Immune-clonal-selection-based nonsubsampled contourlet domain image denoising method

基于免疫克隆选择的非下采样轮廓波域图像去噪方法

Abstract

本发明涉及图像处理技术在图像去噪领域中的应用,尤其是基于免疫克隆选择的非下采样轮廓波域图像去噪方法,其特点是,包括如下步骤:(1)输入含噪图像X,并对其进行L层非下采样轮廓波分解,得到不同尺度上的高频方向子带{Dl,i(m,n),0≤l≤L-1,1≤i≤kl}和低频子带AL(m,n),kl为尺度2-l上高频方向子带的数目,Dl,i(m,n)表示含噪图像在尺度2-l上的第i个高频方向子带上,处于(m,n)像素位置的系数,L为3~5;(2)通过免疫克隆选择法,搜索不同尺度各个高频方向子带的最优去噪阈值{Tl,i,0≤l≤L-1,1≤i≤kl};与现有技术相比,无需知道图像噪声的确切特性,由于采用免疫克隆选择法对去噪阈值进行搜索,可以搜索到更佳的去噪阈值;由于采用非下采样轮廓波变换,可以有效避免因变换工具缺乏平移不变性而产生的抖动失真。
The invention relates to the application of an image processing technology in the field of image denoising, in particular to an immune-clonal-selection-based nonsubsampled contourlet domain image denoising method, which is characterized by comprising the following steps of: (1) inputting a noisy image X, and performing L-layer nonsubsampled contourlet domain decomposition on the noisy image X to obtain high-frequency directional sub-bands {Dl,i(m,n),} in different scales and a low-frequency sub-band AL(m,n), wherein l is more than or equal to 1 and less than or equal to L-1, i is more than or equal to 1 and less than or equal to kl, kl is the number of the high-frequency direction sub-bands in the scale of 2-l, Dl,i(m,n) represents a coefficient at a pixel position (m,n) on the ith high-frequency directional sub-band of the noisy image in the scale of 2-l, and L is 3 to 5; and (2) searching for an optimal denoising threshold value {Tl,i} of each high-frequency directional sub-band in the different scales by using an immune clonal selection method, wherein l is more than or equal to 0 and less than or equal to L-1, and i is more than or equal to 1 and less than or equal to kl. Compared with the prior art, the invention searches for denoising threshold values by adopting the immune clonal selection method without knowing the exact characteristics of image noise, so that better denoising threshold values can be found; and due to the adoption of nonsubsampled contourlet transform, jitter distortion caused by the deficiency of translation invariance of a transform tool can be effectively avoided.

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