The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-7/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 1241–1248, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W3-1241-2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 1241–1248, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W3-1241-2015

  30 Apr 2015

30 Apr 2015

OBJECT-ORIENTED CHANGE DETECTION BASED ON SPATIOTEMPORAL RELATIONSHIP IN MULTITEMPORAL REMOTE-SENSING IMAGES

L. Liang, G. Ying, X. Wen, and Y. Zhang L. Liang et al.
  • The Third Academy of Engineering of Surveying and Mapping, 2 Xinjun Road, 610500 Chengdu, China
  • Geographic National Condition Monitoring Engineering Research Center of Sichuan Province, 2 Xinjun Road, 610500 Chengdu, China

Keywords: Object-oriented, change detection, post classification comparison (PCC), spatiotemporal relationship, Markov Random Field (MRF), remote-sensing images

Abstract. In this paper a novel object-oriented change detection approach in multitemporal remote-sensing images is proposed. In order to improve post classification comparison (PCC) performance, we propose to exploit spatiotemporal relationship between two images acquired at two different times. The probabilities of class transitions are used to describe the temporal dependence information, while the Markov Random Field (MRF) model is utilized to represent the spatial-contextual information. Training sets are required to get initial classification results b maximum likelihood method (ML). Then an estimation procedure: iterated conditional mode (ICM) is present to revise the classification results. Change detection (change/no change) and change type recognitions (from-to types of change) are achieved by compare classification maps acquired at two different times. Experimental results on two QuickBird images confirm that the proposee method can provide higher accuracy than the PCC method, which ignores spatiotemporal relationship between two images.