Volume III-3
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-3, 287-294, 2016
https://doi.org/10.5194/isprs-annals-III-3-287-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-3, 287-294, 2016
https://doi.org/10.5194/isprs-annals-III-3-287-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  03 Jun 2016

03 Jun 2016

IMAGE STITCHING WITH PERSPECTIVE-PRESERVING WARPING

Tianzhu Xiang, Gui-Song Xia, and Liangpei Zhang Tianzhu Xiang et al.
  • State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China

Keywords: Image stitching, Image alignment, Perspective-preserving warping, Similarity transform, Projective transform

Abstract. Image stitching algorithms often adopt the global transform, such as homography, and work well for planar scenes or parallax free camera motions. However, these conditions are easily violated in practice. With casual camera motions, variable taken views, large depth change, or complex structures, it is a challenging task for stitching these images. The global transform model often provides dreadful stitching results, such as misalignments or projective distortions, especially perspective distortion. To this end, we suggest a perspective-preserving warping for image stitching, which spatially combines local projective transforms and similarity transform. By weighted combination scheme, our approach gradually extrapolates the local projective transforms of the overlapping regions into the non-overlapping regions, and thus the final warping can smoothly change from projective to similarity. The proposed method can provide satisfactory alignment accuracy as well as reduce the projective distortions and maintain the multi-perspective view. Experimental analysis on a variety of challenging images confirms the efficiency of the approach.