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Proceedings Paper

Change detection based on integration of multi-scale mixed-resolution information
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Paper Abstract

In this paper, a new method of unsupervised change detection is proposed by modeling multi-scale change detector based on local mixed information and we present a method of automated threshold. A theoretical analysis is presented to demonstrate that more comprehensive information is taken into account by the integration of multi-scale information. The ROC curves show that change detector based on multi-scale mixed information(MSM) is more effective than based on mixed information(MIX). Experiments on artificial and real-world datasets indicate that the multi-scale change detection of mixed information can eliminate the pseudo-change part of the area. Therefore, the proposed algorithm MSM is an effective method for the application of change detection.

Paper Details

Date Published: 2 March 2016
PDF: 6 pages
Proc. SPIE 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015), 99010H (2 March 2016); doi: 10.1117/12.2234908
Show Author Affiliations
Li Wei, Sanming Univ. (China)
Cheng Wang, Xiamen Univ. (China)
Chenglu Wen, Xiamen Univ. (China)


Published in SPIE Proceedings Vol. 9901:
2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015)
Cheng Wang; Rongrong Ji; Chenglu Wen, Editor(s)

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