Abstract
The NeighShrink and ModiNeighShrink areefficient image denoising algorithms that are based on universal threshold and discrete wavelet transform. The improved image denoising method based on wavelet thresholding (IIDMWT) method gives better results than the NeighShrink and ModiNeighShrink by using the modified universal threshold. These methods kill too many wavelet coefficients; some of them may contain useful image information. Thus, we may not get good quality of image using these methods. In this paper, we extend the idea of Cai and Silverman for developing a new image denoising method and determine the coefficients of neighboring window for every subband. The experimental results show that in most of the cases, our proposed method performs better than the NeighShrink, ModiNeighShrink, and IIDMWT in terms of peak signal- to-noise ratio and structural similarity index measure.
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