Image denoising by directional complex diffusion processes based on double-density dual-tree DWT

Cheng Lin Mao, Hong Shen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Wavelet diffusion is a new popular image denoising method by combining the wavelet shrinkage and nonlinear diffusion. In this paper we extend the wavelet diffusion from real axis to complex domain and improve its performance. The double-density dual-tree discrete wavelet transform (DDDT-DWT) is a complex and directional transform. We propose an efficient image denoising algorithm by combining DDDT-DWT and the directional complex nonlinear diffusion process. We compute complex diffusion function based on directional complex wavelets. Experimental results show our algorithm is efficient.

Original languageEnglish
Title of host publicationProceedings - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
Pages698-702
Number of pages5
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 3rd International Congress on Image and Signal Processing, CISP 2010 - Yantai, China
Duration: 16 Oct 201018 Oct 2010

Publication series

NameProceedings - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
Volume2

Conference

Conference2010 3rd International Congress on Image and Signal Processing, CISP 2010
Country/TerritoryChina
CityYantai
Period16/10/1018/10/10

Keywords

  • Complex wavelet transform
  • DDDT-DWT
  • Directional complex nonlinear diffusion
  • Image denoising
  • Wavelet diffusion
  • Wavelet orientation

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