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Wavelet Video Denoising with Regularized Multiresolution Motion Estimation

Abstract

This paper develops a new approach to video denoising, in which motion estimation/compensation, temporal filtering, and spatial smoothing are all undertaken in the wavelet domain. The key to making this possible is the use of a shift-invariant, overcomplete wavelet transform, which allows motion between image frames to be manifested as an equivalent motion of coefficients in the wavelet domain. Our focus is on minimizing spatial blurring, restricting to temporal filtering when motion estimates are reliable, and spatially shrinking only insignificant coefficients when the motion is unreliable. Tests on standard video sequences show that our results yield comparable PSNR to the state of the art in the literature, but with considerably improved preservation of fine spatial details.

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Correspondence to Fu Jin.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Jin, F., Fieguth, P. & Winger, L. Wavelet Video Denoising with Regularized Multiresolution Motion Estimation. EURASIP J. Adv. Signal Process. 2006, 072705 (2006). https://doi.org/10.1155/ASP/2006/72705

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  • DOI: https://doi.org/10.1155/ASP/2006/72705

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