Performance Evaluation of Iterative Denoising Algorithm Based on Variance Stabilizing Transform and Wavelet Thresholding

The restoration of images degraded by noise is one of the most important tasks in image processing. This paper deals with the recovery of an image from a Poisson noisy observations. More precisely, we have combined an iterative denoising algorithm based on Variance Stabilizing Transform (VST) with the conventional Wavelet Thresholding technique. At each iteration, a combination of the Poisson observations with the denoised estimate from the previous iteration is treated as scaled Poisson data and riltered through a VST scheme and wavelet thresholding. Experimental results show the effectiveness of the proposed method for denoising images corrupted by Poisson noise. Performance assessment is provided.