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We compare three optical architectures for compressive imaging: sequential, parallel, and photon sharing. Each of these architectures is analyzed using two different types of projection: (a) principal compo nent projections and (b...
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We compare three optical architectures for compressive imaging: sequential, parallel, and photon sharing. Each of these architectures is analyzed using two different types of projection: (a) principal compo nent projections and (b) pseudo-random projections. Both linear and nonlinear reconstruction methods are studied. The performance of each architecture-projection combination is quantified in terms of reconstructed image quality as a function of measurement noise strength. Using a linear reconstruction operator we find that in all cases of (a) there is a measurement noise level above which compressive imaging is superior to conventional imaging. Normalized by the average object pixel brightness, these threshold noise standard deviations are 6.4, 4.9, and 2.1 for the sequential, parallel, and photon sharing architectures, respectively. We also find that conventional imaging outperforms compressive imaging using pseudo-random projections when linear reconstruction is employed. In all cases the photon sharing architecture is found to be more photon-efficient than the other two optical implementations and thus offers the highest performance among all compressive methods studied here. For example, with principal component projections and a linear reconstruction operator, the photon sharing architecture provides at least 17.6% less reconstruction error than either of the other two architectures for a noise strength of 1.6 times the average object pixel brightness. We also demonstrate that nonlinear reconstruction methods can offer additional performance improvements to all architectures for small values of noise.
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A new technique is presented to detect targets under sea background. Focused on interested areas, the spatial and frequency distributions are first studied, then analytic expression of targets is set up by least square method (LSM...
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A new technique is presented to detect targets under sea background. Focused on interested areas, the spatial and frequency distributions are first studied, then analytic expression of targets is set up by least square method (LSM). According to the shape, frequency, and analytic expression of targets, a matched biorthogonal wavelet is constructed to better enhance targets and eliminate noises. Results show the usefulness of this method for single frame detection (signal to noise ratio SNR ≥ 1.25), which provides a better performance than classic wavelets and morphological filtering.
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Compressive sensing (CS) is a signal processing technique that enables a signal that has a sparse representation in a known basis to be reconstructed using measurements obtained below the Nyquist rate. Single detector image recons...
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Compressive sensing (CS) is a signal processing technique that enables a signal that has a sparse representation in a known basis to be reconstructed using measurements obtained below the Nyquist rate. Single detector image reconstruction applications using CS have been shown to give promising results. In this study, we investigate the application of CS theory to single detector infrared (IR) rosette scanning systems which suffer from low performance compared to costly focal plane array (FPA) detectors. The single detector pseudoimaging rosette scanning system scans the scene with a specific pattern and performs processing to estimate the target location without forming an image. In this context, this generation of scanning systems may be improved by utilizing the samples obtained by the rosette scanning pattern in conjunction with the CS framework. For this purpose, we consider surface-to-air engagement scenarios using IR images containing aerial targets and flares. The IR images have been reconstructed from samples obtained with the rosette scanning pattern and other baseline sampling strategies. It has been shown that the proposed scheme exhibits good reconstruction performance and a large size FPA imaging performance can be achieved using a single IR detector with a rosette scanning pattern.
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We present an optical architecture for the laser optical feedback imaging (LOFI) technique that makes it possible to avoid the effect of the optical parasitic reflections introduced by the optical components located between the la...
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We present an optical architecture for the laser optical feedback imaging (LOFI) technique that makes it possible to avoid the effect of the optical parasitic reflections introduced by the optical components located between the laser source and the studied object. These reflections damage phase and amplitude information contained in the images. This phenomenon is a leading problem that strongly limits the LOFI performance for weak feedback detection. Consequently, it is essential to be able to limit or avoid the effect of these parasitic reflections to reach the optimal LOFI performance.
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Applying fractal coding to image segmentation was attempted as its new application. The encoding method is the same as the conventional fractal coding method, and the fractal-code is used for image segmentation. An image can be se...
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Applying fractal coding to image segmentation was attempted as its new application. The encoding method is the same as the conventional fractal coding method, and the fractal-code is used for image segmentation. An image can be segmented by calculating basins on a dynamical system parametrized by the fractal-code. It is shown that the new method has the ability to segment regions that have fine pixel-patterns as masses.
