Publication Type : Conference Paper
Thematic Areas : Center for Computational Engineering and Networking (CEN)
Publisher : Proceeding of the IEEE International Conference on Green Computing, Communication and Electrical Engineering, ICGCCEE 2014
Source : Proceeding of the IEEE International Conference on Green Computing, Communication and Electrical Engineering, ICGCCEE 2014 (2014)
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
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
Cite this Research Publication : S. Ravindranath, Ram, S. R. N., Subhashini, S., Reddy, A. V. S., Janarth, M., Aswathvignesh, R., Gandhiraj R., and Dr. Soman K. P., “Compressive sensing based image acquisition and reconstruction analysis”, in Proceeding of the IEEE International Conference on Green Computing, Communication and Electrical Engineering, ICGCCEE 2014, 2014.