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Shift-invariant Non-aliasing Multiscale Geometric Analysis Filter Banks: Theory, Design and Application

Published: 10 July 2014 Publication History

Abstract

Although nonsubsampled Contourlet transform (NSCT) has resolved the Shift-invariant limitation of Contourlet transform(CT), the filter width of nonsubsampled pyramidal decomposition in NSCT increases too fast because of binary zero insertion à trous algorithm that can cause border distortion and energy aliasing in image transform domain. This aliasing can be further amplified in the subsequent nonsubsampled directional filter, so there are obvious aliasings and amazing redundancy in SNCT. In this paper, a new approximate shift-invariant non-aliasing pyramidal decomposition was proposed to replace the à trous algorithm nonsubsampled pyramidal de composition in the NSCT, So a new approximate shift-invariant non-aliasing nonsubsampled Contourlet transform(NANSCT) was constructed. Compared to the NSCT, the basis image of the NANSCT has better spatial domain regularity, frequency domain localization and decreased redundancy. The experimental results show that whether PSNR index or in visual effect, the proposed scheme outperforms the traditional CT hard threshold denoising, Contourlet domain HMT denoising and the NSCT hard threshold denoising, and can achieve an excellent balance between suppressing noise effectively and preserving as many image details and edges as possible.

References

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cover image ACM Other conferences
ICIMCS '14: Proceedings of International Conference on Internet Multimedia Computing and Service
July 2014
430 pages
ISBN:9781450328104
DOI:10.1145/2632856
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

  • NSF of China: National Natural Science Foundation of China
  • Beijing ACM SIGMM Chapter

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 July 2014

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Author Tags

  1. Hard threshold
  2. Image denoising
  3. NSCT
  4. Non-aliasing
  5. Shift-invariant

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