

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

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

    NASA Astrophysics Data System (ADS)

    Wells, E.

    2011-05-01

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

  11. Algorithms for contrast enhancement of electronic portal images

    NASA Astrophysics Data System (ADS)

    Díez, S.; Sánchez, S.

    2015-11-01

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

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

    NASA Astrophysics Data System (ADS)

    Liu, Ning; Chen, Xiaohong

    2016-07-01

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

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

    PubMed

    Alavijeh, Fatemeh Shahsavari; Mahdavi-Nasab, Homayoun

    2015-01-01

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

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

    PubMed Central

    Alavijeh, Fatemeh Shahsavari; Mahdavi-Nasab, Homayoun

    2015-01-01

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

  15. Knowledge-based image bandwidth compression and enhancement

    NASA Astrophysics Data System (ADS)

    Saghri, John A.; Tescher, Andrew G.

    1987-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  17. Theory and experimental study on low-light-level images by adaptive mode filter

    NASA Astrophysics Data System (ADS)

    Bai, Lianfa; Zhang, Baomin; Liu, Yunfen; Chen, Qian

    1996-09-01

    Real-time low light level (LLL) image processing technology is the important developmental subject in the area of LLL night vision. But there is an essential distinction between the LLL TV image and ordinary TV image, so the conventional digital image processing technique aren't suitable for LLL image. In this paper, the noise theoretical model of LLL imaging system is described and the LLL image processing system is set up. With regard to the characteristics of LLL image and its noise, a novel noise suppression method, adaptive mode filter, is presented. The experimental results show that the adaptive mode filter can suppress the sharp noise of LLL image effectively, and as for the protection of the image edge, the property of adaptive mode filter is better that of median filter. Finally, the processing results and the conclusions are given.

  18. Enhancing Adaptive Filtering Approaches for Land Data Assimilation Systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. Adapting ISA system warnings to enhance user acceptance.

    PubMed

    Jiménez, Felipe; Liang, Yingzhen; Aparicio, Francisco

    2012-09-01

    Inappropriate speed is a major cause of traffic accidents. Different measures have been considered to control traffic speed, and intelligent speed adaptation (ISA) systems are one of the alternatives. These systems know the speed limits and try to improve compliance with them. This paper deals with an informative ISA system that provides the driver with an advance warning before reaching a road section with singular characteristics that require a lower safe speed than the current speed. In spite of the extensive tests performed using ISA systems, few works show how warnings can be adapted to the driver. This paper describes a method to adapt warning parameters (safe speed on curves, zone of influence of a singular stretch, deceleration process and reaction time) to normal driving behavior. The method is based on a set of tests with and without the ISA system. This adjustment, as well as the analysis of driver acceptance before and after the adaptation and changes in driver behavior (changes in speed and path) resulting from the tested ISA regarding a driver's normal driving style, is shown in this paper. The main conclusion is that acceptance by drivers increased significantly after redefining the warning parameters, but the effect of speed homogenization was not reduced. PMID:22664666

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

    PubMed

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

    2015-05-01

    For ultrasound imaging, speckle is one of the most important factors in the degradation of contrast resolution because it masks meaningful texture and has the potential to interfere with diagnosis. It is expected that researchers would explore appropriate ways to reduce the speckle noise, to find the edges of structures and enhance weak borders between different organs in ultrasound imaging. Inspired by the principle of differential interference contrast microscopy, a "bas-relief map" is proposed that depicts the texture structure of ultrasound images. Based on a bas-relief map, an adaptive bas-relief filter was developed for ultrafast despeckling. Subsequently, an edge map was introduced to enhance the edges of images in real time. The holistic bas-relief map approach has been used experimentally with synthetic phantoms and digital ultrasound B-scan images of liver, kidney and gallbladder. Based on the visual inspection and the performance metrics of the despeckled images, it was found that the bas-relief map approach is capable of effectively reducing the speckle while significantly enhancing contrast and tissue boundaries for ultrasonic images, and its speckle reduction ability is comparable to that of Kuan, Lee and Frost filters. Meanwhile, the proposed technique could preserve more intra-region details compared with the popular speckle reducing anisotropic diffusion technique and more effectively enhance edges. In addition, the adaptive bas-relief filter was much less time consuming than the Kuan, Lee and Frost filter and speckle reducing anisotropic diffusion techniques. The bas-relief map strategy is effective for speckle reduction and live enhancement of ultrasound images, and can provide a valuable tool for clinical diagnosis. PMID:25641600

  1. Thermally Enhanced Photoacoustic Radar Imaging of Biotissues

    NASA Astrophysics Data System (ADS)

    Wang, Wei; Mandelis, Andreas

    2015-06-01

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

  2. Resolution Enhancement of Spaceborne Radiometer Images

    NASA Technical Reports Server (NTRS)

    Krim, Hamid

    2001-01-01

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

  3. Adaptive Optics for Satellite Imaging and Space Debris Ranging

    NASA Astrophysics Data System (ADS)

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

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

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

    USGS Publications Warehouse

    Lemeshewsky, G.P.

    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.

  5. Optical Tissue Clearing to Enhance Imaging Performance for OCT

    NASA Astrophysics Data System (ADS)

    Wang, Ruikang K.; Tuchin, Valery V.

    Optical clearing technology for OCT needs is a growing field of investigations and biomedical applications. This chapter describes basic principles of optical clearing in enhancing the OCT imaging performances through biological tissue. We mainly focus on the use of biocompatible and osmotically active chemical agents to impregnate the tissue, leading to the reduction of tissue scattering, thus enhancing the OCT imaging performances. The mechanisms for such improvements, for example, imaging depth and contrast, were discussed, primarily through the experimental examples.

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

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

    PubMed

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

    2013-09-01

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

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

    PubMed

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

    2016-04-01

    The automatic annotation of medical images is a prerequisite for building comprehensive semantic archives that can be used to enhance evidence-based diagnosis, physician education, and biomedical research. Annotation also has important applications in the automatic generation of structured radiology reports. Much of the prior research work has focused on annotating images with properties such as the modality of the image, or the biological system or body region being imaged. However, many challenges remain for the annotation of high-level semantic content in medical images (e.g., presence of calcification, vessel obstruction, etc.) due to the difficulty in discovering relationships and associations between low-level image features and high-level semantic concepts. This difficulty is further compounded by the lack of labelled training data. In this paper, we present a method for the automatic semantic annotation of medical images that leverages techniques from content-based image retrieval (CBIR). CBIR is a well-established image search technology that uses quantifiable low-level image features to represent the high-level semantic content depicted in those images. Our method extends CBIR techniques to identify or retrieve a collection of labelled images that have similar low-level features and then uses this collection to determine the best high-level semantic annotations. We demonstrate our annotation method using retrieval via weighted nearest-neighbour retrieval and multi-class classification to show that our approach is viable regardless of the underlying retrieval strategy. We experimentally compared our method with several well-established baseline techniques (classification and regression) and showed that our method achieved the highest accuracy in the annotation of liver computed tomography (CT) images. PMID:26890880

  9. Color enhancement in multispectral image of human skin

    NASA Astrophysics Data System (ADS)

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

    2003-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Wang, Hui; Huang, Xifeng; Ping, Jiang

    2009-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  12. 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.

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

    PubMed

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

    2016-01-01

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

  14. 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

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

    PubMed Central

    Persichetti, Andrew S.; Thompson-Schill, Sharon L.; Butt, Omar H.; Brainard, David H.; Aguirre, Geoffrey K.

    2015-01-01

    Color names divide the fine-grained gamut of color percepts into discrete categories. A categorical transition must occur somewhere between the initial encoding of the continuous spectrum of light by the cones and the verbal report of the name of a color stimulus. Here, we used a functional magnetic resonance imaging (fMRI) adaptation experiment to examine the representation of hue in the early visual cortex. Our stimuli varied in hue between blue and green. We found in the early visual areas (V1, V2/3, and hV4) a smoothly increasing recovery from adaptation with increasing hue distance between adjacent stimuli during both passive viewing (Experiment 1) and active categorization (Experiment 2). We examined the form of the adaptation effect and found no evidence that a categorical representation mediates the release from adaptation for stimuli that cross the blue–green color boundary. Examination of the direct effect of stimulus hue on the fMRI response did, however, reveal an enhanced response to stimuli near the blue–green category border. This was largest in hV4 and when subjects were engaged in active categorization of the stimulus hue. In contrast with a recent report from another laboratory (Bird, Berens, Horner, & Franklin, 2014), we found no evidence for a categorical representation of color in the middle frontal gyrus. A post hoc whole-brain analysis, however, revealed several regions in the frontal cortex with a categorical effect in the adaptation response. Overall, our results support the idea that the representation of color in the early visual cortex is primarily fine grained and does not reflect color categories. PMID:26024465

  16. 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.

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

    PubMed

    Jang, Jae-Young

    2015-11-01

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

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

    PubMed Central

    Jang, Jae-Young

    2015-01-01

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

  19. Adaptive lifting scheme with sparse criteria for image coding

    NASA Astrophysics Data System (ADS)

    Kaaniche, Mounir; Pesquet-Popescu, Béatrice; Benazza-Benyahia, Amel; Pesquet, Jean-Christophe

    2012-12-01

    Lifting schemes (LS) were found to be efficient tools for image coding purposes. Since LS-based decompositions depend on the choice of the prediction/update operators, many research efforts have been devoted to the design of adaptive structures. The most commonly used approaches optimize the prediction filters by minimizing the variance of the detail coefficients. In this article, we investigate techniques for optimizing sparsity criteria by focusing on the use of an ℓ 1 criterion instead of an ℓ 2 one. Since the output of a prediction filter may be used as an input for the other prediction filters, we then propose to optimize such a filter by minimizing a weighted ℓ 1 criterion related to the global rate-distortion performance. More specifically, it will be shown that the optimization of the diagonal prediction filter depends on the optimization of the other prediction filters and vice-versa. Related to this fact, we propose to jointly optimize the prediction filters by using an algorithm that alternates between the optimization of the filters and the computation of the weights. Experimental results show the benefits which can be drawn from the proposed optimization of the lifting operators.

  20. Adaptive optics images. III. 87 Kepler objects of interest

    SciTech Connect

    Dressing, Courtney D.; Dupree, Andrea K.; Adams, Elisabeth R.; Kulesa, Craig; McCarthy, Don

    2014-11-01

    The Kepler mission has revolutionized our understanding of exoplanets, but some of the planet candidates identified by Kepler may actually be astrophysical false positives or planets whose transit depths are diluted by the presence of another star. Adaptive optics images made with ARIES at the MMT of 87 Kepler Objects of Interest place limits on the presence of fainter stars in or near the Kepler aperture. We detected visual companions within 1'' for 5 stars, between 1'' and 2'' for 7 stars, and between 2'' and 4'' for 15 stars. For those systems, we estimate the brightness of companion stars in the Kepler bandpass and provide approximate corrections to the radii of associated planet candidates due to the extra light in the aperture. For all stars observed, we report detection limits on the presence of nearby stars. ARIES is typically sensitive to stars approximately 5.3 Ks magnitudes fainter than the target star within 1'' and approximately 5.7 Ks magnitudes fainter within 2'', but can detect stars as faint as ΔKs = 7.5 under ideal conditions.

  1. Adaptive Optics Images. III. 87 Kepler Objects of Interest

    NASA Astrophysics Data System (ADS)

    Dressing, Courtney D.; Adams, Elisabeth R.; Dupree, Andrea K.; Kulesa, Craig; McCarthy, Don

    2014-11-01

    The Kepler mission has revolutionized our understanding of exoplanets, but some of the planet candidates identified by Kepler may actually be astrophysical false positives or planets whose transit depths are diluted by the presence of another star. Adaptive optics images made with ARIES at the MMT of 87 Kepler Objects of Interest place limits on the presence of fainter stars in or near the Kepler aperture. We detected visual companions within 1'' for 5 stars, between 1'' and 2'' for 7 stars, and between 2'' and 4'' for 15 stars. For those systems, we estimate the brightness of companion stars in the Kepler bandpass and provide approximate corrections to the radii of associated planet candidates due to the extra light in the aperture. For all stars observed, we report detection limits on the presence of nearby stars. ARIES is typically sensitive to stars approximately 5.3\\, {{Ks}} magnitudes fainter than the target star within 1'' and approximately 5.7\\, {{Ks}} magnitudes fainter within 2'', but can detect stars as faint as ΔKs = 7.5 under ideal conditions. Observations reported here were obtained at the MMT Observatory, a joint facility of the Smithsonian Institution and the University of Arizona.

