Image denoising by adaptive directional lifting-based discrete wavelet transform and quantization

Naoki Furuhashi, Azusa Oota, Taichi Yoshida, Masaaki Ikehara

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

Abstract

In this paper, we propose the non-local method for image de-noising via adaptive directional lifting-based discrete wavelet transform (ADL) and quantization. The non-local methods such as non-local means are interested in image denoising based on the self-similarity. They search similar blocks and estimate the original value. The proposed method doesn't search but generates new similar blocks by ADL with multiple directions, and quantization to denoise. It improves the denoising quality and reduces the computational complexity. Finally, we compare the proposed and conventional method, and show an advantage of them.

Original languageEnglish
Title of host publicationConference Record of the 47th Asilomar Conference on Signals, Systems and Computers
PublisherIEEE Computer Society
Pages1995-1999
Number of pages5
ISBN (Print)9781479923908
DOIs
Publication statusPublished - 2013 Jan 1
Event2013 47th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: 2013 Nov 32013 Nov 6

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other2013 47th Asilomar Conference on Signals, Systems and Computers
CountryUnited States
CityPacific Grove, CA
Period13/11/313/11/6

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Keywords

  • Image denoising
  • adaptive directional transform
  • lifting structure of discrete wavelet transform

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Cite this

Furuhashi, N., Oota, A., Yoshida, T., & Ikehara, M. (2013). Image denoising by adaptive directional lifting-based discrete wavelet transform and quantization. In Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers (pp. 1995-1999). [6810655] (Conference Record - Asilomar Conference on Signals, Systems and Computers). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2013.6810655