Efficient Dark Channel Prior Based Blind Image De-blurring
Jalees Ahmad, Imran Touqir, Adil Masood Siddiqui · Radioengineering · 2021
Dark channel prior for blind image de-blurring has attained considerable attention in recent past.An interesting observation in blurring process is that the value of dark channel increases after averaging with adjacent high intensity pixels.L o regularization is proposed to curtail the value of dark channel.Half quadratic splitting method is used to solve the non-convex behavior of L o regularization.Furthermore, Discrete Wavelet Transform has been incorporated prior to de-blurring to increase the efficiency of algorithm.The most significant finding of this paper is a universal blind image de-blurring algorithm with reduced computational complexity.Experiments are performed and their results are comparable with state of the art de-blurring methods to evaluate the performance of algorithm.Experimental results also reveals that wavelet based dark channel prior image de-blurring is efficient for both uniform and nonuniform blur.