  2. Patient-adaptive lesion metabolism analysis by dynamic PET images.

    PubMed

    Gao, Fei; Liu, Huafeng; Shi, Pengcheng

    2012-01-01

    Dynamic PET imaging provides important spatial-temporal information for metabolism analysis of organs and tissues, and generates a great reference for clinical diagnosis and pharmacokinetic analysis. Due to poor statistical properties of the measurement data in low count dynamic PET acquisition and disturbances from surrounding tissues, identifying small lesions inside the human body is still a challenging issue. The uncertainties in estimating the arterial input function will also limit the accuracy and reliability of the metabolism analysis of lesions. Furthermore, the sizes of the patients and the motions during PET acquisition will yield mismatch against general purpose reconstruction system matrix, this will also affect the quantitative accuracy of metabolism analyses of lesions. In this paper, we present a dynamic PET metabolism analysis framework by defining a patient adaptive system matrix to improve the lesion metabolism analysis. Both patient size information and potential small lesions are incorporated by simulations of phantoms of different sizes and individual point source responses. The new framework improves the quantitative accuracy of lesion metabolism analysis, and makes the lesion identification more precisely. The requirement of accurate input functions is also reduced. Experiments are conducted on Monte Carlo simulated data set for quantitative analysis and validation, and on real patient scans for assessment of clinical potential. PMID:23286175

  3. 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,

  4. GRAAL: a seeing enhancer for the NIR wide-field imager Hawk-I

    NASA Astrophysics Data System (ADS)

    Paufique, J.; Bruton, A.; Glindemann, A.; Jost, A.; Kolb, J.; Jochum, L.; Le Louarn, M.; Kiekebusch, M.; Hubin, N.; Madec, P.-Y.; Conzelmann, R.; Siebenmorgen, R.; Donaldson, R.; Arsenault, R.; Tordo, S.

    2010-07-01

    We describe the design and development status of GRAAL, the Ground-layer adaptive optics assisted by Laser, which will deliver enhanced images to the Hawk-I instrument on the VLT. GRAAL is an adaptive optics module, part of AOF, the Adaptive optics facility, using four Laser- and one natural guide-stars to measure the turbulence, and correcting for it by deforming the adaptive secondary mirror of a Unit telescope in the Paranal observatory. The outstanding feature of GRAAL is the extremely wide field of view correction, over 10 arcmin diameter, with an image enhancement of about 20% in average in K band. When observing GRAAL will provide FWHM better than 0.3" 40% of the time. Besides the Adaptive optics facility deformable mirror and Laser guide stars, the system uses subelectron L3-CCD and a real-time computing platform, SPARTA. GRAAL completed early this year a final design phase shared internally and outsourced for its mechanical part by the Spanish company NTE. It is now in manufacturing, with a first light in the laboratory planned in 2011.

  5. Wireless Micro-Ball endoscopic image enhancement using histogram information.

    PubMed

    Attar, Abdolrahman; Xie, Xiang; Zhang, Chun; Wang, Zhihua; Yue, Shigang

    2014-01-01

    Wireless endoscopy systems is a new innovative method widely used for gastrointestinal tract examination in recent decade. Wireless Micro-Ball endoscopy system with multiple image sensors is the newest proposed method which can make a full view image of the gastrointestinal tract. But still the quality of images from this new wireless endoscopy system is not satisfactory. It's hard for doctors and specialist to easily examine and interpret the captured images. The image features also are not distinct enough to be used for further processing. So as to enhance these low-contrast endoscopic images a new image enhancement method based on the endoscopic images features and color distribution is proposed in this work. The enhancement method is performed on three main steps namely color space transformation, edge preserving mask formation, and histogram information correction. The luminance component of CIE Lab, YCbCr, and HSV color space is enhanced in this method and then two other components added finally to form an enhanced color image. The experimental result clearly show the robustness of the method. PMID:25570705

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

    NASA Astrophysics Data System (ADS)

    Huebner, Claudia S.

    2015-10-01

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

  7. Algorithm of contrast enhancement for visual document images with underexposure

    NASA Astrophysics Data System (ADS)

    Tian, Da-zeng; Hao, Yong; Ha, Ming-hu; Tian, Xue-dong; Ha, Yan

    2008-03-01

    The visual document image is the electronic image about newspapers, books or magazines taken by the digital camera, the digital vidicon etc. Whose getting is more convenient than got from the scanner. Along with the development of OCR technology, visual document images could be recognized by OCR. Affected by some factors, digital image will be degraded during its acquisition, processing, transmission. One of the main problems affecting image quality, leading to unpleasant pictures, comes from improper exposure to light. So preprocessing is becoming much more significant before recognition in order to get an appropriate image satisfied recognition requirements. For the low contrast images with underexposure, according to the visual document image's characteristic, a new algorithm, based on image background separation, for image object enhance is proposed, The proposed method calculate the threshold of separation firstly, And different processing be taken on foreground and background: Various gray values in image background will be merged into unitary gray value, whereas the contrast of foreground will be enhanced. The proposed algorithm implemented in Visual C++ 6.0, and compared the result of proposed algorithm with the results of Otsu's method and histogram equalization. The experimental results show clearly that this algorithm could enhance the details of image object adequately, increase the recognition rate, and avoid the block effect at the same time.

  8. 75 FR 34988 - Federal Advisory Committee; Defense Science Board 2010 Summer Study on Enhancing Adaptability of...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-21

    ... of the Secretary Federal Advisory Committee; Defense Science Board 2010 Summer Study on Enhancing... meeting. SUMMARY: The Defense Science Board 2010 Summer Study on Enhancing Adaptability of our Military..., USAF, Defense Science Board, 3140 Defense Pentagon, Room 3B888A, Washington, DC 20301-3140, via...

  9. Enhanced Mental Image Mapping in Autism

    ERIC Educational Resources Information Center

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

    2011-01-01

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

  10. Molecular imaging with surface-enhanced Raman spectroscopy nanoparticle reporters

    PubMed Central

    Jokerst, Jesse V.; Pohling, Christoph; Gambhir, Sanjiv S.

    2013-01-01

    Molecular imaging scans cellular and molecular targets in living subjects through the introduction of imaging agents that bind to these targets and report their presence through a measurable signal. The picomolar sensitivity, signal stability, and high multiplexing capacity of Raman spectroscopy satisfies important needs within the field of molecular imaging, and several groups now utilize Raman and surface-enhanced Raman spectroscopy to image molecular targets in small animal models of human disease. This article details the role of Raman spectroscopy in molecular imaging, describes some substrates and imaging agents used in animal models, and illustrates some examples. PMID:24293809

  11. Metric Learning to Enhance Hyperspectral Image Segmentation

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  13. 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. PMID:26811073

  14. Closed-loop adaptive optics using a CMOS image quality metric sensor

    NASA Astrophysics Data System (ADS)

    Ting, Chueh; Rayankula, Aditya; Giles, Michael K.; Furth, Paul M.

    2006-08-01

    When compared to a Shack-Hartmann sensor, a CMOS image sharpness sensor has the advantage of reduced complexity in a closed-loop adaptive optics system. It also has the potential to be implemented as a smart sensor using VLSI technology. In this paper, we present a novel adaptive optics testbed that uses a CMOS sharpness imager built in the New Mexico State University (NMSU) Electro-Optics Research Laboratory (EORL). The adaptive optics testbed, which includes a CMOS image quality metric sensor and a 37-channel deformable mirror, has the capability to rapidly compensate higher-order phase aberrations. An experimental performance comparison of the pinhole image sharpness feedback method and the CMOS imager is presented. The experimental data shows that the CMOS sharpness imager works well in a closed-loop adaptive optics system. Its overall performance is better than that of the pinhole method, and it has a fast response time.

  15. Magnetic resonance imaging for adaptive cobalt tomotherapy: A proposal

    PubMed Central

    Kron, Tomas; Eyles, David; John, Schreiner L; Battista, Jerry

    2006-01-01

    . Rotational delivery is less susceptible to problems related to the use of a low energy megavoltage photon source while the helical delivery reduces the negative impact of the relatively large penumbra inherent in the use of Cobalt sources for radiotherapy. On the other hand, the use of a 60Co source ensures constant dose rate with gantry rotation and makes dose calculation in a magnetic field as easy as the range of secondary electrons is limited. The MR-integrated Cobalt tomotherapy unit, dubbed ‘MiCoTo,’ uses two independent physical principles for image acquisition and treatment delivery. It would offer excellent target definition and will allow following target motion during treatment using fast imaging techniques thus providing the best possible input for adaptive radiotherapy. As an additional bonus, quality assurance of the radiation delivery can be performed in situ using radiation sensitive gels imaged by MRI. PMID:21206640

  16. Image enhancement by nonlinear extrapolation in frequency space

    NASA Astrophysics Data System (ADS)

    Greenspan, Hayit; Anderson, Charles H.

    1994-03-01

    A procedure for creating images with higher resolution than the sampling rate would allow is described. The enhancement algorithm augments the frequency content of the image using shape-invariant properties of edges across scale by using a non-linearity that generates phase- coherent higher harmonics. The procedure utilizes the Laplacian pyramid image representation. Results are presented depicting the power-spectra augmentation and the visual enhancement of several images. Simplicity of computations and ease of implementation allow for real-time applications such as high-definition television.

  17. Enhanced adaptive focusing through semi-transparent media

    PubMed Central

    Di Battista, Diego; Zacharakis, Giannis; Leonetti, Marco

    2015-01-01

    Adaptive optics can focus light through opaque media by compensating the random phase delay acquired while crossing a scattering curtain. The technique is commonly exploited in many fields, including astrophysics, microscopy, biomedicine and biology. A turbid lens has the capability of producing foci with a resolution higher than conventional optics, however it has a fundamental limit: to obtain a sharp focus one has to introduce a strongly scattering medium in the optical path. Indeed a tight focusing needs strong scattering and, as a consequence, high resolution focusing is obtained only for weakly transmitting samples. Here we describe a novel method allowing to obtain highly concentrated optical spots even by introducing a minimum amount of scattering in the beam path with semi-transparent materials. By filtering the pseudo-ballistic components of the transmitted beam we are able to experimentally overcome the limits of the adaptive focus resolution, gathering light on a spot with a diameter which is one third of the original speckle correlation function. PMID:26620906

  18. Enhanced adaptive focusing through semi-transparent media

    NASA Astrophysics Data System (ADS)

    di Battista, Diego; Zacharakis, Giannis; Leonetti, Marco

    2015-12-01

    Adaptive optics can focus light through opaque media by compensating the random phase delay acquired while crossing a scattering curtain. The technique is commonly exploited in many fields, including astrophysics, microscopy, biomedicine and biology. A turbid lens has the capability of producing foci with a resolution higher than conventional optics, however it has a fundamental limit: to obtain a sharp focus one has to introduce a strongly scattering medium in the optical path. Indeed a tight focusing needs strong scattering and, as a consequence, high resolution focusing is obtained only for weakly transmitting samples. Here we describe a novel method allowing to obtain highly concentrated optical spots even by introducing a minimum amount of scattering in the beam path with semi-transparent materials. By filtering the pseudo-ballistic components of the transmitted beam we are able to experimentally overcome the limits of the adaptive focus resolution, gathering light on a spot with a diameter which is one third of the original speckle correlation function.

