COVID-19 Detection using Compressive Sensing

Compressive Sensing (CS) is a recent signal processing technique and extremely popular as it samples the signal at a sub-Nyquist rate. CS simplifies the signal acquisition by taking into account fewer random samples which, in turn, make signal reconstruction faster due to reduced sample size. In this paper, various acquisition, as well as reconstruction strategies, have been reviewed critically and the feasibility of implementation of CS in various fields, be it for continuous signals, periodic signals, wideband signals, have been discussed. We have also proposed an algorithm for the detection of COVID-19 using Lung X-ray dataset.