An Enhanced MoBayesShrink Thresholding for Medical Image Denoising
Manoj Diwakar, Tejeswi Chauhan, Pankaj Negi, Dheeraj Negi, Bharat Bhardwaj, Prabhishek Singh · 2019
The digital image carries a lot of pictorial information which has now become one of the chief ways of communication in this generation. The transmission of media especially image is often corrupted by the Gaussian noise due to various issues. This noise is needed to be removed. Image denoising technique is applied to remove such noise and make it of high quality. This additive Gaussian noise can be removed using wavelet denoising technique. This paper presents a better method that controls the threshold (T) adaptively to eliminate noise. Experimental results of the proposed method are better than the existing denoising algorithm Such as NSTISM(19), SPBIDM(18), BayesShrink, NormalShrink, and ModifiedBayesShrink.