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Algorithm. We develop a two-step algorithm.
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The hard-thresholding approach delivers an initial estimate.
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The Wiener filtering approach to produces the final estimate.
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Transform choice. In our experiments, we used 2D DFT and 3D DFT for and , respectively.
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Complexity reduction. Efficient trade-off between denoising performance and computational complexity. Constarints:
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Restrict the maximum number of matched blocks.
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Perform block-matching within a local neighborhood of fixed size, rather than doing it in the whole image.
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Use a step greater than unity to slide to every next reference block.
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Running time. The execution time of the algorithm that we used for the reported results is about 8 seconds for an image of size 256x256, on a 3 GHz Pentium workstation.
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