Imaging Components, Systems, and Processing

Adaptive denoising for simplified signal-dependent random noise model in optoelectronic detector

[+] Author Affiliations
Yu Zhang, Guangyi Wang

Hangzhou Dianzi University, Key Laboratory for RF Circuits and Systems, Ministry of Education, Hangzhou, China

Hangzhou Dianzi University, Institute of Electronic and Information, Hangzhou, China

Weiping Wang

Hangzhou Dianzi University, Institute of Electronic and Information, Hangzhou, China

Jiangtao Xu

Tianjin University, School of Electronic and Information Engineering, Tianjin, China

Opt. Eng. 56(5), 053105 (May 13, 2017). doi:10.1117/1.OE.56.5.053105
History: Received January 9, 2017; Accepted April 27, 2017
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Abstract.  Existing denoising algorithms based on a simplified signal-dependent noise model are valid under the assumption of the predefined parameters. Consequently, these methods fail if the predefined conditions are not satisfied. An adaptive method for eliminating random noise from the simplified signal-dependent noise model is presented in this paper. A linear mapping function between multiplicative noise and noiseless image data is established using the Maclaurin formula. Through demonstrations of the cross-correlation between random variables and independent random variable functions, the mapping function between the variances of multiplicative noise and noiseless image data is acquired. Accordingly, the adaptive denoising model of simplified signal-dependent noise in the wavelet domain is built. The experimental results confirm that the proposed method outperforms conventional ones.

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© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

Yu Zhang ; Weiping Wang ; Guangyi Wang and Jiangtao Xu
"Adaptive denoising for simplified signal-dependent random noise model in optoelectronic detector", Opt. Eng. 56(5), 053105 (May 13, 2017). ; http://dx.doi.org/10.1117/1.OE.56.5.053105


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