Iterative Blind Deconvolution Algorithm for Support Domain Based on Information Entropy

Abstract

Aiming at the problem of deconvolution which is easy to appear in traditional iterative blind deconvolution algorithm, an improved iterative blind deconvolution algorithm is proposed. The information entropy algorithm is used to calculate the limited support domain of the image, and the iterative replacement of the space and the frequency domain is performed in the support domain, thereby effectively solving the fuzzy problem. The simulation results show that compared with the original iterative blind deconvolution algorithm, the image has higher peak signal-to-noise ratio (SNR), faster convergence and better recovery.