Volume XLI-B3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 487-494, 2016
https://doi.org/10.5194/isprs-archives-XLI-B3-487-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 487-494, 2016
https://doi.org/10.5194/isprs-archives-XLI-B3-487-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  09 Jun 2016

09 Jun 2016

A UNIFIED BLENDING FRAMEWORK FOR PANORAMA COMPLETION VIA GRAPH CUTS

Kai Chen1, Jian Yao1, Menghan Xia1, Xinyuan Gui2, Xiaohu Lu1, and Li Li1 Kai Chen et al.
  • 1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, Hubei, P.R. China
  • 2School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, P.R. China

Keywords: Image Completion, Panorama, Graph Cuts, Luminance Compensation, Image Blending, Feathering

Abstract. In this paper, we propose a unified framework for efficiently completing streetview and indoor 360° panoramas due to the lack of bottom areas caused by the occlusion of the acquisition platform. To greatly reduce the severe distortion at the bottom of the panorama, we first reproject it onto the ground perspective plane containing the whole occluded region to be completed. Then, we formulate the image completion problem in an improved graph cuts optimization framework based on the statistics of similar patches by strengthening the boundary constraints. To further eliminate image luminance differences and color deviations and conceal geometrical parallax among the optimally selected patches for completion, we creatively apply a multi-bland image blending algorithm for perfect image mosaicking from the completed patches and the originally reprojected image. Finally, we back-project the completed and blended ground perspective image into the cylindrical-projection panorama followed by a simple feathering to further reduce artifacts in the panorama. Experimental results on some representative non-panoramic images and streetview and indoor panoramas demonstrate the efficiency and robustness of the proposed method even in some challenging cases.