  19. Investigation of an electronic image enhancer for radiographs

    NASA Technical Reports Server (NTRS)

    Vary, A.

    1972-01-01

    Radiographs of nuclear and aerospace components were studied with a closed-circuit television system to determine the advantages of electronic enhancement in radiographic nondestructive evaluation. The radiographic images were examined on a television monitor under various degrees of magnification and enhancement. The enhancement was accomplished by generating a video signal whose amplitude is proportional to the rate of change of density. Points, lines, edges, and other density variations that are faintly registered in the original image are rendered in sharp relief. Examples of the applications of this mode of enhancement are discussed together with the system's dynamic response and resolution.

  20. Adaptative Peer to Peer Data Sharing for Technology Enhanced Learning

    NASA Astrophysics Data System (ADS)

    Angelaccio, Michele; Buttarazzi, Berta

    Starting from the hypothesis that P2P Data Sharing in a direct teaching scenario (e.g.: a classroom lesson) may lead to relevant benefits, this paper explores the features of EduSHARE a Collaborative Learning System useful for Enhanced Learning Process.

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

    PubMed

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

    2015-03-01

    We present a framework for image classification that extends beyond the window sampling of fixed spatial pyramids and is supported by a new learning algorithm. Based on the observation that fixed spatial pyramids sample a rather limited subset of the possible image windows, we propose a method that accounts for a comprehensive set of windows densely sampled over location, size, and aspect ratio. A concise high-level image feature is derived to effectively deal with this large set of windows, and this higher level of abstraction offers both efficient handling of the dense samples and reduced sensitivity to misalignment. In addition to dense window sampling, we introduce generalized adaptive l(p)-norm multiple kernel learning (GA-MKL) to learn a robust classifier based on multiple base kernels constructed from the new image features and multiple sets of prelearned classifiers from other classes. With GA-MKL, multiple levels of image features are effectively fused, and information is shared among different classifiers. Extensive evaluation on benchmark datasets for object recognition (Caltech256 and Caltech101) and scene recognition (15Scenes) demonstrate that the proposed method outperforms the state-of-the-art under a broad range of settings. PMID:24968365

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  3. Wavelet for Ultrasonic Flaw Enhancement and Image Compression

    NASA Astrophysics Data System (ADS)

    Cheng, W.; Tsukada, K.; Li, L. Q.; Hanasaki, K.

    2003-03-01

    Ultrasonic imaging has been widely used in Non-destructive Testing (NDT) and medical application. However, the image is always degraded by blur and noise. Besides, the pressure on both storage and transmission gives rise to the need of image compression. We apply 2-D Discrete Wavelet Transform (DWT) to C-scan 2-D images to realize flaw enhancement and image compression, taking advantage of DWT scale and orientation selectivity. The Wavelet coefficient thresholding and scalar quantization are employed respectively. Furthermore, we realize the unification of flaw enhancement and image compression in one process. The reconstructed image from the compressed data gives a clearer interpretation of the flaws at a much smaller bit rate.

  4. 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

  5. Molecular imaging with surface-enhanced CARS on nanostructures

    NASA Astrophysics Data System (ADS)

    Steuwe, Christian; Kaminski, Clemens F.; Baumberg, Jeremy J.; Mahajan, Sumeet

    2012-03-01

    Strongly localized electromagnetic fields in the vicinity of nanoparticles and nanogaps greatly enhance spectroscopic signals near them such as in surface-enhanced Raman spectroscopy (SERS). In this work we combine this plasmonic surface enhancement with coherent anti-Stokes Raman spectroscopy (CARS) on reproducible nanostructured surfaces. Surface-enhanced CARS (SECARS) gives rise to very strong enhancements and we find that an enhancement of ~105 can be obtained over standard CARS. Using our nanostructured surfaces, we demonstrate strong correlation between plasmon resonances and surface-enhanced CARS intensities. Furthermore, fast imaging of molecular monolayers is performed. Our work paves the way for reliable single molecule Raman spectroscopy and fast molecular imaging on plasmonic surfaces.

  6. Optimization of background subtraction for image enhancement

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  7. "Relative CIR": an image enhancement and visualization technique

    USGS Publications Warehouse

    Fleming, Michael D.

    1993-01-01

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

  8. Transfer of perceptual adaptation to space sickness: What enhances an individual's ability to adapt?

    NASA Technical Reports Server (NTRS)

    1993-01-01

    The objectives of this project were to explore systematically the determiners of transfer of perceptual adaptation as these principles might apply to the space adaptation syndrome. The perceptual experience of an astronaut exposed to the altered gravitational forces involved in spaceflight shares much with that of the subject exposed in laboratory experiments to optically induced visual rearrangement with tilt and dynamic motion illusions such as vection; and experiences and symptoms reported by the trainee who is exposed to the compellingly realistic visual imagery of flight simulators and virtual reality systems. In both of these cases the observer is confronted with a variety of inter- and intrasensory conflicts that initially disrupt perception, as well as behavior, and also produce symptoms of motion sickness.

  9. IR CMOS: near infrared enhanced digital imaging (Presentation Recording)

    NASA Astrophysics Data System (ADS)

    Pralle, Martin U.; Carey, James E.; Joy, Thomas; Vineis, Chris J.; Palsule, Chintamani

    2015-08-01

    SiOnyx has demonstrated imaging at light levels below 1 mLux (moonless starlight) at video frame rates with a 720P CMOS image sensor in a compact, low latency camera. Low light imaging is enabled by the combination of enhanced quantum efficiency in the near infrared together with state of the art low noise image sensor design. The quantum efficiency enhancements are achieved by applying Black Silicon, SiOnyx's proprietary ultrafast laser semiconductor processing technology. In the near infrared, silicon's native indirect bandgap results in low absorption coefficients and long absorption lengths. The Black Silicon nanostructured layer fundamentally disrupts this paradigm by enhancing the absorption of light within a thin pixel layer making 5 microns of silicon equivalent to over 300 microns of standard silicon. This results in a demonstrate 10 fold improvements in near infrared sensitivity over incumbent imaging technology while maintaining complete compatibility with standard CMOS image sensor process flows. Applications include surveillance, nightvision, and 1064nm laser see spot. Imaging performance metrics will be discussed. Demonstrated performance characteristics: Pixel size : 5.6 and 10 um Array size: 720P/1.3Mpix Frame rate: 60 Hz Read noise: 2 ele/pixel Spectral sensitivity: 400 to 1200 nm (with 10x QE at 1064nm) Daytime imaging: color (Bayer pattern) Nighttime imaging: moonless starlight conditions 1064nm laser imaging: daytime imaging out to 2Km

  10. Multi-Image Registration for an Enhanced Vision System

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  11. Image resolution enhancement via image restoration using neural network

    NASA Astrophysics Data System (ADS)

    Zhang, Shuangteng; Lu, Yihong

    2011-04-01

    Image super-resolution aims to obtain a high-quality image at a resolution that is higher than that of the original coarse one. This paper presents a new neural network-based method for image super-resolution. In this technique, the super-resolution is considered as an inverse problem. An observation model that closely follows the physical image acquisition process is established to solve the problem. Based on this model, a cost function is created and minimized by a Hopfield neural network to produce high-resolution images from the corresponding low-resolution ones. Not like some other single frame super-resolution techniques, this technique takes into consideration point spread function blurring as well as additive noise and therefore generates high-resolution images with more preserved or restored image details. Experimental results demonstrate that the high-resolution images obtained by this technique have a very high quality in terms of PSNR and visually look more pleasant.

  12. Offset-sparsity decomposition for automated enhancement of color microscopic image of stained specimen in histopathology

    NASA Astrophysics Data System (ADS)

    Kopriva, Ivica; Hadžija, Marijana Popović; Hadžija, Mirko; Aralica, Gorana

    2015-07-01

    We propose an offset-sparsity decomposition method for the enhancement of a color microscopic image of a stained specimen. The method decomposes vectorized spectral images into offset terms and sparse terms. A sparse term represents an enhanced image, and an offset term represents a "shadow." The related optimization problem is solved by computational improvement of the accelerated proximal gradient method used initially to solve the related rank-sparsity decomposition problem. Removal of an image-adapted color offset yields an enhanced image with improved colorimetric differences among the histological structures. This is verified by a no-reference colorfulness measure estimated from 35 specimens of the human liver, 1 specimen of the mouse liver stained with hematoxylin and eosin, 6 specimens of the mouse liver stained with Sudan III, and 3 specimens of the human liver stained with the anti-CD34 monoclonal antibody. The colorimetric difference improves on average by 43.86% with a 99% confidence interval (CI) of [35.35%, 51.62%]. Furthermore, according to the mean opinion score, estimated on the basis of the evaluations of five pathologists, images enhanced by the proposed method exhibit an average quality improvement of 16.60% with a 99% CI of [10.46%, 22.73%].

  13. Image fusion for enhanced visualization of brain imaging

    NASA Astrophysics Data System (ADS)

    Socolinsky, Diego A.; Wolff, Lawrence B.

    1999-05-01

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

  14. Film adhesive enhances neutron radiographic images

    NASA Technical Reports Server (NTRS)

    Reed, M. W.

    1978-01-01

    Resolution of neutron radiographic images of thermally conductive film is increased by replacing approximately 5 percent of aluminum powder, which provides thermal conductivity, with gadolinium oxide. Oxide is also chemically stable.

  15. Enhanced neutron imaging detector using optical processing

    SciTech Connect

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

    1992-08-01

    Existing neutron imaging detectors have limited count rates due to inherent property and electronic limitations. The popular multiwire proportional counter is qualified by gas recombination to a count rate of less than 10{sup 5} n/s over the entire array and the neutron Anger camera, even though improved with new fiber optic encoding methods, can only achieve 10{sup 6} cps over a limited array. We present a preliminary design for a new type of neutron imaging detector with a resolution of 2--5 mm and a count rate capability of 10{sup 6} cps pixel element. We propose to combine optical and electronic processing to economically increase the throughput of advanced detector systems while simplifying computing requirements. By placing a scintillator screen ahead of an optical image processor followed by a detector array, a high throughput imaging detector may be constructed.

  16. Digital enhancement of multispectral MSS data for maximum image visibility

    NASA Technical Reports Server (NTRS)

    Algazi, V. R.

    1973-01-01

    A systematic approach to the enhancement of images has been developed. This approach exploits two principal features involved in the observation of images: the properties of human vision and the statistics of the images being observed. The rationale of the enhancement procedure is as follows: in the observation of some features of interest in an image, the range of objective luminance-chrominance values being displayed is generally limited and does not use the whole perceptual range of vision of the observer. The purpose of the enhancement technique is to expand and distort in a systematic way the grey scale values of each of the multispectral bands making up a color composite, to enhance the average visibility of the features being observed.

