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We propose a new multichannel image denoising algorithm. To exploit important inter-channel dependencies, we first use dynamic programming to learn an explicit dyadic tree representation of the common structure of the channels. Based on this dyadic tree, optimal Haar wavelet thresholding is then applied to denoise the image. In addition to the original channels, the algorithm can employ multiple derived...
During the image acquisition and communication the image is corrupted by noise. This is a classical problem in the field of signal or image processing. In this paper local statistical function is used to find the percentage of noise affected in the noise image. Dynamic denoising algorithm is used simultaneously as a tool for enhancing and tracking image pixel. The pixels are chosen based on the prediction...
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