Morphological wavelet transform with adaptive dyadic structures

Zhen James Xiang, Peter J. Ramadge

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

2 Scopus citations

Abstract

We propose a two component method for denoising multidimensional signals, e.g. images. The first component uses a dynamic programing algorithm of complexity O(N logN) to find an optimal dyadic tree representation of a given multidimensional signal of N samples. The second component takes a signal with given dyadic tree representation and formulates the denoising problem for this signal as a Second Order Cone Program of size O(N). To solve the overall denoising problem, we apply these two algorithms iteratively to search for a jointly optimal denoised signal and dyadic tree representation. Experiments on images confirm that the approach yields denoised signals with improved PSNR and edge preservation.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages1677-1680
Number of pages4
DOIs
StatePublished - 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: Sep 26 2010Sep 29 2010

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country/TerritoryHong Kong
CityHong Kong
Period9/26/109/29/10

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition

Keywords

  • Dynamic programming
  • Image enhancement
  • Morphological operations
  • Multidimensional signal processing
  • Wavelet transforms

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