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

Fei Shi, Beibei Wang, Ivan Selesnick, Yao Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Volume6077
DOIs
StatePublished - 2006
EventVisual Communications and Image Processing 2006 - San Jose, CA, United States
Duration: Jan 17 2006Jan 19 2006

Other

OtherVisual Communications and Image Processing 2006
CountryUnited States
CitySan Jose, CA
Period1/17/061/19/06

Fingerprint

Discrete wavelet transforms
wavelet analysis
coding
redundancy
Decomposition
decomposition
Redundancy
video compression
dyadics
coefficients
Image compression
Image coding
projection
spacing

Keywords

  • 3-D transform
  • Anisotropic decomposition
  • Dual-tree wavelet transform
  • Video coding
  • Video denoising

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Shi, F., Wang, B., Selesnick, I., & Wang, Y. (2006). A new structure of 3-D dual-tree discrete wavelet transform and applications to video denoising and coding. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 6077). [60771C] https://doi.org/10.1117/12.645922

A new structure of 3-D dual-tree discrete wavelet transform and applications to video denoising and coding. / Shi, Fei; Wang, Beibei; Selesnick, Ivan; Wang, Yao.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 6077 2006. 60771C.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shi, F, Wang, B, Selesnick, I & Wang, Y 2006, A new structure of 3-D dual-tree discrete wavelet transform and applications to video denoising and coding. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 6077, 60771C, Visual Communications and Image Processing 2006, San Jose, CA, United States, 1/17/06. https://doi.org/10.1117/12.645922
Shi F, Wang B, Selesnick I, Wang Y. A new structure of 3-D dual-tree discrete wavelet transform and applications to video denoising and coding. In Proceedings of SPIE - The International Society for Optical Engineering. Vol. 6077. 2006. 60771C https://doi.org/10.1117/12.645922
Shi, Fei ; Wang, Beibei ; Selesnick, Ivan ; Wang, Yao. / A new structure of 3-D dual-tree discrete wavelet transform and applications to video denoising and coding. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 6077 2006.
@inproceedings{3ba5a401ce4e4385868536b666648230,
title = "A new structure of 3-D dual-tree discrete wavelet transform and applications to video denoising and coding",
abstract = "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.",
keywords = "3-D transform, Anisotropic decomposition, Dual-tree wavelet transform, Video coding, Video denoising",
author = "Fei Shi and Beibei Wang and Ivan Selesnick and Yao Wang",
year = "2006",
doi = "10.1117/12.645922",
language = "English (US)",
isbn = "0819461172",
volume = "6077",
booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",

}

TY - GEN

T1 - A new structure of 3-D dual-tree discrete wavelet transform and applications to video denoising and coding

AU - Shi, Fei

AU - Wang, Beibei

AU - Selesnick, Ivan

AU - Wang, Yao

PY - 2006

Y1 - 2006

N2 - 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.

AB - 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.

KW - 3-D transform

KW - Anisotropic decomposition

KW - Dual-tree wavelet transform

KW - Video coding

KW - Video denoising

UR - http://www.scopus.com/inward/record.url?scp=33645977189&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33645977189&partnerID=8YFLogxK

U2 - 10.1117/12.645922

DO - 10.1117/12.645922

M3 - Conference contribution

SN - 0819461172

SN - 9780819461179

VL - 6077

BT - Proceedings of SPIE - The International Society for Optical Engineering

ER -