An Efficient Stereo Matching Algorithm Based on Intensity Weighted Correlation

摘要

This paper presents an efficient intensity weighted matching algorithm for stereo vision applications. The proposed algorithm makes use of intensity weighted values instead of grayscale value for each pixel in the support window in order to improve the quality of disparity map. The idea is derived from the bionics fundamentals, namely retinal center detector commonly permits high resolution in the interested regions, whereas others do not require the identical resolution. Therefore, this algorithm enables the intensity weight of the kernel pixel to be the highest in the window. With the proposed algorithm, the disparity map is improved significantly with little incremental computation cost compared with the fixed-window (FW) SAD algorithm. Experimental evaluation is performed using benchmark stereo pairs. The simulation results demonstrate that the proposed algorithm can achieve bad pixel percentage of disparity map lower than the SAD algorithm.