针对Contourlet多尺度阈值去噪算法中阈值的选取忽略了方向信息影响的问题,提出一种基于邻域窗能量平均的自适应阈值去噪算法.根据Contourlet系数能量分布特点,将系数划分到三个不同的区域,对三个区域的阈值采用不同的因子进行调整,从而得到更好的去噪效果.实验结果表明,与小波阈值去噪、Contourlet阈值去噪以及Contourlet多尺度阈值去噪相比,该算法在峰值信噪比以及视觉效果上都有明显的提高,且能够有效地保留图像边缘细节信息.%Concerning the defects of multi-scale threshold on directional information using Contourlet transform, a new adaptive threshold denoising algorithm was proposed, which was based on average energy of neighboring window. According to the distribution of the coefficients energy, the Contourlet coefficients were divided up into three areas. The noise could be reduced obviously by adjusting the threshold of these areas with different variables. In contrast with the wavelet threshold, Contourlet threshold and multi-scale threshold using Contourlet transform, the experimental results demonstrate that the new algorithm has superiority in Peak Signal-to-Noise Ratio (PSNR) and visual effect, which can maintain effectively the edges of the image.
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