A Compressed Sensing Approach to Image Reconstruction |
Author(s): |
| Arvinder Kaur , Punjab University, Chandigarh., India; Sumit Budhiraja, Punjab University, Chandigarh., India |
Keywords: |
| Compressed sensing (CS), Sparsity, sparse matrix, nonlinear image reconstruction |
Abstract |
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compressed sensing is a new technique that discards the Shannon Nyquist theorem for reconstructing a signal. It uses very few random measurements that were needed traditionally to recover any signal or image. The need of this technique comes from the fact that most of the information is provided by few of the signal coefficients, then why do we have to acquire all the data if it is thrown away without being used. A number of review articles and research papers have been published in this area. But with the increasing interest of practitioners in this emerging field it is mandatory to take a fresh look at this method and its implementations. The main aim of this paper is to review the compressive sensing theory and its applications. |
Other Details |
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Paper ID: IJSRDV1I6005 Published in: Volume : 1, Issue : 6 Publication Date: 01/09/2013 Page(s): 1292-1294 |
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