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.
[1] CHEN G Y, XIE W F, ZHAO Y J. Wavelet-Based Denoising: A Brief Review // Proc of the 4th International Conference on Intelligent Control and Information Processing. Beijing, China, 2013: 570-574. [2] DONOHO D L. De-noising by Soft-Thresholding. IEEE Trans on Information Theory, 1995, 41(3): 613-627. [3] 李 智,张根耀,王 蓓.基于一种新的阈值函数的小波图像去噪.计算机技术与发展, 2014, 24(11): 100-106. (LI Z, ZHANG G Y, WANG B. Wavelet Image Denoising Based on a New Threshold Function. Computer Technology and Development, 2014, 24(11): 100-106.) [4] 李秋妮,晁爱农,史德琴,等.一种新的小波半软阈值图像去噪方法.计算机工程与科学, 2014, 36(8): 1566-1570. (LI Q N, CHAO A N, SHI D Q, et al. A Novel Image Denoising Method of Wavelet Semi-soft Threshold. Computer Engineering & Science, 2014, 36(8): 1566-1570.) [5] CHANG S G, YU B, VETTERLI M. Adaptive Wavelet Thresholding for Image Denoising and Compression. IEEE Trans on Image Processing, 2000, 9(9): 1532-1546. [6] CHANG S G, YU B, VETTERLI M. Spatially Adaptive Wavelet Thresholding with Context Modeling for Image Denoising. IEEE Trans on Image Processing, 2000, 9(9): 1522-1531. [7] 侯建华,熊承义,田晓梅.广义高斯分布及其在图像去噪中的应用.中南民族大学学报(自然科学版), 2005, 24(3): 44-47. (HOU J H, XIONG C Y, TIAN X M. Generalized Gaussian Distribution and Its Application in Image Denoising. Journal of South-Central University for Nationalities(Natural Sciences), 2005, 24(3): 44-47.) [8] MATSUYAMA E, TSAI D Y, LEE Y, et al. Comparison of a Discrete Wavelet Transform Method and a Modified Undecimated Discrete Wavelet Transform Method for Denoising of Mammograms // Proc of the 35th Annual International Conference on Engineering in Medicine and Biology Society. Osaka, Japan, 2013: 3403-3406. [9] STARCK J L, FADILI J, MURTAGH F. The Undecimated Wavelet Decomposition and Its Reconstruction. IEEE Trans on Image Processing, 2007, 16(2): 297-309. [10] WANG X Y, YANG H Y, FU Z K. A New Wavelet-Based Image Denoising Using Undecimated Discrete Wavelet Transform and Least Square Support Vector Machine. Expert Systems with Applications, 2010, 37(10): 7040-7049. [11] MENCATTINI A, RABOTTINO G, SALMERI M, et al. Denoising and Enhancement of Mammographic Images under the Assumption of Heteroscedastic Additive Noise by an Optimal Subband Thre-sholding. International Journal of Wavelets, Multiresolution an Information Processing, 2010, 8(5): 713-741. [12] SIMONCELLI E P. Bayesian Denoising of Visual Images in the Wavelet Domain // MLLER P, VIDAKOVIC B, eds. Bayesian Inference and in Wavelet Based Models. New York, USA: Springer-Verlag, 1999. [13] PORTILLA J, SIMONCELLI E P. A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients. International Journal of Computer Vision, 2000, 40(1): 49-70. [14] DONOHO D L, JOHNSTONE J M. Ideal Spatial Adaptation via Wavelet Shrinkage. Biometrika, 1994, 81(3): 425-455. [15] 李军侠,水鹏朗.基于广义高斯最大似然估计的小波域类LMMSE 滤波算法.电子与信息学报, 2007, 29(12): 2853- 2857. (LI J X, SHUI P L. Wavelet Domain LMMSE-Like Denoising Algorithm Based on GGD ML Estimation. Journal of Electronics & Information Technology, 2007, 29(12): 2853-2857.)