Disparity map optimization using sparse gradient measurement under intensity-edge constraints

作者：Miao, Jun; Chu, Jun^*; Zhang, Guimei

来源：Signal, Image and Video Processing, 2016, 10(1): 161-169.

DOI：10.1007/s11760-014-0722-8

• Stereo matching
• Disparity map
• Convex optimization
• Half-quadratic splitting algorithm

Common local stereo methods often compute integer-valued disparities at support windows. The implicit assumption of a constant disparity value in support windows generally does not produce accurate results on slanted surfaces. In this paper, we propose a global optimization method for reconstructing disparity maps. Our optimization strategy is an extension of Xu's (ACM Trans Graph 30(6): 112, 2011) image smoothing algorithm. The strategy is to develop a sparse gradients counting model of the disparity map, coupled with the priors of intensity edges of the reference image. Based on this model, the disparity optimization problem is then formulated as a constrained optimization objective function, which is finally solved via the half-quadratic splitting algorithm. Experimental results demonstrated that the proposed approach improves the quality of the disparity maps regarding slanted surfaces and local discontinuity preservation.

• 出版日期2016-1
• 单位南昌航空大学; 南昌大学