Image noise reduction based on block matching in wavelet frame domain

This paper describes the shear wavelet frame transform (SWFT) with two sets of block matching for the application of image denoising. Using the SWFT, we can analyze anisotropic features, such as edges in images. To assign the directionality we use a shear matrix for the continuous wavelet transform. Block matching with 3-D collaborative filtering has been incorporated for hard thresholding of reference block. We deploy two sets of the search neighborhood blocks to avoid the artifacts while removing heavy noise. The proposed algorithm is evaluated on standard benchmark images and outperforms the recent state-of-the-art methods in terms of peak signal to noise ratio.