Compressive Sensing based Image Reconstruction Algorithms – A Performance Review

Compressive Sensing based Image Reconstruction Algorithms – A Performance Review
Author(s):
Dr. Vasudha S, Anupama H, Dr. S Shanthala, Dr. H.R. Mahadevaswamy
Keywords:
Compressive Sensing, Matching Pursuit, Basis Pursuit, Greedy algorithm, Sparse representation, Smoothed L0 norm
Abstract
Compressive Sensing (CS) is a powerful high resolution image modelling technique which has been successfully applied in digital image processing and various computer vision applications. This paper will portrait the current image reconstruction algorithms, their drawbacks and an overview of performance metrics such as image quality and PSNR improvements. The performance metric modelling is carried to trade-off choice of reconstruction algorithm with the quality of the reconstructed image considering various applications.
Article Details
Unique Paper ID: 144669 Publication Volume & Issue: Volume 4, Issue 1 Page(s): 367 - 371
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