Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1689-1694, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1689-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1689-1694, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1689-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

CHANGE DETECTION OF HIGH-RESOLUTION REMOTE SENSING IMAGES BASED ON ADAPTIVE FUSION OF MULTIPLE FEATURES

G. H. Wang1, H. B. Wang2, W. F. Fan2, Y. Liu2, and C. Chen2 G. H. Wang et al.
  • 1China University of Mining and Technology, Xuzhou 221116, China
  • 2Satelite Surveying and Mapping Application, NASG, Beijing 100830, China

Keywords: Change Detection, Color Gistogram, Linear Gradient Histogram, EMD distance, Histogram Curvature

Abstract. In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.