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采用小波系数极大值跟踪法去除图像噪声,建立了尺度间小波系数极大值跟踪矩阵,标识出小波系数极大值的信噪属性,剔除了噪声部分对应小波系数极大值,从而抑制了噪声污染。与常规去噪方法相比,该方法不仅有效地去除了噪声,同时保持了图像边沿细节,具有良好的消除噪声效果。
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小波变换 极大值 Lipschitz 指数 奇异性In this paper, we propose a new denoising method, which distinguishes the coefficients' extremums belonging either or to image to noise by the tracking matrixes of the extremums in wavelet domain. The coefficients' extremums that belong to image have transmission property from coarse to fine scale, but the coefficients' extremums that belong to noise do not have. We evaluate the tracking marixes of the extremums different number base on the transmission property of each extremums from coarse to fine scale. The tracking matrixes of the extremums express the different transmission property. By the tracking matrixes of the extremums, we differentiate the wavelet coefficients' extremums and then remove the coefficients' extremums belonging to noise. Experimental results show that the denoising proposed in this paper is effective both in reserving the edge and in removing noise.