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提出了一种针对脉冲噪声的参数自调整图像滤波算法,该算法将基于相关性双阈值噪声检测的非线性滤波算法和基于最小相邻图像均方差的参数自调整算法有机地结合在一起,不需要了解原图像和噪声污染的信息,可以直接通过参数自调整算法对非线性滤波算法中的参数自动地进行优化选择。基于Matlab的仿真试验表明,该算法对脉冲噪声有非常好的抑制能力,并且能够很好地保护图像的细节信息,对各类不同密度的脉冲噪声图像进行滤波均能得到令人满意的结果。
A parameter self-adjusting image filtering algorithm for impulsive noise is proposed. The algorithm combines the non-linear filtering algorithm based on correlated double threshold noise detection and the parameter self-adjusting algorithm based on the mean square error of the minimum adjacent image, and does not organically combine Need to understand the original image and noise pollution information, you can directly through the parameter self-tuning algorithm for nonlinear filtering algorithm parameters automatically optimize selection. The simulation experiment based on Matlab shows that the proposed algorithm can restrain the impulsive noise very well, and can well preserve the detail information of the image, and can obtain satisfactory results for all kinds of impulsive noise images of different densities.