Abstract: The selection of bandwidths and weights on sampling points plays an important role in Mean Shift based image smoothing. To effectively keep the information on the edges and details of color images, a new smoothing algorithm based on adaptive Mean Shift is proposed. Firstly, an adaptive spatial bandwidth is decided in terms of gray relational degree of color information; then, an adaptive range bandwidth is calculated based on color coarseness；Additionally, the weight of sampling points is computed in the light of color difference; Finally, the filtered value of current point is gotten by the above adaptive Mean Shift algorithm. Experimental results show that the proposed method is superior to some Mean Shift filtering and several widely-used filters in both visual effect and the ability of retaining useful information.

Key words: Mean Shift, weight, adaptive bandwidth, gray relational analysis, color coarseness

摘要： 利用Mean Shift算法对图像进行滤波时，带宽和采样点权重的选择至关重要。为有效保留彩色图像中边缘等细节信息，提出了一种基于自适应Mean Shift算法的彩色图像滤波算法。该算法首先根据图像颜色信息的灰色关联度来定义自适应空域带宽；然后利用颜色粗糙度计算自适应值域带宽；再根据彩色差别获得各采样点的权重；最后用改进后的自适应Mean Shift算法对图像进行滤波。实验结果表明，与基于Mean Shift算法的滤波算法和常见滤波算法相比，该算法的滤波效果不仅更符合人眼的视觉感知，且能更好地保留边缘等细节信息。

关键词: Mean Shift, 权重, 自适应带宽, 灰色关联分析, 颜色粗糙度