Ms. Beibei Wang Profile

Beibei Wang

at Polytechnic Institute of New York Univ

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Proceedings Article | 19 January 2006 Paper

A new structure of 3D dual-tree discrete wavelet transforms and applications to video denoising and coding

Fei Shi, Beibei Wang, Ivan Selesnick, Yao Wang

Proceedings Volume 6077, 60771C (2006) https://doi.org/10.1117/12.645922

KEYWORDS: Video, Wavelets, Discrete wavelet transforms, Video coding, Denoising, Wavelet transforms, 3D image processing, 3D imaging standards, Visualization, 3D video compression

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This paper introduces an anisotropic decomposition structure of a recently introduced 3-D dual-tree discrete wavelet transform (DDWT), and explores the applications for video denoising and coding. The 3-D DDWT is an attractive video representation because it isolates motion along different directions in separate subbands, and thus leads to sparse video decompositions. Our previous investigation shows that the 3-D DDWT, compared to the standard discrete wavelet transform (DWT), complies better with the statistical models based on sparse presumptions, and gives better visual and numerical results when used for statistical denoising algorithms. Our research on video compression also shows that even with 4:1 redundancy, the 3-D DDWT needs fewer coefficients to achieve the same coding quality (in PSNR) by applying the iterative projection-based noise shaping scheme proposed by Kingsbury. The proposed anisotropic DDWT extends the superiority of isotropic DDWT with more directional subbands without adding to the redundancy. Unlike the original 3-D DDWT which applies dyadic decomposition along all three directions and produces isotropic frequency spacing, it has a non-uniform tiling of the frequency space. By applying this structure, we can improve the denoising results, and the number of significant coefficients can be reduced further, which is beneficial for video coding.

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