Comparison of Image Reconstruction Algorithms using Compressive Sensing

There is a huge increase in data in terms of data conversion that effects the performance and complexity of the devices like analog-to-digital converters (ADC).The standard ADC uses the conventional Shannon-Nyquist Theorem which says that sampling frequency should be twice of the maximum frequency. These samples require very huge storage.Compressive sensing(CS) which gives solution to this problem. In CS we decrease the sampling rate much less than the Nyquist rate and reconstruct the original signal.There are different reconstruction algorithms evolved since from its origin each. In this paper, we are making a comparison between the performances of Orthogonal Matching Pursuit(OMP) and Regularised Orthogonal Matching Pursuit(ROMP) algorithms for image reconstruction.