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Compressive sensing based image acquisition and reconstruction analysis

Publication Type : Conference Paper

Publisher : Proceeding of the IEEE International Conference on Green Computing, Communication and Electrical Engineering, ICGCCEE 2014

Authors : Dr. Gandhiraj R., S. Ravindranath, Ram, S. R. N., Subhashini, S., Reddy, A. V. S., Janarth, M., Aswathvignesh, R., and Dr. Soman K. P

Campus : Coimbatore

School : School of Engineering

Department : Electronics and Communication

Verified : Yes

Year : 2014

Abstract : Compressive sensing is a technique by which images are acquired and reconstructed from a relatively fewer measurements than what the Nyquist rate suggests. Compressive sensing is applicable when the signals under consideration are sparse, and most of the images are sparse in wavelet or frequency domain. In this paper, the mathematical formulation of compressive sensing is explained where in various notations and parameters like measurement matrices and sparsity-inducing matrices are dealt in detail. A deterministic measurement matrix, known as chess measurement matrix is implemented in an aperture assembly. Several reconstruction algorithms are analysed and the images reconstructed with PSNR plotted for every case. Based upon the results, it is proved that OMP is the efficient reconstruction algorithm among all. © 2014 IEEE

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