吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (增刊1): 204-208.

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Dense disparity map optimization algorithm based on convex set theory

GAO Kai, CHEN He-xin, ZHAO Yan, GENG Ying-nan, LI Chang-ming   

  1. College of Communication Engineering, Jilin University, Changchun 130012, China
  • Received:2012-06-05 Published:2013-06-01

Abstract:

According to the mismatch problem in less textured area of stereo match algorithms in computer vision field,in order to find the optimal disparity map of the stereo image pair,a method using the sub-gradient projection method to solve strict convex function which composed by the pixel error function of the shaped image pairs and quadratic smoothing factor of disparity map was proposed,which was restrained by the convex constraint set of total variation function.Experimental results show that the method can keep the edge of primal disparity map well,reduce the mismatch in the less textured area of disparity generated by primal stereo matching algorithm,and get the better optimization disparity map effectively.

Key words: stereo matching, convex optimization, sub-gradient projection, total variation, quadratic smoothing factor

CLC Number: 

  • TN919.8

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