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

    PubMed

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

    2009-11-01

    Based on enhanced upconversion, we demonstrate a highly efficient method for converting a full image from one part of the electromagnetic spectrum into a new desired wavelength region. By illuminating a metal transmission mask with a 765 nm Gaussian beam to create an image and subsequently focusing the image inside a nonlinear PPKTP crystal located in the high intra-cavity field of a 1342 nm solid-state Nd:YVO(4) laser, an upconverted image at 488 nm is generated. We have experimentally achieved an upconversion efficiency of 40% under CW conditions. The proposed technique can be further adapted for high efficiency mid-infrared image upconversion where direct and fast detection is difficult or impossible to perform with existing detector technologies. PMID:19997325

  18. Microwave Imaging of Human Forearms: Pilot Study and Image Enhancement

    PubMed Central

    Gilmore, Colin; Zakaria, Amer; Pistorius, Stephen; LoVetri, Joe

    2013-01-01

    We present a pilot study using a microwave tomography system in which we image the forearms of 5 adult male and female volunteers between the ages of 30 and 48. Microwave scattering data were collected at 0.8 to 1.2 GHz with 24 transmitting and receiving antennas located in a matching fluid of deionized water and table salt. Inversion of the microwave data was performed with a balanced version of the multiplicative-regularized contrast source inversion algorithm formulated using the finite-element method (FEM-CSI). T1-weighted MRI images of each volunteer's forearm were also collected in the same plane as the microwave scattering experiment. Initial “blind” imaging results from the utilized inversion algorithm show that the image quality is dependent on the thickness of the arm's peripheral adipose tissue layer; thicker layers of adipose tissue lead to poorer overall image quality. Due to the exible nature of the FEM-CSI algorithm used, prior information can be readily incorporated into the microwave imaging inversion process. We show that by introducing prior information into the FEM-CSI algorithm the internal anatomical features of all the arms are resolved, significantly improving the images. The prior information was estimated manually from the blind inversions using an ad hoc procedure. PMID:24023539

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  1. Photographic copy of computer enhanced color photographic image. Photographer and ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photographic copy of computer enhanced color photographic image. Photographer and computer draftsman unknown. Original photographic image located in the office of Modjeski and Masters, Consulting Engineers at 1055 St. Charles Avenue, New Orleans, LA 70130. COMPUTER ENHANCED COLOR PHOTOGRAPH SHOWING THE PROPOSED HUEY P. LONG BRIDGE WIDENING LOOKING FROM THE WEST BANK TOWARD THE EAST BANK. - Huey P. Long Bridge, Spanning Mississippi River approximately midway between nine & twelve mile points upstream from & west of New Orleans, Jefferson, Jefferson Parish, LA

  2. NEQR: a novel enhanced quantum representation of digital images

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Lu, Kai; Gao, Yinghui; Wang, Mo

    2013-08-01

    Quantum computation is becoming an important and effective tool to overcome the high real-time computational requirements of classical digital image processing. In this paper, based on analysis of existing quantum image representations, a novel enhanced quantum representation (NEQR) for digital images is proposed, which improves the latest flexible representation of quantum images (FRQI). The newly proposed quantum image representation uses the basis state of a qubit sequence to store the gray-scale value of each pixel in the image for the first time, instead of the probability amplitude of a qubit, as in FRQI. Because different basis states of qubit sequence are orthogonal, different gray scales in the NEQR quantum image can be distinguished. Performance comparisons with FRQI reveal that NEQR can achieve a quadratic speedup in quantum image preparation, increase the compression ratio of quantum images by approximately 1.5X, and retrieve digital images from quantum images accurately. Meanwhile, more quantum image operations related to gray-scale information in the image can be performed conveniently based on NEQR, for example partial color operations and statistical color operations. Therefore, the proposed NEQR quantum image model is more flexible and better suited for quantum image representation than other models in the literature.

  3. Discrete cosine transform-based local adaptive filtering of images corrupted by nonstationary noise

    NASA Astrophysics Data System (ADS)

    Lukin, Vladimir V.; Fevralev, Dmitriy V.; Ponomarenko, Nikolay N.; Abramov, Sergey K.; Pogrebnyak, Oleksiy; Egiazarian, Karen O.; Astola, Jaakko T.

    2010-04-01

    In many image-processing applications, observed images are contaminated by a nonstationary noise and no a priori information on noise dependence on local mean or about local properties of noise statistics is available. In order to remove such a noise, a locally adaptive filter has to be applied. We study a locally adaptive filter based on evaluation of image local activity in a ``blind'' manner and on discrete cosine transform computed in overlapping blocks. Two mechanisms of local adaptation are proposed and applied. The first mechanism takes into account local estimates of noise standard deviation while the second one exploits discrimination of homogeneous and heterogeneous image regions by adaptive threshold setting. The designed filter performance is tested for simulated data as well as for real-life remote-sensing and maritime radar images. Recommendations concerning filter parameter setting are provided. An area of applicability of the proposed filter is defined.

  4. Quality evaluation of adaptive optical image based on DCT and Rényi entropy

    NASA Astrophysics Data System (ADS)

    Xu, Yuannan; Li, Junwei; Wang, Jing; Deng, Rong; Dong, Yanbing

    2015-04-01

    The adaptive optical telescopes play a more and more important role in the detection system on the ground, and the adaptive optical images are so many that we need find a suitable method of quality evaluation to choose good quality images automatically in order to save human power. It is well known that the adaptive optical images are no-reference images. In this paper, a new logarithmic evaluation method based on the use of the discrete cosine transform(DCT) and Rényi entropy for the adaptive optical images is proposed. Through the DCT using one or two dimension window, the statistical property of Rényi entropy for images is studied. The different directional Rényi entropy maps of an input image containing different information content are obtained. The mean values of different directional Rényi entropy maps are calculated. For image quality evaluation, the different directional Rényi entropy and its standard deviation corresponding to region of interest is selected as an indicator for the anisotropy of the images. The standard deviation of different directional Rényi entropy is obtained as the quality evaluation value for adaptive optical image. Experimental results show the proposed method that the sorting quality matches well with the visual inspection.

  5. Tracking features in retinal images of adaptive optics confocal scanning laser ophthalmoscope using KLT-SIFT algorithm.

    PubMed

    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

  6. Image Processing for Binarization Enhancement via Fuzzy Reasoning

    NASA Technical Reports Server (NTRS)

    Dominguez, Jesus A. (Inventor)

    2009-01-01

    A technique for enhancing a gray-scale image to improve conversions of the image to binary employs fuzzy reasoning. In the technique, pixels in the image are analyzed by comparing the pixel's gray scale value, which is indicative of its relative brightness, to the values of pixels immediately surrounding the selected pixel. The degree to which each pixel in the image differs in value from the values of surrounding pixels is employed as the variable in a fuzzy reasoning-based analysis that determines an appropriate amount by which the selected pixel's value should be adjusted to reduce vagueness and ambiguity in the image and improve retention of information during binarization of the enhanced gray-scale image.

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

    PubMed

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

    2016-09-01

    The founding population in most new species introductions, or at the leading edge of an ongoing invasion, is likely to be small. Severe Allee effects-reductions in individual fitness at low population density-may then result in a failure of the species to colonize, even if the habitat could support a much larger population. Using a simulation model for plant populations that incorporates demography, mating systems, quantitative genetics, and pollinators, we show that Allee effects can potentially be overcome by transient hybridization with a resident species or an earlier colonizer. This mechanism does not require the invocation of adaptive changes usually attributed to invasions following hybridization. We verify our result in a case study of sequential invasions by two plant species where the outcrosser Cakile maritima has replaced an earlier, inbreeding, colonizer Cakile edentula (Brassicaceae). Observed historical rates of replacement are consistent with model predictions from hybrid-alleviated Allee effects in outcrossers, although other causes cannot be ruled out. PMID:27601582

  8. Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform

    NASA Astrophysics Data System (ADS)

    Wu, Zhi-guo; Wang, Ming-jia; Han, Guang-liang

    2011-08-01

    Being an efficient method of information fusion, image fusion has been used in many fields such as machine vision, medical diagnosis, military applications and remote sensing. In this paper, Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing, including segmentation, target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First, the two original images are decomposed by wavelet transform. Then, based on the PCNN, a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength, so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So, the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment, the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range, which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore, by this algorithm, the threshold adjusting constant is estimated by appointed iteration number. Furthermore, In order to sufficient reflect order of the firing time, the threshold adjusting constant αΘ is estimated by appointed iteration number. So after the iteration achieved, each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules, the experiments upon Multi-focus image are done. Moreover

  9. Enhanced facial recognition for thermal imagery using polarimetric imaging.

    PubMed

    Gurton, Kristan P; Yuffa, Alex J; Videen, Gorden W

    2014-07-01

    We present a series of long-wave-infrared (LWIR) polarimetric-based thermal images of facial profiles in which polarization-state information of the image-forming radiance is retained and displayed. The resultant polarimetric images show enhanced facial features, additional texture, and details that are not present in corresponding conventional thermal imagery. It has been generally thought that conventional thermal imagery (MidIR or LWIR) could not produce the detailed spatial information required for reliable human identification due to the so-called "ghosting" effect often seen in thermal imagery of human subjects. By using polarimetric information, we are able to extract subtle surface features of the human face, thus improving subject identification. Polarimetric image sets considered include the conventional thermal intensity image, S0, the two Stokes images, S1 and S2, and a Stokes image product called the degree-of-linear-polarization image. PMID:24978755

  10. Spaceborne multiview image compression based on adaptive disparity compensation with rate-distortion optimization

    NASA Astrophysics Data System (ADS)

    Li, Shigao; Su, Kehua; Jia, Liming

    2016-01-01

    Disparity compensation (DC) and transform coding are incorporated into a hybrid coding to reduce the code-rate of multiview images. However, occlusion and inaccurate disparity estimations (DE) impair the performance of DC, especially in spaceborne images. This paper proposes an adaptive disparity-compensation scheme for the compression of spaceborne multiview images, including stereo image pairs and three-line-scanner images. DC with adaptive loop filter is used to remove redundancy between reference images and target images and a wavelet-based coding method is used to encode reference images and residue images. In occlusion regions, the DC efficiency may be poor because no interview correlation exists. A rate-distortion optimization method is thus designed to select the best prediction mode for local regions. Experimental results show that the proposed scheme can provide significant coding gain compared with some other similar coding schemes, and the time complexity is also competitive.

  11. Altered Visual Adaptation to Body Shape in Eating Disorders: Implications for Body Image Distortion.

    PubMed

    Mohr, Harald M; Rickmeyer, Constanze; Hummel, Dennis; Ernst, Mareike; Grabhorn, Ralph

    2016-07-01

    Previous research has shown that after adapting to a thin body, healthy participants (HP) perceive pictures of their own bodies as being fatter and vice versa. This aftereffect might contribute to the development of perceptual body image disturbances in eating disorders (ED).In the present study, HP and ED completed a behavioral experiment to rate manipulated pictures of their own bodies after adaptation to thin or fat body pictures. After adapting to a thin body, HP judged a thinner than actual body picture to be the most realistic and vice versa, resembling a typical aftereffect. ED only showed such an adaptation effect when they adapted to fat body pictures.The reported results indicate a relationship between body image distortion in ED and visual body image adaptation. It can be suspected that due to a pre-existing, long-lasting adaptation to thin body shapes in ED, an additional visual adaption to thin body shapes cannot be induced. Hence this pre-existing adaptation to thin body shapes could induce perceptual body image distortions in ED. PMID:26921409

  12. Embedded image enhancement for high-throughput cameras

    NASA Astrophysics Data System (ADS)

    Geerts, Stan J. C.; Cornelissen, Dion; de With, Peter H. N.

    2014-03-01

    This paper presents image enhancement for a novel Ultra-High-Definition (UHD) video camera offering 4K images and higher. Conventional image enhancement techniques need to be reconsidered for the high-resolution images and the low-light sensitivity of the new sensor. We study two image enhancement functions and evaluate and optimize the algorithms for embedded implementation in programmable logic (FPGA). The enhancement study involves high-quality Auto White Balancing (AWB) and Local Contrast Enhancement (LCE). We have compared multiple algorithms from literature, both with objective and subjective metrics. In order to objectively compare Local Contrast (LC), an existing LC metric is modified for LC measurement in UHD images. For AWB, we have found that color histogram stretching offers a subjective high image quality and it is among the algorithms with the lowest complexity, while giving only a small balancing error. We impose a color-to-color gain constraint, which improves robustness of low-light images. For local contrast enhancement, a combination of contrast preserving gamma and single-scale Retinex is selected. A modified bilateral filter is designed to prevent halo artifacts, while significantly reducing the complexity and simultaneously preserving quality. We show that by cascading contrast preserving gamma and single-scale Retinex, the visibility of details is improved towards the level appropriate for high-quality surveillance applications. The user is offered control over the amount of enhancement. Also, we discuss the mapping of those functions on a heterogeneous platform to come to an effective implementation while preserving quality and robustness.

