Image deblurring using Bayesian framework

Abstract

This paper proposes a new method for identifying the blur model and its parameters to restore the image from the blurred image. This is based on the specific distortions caused by the distorting operator in the Fourier spectrum amplitude of an image. Due to the ill-posed nature of image restoration (IR) process, prior knowledge of natural images is used to regularize the IR problem. The Bayesian approach provides the means to incorporate prior knowledge in data analysis. The choice of prior is very important. A comparative analysis using various priors was studied qualitatively. The sparse and redundant prior method gives better results both subjectively and objectively when compared with other priors. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.