基于HSV彩色空间的矢量形态学算子

Vector morphological operators in HSV color space

在HSV彩色空间中,现有的矢量形态学算子对彩色像素的排序依据V、S、H顺序分层进行,从而违背了彩色图像中三个分量的平等原则,导致矢量形态学滤波算子难以去除彩色图像中由色调和饱和度分量引起的噪声,因此滤波算子性能较差.文中提出了一种基于HSV三分量混合运算的矢量形态学排序规则,并根据该规则定义了新的矢量形态学腐蚀、膨胀算子以及常用的矢量形态学滤波算子.实验结果表明,新的矢量形态学滤波算子较现有的矢量形态学滤波算子具有更强的噪声抑制性能,在保证图像不增加新的彩色像素的同时,去除了噪声并保留了图像细节,滤波后的图像具有较高的峰值信噪比和较小的均方根误差.

In HSV color space, the current vector morphological operators have low capability to reduce color noise caused by hue and saturation in color image processing. Because they sort the color pixels according to the hierarchical ordering of V, S, H, which is against the equal principle of the three channels in color image processing. A novel vector ordering based on the combination of H, S and V is proposed in this paper, and the associated vector morphological erosion, dilation and composite filtering operators are defined. Compared with the popular vector morphological operators, experimental results show that the new operators can reduce the color noise effectively without any new color pixels while preserving the image details. And the filtered images have higher peak signal-to-noise ratio （PSNR） and lower mean square error （MSE）.