  13. Enhanced Adaptive Management: Integrating Decision Analysis, Scenario Analysis and Environmental Modeling for the Everglades

    NASA Astrophysics Data System (ADS)

    Convertino, Matteo; Foran, Christy M.; Keisler, Jeffrey M.; Scarlett, Lynn; Loschiavo, Andy; Kiker, Gregory A.; Linkov, Igor

    2013-10-01

    We propose to enhance existing adaptive management efforts with a decision-analytical approach that can guide the initial selection of robust restoration alternative plans and inform the need to adjust these alternatives in the course of action based on continuously acquired monitoring information and changing stakeholder values. We demonstrate an application of enhanced adaptive management for a wetland restoration case study inspired by the Florida Everglades restoration effort. We find that alternatives designed to reconstruct the pre-drainage flow may have a positive ecological impact, but may also have high operational costs and only marginally contribute to meeting other objectives such as reduction of flooding. Enhanced adaptive management allows managers to guide investment in ecosystem modeling and monitoring efforts through scenario and value of information analyses to support optimal restoration strategies in the face of uncertain and changing information.

  14. Enhanced adaptive management: integrating decision analysis, scenario analysis and environmental modeling for the Everglades.

    PubMed

    Convertino, Matteo; Foran, Christy M; Keisler, Jeffrey M; Scarlett, Lynn; LoSchiavo, Andy; Kiker, Gregory A; Linkov, Igor

    2013-01-01

    We propose to enhance existing adaptive management efforts with a decision-analytical approach that can guide the initial selection of robust restoration alternative plans and inform the need to adjust these alternatives in the course of action based on continuously acquired monitoring information and changing stakeholder values. We demonstrate an application of enhanced adaptive management for a wetland restoration case study inspired by the Florida Everglades restoration effort. We find that alternatives designed to reconstruct the pre-drainage flow may have a positive ecological impact, but may also have high operational costs and only marginally contribute to meeting other objectives such as reduction of flooding. Enhanced adaptive management allows managers to guide investment in ecosystem modeling and monitoring efforts through scenario and value of information analyses to support optimal restoration strategies in the face of uncertain and changing information. PMID:24113217

  15. Enhanced Adaptive Management: Integrating Decision Analysis, Scenario Analysis and Environmental Modeling for the Everglades

    PubMed Central

    Convertino, Matteo; Foran, Christy M.; Keisler, Jeffrey M.; Scarlett, Lynn; LoSchiavo, Andy; Kiker, Gregory A.; Linkov, Igor

    2013-01-01

    We propose to enhance existing adaptive management efforts with a decision-analytical approach that can guide the initial selection of robust restoration alternative plans and inform the need to adjust these alternatives in the course of action based on continuously acquired monitoring information and changing stakeholder values. We demonstrate an application of enhanced adaptive management for a wetland restoration case study inspired by the Florida Everglades restoration effort. We find that alternatives designed to reconstruct the pre-drainage flow may have a positive ecological impact, but may also have high operational costs and only marginally contribute to meeting other objectives such as reduction of flooding. Enhanced adaptive management allows managers to guide investment in ecosystem modeling and monitoring efforts through scenario and value of information analyses to support optimal restoration strategies in the face of uncertain and changing information. PMID:24113217

  16. IGF-2 is necessary for retinoblastoma-mediated enhanced adaptation after small-bowel resection.

    PubMed

    Choi, Pamela M; Sun, Raphael C; Sommovilla, Josh; Diaz-Miron, Jose; Guo, Jun; Erwin, Christopher R; Warner, Brad W

    2014-11-01

    Previously, we have demonstrated that genetically disrupting retinoblastoma protein (Rb) expression in enterocytes results in taller villi, mimicking resection-induced adaption responses. Rb deficiency also results in elevated insulin-like growth factor-2 (IGF-2) expression in villus enterocytes. We propose that postoperative disruption of Rb results in enhanced adaptation which is driven by IGF-2. Inducible, intestine-specific Rb-null mice (iRbIKO) and wild-type (WT) littermates underwent a 50% proximal small-bowel resection (SBR) at 7-9 weeks of age. They were then given tamoxifen on postoperative days (PODs) 4-6 and harvested on POD 28. The experiment was then repeated on double knockouts of both IGF-2 and Rb (IGF-2 null/iRbIKO). iRbIKO mice demonstrated enhanced resection-induced adaptive villus growth after SBR and increased IGF-2 messenger RNA (mRNA) in ileal villus enterocytes compared to their WT littermates. In the IGF-2 null/iRbIKO double-knockout mice, there was no additional villus growth beyond what was expected of normal resection-induced adaptation. Adult mice in which Rb is inducibly deleted from the intestinal epithelium following SBR have augmented adaptive growth. IGF-2 expression is necessary for enhanced adaptation associated with acute intestinal Rb deficiency. PMID:25002022

  17. IGF-2 is necessary for Retinoblastoma-mediated enhanced adaptation after small bowel resection

    PubMed Central

    Choi, Pamela M.; Sun, Raphael C.; Sommovilla, Josh; Diaz-Miron, Jose; Guo, Jun; Erwin, Christopher R.; Warner, Brad W.

    2014-01-01

    Background Previously, we have demonstrated that genetically disrupting retinoblastoma protein (Rb) expression in enterocytes results in taller villi, mimicking resection-induced adaption responses. Rb deficiency also results in elevated IGF-2 expression in villus enterocytes. We propose that postoperative disruption of Rb results in enhanced adaptation which is driven by IGF-2. Methods Inducible, intestine-specific Rb-null mice (iRbIKO) and wild-type littermates (WT) underwent a 50% proximal small bowel resection (SBR) at 7–9 weeks of age. They were then were given tamoxifen on POD 4–6, and harvested on POD 28. The experiment was then repeated on double knockouts of both IGF-2 and Rb (IGF-2 null/iRbIKO). Results iRbIKO mice demonstrated enhanced resection-induced adaptive villus growth after SBR and increased IGF-2 mRNA in ileal villus enterocytes compared to their WT littermates. In the IGF-2 null/iRbIKO double knockout mice, there was no additional villus growth beyond what was expected of normal resection-induced adaptation. Conclusions Adult mice in which Rb is inducibly deleted from the intestinal epithelium following SBR have augmented adaptive growth. IGF-2 expression is necessary for enhanced adaptation associated with acute intestinal Rb deficiency. PMID:25002022

  18. 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.

  19. Enhancing images with Intensity-Dependent Spread functions

    NASA Technical Reports Server (NTRS)

    Reese, Greg

    1992-01-01

    The theory of Intensity-Dependent Spread functions (IDS), a model of the human visual system proposed by Cornsweet (1985), is applied to image enhancement. An artificial image is examined which illustrates the characteristics of IDS processing and shows how the theoretical results translate into visual effects. Examples of realistic scenes that have been enhanced by IDS are presented. The system is shown to be particularly useful for bringing out detail in regions of low-contrast images. IDS can be readily implemented on a parallel computer.

  20. The New England Climate Adaptation Project: Enhancing Local Readiness to Adapt to Climate Change through Role-Play Simulations

    NASA Astrophysics Data System (ADS)

    Rumore, D.; Kirshen, P. H.; Susskind, L.

    2014-12-01

    Despite scientific consensus that the climate is changing, local efforts to prepare for and manage climate change risks remain limited. How we can raise concern about climate change risks and enhance local readiness to adapt to climate change's effects? In this presentation, we will share the lessons learned from the New England Climate Adaptation Project (NECAP), a participatory action research project that tested science-based role-play simulations as a tool for educating the public about climate change risks and simulating collective risk management efforts. NECAP was a 2-year effort involving the Massachusetts Institute of Technology, the Consensus Building Institute, the National Estuarine Research Reserve System, and four coastal New England municipalities. During 2012-2013, the NECAP team produced downscaled climate change projections, a summary risk assessment, and a stakeholder assessment for each partner community. Working with local partners, we used these assessments to create a tailored, science-based role-play simulation for each site. Through a series of workshops in 2013, NECAP engaged between 115-170 diverse stakeholders and members of the public in each partner municipality in playing the simulation and a follow up conversation about local climate change risks and possible adaptation strategies. Data were collected through before-and-after surveys administered to all workshop participants, follow-up interviews with 25 percent of workshop participants, public opinion polls conducted before and after our intervention, and meetings with public officials. This presentation will report our research findings and explain how science-based role-play simulations can be used to help communicate local climate change risks and enhance local readiness to adapt.

  1. CometCIEF: A Web-based Image Enhancement Facility to digitally enhance images of cometary comae

    NASA Astrophysics Data System (ADS)

    Samarasinha, N.; Martin, P.; Larson, S.

    2014-07-01

    The detailed analysis of cometary comae provides an observational basis to investigate both the nucleus as well as the coma of comets. The structures in the coma are indicative of the anisotropic emission of gas and dust from the nucleus. Therefore, accurate identifications and measurements of spatial information related to coma structures are needed for realistic quantitative interpretation of coma observations. In many instances, the coma features are only a few percent above the ambient background coma and require enhancement of such features to unambiguously identify them, to make measurements on them, and to carry out subsequent detailed analyses. There is a number of image enhancement techniques used by cometary scientists. Despite this, the wider applicability of many advanced enhancement techniques is limited due to the non-availability of relevant software as open source. To alleviate this, we are making available a number of such techniques using a user-friendly web interface. In this image enhancement facility available at http://www.psi.edu/research/cometimen one can upload a fits format image of a cometary coma and digitally enhance it using an image enhancement technique of the user's choice. The user can then easily download the enhanced image as well as any associated images generated during the enhancement as fits files for detailed analysis later at the user's institution. The available image enhancement techniques at the facility are: (a) division by azimuthal average; (b) division by azimuthal median; (c) azimuthal renormalization; (d) division by 1/ρ profile, where ρ is the sky-plane projected distance from the nucleus; and (e) radially variable spatial filtering. The site provides documentation describing the above enhancement techniques as well as a tutorial showing the application of the enhancement techniques to actual cometary images and how the results may vary with different input parameters. In addition, the source codes as well as

  2. 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. PMID:26093936

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  4. Color Histogram Diffusion for Image Enhancement

    NASA Technical Reports Server (NTRS)

    Kim, Taemin

    2011-01-01

    Various color histogram equalization (CHE) methods have been proposed to extend grayscale histogram equalization (GHE) for color images. In this paper a new method called histogram diffusion that extends the GHE method to arbitrary dimensions is proposed. Ranges in a histogram are specified as overlapping bars of uniform heights and variable widths which are proportional to their frequencies. This diagram is called the vistogram. As an alternative approach to GHE, the squared error of the vistogram from the uniform distribution is minimized. Each bar in the vistogram is approximated by a Gaussian function. Gaussian particles in the vistoram diffuse as a nonlinear autonomous system of ordinary differential equations. CHE results of color images showed that the approach is effective.

  5. Algorithms evaluation for fundus images enhancement

    NASA Astrophysics Data System (ADS)

    Braem, V.; Marcos, M.; Bizai, G.; Drozdowicz, B.; Salvatelli, y. A.

    2011-12-01

    Color images of the retina inherently involve noise and illumination artifacts. In order to improve the diagnostic quality of the images, it is desirable to homogenize the non-uniform illumination and increase contrast while preserving color characteristics. The visual result of different pre-processing techniques can be very dissimilar and it is necessary to make an objective assessment of the techniques in order to select the most suitable. In this article the performance of eight algorithms to correct the non-uniform illumination, contrast modification and color preservation was evaluated. In order to choose the most suitable a general score was proposed. The results got good impression from experts, although some differences suggest that not necessarily the best statistical quality of image is the one of best diagnostic quality to the trained doctor eye. This means that the best pre-processing algorithm for an automatic classification may be different to the most suitable one for visual diagnosis. However, both should result in the same final diagnosis.

  6. The adaptive-loop-gain adaptive-scale CLEAN deconvolution of radio interferometric images

    NASA Astrophysics Data System (ADS)

    Zhang, L.; Zhang, M.; Liu, X.

