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JACIII Vol.23 No.4 pp. 625-633
doi: 10.20965/jaciii.2019.p0625
(2019)

Paper:

Disparity Optimization Algorithm for Stereo Matching Using Improved Guided Filter

Yanyan Xu, Xiangyang Xu, and Rui Yu

Beijing Institute of Technology
No.5 Zhong Guan Cun South Street, Haidian District, Beijing 100081, China

Received:
March 16, 2018
Accepted:
January 4, 2019
Published:
July 20, 2019
Keywords:
stereo matching, guided filter, segment tree
Abstract
Disparity Optimization Algorithm for Stereo Matching Using Improved Guided Filter

Disparity result on dataset teddy

A disparity optimization algorithm based on an improved guided filter is proposed to smooth the disparity image. A well-known problem to local stereo matching is the low matching accuracy and staircase effect in regions with weak texture and slope. Our disparity optimization method solves this problem and achieve a smooth disparity. First, the initial disparity image is obtained by a local stereo matching algorithm using segment tree. Then, the guided filter is improved by using gradient domain information. Lastly, the improved guided filter is adopted as the disparity optimization method to smooth the disparity image. Experiments conducted on the Middlebury data sets demonstrate that by using the proposed algorithm in this paper, the smoothness of the disparity map in slope regions is improved, and a higher precision of dense disparity is obtained.

Cite this article as:
Y. Xu, X. Xu, and R. Yu, “Disparity Optimization Algorithm for Stereo Matching Using Improved Guided Filter,” J. Adv. Comput. Intell. Intell. Inform., Vol.23, No.4, pp. 625-633, 2019.
Data files:
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Last updated on Dec. 10, 2019