Volume XLII-2/W7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 831-835, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-831-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 831-835, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-831-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  13 Sep 2017

13 Sep 2017

AN INTEGRATED FUSION FRAMEWORK FOR JOINT INFORMATION RECONSTRUCTION AND RESOLUTION ENHANCEMENT

X. Meng1, H. Shen1,4, Q. Yuan2,4, H. Li1, and L. Zhang3,4 X. Meng et al.
  • 1School of Resource and Environmental Sciences, Wuhan University, China
  • 2School of Geodesy and Geomatics, Wuhan University, China
  • 3State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, China
  • 4Collaborative Innovation Center of Geospatial Technology, Wuhan University, China

Keywords: Integrated Framework, Image Fusion, Information Reconstruction, Resolution Enhancement, Clouds, Cloud Shadows

Abstract. In this paper, an integrated fusion framework for joint information reconstruction and resolution enhancement is proposed. In the proposed framework, an integrated variational model based on multi-source and multi-temporal remote sensing images is constructed, which is able to simultaneously achieve resolution enhancement and joint cloud and cloud shadow removal. In addition, the ground feature changes between multi-temporal scenes are comprehensively considered. Through this integrated framework, a promising cloud and cloud shadow free fused image with both high spatial and spectral resolutions is obtained. The experimental results confirm the effectiveness of the proposed method.