    2016-05-01

    CLEAN algorithms are a class of deconvolution solvers which are widely used to remove the effect of the telescope Point Spread Function (PSF). Loop gain is one important parameter in CLEAN algorithms. Currently the parameter is fixed during deconvolution, which restricts the performance of CLEAN algorithms. In this paper, we propose a new deconvolution algorithm with an adaptive loop gain scheme, which is referred to as the adaptive-loop-gain adaptive-scale CLEAN (Algas-Clean) algorithm. The test results show that the new algorithm can give a more accurate model with faster convergence.

  7. Adaptive Wavefront Calibration and Control for the Gemini Planet Imager

    SciTech Connect

    Poyneer, L A; Veran, J

    2007-02-02

    Quasi-static errors in the science leg and internal AO flexure will be corrected. Wavefront control will adapt to current atmospheric conditions through Fourier modal gain optimization, or the prediction of atmospheric layers with Kalman filtering.

  8. Embedded Bone Fragment Detection in Chicken Fillets using Transmittance Image Enhancement and Hyperspectral Reflectance Imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper is concerned with the detection of bone fragments embedded in compressed de-boned skinless chicken breast fillets by enhancing single-band transmittance images generated by back-lighting and exploiting spectral information from hyperspectral reflectance images. Optical imaging of chicken ...

  9. Adaptive memory: Animacy enhances free recall but impairs cued recall.

    PubMed

    Popp, Earl Y; Serra, Michael J

    2016-02-01

    Recent research suggests that human memory systems evolved to remember animate things better than inanimate things. In the present experiments, we examined whether these effects occur for both free recall and cued recall. In Experiment 1, we directly compared the effect of animacy on free recall and cued recall. Participants studied lists of objects and lists of animals for free-recall tests, and studied sets of animal-animal pairs and object-object pairs for cued-recall tests. In Experiment 2, we compared participants' cued recall for English-English, Swahili-English, and English-Swahili word pairs involving either animal or object English words. In Experiment 3, we compared participants' cued recall for animal-animal, object-object, animal-object, and object-animal pairs. Although we were able to replicate past effects of animacy aiding free recall, animacy typically impaired cued recall in the present experiments. More importantly, given the interactions found in the present experiments, we conclude that some factor associated with animacy (e.g., attention capture or mental arousal) is responsible for the present patterns of results. This factor seems to moderate the relationship between animacy and memory, producing a memory advantage for animate stimuli in scenarios where the moderator leads to enhanced target retrievability but a memory disadvantage for animate stimuli in scenarios where the moderator leads to impaired association memory. PMID:26375781

  10. Research on an Improved Medical Image Enhancement Algorithm Based on P-M Model.

    PubMed

    Dong, Beibei; Yang, Jingjing; Hao, Shangfu; Zhang, Xiao

    2015-01-01

    Image enhancement can improve the detail of the image and so as to achieve the purpose of the identification of the image. At present, the image enhancement is widely used in medical images, which can help doctor's diagnosis. IEABPM (Image Enhancement Algorithm Based on P-M Model) is one of the most common image enhancement algorithms. However, it may cause the lost of the texture details and other features. To solve the problems, this paper proposes an IIEABPM (Improved Image Enhancement Algorithm Based on P-M Model). Simulation demonstrates that IIEABPM can effectively solve the problems of IEABPM, and improve image clarity, image contrast, and image brightness. PMID:26628929

  11. Contrast-enhanced imaging of cerebral vasculature with laser speckle

    NASA Astrophysics Data System (ADS)

    Murari, K.; Li, N.; Rege, A.; Jia, X.; All, A.; Thakor, N.

    2007-08-01

    High-resolution cerebral vasculature imaging has applications ranging from intraoperative procedures to basic neuroscience research. Laser speckle, with spatial contrast processing, has recently been used to map cerebral blood flow. We present an application of the technique using temporal contrast processing to image cerebral vascular structures with a field of view a few millimeters across and approximately 20 μm resolution through a thinned skull. We validate the images using fluorescent imaging and demonstrate a factor of 2-4 enhancement in contrast-to-noise ratios over reflectance imaging using white or spectrally filtered green light. The contrast enhancement enables the perception of approximately 10%-30% more vascular structures without the introduction of any contrast agent.

  12. Quantification of background enhancement in breast magnetic resonance imaging

    PubMed Central

    Klifa, C; Suzuki, S; Aliu, S; Singer, L; Wilmes, L; Newitt, D; Joe, B; Hylton, N

    2011-01-01

    Purpose To present a novel technique for measuring tissue enhancement in breast fibroglandular tissue regions on contrast-enhanced breast MR images aimed at quantifying the enhancement of breast parenchyma, also known as “background enhancement”. Materials and Methods Our quantitative method for measuring breast MRI background enhancement was evaluated in a population of 16 healthy volunteers. We also demonstrate the use of our new technique in the case study of one subject classified as high risk for developing breast cancer who underwent 3 months of tamoxifen therapy. Results We obtained quantitative measures of background enhancement in all cases. The high-risk patient exhibited a 37% mean reduction in background enhancement with treatment. Conclusion Our quantitative method is a robust and promising tool that may allow investigators to quantify and document the potential adverse effect of background enhancement on diagnostic accuracy in larger populations. PMID:21509883

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

    PubMed

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

    2014-01-01

    Color flow imaging has been well applied in clinical diagnosis. For the high quality color flow images, clutter filter is important to separate the Doppler signals from blood and tissue. Traditional clutter filters, such as finite impulse response, infinite impulse response and regression filters, were applied, which are based on the hypothesis that the clutter signal is stationary or tissue moves slowly. However, in realistic clinic color flow imaging, the signals are non-stationary signals because of accelerated moving tissue. For most related papers, simulated RF signals are widely used without in vivo I/Q signal. Hence, in this paper, adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, was proposed based on in vivo carotid I/Q signal in realistic color flow imaging. To get the best performance, the optimal polynomial order of polynomial regression filter and the optimal polynomial order for estimation of instantaneous clutter frequency respectively were confirmed. Finally, compared with the mean blood velocity and quality of 2-D color flow image, the experiment results show that adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, can significantly enhance the mean blood velocity and get high quality 2-D color flow image. PMID:24211911

  14. An Adaptive Digital Image Watermarking Algorithm Based on Morphological Haar Wavelet Transform

    NASA Astrophysics Data System (ADS)

    Huang, Xiaosheng; Zhao, Sujuan

    At present, much more of the wavelet-based digital watermarking algorithms are based on linear wavelet transform and fewer on non-linear wavelet transform. In this paper, we propose an adaptive digital image watermarking algorithm based on non-linear wavelet transform--Morphological Haar Wavelet Transform. In the algorithm, the original image and the watermark image are decomposed with multi-scale morphological wavelet transform respectively. Then the watermark information is adaptively embedded into the original image in different resolutions, combining the features of Human Visual System (HVS). The experimental results show that our method is more robust and effective than the ordinary wavelet transform algorithms.

  15. AVES-IMCO: an adaptive optics visible spectrograph and imager/coronograph for NAOS

    NASA Astrophysics Data System (ADS)

    Beuzit, Jean-Luc; Lagrange, A.-M.; Mouillet, D.; Chauvin, G.; Stadler, E.; Charton, J.; Lacombe, F.; AVES-IMCO Team

    2001-05-01

    The NAOS adaptive optics system will very soon provide diffraction-limited images on the VLT, down to the visible wavelengths (0.020 arcseconds at 0.83 micron for instance). At the moment, the only instrument dedicated to NAOS is the CONICA spectro-imager, operating in the near-infrared from 1 to 5 microns. We are now proposing to ESO, in collaboration with an Italian group, the development of a visible spectrograph/imager/coronograph, AVES-IMCO (Adaptive Optics Visual Echelle Spectrograph and IMager/COronograph). We present here the general concept of the new instrument as well as its expected performances in the different modes.

  16. Research on adaptive segmentation and activity classification method of filamentous fungi image in microbe fermentation

    NASA Astrophysics Data System (ADS)

    Cai, Xiaochun; Hu, Yihua; Wang, Peng; Sun, Dujuan; Hu, Guilan

    2009-10-01

    The paper presents an adaptive segmentation and activity classification method for filamentous fungi image. Firstly, an adaptive structuring element (SE) construction algorithm is proposed for image background suppression. Based on watershed transform method, the color labeled segmentation of fungi image is taken. Secondly, the fungi elements feature space is described and the feature set for fungi hyphae activity classification is extracted. The growth rate evaluation of fungi hyphae is achieved by using SVM classifier. Some experimental results demonstrate that the proposed method is effective for filamentous fungi image processing.

  17. Image retargeting using non-uniform scaling with adaptive local search window

    NASA Astrophysics Data System (ADS)

    Wang, Shanshan; Abdel-Dayem, Amr

    2011-10-01

    This paper presents a new content-aware image-retargeting scheme, based on non-uniform scaling, to adaptively adjust the image's dimensions for various screen sizes. Based on an importance map, the energy contribution for each line in the reduced dimension to the overall energy within the image is computed. Then, the image is adaptively mapped and resampled based on the energy contribution function. Experimental results showed that the performance of the proposed scheme is comparable to seam carving in visual quality. However, it is computationally less expensive.

  18. Enhancing Tabletop X-Ray Phase Contrast Imaging with Nano-Fabrication

    NASA Astrophysics Data System (ADS)

    Miao, Houxun; Gomella, Andrew A.; Harmon, Katherine J.; Bennett, Eric E.; Chedid, Nicholas; Znati, Sami; Panna, Alireza; Foster, Barbara A.; Bhandarkar, Priya; Wen, Han

    2015-08-01

    X-ray phase-contrast imaging is a promising approach for improving soft-tissue contrast and lowering radiation dose in biomedical applications. While current tabletop imaging systems adapt to common x-ray tubes and large-area detectors by employing absorptive elements such as absorption gratings or monolithic crystals to filter the beam, we developed nanometric phase gratings which enable tabletop x-ray far-field interferometry with only phase-shifting elements, leading to a substantial enhancement in the performance of phase contrast imaging. In a general sense the method transfers the demands on the spatial coherence of the x-ray source and the detector resolution to the feature size of x-ray phase masks. We demonstrate its capabilities in hard x-ray imaging experiments at a fraction of clinical dose levels and present comparisons with the existing Talbot-Lau interferometer and with conventional digital radiography.

  19. Enhancing Tabletop X-Ray Phase Contrast Imaging with Nano-Fabrication.

    PubMed

    Miao, Houxun; Gomella, Andrew A; Harmon, Katherine J; Bennett, Eric E; Chedid, Nicholas; Znati, Sami; Panna, Alireza; Foster, Barbara A; Bhandarkar, Priya; Wen, Han

    2015-01-01

    X-ray phase-contrast imaging is a promising approach for improving soft-tissue contrast and lowering radiation dose in biomedical applications. While current tabletop imaging systems adapt to common x-ray tubes and large-area detectors by employing absorptive elements such as absorption gratings or monolithic crystals to filter the beam, we developed nanometric phase gratings which enable tabletop x-ray far-field interferometry with only phase-shifting elements, leading to a substantial enhancement in the performance of phase contrast imaging. In a general sense the method transfers the demands on the spatial coherence of the x-ray source and the detector resolution to the feature size of x-ray phase masks. We demonstrate its capabilities in hard x-ray imaging experiments at a fraction of clinical dose levels and present comparisons with the existing Talbot-Lau interferometer and with conventional digital radiography. PMID:26315891

  20. Enhancing Tabletop X-Ray Phase Contrast Imaging with Nano-Fabrication

    PubMed Central

    Miao, Houxun; Gomella, Andrew A.; Harmon, Katherine J.; Bennett, Eric E.; Chedid, Nicholas; Znati, Sami; Panna, Alireza; Foster, Barbara A.; Bhandarkar, Priya; Wen, Han

    2015-01-01

    X-ray phase-contrast imaging is a promising approach for improving soft-tissue contrast and lowering radiation dose in biomedical applications. While current tabletop imaging systems adapt to common x-ray tubes and large-area detectors by employing absorptive elements such as absorption gratings or monolithic crystals to filter the beam, we developed nanometric phase gratings which enable tabletop x-ray far-field interferometry with only phase-shifting elements, leading to a substantial enhancement in the performance of phase contrast imaging. In a general sense the method transfers the demands on the spatial coherence of the x-ray source and the detector resolution to the feature size of x-ray phase masks. We demonstrate its capabilities in hard x-ray imaging experiments at a fraction of clinical dose levels and present comparisons with the existing Talbot-Lau interferometer and with conventional digital radiography. PMID:26315891

  1. Application of adaptive optics in retinal imaging: a quantitative and clinical comparison with standard cameras

    NASA Astrophysics Data System (ADS)

    Barriga, E. S.; Erry, G.; Yang, S.; Russell, S.; Raman, B.; Soliz, P.

