Results 21 to 30 of about 1,231,296 (158)
Improved sparse representation using adaptive spatial support for effective target detection in hyperspectral imagery [PDF]
, 2013 With increasing applications of hyperspectral imagery (HSI) in agriculture, mineralogy, military, and other fields, one of the fundamental tasks is accurate detection of the target of interest.
Li, Xiaohui +3 more
core +3 more sources
Compressed sensing of monostatic and multistatic SAR [PDF]
, 2013 In this letter, we study the impact of compressed data collections from a synthetic aperture radar (SAR) sensor on the reconstruction quality of a scene of interest.
Çetin, Müjdat +5 more
core +1 more source
New Directions In Sparse Sampling and Estimation For Underdetermined Systems [PDF]
, 2013 A central objective in signal processing is to infer meaningful information from a set of measurements or data. While most signal models have an overdetermined structure (the number of unknowns less than the number of equations), traditionally very few ...
Piya Pal, Pal, Piya
core +1 more source
Sparse poisson intensity reconstruction algorithms [PDF]
2009 IEEE/SP 15th Workshop on Statistical Signal Processing, 2009 The observations in many applications consist of counts of discrete events, such as photons hitting a dector, which cannot be effectively modeled using an additive bounded or Gaussian noise model, and instead require a Poisson noise model. As a result, accurate reconstruction of a spatially or temporally distributed phenomenon (f) from Poisson data (y)
Harmany, Zachary T. +2 more
openaire +2 more sources
Adaptive thresholding for sparse image reconstruction
Telfor Journal, 2023 The performance of the class of sparse reconstruction algorithms which is based on the iterative thresholding is highly dependent on a selection of the appropriate threshold value, controlling a trade-off between the algorithm execution time and the solution accuracy. This is why most of the state-of-the-art reconstruction algorithms employ some method
Volarić, Ivan, Sučić, Viktor
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The cosparse analysis model and algorithms [PDF]
, 2013 After a decade of extensive study of the sparse representation synthesis model, we can safely say that this is a mature and stable field, with clear theoretical foundations, and appealing applications.
Gribonval, Rémi +7 more
core +1 more source
Generalized sparse Bayesian learning and application to image reconstruction [PDF]
, 2023 Image reconstruction based on indirect, noisy, or incomplete data remains an important yet challenging task. While methods such as compressive sensing have demonstrated high-resolution image recovery in various settings, there remain issues of robustness
Glaubitz, Jan +8 more
core +1 more source
Learning hash functions using sparse reconstruction
, 2014 Approximate nearest neighbor (ANN) search is becoming an increasingly important technique in large-scale problems. Recently many approaches have been developed due to fast query and low storage cost.
Yong Yuan +5 more
core +1 more source
Exact CS Reconstruction Condition of Undersampled Spectrum-Sparse Signals [PDF]
, 2013 Compressive sensing (CS) reconstruction of a spectrum-sparse signal from undersampled data is, in fact, an ill-posed problem. In this paper, we mathematically prove that, in certain cases, the exact CS reconstruction of a spectrum-sparse signal from ...
Guozheng Wang +3 more
core +1 more source
Structure-Based Bayesian Sparse Reconstruction [PDF]
IEEE Transactions on Signal Processing, 2012 Sparse signal reconstruction algorithms have attracted research attention due to their wide applications in various fields. In this paper, we present a simple Bayesian approach that utilizes the sparsity constraint and a priori statistical information (Gaussian or otherwise) to obtain near optimal estimates.
Ahmed Abdul Quadeer +1 more
openaire +4 more sources