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Patch-based multiple view image denoising with occlusion handling

A novel patch-based multi-view image denoising algorithm is proposed. This method leverages the 3D focus image stacks structure to exploit self-similarity and image redundancy inherent in multiple view images. Then a depth-guided adaptive window and dynamic view selection criterion is developed to aid proper selection of most consistent patches for the multi-view image denoising. Extensive experiments have been performed. Comparing the outcomes against those of state of the art image denoising algorithms, our proposed algorithm demonstrates significant performance advantage.