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Specific Changes Detection in Visible-Band VHR Images using Classification Likelihood Space
Li FM(李非墨); Li SX(李书晓); Zhu CF(朱承飞); Lan XS(兰晓松); Chang HX(常红星); Li FM(李非墨)
2015-12
Conference Name2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)
Source Publication2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)
Conference Date2015-12
Conference Place马来西亚,吉隆坡
AbstractObject-based post-classification change detection methods are effective for very high resolution images, but their effectiveness is limited by incomplete class hierarchy and complex image object comparison. In this paper, a novel Classification Likelihood Space (CLS) is proposed to synthesize the effective object-based image analysis and easy-to-implement post-classification comparison, serving as a well tradeoff between performance and complexity. The proposed algorithm is tested on a dataset which comprises 102 pairs of visible-band very high resolution real satellite images, and a great improvement is observed over traditional post-classification comparison.
KeywordVery High Resolution Images Change Detection
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14581
Collection综合信息系统研究中心
Corresponding AuthorLi FM(李非墨)
Affiliation中国科学院自动化研究所
Recommended Citation
GB/T 7714
Li FM,Li SX,Zhu CF,et al. Specific Changes Detection in Visible-Band VHR Images using Classification Likelihood Space[C],2015.
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