Color image denoising with wavelet thresholding based on human visual system model

Recent research in transform-based image denoising has focused on the wavelet transform due to its superior performance over other transform. Performance is often measured solely in terms of PSNR and denoising algorithms are optimized for this quantitative metric. The performance in terms of subject...

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Bibliographic Details
Published in:Signal processing. Image communication 2005-02, Vol.20 (2), p.115-127
Main Authors: Huang, Kai-qi, Wu, Zhen-yang, Fung, George S.K., Chan, Francis H.Y.
Format: Article
Language:English
Subjects:
Applied sciences
Color image denoising
Contrast sensitivity function
Exact sciences and technology
Human visual system model
Image processing
Information, signal and communications theory
Masking
Signal processing
Telecommunications and information theory
Wavelet thresholding
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Summary:Recent research in transform-based image denoising has focused on the wavelet transform due to its superior performance over other transform. Performance is often measured solely in terms of PSNR and denoising algorithms are optimized for this quantitative metric. The performance in terms of subjective quality is typically not evaluated. Moreover, human visual system (HVS) is often not incorporated into denoising algorithm. This paper presents a new approach to color image denoising taking into consideration HVS model. The denoising process takes place in the wavelet transform domain. A Contrast Sensitivity Function (CSF) implementation is employed in the subband of wavelet domain based on an invariant single factor weighting and noise masking is adopted in succession. Significant improvement is reported in the experimental results in terms of perceptual error metrics and visual effect.
ISSN:0923-5965
1879-2677
DOI:10.1016/j.image.2004.08.002