基于旋转不变像素相关性的加权中值滤波器

作为一种典型的非线性滤波器，加权中值滤波器可以通过权值系数调整图像的滤波性能。但是在传统加权中值滤波器中，模板内各个像素都对应唯一的权值系数，没有考虑到滤波模板下像素之间的相关性。因此，将权值与模板下两两像素间相关性对应，提出一种新的加权中值滤波模型。同时考虑到图像旋转、翻转情况下滤波的稳定性，进行对称性设计，降低权值模型复杂度，采用差分进化算法对权值进行寻优。对不同滤波器进行权值寻优实验可以看出，基于旋转不变像素相关性的权值模型具有更好的收敛性；灰度图像和彩色图像脉冲噪声的滤波实验结果表明,其在抑制图像噪声，细节和边缘保护以及彩色图像的色调保持方面，优于传统加权中值滤波算法。

Weighted Median Filter Based on Rotation Invariant Pixel Correlations

As one of the most typical nonlinear filters, weighted median filter has considerable filter behavior by assigning weights. But each pixel has only one weight in the traditional weighted median filter. Correlations between pixel and other pixels under the filtering template are not considered. A novel weighted median filter model is proposed here where the weights correspond to these correlations. In order to keep stability when filtering on rotated and reversed images, symmetry of the correlations is utilized and can reduce the model complexity. Differential evolution algorithm is adopted for the weights optimization. Experiments about weights optimization show that this rotation invariant model exhibits faster convergence characteristics. Impulsive noise removal both on different gray images and color images show that it preserves better properties of edges or details, and has efficient noise attenuation and chromaticity retention.