Undecimated Wavelet Bayesian Image Denoising Method with Its Threshold Determined by Curve Fitting
WANG Xianghai1,2, LIU Xiaoqian2, ZHANG Aidi2, FU Bo1
1.School of Computer and Information Technology, Liaoning Normal University, Dalian 116029 2.School of Mathematics, Liaoning Normal University, Dalian 116029
Abstract The undecimated discrete wavelet transform(UDWT) possesses local features of time and frequency and shift-invariant property of reducing the pseudo-Gibbs phenomenon. In this paper, after the UDWT coefficients are analyzed, the conclusion that the UDWT coefficients have strong non-Gaussian statistical property is obtained. Grounded on the property, a generalized guassian distribution model is established. To improve the precision of standard deviation estimation of the noise image, a method of curve fitting is proposed based on the standard deviation of image, and thus the denoising threshold is determined. Based on the shift-invariant property of UDWT, the proposed method effectively reduces the pseudo-Gibbs phenomenon of the traditional wavelet denoising method. Meanwhile, the denoising effect is enhanced by improving the accuracy of denoising threshold. A large number of simulation experiments verifies the effectiveness of the proposed method.
Fund:Supported by National Natural Science Foundation of China (No.41271422, 61402214), the Specialized Research Fund for the Doctoral Program of Higher Education (No.20132136110002), Doctoral Research Foundation of Liaoning Province(No.20121076), Scientific Research Program of Education Department of Liaoning Province (No.L2014423)
About author:: (WANG Xianghai, born in 1965, Ph. D. , professor. His research interests include computer graphics and multimedia in formation processing. )(LIU Xiaoqian, born in 1988, master student. Her research interests include multiscale analysis and image processing. )(ZHANG Aidi, born in 1991, master student. Her research in terests include image processing based on partial differential equation. )(FU Bo(Corresponding author), born in 1983, Ph. D. , lectu rer. His research interests include visual information proce ssing. )
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2016, Vol. 29 
