Estimating the Size of the Point Spread Function Using Fuzzy Logic for Blind Restoration of Satellite Image

Abstract

Abstract-Despite the considerable progress in the field of imaging, the acquired image can undergo certain degradations which are mainly summarized in blur and noise. The objective of the restoration is to estimate from the observed image an image as close as possible to the original image. The iterative blind deconvolution (IBD) can be used effectively when no information about the distortion is known. This algorithm starts with a random initial estimate of the point spread function (PSF) whose its size affects strongly the restoration process of the degraded image. In this paper, we have implemented a fuzzy inference system (FIS) to determine the size of the PSF through the examination of the blurred satellite image edges and the measurement of the blur width in pixels around an obviously sharp object. The obtained results are encouraging, which confirms the good performance of the proposed approach.

Image Deblurring using Wiener Filtering and Siamese Neural Network

“…Image deblurring is the recovery of the original image that was convoluted with a Point Spread Function (PSF) [3] and the addition of noise. Blind deconvolution is used to deblur an image without knowing the PSF used for convoluting the original image, whereas non-blind deconvolution methods use a known PSF for performing deconvolution.…”