Image denoising using bilateral filter in subsampled pyramid and nonsubsampled directional filter bank domain
S. Amala Shanthi, Chellakkon Helen Sulochana, S. Albert Jerome · Journal of Intelligent & Fuzzy Systems · 2016
A vital task in image denoising is to preserve edges and image features while removing noise. This paper presents an efficient algorithm for noise removal by incorporating an adaptive bilateral filter in the subsampled pyramid and nonsubsampled directional filter bank (SPNSDFB). This filter bank de composes the noisy image into subbands of different frequency and orientation. Owing to its multiscale, multidirectional and lack of shift variance capability, it provides an efficient representation of intrinsic geometric structures of an image. By the fusion of the bilateral filter in SPNSDFB domain and optimum selection of parameters of the adaptive bilateral filter, the proposed algorithm minimizes mean square error (MSE) between the original image and the denoised image even at high noise densities. Experimental results show that the algorithm is found to be competitive in denoising performance due to its better edge preservation and improves peak signal-to-noise-ratio and image visual impression.