Xing PANG, Yi ZHANG, Jing HAN, and Lian-fa BAI^*

Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing 210094, China

(Received April 29, 2014; Accepted August 26, 2014)

An algorithm is proposed which the tree structure of dynamic programming with self-adaptive parameters and a disparity iterative refinement to improve stereo matching performance. The algorithm model consists of an initialization model and a disparity iterative refinement. To obtain the initial disparity map with “clear” background and whole details, the tree structure of dynamic programming with self-adaptive parameters is presented. A disparity iterative refinement is proposed to estimate the disparity of unreliable pixels in the doubtful regions. The disparity iterative refinement consists of a doubtful regions growing method and a disparity filling based on color similarity. The results of experiment evaluated with Middlebury data sets show that our algorithm can effectively ameliorate “fatting inflating” by occlusion and obtains a high quality of disparity map.

Key words: the tree structure of dynamic programming, self-adaptive parameters, a disparity iterative refinement, a doubtful regions growing method, a disparity filling

^*E-mail address: mrblf@163.com