Bivariate shrinkage using undecimated dual-tree complex wavelet transform for image denoising

被引:1
|
作者
Yang, Peng [1 ]
Yang, Guowei [1 ]
机构
[1] Nanchang Hangkong Univ, Sch Informat Engn, Nanchang, Jiangxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Image denoising; undecimated dual-tree complex wavelet transform; bivariate shrinkage; INTERSCALE; SIGNAL; SCALE;
D O I
10.3233/IFS-152037
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we present a bivariate shrinkage method for denoising of images corrupted with additive white Gaussian noise. The proposed method first employs undecimated dual-tree complex wavelet transform on noisy image, which can keep a direct one-to-one relationship between the co-located complex wavelet coefficients at all scales. After that, it estimates the wavelet coefficients by taking into account the parent-child dependency under the non-Gaussian bivariate model, and completes the denoising procedure. Experimental results on test images show that our method can not only eliminate different levels of noise but also obtain fine structures preservation.
引用
收藏
页码:3111 / 3122
页数:12
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