Hybrid image denoising method based on non-subsampled contourlet transform and bandelet transform

被引:26
|
作者
Wang, Xiaokai [1 ]
Chen, Wenchao [2 ]
Gao, Jinghuai [1 ,2 ]
Wang, Chao [3 ]
机构
[1] Xi An Jiao Tong Univ, Dept Computat Geosci, 28 Xianning West Rd, Xian, Shaanxi, Peoples R China
[2] Xi An Jiao Tong Univ, Dept Commun & Informat Engn, 28 Xianning West Rd, Xian, Shaanxi, Peoples R China
[3] Chinese Acad Sci, Inst Geochem, SKLODG, 99 Lincheng West Rd, Guiyang, Guizhou, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
image denoising; wavelet transforms; image colour analysis; AWGN; visual quality performance; peak signal-to-noise ratio; Poisson noise; Gaussian white noise; greyscale image; colour benchmark image; second generation bandelet transform; nonsubsampled contourlet transform; hybrid image denoising method; REPRESENTATION;
D O I
10.1049/iet-ipr.2017.0647
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The second generation bandelet transform uses the two-dimensional (2D) separable wavelet transform to improve its image denoising and compression performance. However, the 2D separable wavelet transform is not a shift-invariant transform and therefore cannot capture geometric information well. The authors propose a hybrid image denoising method in which the 2D separable wavelet transform in the second generation bandelet transform is replaced with the non-subsampled contourlet transform. The results of the application of the proposed method to several greyscale and colour benchmark images contaminated with various levels of Gaussian white noise and Poisson noise indicate that the proposed method has good peak signal-to-noise ratio and visual quality performance.
引用
收藏
页码:778 / 784
页数:7
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