基于色度分割与图割算法的视差估计算法

Disparity Estimation Algorithm Based on Color Segmentation and Graph Cut Algorithm

为提高视差估计的准确度,提出了一种基于色度分割和图割算法的视差估计算法.该算法采用均值漂移算法对当前图像进行色度分割,并对每个色度分割区域的像素集合分别用图割算法在参考图像中进行像素匹配,进而估计出当前图像的视差.与传统的全局优化算法不同,文中提出的视差估计算法将每个色度分割区域作为整体分别进行全局优化,因而可以提高物体边缘的视差估计准确度.实验结果表明,该算法的视差估计结果更加准确.

In order to improve the accuracy of disparity estimation, an algorithm based on color segmentation and graph cut algorithm is proposed. In this algorithm, the current image is segmented into several color areas by employing the mean shift algorithm, and the graph cut is implemented on the pixel set of each color area to allocate disparities for the pixels in the color area. Unlike the traditional global optimization algorithm, the proposed algo- rithm takes the pixel set of a color area rather than the whole image as an entirety to perform the global optimization, thus improving the disparity accuracy of object boundaries. Experimental results demonstrate that the proposed algorithm is more effective than the traditional one.