Publication Type:

Conference Paper

Source:

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

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84910597323&partnerID=40&md5=bbebacd2af03a329b59710f2472ba7bf

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

Notes:

cited By 0; Conference of 2014 IEEE International Conference on Green Computing, Communication and Electrical Engineering, ICGCCEE 2014 ; Conference Date: 6 March 2014 Through 8 March 2014; Conference Code:108513

Cite this Research Publication

S. Ravindranath, Ram, S. R. N., Subhashini, S., Reddy, A. V. S., Janarth, M., Aswathvignesh, R., Gandhiraj, R., and 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.