Results 11 to 20 of about 83,836 (252)
Sparsity and Incoherence in Compressive Sampling [PDF]
Inverse Problems, 2006 We consider the problem of reconstructing a sparse signal $x^0\in\R^n$ from a limited number of linear measurements. Given $m$ randomly selected samples of $U x^0$, where $U$ is an orthonormal matrix, we show that $\ell_1$ minimization recovers $x^0 ...
Baraniuk R G Davenport M DeVore R Wakin M +11 more
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Imaging via Compressive Sampling [Introduction to compressive sampling and recovery via convex programming] [PDF]
IEEE Signal Processing Magazine, 2008 There is an extensive body of literature on image compression, but the central concept is straightforward: we transform the image into an appropriate basis and then code only the important expansion coefficients.
Romberg, Justin
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PhotoniX, 2022 High-throughput imaging is highly desirable in intelligent analysis of computer vision tasks. In conventional design, throughput is limited by the separation between physical image capture and digital post processing.
Zhihong Zhang +7 more
doaj +2 more sources
Compressive Video Sampling [PDF]
, 2008 Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland ...
Stankovic, V., Stankovic, L., Cheng, S.
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Compressive Sampling Using a Pushframe Camera [PDF]
OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP), 2021 Pushframe parallellized single pixel camera imaging utilizes scanning motion to apply linear sampling masks to rapidly compressively sense a scene. We demonstrate strongly performing static binarized noiselet mask designs, tailored for pushframe hardware.
Stuart Bennett +6 more
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Variable Density Compressed Image Sampling [PDF]
IEEE Transactions on Image Processing, 2010 Compressed sensing (CS) provides an efficient way to acquire and reconstruct natural images from a limited number of linear projection measurements leading to sub-Nyquist sampling rates. A key to the success of CS is the design of the measurement ensemble.
Zhongmin, Wang, Gonzalo R, Arce
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Quadrature Compressive Sampling SAR Imaging [PDF]
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018 4 pages, 2 figures, submitted to IGARSS ...
Yang, Huizhang +3 more
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High-performance Microwave Computational Imaging System Based on Information Metamaterials
Leida xuebao, 2021 In this paper, we propose a detailed architectural design, principle of operation, and modeling analysis of a high-performance microwave computational imaging system based on information metamaterials.
Jiaqi HAN +5 more
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Vaguelette-Wavelet Deconvolution via Compressive Sampling
IEEE Access, 2019 Vaguelette-wavelet deconvolution (VWD) is known as a transform-based image restoration technique that involves applying wavelet-domain denoising to an observed image, followed by the Fourier-domain blur inversion, which can prevent noise amplification in
Chihiro Tsutake, Toshiyuki Yoshida
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Compressive Sampling of Binary Images [PDF]
2008 Congress on Image and Signal Processing, 2008 Compressive sampling is a novel framework that exploits sparsity of a signal in a transform domain to perform sampling below the Nyquist rate. In this paper, we apply compressive sampling to reduce the sampling rate of binary images. A system is proposed whereby the image is split into non-overlapping blocks of equal size and compressive sampling is ...
Stankovic, V., Stankovic, L., Cheng, S.
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