期刊
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
卷 42, 期 -, 页码 145-160出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jvcir.2016.11.016
关键词
Iterative guided filter; Disparity map; Gradient difference; Absolute difference; Undirected graph segmentation; Stereo matching algorithm
资金
- Universiti Sains Malaysia [PLD-0025/13(R)]
- Universiti Teknikal Malaysia Melaka
Stereo matching process is a difficult and challenging task due to many uncontrollable factors that affect the results. These factors include the radiometric variations and illumination inconsistence. The absolute differences (AD) algorithms work fast, but they are too sensitive to noise and low textured areas. Therefore, this paper proposes an improved algorithm to overcome these limitations. First, the proposed algorithm utilizes per-pixel difference adjustment for AD and gradient matching to reduce the radiometric distortions. Then, both differences are combined with census transform to reduce the effect of illumination variations. Second, a new approach of iterative guided filter is introduced at cost aggregation to preserve and improve the object boundaries. The undirected graph segmentation is used at the last stage in order to smoothen the low textured areas. The experimental results on the standard indoor and outdoor datasets show that the proposed algorithm produces smooth disparity maps and accurate results. (C) 2016 Elsevier Inc. All rights reserved.
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