    2005-04-01

    Aim: The objective of this project was to evaluate high resolution images from an adaptive optics retinal imager through comparisons with standard film-based and standard digital fundus imagers. Methods: A clinical prototype adaptive optics fundus imager (AOFI) was used to collect retinal images from subjects with various forms of retinopathy to determine whether improved visibility into the disease could be provided to the clinician. The AOFI achieves low-order correction of aberrations through a closed-loop wavefront sensor and an adaptive optics system. The remaining high-order aberrations are removed by direct deconvolution using the point spread function (PSF) or by blind deconvolution when the PSF is not available. An ophthalmologist compared the AOFI images with standard fundus images and provided a clinical evaluation of all the modalities and processing techniques. All images were also analyzed using a quantitative image quality index. Results: This system has been tested on three human subjects (one normal and two with retinopathy). In the diabetic patient vascular abnormalities were detected with the AOFI that cannot be resolved with the standard fundus camera. Very small features, such as the fine vascular structures on the optic disc and the individual nerve fiber bundles are easily resolved by the AOFI. Conclusion: This project demonstrated that adaptive optic images have great potential in providing clinically significant detail of anatomical and pathological structures to the ophthalmologist.

  2. Adaptive optics OCT using 1060nm swept source and dual deformable lenses for human retinal imaging

    NASA Astrophysics Data System (ADS)

    Jian, Yifan; Lee, Sujin; Cua, Michelle; Miao, Dongkai; Bonora, Stefano; Zawadzki, Robert J.; Sarunic, Marinko V.

    2016-03-01

    Adaptive optics concepts have been applied to the advancement of biological imaging and microscopy. In particular, AO has also been very successfully applied to cellular resolution imaging of the retina, enabling visualization of the characteristic mosaic patterns of the outer retinal layers using flood illumination fundus photography, Scanning Laser Ophthalmoscopy (SLO), and Optical Coherence Tomography (OCT). Despite the high quality of the in vivo images, there has been a limited uptake of AO imaging into the clinical environment. The high resolution afforded by AO comes at the price of limited field of view and specialized equipment. The implementation of a typical adaptive optics imaging system results in a relatively large and complex optical setup. The wavefront measurement is commonly performed using a Hartmann-Shack Wavefront Sensor (HS-WFS) placed at an image plane that is optically conjugated to the eye's pupil. The deformable mirror is also placed at a conjugate plane, relaying the wavefront corrections to the pupil. Due to the sensitivity of the HS-WFS to back-reflections, the imaging system is commonly constructed from spherical mirrors. In this project, we present a novel adaptive optics OCT retinal imaging system with significant potential to overcome many of the barriers to integration with a clinical environment. We describe in detail the implementation of a compact lens based wavefront sensorless adaptive optics (WSAO) 1060nm swept source OCT human retinal imaging system with dual deformable lenses, and present retinal images acquired in vivo from research volunteers.

  3. Resolution enhancement in digital x-ray imaging

    NASA Astrophysics Data System (ADS)

    Gravel, Pierre; Després, Philippe; Beaudoin, Gilles; de Guise, Jacques A.

    2006-05-01

    We have developed a restoration method for radiographs that enhances image sharpness and reveals bone microstructures that were initially hidden in the soft-tissue glare. The method is two fold: the image is first deconvolved using the Richardson-Lucy algorithm and is then divided with a signal modelling the soft-tissue distribution to increase the overall contrast. Each step has its own merits but the power of the restoration method lies in their combination. The originality of the method is its reliance on a priori information at each step in the processing. We have measured and modelled analytically the point-spread function of a low-dose gas microstrip x-ray detector at several beam energies. We measured the relationship between the local image intensity and the noise variance for these images. The soft-tissue signal was also modelled using a minimum-curvature filtering technique. These results were then combined into an image deconvolution procedure that uses wavelet filtering to reduce restoration noise while keeping the enhanced small-scale features. The method was applied successfully to images of a human-torso phantom and improved the contrast of small details on the bones and in the soft tissues. We measured a mean 54% increase in signal to noise ratio and a mean 105% increase in contrast to noise ratio in the 70 and 140 kVp images we analysed. The method was designed to facilitate the analysis of radiographs by relying on two levels of visual inspection. The contrast of the full image is first enhanced by division with the signal modelling the soft-tissue distribution. Based on the result, a radiologist might decide to zoom in on a given image section. The full restoration method is then applied to that region of interest. Indeed, full image deconvolution is often unnecessary since enhanced small-scale details are not visible at large scale; only the section of interest is processed which is more efficient.

  4. Novel Imaging Enhancements in Capsule Endoscopy

    PubMed Central

    Van Gossum, Andre

    2013-01-01

    Video capsule endoscopy that was launched 10 years ago has become a first-line procedure for examining the small bowel. The most common indications for capsule endoscopy are obscure gastrointestinal bleeding, Crohn's disease, polyposis syndromes, and evaluation of patients with complicated celiac disease. The ideal capsule should improve the quality of the image and have a faster frame rate than the currently available one. There should be a therapeutic capsule capable of performing a biopsy, aspirating fluid, delivering drugs, and measuring the motility of the small bowel wall. Another major leap forward would be the capability of remote control of capsule's movement in order to navigate it to reach designated anatomical areas for carrying out a variety of therapeutic options. Technology for improving the capability of the future generation capsules almost within grasp and it would not be surprising to witness the realization of these giant steps within the coming decade. In this review we will focus on the current clinical applications of capsule endoscopy for imaging of the small bowel and colon and will additionally give an outlook on future concepts and developments of capsule endoscopy. PMID:23878532

  5. Manganese-Enhanced Magnetic Resonance Imaging (MEMRI)

    PubMed Central

    Massaad, Cynthia A.; Pautler, Robia G.

    2012-01-01

    The use of manganese ions (Mn2+) as an MRI contrast agent was introduced over 20 years ago in studies of Mn2+ toxicity in anesthetized rats (1). Manganese-enhanced MRI (MEMRI) evolved in the late nineties when Koretsky and associates pioneered the use of MEMRI for brain activity measurements (2) as well as neuronal tract tracing (3). Currently, MEMRI has three primary applications in biological systems: (1) contrast enhancement for anatomical detail, (2) activity-dependent assessment and (3) tracing of neuronal connections or tract tracing. MEMRI relies upon the following three main properties of Mn2+: (1) it is a paramagnetic ion that shortens the spin lattice relaxation time constant (T1) of tissues, where it accumulates and hence functions as an excellent T1 contrast agent; (2) it is a calcium (Ca2+) analog that can enter excitable cells, such as neurons and cardiac cells via voltage-gated Ca2+ channels; and (3) once in the cells Mn2+ can be transported along axons by microtubule-dependent axonal transport and can also cross synapses trans-synaptically to neighboring neurons. This chapter will emphasize the methodological approaches towards the use of MEMRI in biological systems. PMID:21279601

  6. MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods

    PubMed Central

    Schmidt, Johannes F. M.; Santelli, Claudio; Kozerke, Sebastian

    2016-01-01

    An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods. PMID:27116675

  7. MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods.

    PubMed

    Schmidt, Johannes F M; Santelli, Claudio; Kozerke, Sebastian

    2016-01-01

    An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods. PMID:27116675

  8. The effect of retinal image error update rate on human vestibulo-ocular reflex gain adaptation.

    PubMed

    Fadaee, Shannon B; Migliaccio, Americo A

    2016-04-01

    The primary function of the angular vestibulo-ocular reflex (VOR) is to stabilise images on the retina during head movements. Retinal image movement is the likely feedback signal that drives VOR modification/adaptation for different viewing contexts. However, it is not clear whether a retinal image position or velocity error is used primarily as the feedback signal. Recent studies examining this signal are limited because they used near viewing to modify the VOR. However, it is not known whether near viewing drives VOR adaptation or is a pre-programmed contextual cue that modifies the VOR. Our study is based on analysis of the VOR evoked by horizontal head impulses during an established adaptation task. Fourteen human subjects underwent incremental unilateral VOR adaptation training and were tested using the scleral search coil technique over three separate sessions. The update rate of the laser target position (source of the retinal image error signal) used to drive VOR adaptation was different for each session [50 (once every 20 ms), 20 and 15/35 Hz]. Our results show unilateral VOR adaptation occurred at 50 and 20 Hz for both the active (23.0 ± 9.6 and 11.9 ± 9.1% increase on adapting side, respectively) and passive VOR (13.5 ± 14.9, 10.4 ± 12.2%). At 15 Hz, unilateral adaptation no longer occurred in the subject group for both the active and passive VOR, whereas individually, 4/9 subjects tested at 15 Hz had significant adaptation. Our findings suggest that 1-2 retinal image position error signals every 100 ms (i.e. target position update rate 15-20 Hz) are sufficient to drive VOR adaptation. PMID:26715411

  9. A contrast enhancement technique for low light images

    NASA Astrophysics Data System (ADS)

    Singh, Ankita; Gupta, K. K.

    2016-03-01

    Digital Imagery systems are traditionally bad in low light conditions. In this paper, a new algorithm for contrast improvement is proposed. The algorithm consists of two stages. The first stage is decomposing the input image into four subbands by applying two-dimensional discrete wavelet transform and estimates the singular value matrix of sub band image. The second stage is that it reconstructs the enhanced image by applying the inverse DWT. The technique is compared with conventional image equalization technique such as standard General Histogram Equalization (GHE) and other state-of-the-art techniques such as Quadrant Dynamic Histogram Equalization (QDHE), Singular-Value-Wavelet based image Equalization (SVWE) and Singular Value Equalization (SVE) on the basis of their Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE) values. The simulation results indicated that the image contrast enhanced by the purposed method was higher than that of the images enhanced by the other conventional state-of-the-art techniques.

  10. The evolving role of response-adapted PET imaging in Hodgkin lymphoma

    PubMed Central

    Coyle, Michael; Kostakoglu, Lale; Evens, Andrew M.

