Results 61 to 70 of about 302,463 (187)
Sparsity-driven image formation and space-variant focusing for SAR [PDF]
, 2011 In synthetic aperture radar (SAR) imaging, the presence of moving targets in the scene causes phase errors in the SAR data and subsequently defocusing in the formed image. The defocusing caused by the moving targets exhibits space-variant characteristics,
Çetin, Müjdat, Önhon, Özben Naime
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RIPless Based Radar Waveform Analysis in Sparse Microwave Imaging
Leida xuebao, 2013 The echo data can be modeled as the product of the Toeplitz matrix and reflectivity of the observed scene. The row of the Toeplitz matrix is the time-shift of the transmitted signal.
Zhao Yao +3 more
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Inverse Synthetic Aperture Radar Sparse Imaging Exploiting the Group Dictionary Learning
Remote Sensing, 2021 Sparse imaging relies on sparse representations of the target scenes to be imaged. Predefined dictionaries have long been used to transform radar target scenes into sparse domains, but the performance is limited by the artificially designed or existing ...
Changyu Hu +3 more
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Compressive Imaging of Subwavelength Structures II. Periodic Rough Surfaces
, 2011 A compressed sensing scheme for near-field imaging of corrugations of relative sparse Fourier components is proposed. The scheme employs random sparse measurement of near field to recover the angular spectrum of the scattered field.
Albert Fannjiang +32 more
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Sparse Representation for Color Image Restoration [PDF]
IEEE Transactions on Image Processing, 2008 Sparse representations of signals have drawn considerable interest in recent years. The assumption that natural signals, such as images, admit a sparse decomposition over a redundant dictionary leads to efficient algorithms for handling such sources of data.
Julien, Mairal +2 more
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Sparse Bayesian image restoration
2010 IEEE International Conference on Image Processing, 2010 In this paper we propose a novel Bayesian algorithm for image restoration and parameter estimation. We utilize an image prior where Gaussian distributions are placed per pixel in the high-pass filter outputs of the image. By following the hierarchical Bayesian framework, we simultaneously estimate the unknown image and hyperparameters for both the ...
S. Derin Babacan +2 more
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(k,q)-Compressed Sensing for dMRI with Joint Spatial-Angular Sparsity Prior
, 2017 Advanced diffusion magnetic resonance imaging (dMRI) techniques, like diffusion spectrum imaging (DSI) and high angular resolution diffusion imaging (HARDI), remain underutilized compared to diffusion tensor imaging because the scan times needed to ...
E Candès +6 more
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LASAR High-resolution 3D Imaging Algorithm Based on Sparse Bayesian Regularization
Leida xuebao, 2018 Linear Array Synthetic Aperture Radar (LASAR) is a novel and promising radar imaging technique. It is difficult to achieve high-resolution LASAR three-dimensional (3D) imaging using the traditional imaging methods based on match filter, because of ...
Yan Min +4 more
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Sparse seismic imaging using variable projection
, 2012 We consider an important class of signal processing problems where the signal of interest is known to be sparse, and can be recovered from data given auxiliary information about how the data was generated.
Aravkin, Aleksandr Y. +2 more
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Effective Visualization of Sparse Image-to-Image Correspondences
, 2020 Rendering, Images, and ...
Andújar Gran, Carlos Antonio|| +2 more
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