Denoising of Images Corrupted By Mixed Noise Using Improved WESNR Method

Digital images play very consequential role in modern day to day life applications as well as in the areas of researches and technologies. Effectively remove noise from an image while keeping its features intact is a fundamental problem of image processing. Image denoising is the process or technique of removing noise from images. One typical kind of mixed noise is Impulse Noise (IN) coupled with Additive White Gaussian Noise (AWGN). This work introduces a method of denoising using Decision Based (DB) Weighted Encoding with Sparse Nonlocal Regularization (WESNR) to remove mixed IN and AWGN. Experimental results shown in terms of both visual quality as well as in quantitative measures that proposed method achieves leading mixed noise removal performance.