    2016-01-01

    18F-fluorodeoxyglucose positron emission tomography with (FDG-PET) has a well-established role in the pre- and post-treatment staging of Hodgkin lymphoma (HL), however its use as a predictive therapeutic tool via responded-adapted therapy continues to evolve. There have been a multitude of retrospective and noncontrolled clinical studies showing that early (or interim) FDG-PET is highly prognostic in HL, particularly in the advanced-stage setting. Response-adapted treatment approaches in HL are attempting to diminish toxicity for low-risk patients by minimizing therapy, and conversely, intensify treatment for high-risk patients. Results from phase III noninferiority studies in early-stage HL with negative interim FDG-PET that randomized patients to chemotherapy alone versus combined modality therapy showed a continued small improvement in progression-free survival for patients who did not receive radiation. Preliminary reports of data escalating therapy for positive interim FDG-PET in early-stage HL and for de-escalation of therapy [i.e. bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine and prednisone (BEACOPP)] for negative interim FDG-PET in advanced stage HL (i.e. deletion of bleomycin) have demonstrated improved outcomes. Maturation of these studies and continued follow up of all response-adapted studies are needed. Altogether, the treatment of HL remains an individualized clinical management choice for physicians and patients. Continued refinement and optimization of FDG-PET is needed, including within the context of targeted therapeutic agents. In addition, a number of new and novel techniques of functional imaging, including metabolic tumor volume and tumor proliferation, are being explored in order to enhance staging, characterization, prognostication and ultimately patient outcome. PMID:27054026

  11. The evolving role of response-adapted PET imaging in Hodgkin lymphoma.

    PubMed

    Coyle, Michael; Kostakoglu, Lale; Evens, Andrew M

    2016-04-01

    (18)F-fluorodeoxyglucose positron emission tomography with (FDG-PET) has a well-established role in the pre- and post-treatment staging of Hodgkin lymphoma (HL), however its use as a predictive therapeutic tool via responded-adapted therapy continues to evolve. There have been a multitude of retrospective and noncontrolled clinical studies showing that early (or interim) FDG-PET is highly prognostic in HL, particularly in the advanced-stage setting. Response-adapted treatment approaches in HL are attempting to diminish toxicity for low-risk patients by minimizing therapy, and conversely, intensify treatment for high-risk patients. Results from phase III noninferiority studies in early-stage HL with negative interim FDG-PET that randomized patients to chemotherapy alone versus combined modality therapy showed a continued small improvement in progression-free survival for patients who did not receive radiation. Preliminary reports of data escalating therapy for positive interim FDG-PET in early-stage HL and for de-escalation of therapy [i.e. bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine and prednisone (BEACOPP)] for negative interim FDG-PET in advanced stage HL (i.e. deletion of bleomycin) have demonstrated improved outcomes. Maturation of these studies and continued follow up of all response-adapted studies are needed. Altogether, the treatment of HL remains an individualized clinical management choice for physicians and patients. Continued refinement and optimization of FDG-PET is needed, including within the context of targeted therapeutic agents. In addition, a number of new and novel techniques of functional imaging, including metabolic tumor volume and tumor proliferation, are being explored in order to enhance staging, characterization, prognostication and ultimately patient outcome. PMID:27054026

  12. Contrast-Enhanced Magnetic Resonance Imaging in Pediatric Patients: Review and Recommendations for Current Practice

    PubMed Central

    Bhargava, Ravi; Hahn, Gabriele; Hirsch, Wolfgang; Kim, Myung-Joon; Mentzel, Hans-Joachim; Olsen, Øystein E.; Stokland, Eira; Triulzi, Fabio; Vazquez, Elida

    2013-01-01

    Magnetic resonance imaging (MRI), frequently with contrast enhancement, is the preferred imaging modality for many indications in children. Practice varies widely between centers, reflecting the rapid pace of change and the need for further research. Guide-line changes, for example on contrast-medium choice, require continued practice reappraisal. This article reviews recent developments in pediatric contrast-enhanced MRI and offers recommendations on current best practice. Nine leading pediatric radiologists from internationally recognized radiology centers convened at a consensus meeting in Bordeaux, France, to discuss applications of contrast-enhanced MRI across a range of indications in children. Review of the literature indicated that few published data provide guidance on best practice in pediatric MRI. Discussion among the experts concluded that MRI is preferred over ionizing-radiation modalities for many indications, with advantages in safety and efficacy. Awareness of age-specific adaptations in MRI technique can optimize image quality. Gadolinium-based contrast media are recommended for enhancing imaging quality. The choice of most appropriate contrast medium should be based on criteria of safety, tolerability, and efficacy, characterized in age-specific clinical trials and personal experience. PMID:25114547

  13. Multichannel Speech Enhancement Based on Generalized Gamma Prior Distribution with Its Online Adaptive Estimation

    NASA Astrophysics Data System (ADS)

    Dat, Tran Huy; Takeda, Kazuya; Itakura, Fumitada

    We present a multichannel speech enhancement method based on MAP speech spectral magnitude estimation using a generalized gamma model of speech prior distribution, where the model parameters are adapted from actual noisy speech in a frame-by-frame manner. The utilization of a more general prior distribution with its online adaptive estimation is shown to be effective for speech spectral estimation in noisy environments. Furthermore, the multi-channel information in terms of cross-channel statistics are shown to be useful to better adapt the prior distribution parameters to the actual observation, resulting in better performance of speech enhancement algorithm. We tested the proposed algorithm in an in-car speech database and obtained significant improvements of the speech recognition performance, particularly under non-stationary noise conditions such as music, air-conditioner and open window.

  14. Adaptive divergence of a transcriptional enhancer between populations of Drosophila melanogaster

    PubMed Central

    Glaser-Schmitt, Amanda; Catalán, Ana; Parsch, John

    2013-01-01

    As species colonize new habitats they must adapt to the local environment. Much of this adaptation is thought to occur at the regulatory level; however, the relationships among genetic polymorphism, expression variation and adaptation are poorly understood. Drosophila melanogaster, which expanded from an ancestral range in sub-Saharan Africa around 15 000 years ago, represents an excellent model system for studying regulatory evolution. Here, we focus on the gene CG9509, which differs in expression between an African and a European population of D. melanogaster. The expression difference is caused by variation within a transcriptional enhancer adjacent to the CG9509 coding sequence. Patterns of sequence variation indicate that this enhancer was the target of recent positive selection, suggesting that the expression difference is adaptive. Analysis of the CG9509 enhancer in new population samples from Europe, Asia, northern Africa and sub-Saharan Africa revealed that sequence polymorphism is greatly reduced outside the ancestral range. A derived haplotype absent in sub-Saharan Africa is at high frequency in all other populations. These observations are consistent with a selective sweep accompanying the range expansion of the species. The new data help identify the sequence changes responsible for the difference in enhancer activity. PMID:24218636

  15. Can Survival Processing Enhance Story Memory? Testing the Generalizability of the Adaptive Memory Framework

    ERIC Educational Resources Information Center

    Seamon, John G.; Bohn, Justin M.; Coddington, Inslee E.; Ebling, Maritza C.; Grund, Ethan M.; Haring, Catherine T.; Jang, Sue-Jung; Kim, Daniel; Liong, Christopher; Paley, Frances M.; Pang, Luke K.; Siddique, Ashik H.

    2012-01-01

    Research from the adaptive memory framework shows that thinking about words in terms of their survival value in an incidental learning task enhances their free recall relative to other semantic encoding strategies and intentional learning (Nairne, Pandeirada, & Thompson, 2008). We found similar results. When participants used incidental survival…

  16. Adaptive Memory: Young Children Show Enhanced Retention of Fitness-Related Information

    ERIC Educational Resources Information Center

    Aslan, Alp; Bauml, Karl-Heinz T.

    2012-01-01

    Evolutionary psychologists propose that human cognition evolved through natural selection to solve adaptive problems related to survival and reproduction, with its ultimate function being the enhancement of reproductive fitness. Following this proposal and the evolutionary-developmental view that ancestral selection pressures operated not only on…

  17. Non-adaptive and adaptive hybrid approaches for enhancing water quality management

    NASA Astrophysics Data System (ADS)

    Kalwij, Ineke M.; Peralta, Richard C.

    2008-09-01

    SummaryUsing optimization to help solve groundwater management problems cost-effectively is becoming increasingly important. Hybrid optimization approaches, that combine two or more optimization algorithms, will become valuable and common tools for addressing complex nonlinear hydrologic problems. Hybrid heuristic optimizers have capabilities far beyond those of a simple genetic algorithm (SGA), and are continuously improving. SGAs having only parent selection, crossover, and mutation are inefficient and rarely used for optimizing contaminant transport management. Even an advanced genetic algorithm (AGA) that includes elitism (to emphasize using the best strategies as parents) and healing (to help assure optimal strategy feasibility) is undesirably inefficient. Much more efficient than an AGA is the presented hybrid (AGCT), which adds comprehensive tabu search (TS) features to an AGA. TS mechanisms (TS probability, tabu list size, search coarseness and solution space size, and a TS threshold value) force the optimizer to search portions of the solution space that yield superior pumping strategies, and to avoid reproducing similar or inferior strategies. An AGCT characteristic is that TS control parameters are unchanging during optimization. However, TS parameter values that are ideal for optimization commencement can be undesirable when nearing assumed global optimality. The second presented hybrid, termed global converger (GC), is significantly better than the AGCT. GC includes AGCT plus feedback-driven auto-adaptive control that dynamically changes TS parameters during run-time. Before comparing AGCT and GC, we empirically derived scaled dimensionless TS control parameter guidelines by evaluating 50 sets of parameter values for a hypothetical optimization problem. For the hypothetical area, AGCT optimized both well locations and pumping rates. The parameters are useful starting values because using trial-and-error to identify an ideal combination of control

  18. Image contrast enhancement in angular domain optical imaging of turbid media.

    PubMed

    Vasefi, Fartash; Kaminska, Bozena; Chapman, Glenn H; Carson, Jeffrey J L

    2008-12-22

    Imaging structures within a turbid medium using Angular Domain Imaging (ADI) employs an angular filter array to separate weakly scattered photons from those that are highly scattered. At high scattering coefficients, ADI contrast declines due to the large fraction of non-uniform background scattered light still within the acceptance angle. This paper demonstrates various methods to enhance the image contrast in ADI. Experiments where a wedge prism was used to deviate the laser source so that scattered photons could be imaged and subtracted from the image obtained by standard ADI provided the greatest improvement in image contrast. PMID:19104579

  19. Widefield quantitative multiplex surface enhanced Raman scattering imaging in vivo.

    PubMed

    McVeigh, Patrick Z; Mallia, Rupananda J; Veilleux, Israel; Wilson, Brian C

    2013-04-01

    In recent years numerous studies have shown the potential advantages of molecular imaging in vitro and in vivo using contrast agents based on surface enhanced Raman scattering (SERS), however the low throughput of traditional point-scanned imaging methodologies have limited their use in biological imaging. In this work we demonstrate that direct widefield Raman imaging based on a tunable filter is capable of quantitative multiplex SERS imaging in vivo, and that this imaging is possible with acquisition times which are orders of magnitude lower than achievable with comparable point-scanned methodologies. The system, designed for small animal imaging, has a linear response from (0.01 to 100 pM), acquires typical in vivo images in <10 s, and with suitable SERS reporter molecules is capable of multiplex imaging without compensation for spectral overlap. To demonstrate the utility of widefield Raman imaging in biological applications, we show quantitative imaging of four simultaneous SERS reporter molecules in vivo with resulting probe quantification that is in excellent agreement with known quantities (R²>0.98). PMID:23591913

  20. 3D segmentation of masses in DCE-MRI images using FCM and adaptive MRF

    NASA Astrophysics Data System (ADS)

    Zhang, Chengjie; Li, Lihua

    2014-03-01

    Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a sensitive imaging modality for the detection of breast cancer. Automated segmentation of breast lesions in DCE-MRI images is challenging due to inherent signal-to-noise ratios and high inter-patient variability. A novel 3D segmentation method based on FCM and MRF is proposed in this study. In this method, a MRI image is segmented by spatial FCM, firstly. And then MRF segmentation is conducted to refine the result. We combined with the 3D information of lesion in the MRF segmentation process by using segmentation result of contiguous slices to constraint the slice segmentation. At the same time, a membership matrix of FCM segmentation result is used for adaptive adjustment of Markov parameters in MRF segmentation process. The proposed method was applied for lesion segmentation on 145 breast DCE-MRI examinations (86 malignant and 59 benign cases). An evaluation of segmentation was taken using the traditional overlap rate method between the segmented region and hand-drawing ground truth. The average overlap rates for benign and malignant lesions are 0.764 and 0.755 respectively. Then we extracted five features based on the segmentation region, and used an artificial neural network (ANN) to classify between malignant and benign cases. The ANN had a classification performance measured by the area under the ROC curve of AUC=0.73. The positive and negative predictive values were 0.86 and 0.58, respectively. The results demonstrate the proposed method not only achieves a better segmentation performance in accuracy also has a reasonable classification performance.