{
"item_title" : "Sparse Signal Processing and Compressed Sensing Recovery",
"item_author" : [" Sahoo Sujit Kumar", "Makur Anamitra "],
"item_description" : "The presented work revolves around sparsity. It contributes to dictionary training for sparse representation with a new algorithm and analysis. It showcases the usability of trained dictionary in image processing problems. It demonstrates a new framework for image recovery (inpainting and denoising) using sparse representation. In the end, it proposes an extension of the well-known sparse signal recovery algorithm, Orthogonal Matching Pursuit (OMP) for compressed sensing. It also provides a complete analysis of the proposed extension, and its theoretical guarantees.",
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Overview
The presented work revolves around sparsity. It contributes to dictionary training for sparse representation with a new algorithm and analysis. It showcases the usability of trained dictionary in image processing problems. It demonstrates a new framework for image recovery (inpainting and denoising) using sparse representation. In the end, it proposes an extension of the well-known sparse signal recovery algorithm, Orthogonal Matching Pursuit (OMP) for compressed sensing. It also provides a complete analysis of the proposed extension, and its theoretical guarantees.
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Details
- ISBN-13: 9783659762130
- ISBN-10: 365976213X
- Publisher: LAP Lambert Academic Publishing
- Publish Date: July 2015
- Dimensions: 9 x 6 x 0.32 inches
- Shipping Weight: 0.46 pounds
- Page Count: 136
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