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Superpixel-based foreground-preserving image stitching.

Authors :
Miao, Xinpeng
Qu, Tao
Chen, Xi
He, Chu
Source :
Machine Vision & Applications. Jan2023, Vol. 34 Issue 1, p1-15. 15p.
Publication Year :
2023

Abstract

Image stitching aims to stitch multiple images with overlapping areas into a high-resolution image with natural appearance, no ghosting and no seam, so as to obtain a wide field of vision. And the stitching is required to be as fast as possible. In this article, we discuss the loss of foreground object caused by the seam-cut method for image stitching. Moreover, we propose an improved seam-cut method based on superpixel to solve this problem. The proposed method uses the matching information of feature points and superpixel segmentation to divide the scene into foreground and background. By adjusting the penalty value of foreground superpixels in the superpixel-based seam-cut method, the foreground object can avoid the cutting of optimal seam. The experimental results demonstrate that our method will not cause the ghosting of foreground object or the loss of foreground object in the stitching result in the scene with large parallax. In this method, the foreground object will be preserved completely. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09328092
Volume :
34
Issue :
1
Database :
Academic Search Index
Journal :
Machine Vision & Applications
Publication Type :
Academic Journal
Accession number :
161092803
Full Text :
https://doi.org/10.1007/s00138-022-01363-1