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In this work, we propose a sparse Bayesian dictionary learning framework with structure prior which connects nonlocal self-similarity and sparse Bayesian dictionary learning. A Gamma-Gaussian prior is used to impose sparsity and a nonlocal beta process is utilized to introduce the nonlocal self-similarity as a structure prior for image denoising. Unlike most of the existing image denoising methods,...
In this paper, we present a method using pixel-level information, local region-level information and global-level information to remove shadow. At the pixel-level, we employ GMM to model the behavior of cast shadow for every pixel in the HSV color space, as it can deal with complex illumination conditions. However, unlike the GMM for background which can obtain sample every frame, this model for shadow...
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