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Journal of Applied Remote Sensing • new

Gaussian mixed model in support of semiglobal matching leveraged by ground control points
Author(s): Hao Ma; Shunyi Zheng; Chang Li; Yingsong Li; Li Gui
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Paper Abstract

Semiglobal matching (SGM) has been widely applied in large aerial images because of its good tradeoff between complexity and robustness. The concept of ground control points (GCPs) is adopted to make SGM more robust. We model the effect of GCPs as two data terms for stereo matching between high-resolution aerial epipolar images in an iterative scheme. One term based on GCPs is formulated by Gaussian mixture model, which strengths the relation between GCPs and the pixels to be estimated and encodes some degree of consistency between them with respect to disparity values. Another term depends on pixel-wise confidence, and we further design a confidence updating equation based on three rules. With this confidence-based term, the assignment of disparity can be heuristically selected among disparity search ranges during the iteration process. Several iterations are sufficient to bring out satisfactory results according to our experiments. Experimental results validate that the proposed method outperforms surface reconstruction, which is a representative variant of SGM and behaves excellently on aerial images.

Paper Details

Date Published: 23 June 2017
PDF: 13 pages
J. Appl. Remote Sens. 11(2) 025014 doi: 10.1117/1.JRS.11.025014
Published in: Journal of Applied Remote Sensing Volume 11, Issue 2
Show Author Affiliations
Hao Ma, Wuhan Univ. (China)
Shunyi Zheng, Wuhan Univ. (China)
Collaborative Innovation Ctr. of Geospatial Technology (China)
Chang Li, Central China Normal Univ. (China)
Yingsong Li, Wuhan Univ. (China)
Li Gui, Wuhan Univ. (China)
Collaborative Innovation Ctr. of Geospatial Technology (China)

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