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Proceedings Paper

Parallax handling of image stitching using dominant-plane homography
Author(s): Zhaofeng Pang; Cheng Li; Baojun Zhao; Linbo Tang
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Paper Abstract

In this paper, we present a novel image stitching method to handle parallax in practical application. For images with significant amount of parallax, the more effective approach is to align roughly and globally the overlapping regions and then apply a seam-cutting method to composite naturally stitched images. It is well known that images can be modeled by various planes result from the projective parallax under non-ideal imaging condition. The dominant-plane homography has important advantages of warping an image globally and avoiding some local distortions. The proposed method primarily addresses large parallax problem through two steps: (1) selecting matching point pairs located on the dominant plane, by clustering matching correspondences and then measuring the cost of each cluster; and (2) in order to obtain a plausible seam, edge maps of overlapped area incorporation arithmetic is adopted to modify the standard seam-cutting method. Furthermore, our approach is demonstrated to achieve reliable performance of handling parallax through a mass of experimental comparisons with state-of-the-art methods.

Paper Details

Date Published: 8 October 2015
PDF: 7 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 967520 (8 October 2015); doi: 10.1117/12.2199793
Show Author Affiliations
Zhaofeng Pang, Beijing Institute of Technology (China)
Beijing Key Lab. of Embedded Real-time Information Processing Technology (China)
Cheng Li, Beijing Institute of Technology (China)
Beijing Key Lab. of Embedded Real-time Information Processing Technology (China)
Baojun Zhao, Beijing Institute of Technology (China)
Beijing Key Lab. of Embedded Real-time Information Processing Technology (China)
Linbo Tang, Beijing Institute of Technology (China)
Beijing Key Lab. of Embedded Real-time Information Processing Technology (China)


Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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