[1]方洁.基于非抽样Contourlet变换的最佳软阈值图像去噪[J].计算机技术与发展,2011,(02):102-104.
　FANG Jie.Image Denoising Based on Nonsubsampled Contourlet Transform and Best Soft Threshold[J].,2011,(02):102-104.
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基于非抽样Contourlet变换的最佳软阈值图像去噪()

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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

Title:: Image Denoising Based on Nonsubsampled Contourlet Transform and Best Soft Threshold

Keywords:: nonsubsampled Contourlet transform; best soft threshold; image denoising

摘要:: 研究了小波变换在图像处理中的缺陷,以及Contourlet变换在图像处理中产生伪Gibbs失真的原因。为了在多尺度分析框架下改进图像去噪的效果,提出了一种基于非抽样Contourlet变换的图像去噪算法,利用非抽样Contourlet变换的多尺度多方向性以及平移不变性,对加噪图像进行非抽样Contourlet变换得到变换系数,然后对变换系数采用分层最佳软阈值处理,最后将其反变换得到去噪后的图像。实验结果表明,与Contourlet变换图像去噪算法相比,该算法可以达到更好的效果

Abstract:: Disadvantages of wavelet and pseudo-Gibbbs phenomenon produced by the Contourlet transform in image processing are studied.For improving the effect of image denoising in multi-scale,an algorithm for image denoising based on the nonsubsampled Contourlet transform and best soft threshold is proposed.The coefficients are obtained by image decomposition using the nonsubsampled Contourlet transform,which is of multi-scale and multi-direction and shift-invariant.The coefficients are disposed with an algorithm of the level best soft threshold.Denoised image is obtained by the reconstruction of the coefficients.Compared with other algorithms,this algorithm can get better effect

[1]冯太平闫仁武.基于非抽样Contourlet变换的多聚焦图像融合算法[J].计算机技术与发展,2012,(02):57.
　FENG Tai-ping,YAN Ren-wu.Multi-Focus Image Fusion Algorithm Based on Nonsubsampled Contourlet Transform[J].,2012,(02):57.

更新日期/Last Update: 1900-01-01