Wavelet-based color image denoising

B. A. Thomas; J. J. Rodríguez

doi:10.1109/icip.2000.899831

Wavelet-based color image denoising

B. A. Thomas, J. J. Rodríguez

Research output: Contribution to conference › Paper › peer-review

9 Scopus citations

Abstract

This paper introduces a new approach to color image denoising that exploits scale-specific, cross-component edge correspondences inherent in color image data. Processing takes place in the Wavelet Transform Modulus Maxima domain wherein image data is represented in terms of a set of multiscale edgemaps. Denoising is accomplished by building noise suppression masks which discriminate noise related edges from physically significant edges. Experimental results show that the new approach outperforms wavelet thresholding in images containing irregular textures.

Original language	English (US)
Pages	804-807
Number of pages	4
DOIs	https://doi.org/10.1109/icip.2000.899831
State	Published - 2000
Event	International Conference on Image Processing (ICIP 2000) - Vancouver, BC, Canada Duration: Sep 10 2000 → Sep 13 2000

Other

Other	International Conference on Image Processing (ICIP 2000)
Country/Territory	Canada
City	Vancouver, BC
Period	9/10/00 → 9/13/00

ASJC Scopus subject areas

Hardware and Architecture
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

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10.1109/icip.2000.899831

Cite this

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title = "Wavelet-based color image denoising",

abstract = "This paper introduces a new approach to color image denoising that exploits scale-specific, cross-component edge correspondences inherent in color image data. Processing takes place in the Wavelet Transform Modulus Maxima domain wherein image data is represented in terms of a set of multiscale edgemaps. Denoising is accomplished by building noise suppression masks which discriminate noise related edges from physically significant edges. Experimental results show that the new approach outperforms wavelet thresholding in images containing irregular textures.",

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year = "2000",

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AB - This paper introduces a new approach to color image denoising that exploits scale-specific, cross-component edge correspondences inherent in color image data. Processing takes place in the Wavelet Transform Modulus Maxima domain wherein image data is represented in terms of a set of multiscale edgemaps. Denoising is accomplished by building noise suppression masks which discriminate noise related edges from physically significant edges. Experimental results show that the new approach outperforms wavelet thresholding in images containing irregular textures.

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T2 - International Conference on Image Processing (ICIP 2000)

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Wavelet-based color image denoising

Abstract

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