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Proceedings Paper

Adaptive dual-feature image stitching based on moving-DLT
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Paper Abstract

Image stitching is to create a wider viewing angle image with high quality from a series of images which have overlapping regions. It is one of the most important fields of image processing. The traditional global homography method, such as AutoStitch, will be invalid when the scene is not planar or the views differ not purely by rotation. The local homography warping method, which is based on the grid optimization algorithm, such as as-projective-as-possible(APAP) warping can get a better result relative to global homography method, but it deeply relies on the quality and quantity of matching points. In this paper, a new method for low texture scene stitching was proposed which combines point features and line features to compute local warping matrix. So the method can get enough features in low texture region. Our results are compared with APAP and AutoStitch method. The results show that our method have less ghosting and deformation.

Paper Details

Date Published: 12 December 2018
PDF: 5 pages
Proc. SPIE 10846, Optical Sensing and Imaging Technologies and Applications, 108462T (12 December 2018); doi: 10.1117/12.2505590
Show Author Affiliations
Mowen Xue, Beihang Univ. (China)
Xudong Li, Beihang Univ. (China)
Hongzhi Jiang, Beihang Univ. (China)
Huijie Zhao, Beihang Univ. (China)

Published in SPIE Proceedings Vol. 10846:
Optical Sensing and Imaging Technologies and Applications
Mircea Guina; Haimei Gong; Jin Lu; Dong Liu, Editor(s)

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