IMAGE PROCESSING USING BLIND DECONVOLUTION DEBLURRING TECHNIQUE
Sonia Saini, Lalit Himral · 2014
Image processing is an important component of modern technologies because human depends so much on the visual information than the creatures. The challenge to scientists, engineers and business people is to quickly extract the valuable information from the raw image data. This paper focused on image restoration which is sometimes referred to image deblurring or image deconvolution. Image restoration is concerned with the reconstruction or estimation of blur parameters of the uncorrupted image from a blurred and noisy one. The goal of blur identification is to estimate the attributes of the imperfect imaging system from the observed degraded image itself prior to the restoration process (Kundur and Hatzinakos, 1996). Blind Deconvolution algorithm can be used effectively when no information about the blurring and noise is known. The algorithm restores the image and the point spread function (PSF). The aim of this paper to show the effective Blind Deconvolution algorithm for image restoration which is the recovery in the form of a sharp version of blurred image when the blur kernel is unknown.