Selective image smoothing via dyadic wavelet-based conduction equation

Chwen Jye Sze*, Hong Yaun Mark Liao, Shih-Kun Huang, Chun Shien Lu

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

Abstract

In this paper, we propose a new dyadic wavelet-based conduction approach for selective image smoothing. In our approach, a nonlinear conductivity function is considered in the wavelet-based function decomposition and reconstruction process. Since the proposed approach does not require to solve a PDE, it is therefore more efficient and accurate than the conventional nonlinear diffusion/conduction-based methods. Experimental results using both 1-D synthetic data and a real image demonstrated that the proposed method can efficiently remove noises and preserve real data.

Original languageEnglish
Pages400-408
Number of pages9
DOIs
StatePublished - 1 Dec 1999
EventProceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99) - Madison, WI, USA
Duration: 23 Aug 199925 Aug 1999

Conference

ConferenceProceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99)
CityMadison, WI, USA
Period23/08/9925/08/99

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