Hybrid noise removal in color images using wavelet shrinkage approaches of PURE-LET and Neighshrink SURE

Abstract

Image denoising is an indispensable task where the complication of noise is prevalent and the contrast of low cost surveillance camera is more over low due to various image acquisitions. For the past two decades, denoising is performed by the Wavelet transform. The proposed work presents a novel approach of denoising by Poisson Unbiased Risk Estimate- Linear Expansion of Threshold (PURE-LET) and Neighshrink-Stein’s Unbiased Risk Estimate (SURE) for mixed Poisson and Gaussian noise. Finally the potential of the proposed approach through extensive comparisons with state-of-the-art techniques that are specifically tailored to the estimation of Poisson intensities are demonstrated. Neigh Shrink is an efficient image denoising algorithm based on the Discrete Wavelet Transform (DWT).The observed results reported here are in encouraging agreement.