Abstract
Stereo vision is a hot research topic in the field of computer vision and 3D video display.Disparity map is one of the most crucial steps. A novel constant computational complexity algorithm based on separable successive weight summation (SWS) is presented. The proposed algorithm eliminates iteration and support area independently, which saves computation and memory space .The similar measure of gradient is also applied to improve the original algorithm. Image segmentation and edge detection is used for the stereo matching to accelerate the speed and improve the accuracy of matching algorithm.The image of edge is extracted to reduce the search scope for the stereo matching algorithm. Dense disparity map was obtained through local optimization.Experimental results show that the algorithm is efficient and can well reduce the matching noise and improve the matching precision in depth discontinuities and low-texture region.
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