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Image interpolation is a critical step in panoramic image unwrapping studies. Information calculated in the Cartesian coordinates, although broadly applied, applies to operation between rectangles that will destroy the compressed ...
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Image interpolation is a critical step in panoramic image unwrapping studies. Information calculated in the Cartesian coordinates, although broadly applied, applies to operation between rectangles that will destroy the compressed depth information. The polar coordinates, in contrast, can store depth information by handing between rectangle and circle to obtain more true images. A fan-ring interpolation based on the polar coordinates is proposed for unwrapping panoramic images in this study through replanning the pixel search path in the panorama, and is then supported by redefining third-order interpolation. We validate our method on synthetic and practical images. Compared with competitor models, the unwrapping image obtained from the fan-ring interpolation can provide better quality in subjective and objective evaluation with guaranteed accuracy. (c) 2022 Optical Society of America
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Digital zoom is widely used in daily life from zooming a captured image to navigating through live maps. The applications are simple but application domains benefit large number of users. This manuscript proposes a novel approach ...
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Digital zoom is widely used in daily life from zooming a captured image to navigating through live maps. The applications are simple but application domains benefit large number of users. This manuscript proposes a novel approach to escalate zoom limits by modifying the zoom tolerance bound of an image. The approach focuses on preserving original information and transfer it to zoomed image. Digital zoom is achieved by first representing the original image as a set mathematical model representing underlying statistical parameters. The sets in model are further analyzed to calculate set variance; which in turn is used for localizing fluctuations and generate polynomial for each set. These polynomial are then used for implementing variable order interpolation scheme. Experimental results confirm that the present technique outperforms existing techniques in terms of image quality measurement parameters. The discussed approach can be implemented on RGB or grayscale images equivalently.
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The aims of this paper are twofold: to offer a short history of image retrieval, and secondly and relatedly, to critique the metanarrative of modernity emerging in the literature of knowledge organization and information retrieval...
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The aims of this paper are twofold: to offer a short history of image retrieval, and secondly and relatedly, to critique the metanarrative of modernity emerging in the literature of knowledge organization and information retrieval. The paper reviews the emerging grand narrative in relation to knowledge organization and information retrieval that sees them as specific aspects of modernity and technological efficiency. This grand narrative is particularly interested in technology even when it is contextualising technology. A more nuanced history emerges when the focus moves to the representation, organization, and retrieval of images. This literature foregrounds not only the technology but also issues relating to definitions of the "subject" and issues relating to interpretation and meaning-making.
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In many applications such as video surveillance or defect detection, the perception of information related to a scene is limited in areas with strong contrasts. The high dynamic range (HDR) capture technique can deal with these li...
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In many applications such as video surveillance or defect detection, the perception of information related to a scene is limited in areas with strong contrasts. The high dynamic range (HDR) capture technique can deal with these limitations. The proposed method has the advantage of automatically selecting multiple exposure times to make outputs more visible than fixed exposure ones. A real-time hardware implementation of the HDR technique that shows more details both in dark and bright areas of a scene is an important line of research. For this purpose, we built a dedicated smart camera that performs both capturing and HDR video processing from three exposures. What is new in our work is shown through the following points: HDR video capture through multiple exposure control, HDR memory management, HDR frame generation, and representation under a hardware context. Our camera achieves a real-time HDR video output at 60 fps at 1.3 megapixels and demonstrates the efficiency of our technique through an experimental result. Applications of this HDR smart camera include the movie industry, the mass-consumer market, military, automotive industry, and surveillance.
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Low-cost compact sensors for ultrasmall systems are a pressing need in many new applications. One potential solution is a shallow aspect ratio system using a lenslet array to form multiple undersampled subimages of a scene on a si...
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Low-cost compact sensors for ultrasmall systems are a pressing need in many new applications. One potential solution is a shallow aspect ratio system using a lenslet array to form multiple undersampled subimages of a scene on a single focal plane array, where processing techniques then produce an upsampled restored image. We have investigated the optimization and theoretical limits of the performance of such arrays. We have built a hardware simulator and developed algorithms to process imagery similar to that of a full lenslet imaging sensor, which allowed us to quickly test optical components, algorithms, and complete system designs for future lenslet imaging systems.
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