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Patch-Based Video Denoising With Optical Flow Estimation
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DOI：10.1109/TIP.2016.2551639.png)
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Abstract
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A novel image sequence denoising algorithm is presented. The proposed approach takes advantage of the self-similarity and redundancy of adjacent frames. The algorithm is inspired by fusion algorithms, and as the number of frames increases, it tends to a pure temporal average. The use of motion compensation by regularized optical flow methods permits robust patch comparison in a spatiotemporal volume. The use of principal component analysis ensures the correct preservation of fine texture and details. An extensive comparison with the state-of-the-art methods illustrates the superior performance of the proposed approach, with improved texture and detail reconstruction.
Keywords:
Video denoising
patch processing
optical flow
non-local means
motion compensation
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