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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
会议名称2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)
会议录名称2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)
会议日期2015-12
会议地点马来西亚,吉隆坡
摘要Object-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.
关键词Very High Resolution Images Change Detection
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/14581
专题综合信息系统研究中心
通讯作者Li FM(李非墨)
作者单位中国科学院自动化研究所
推荐引用方式
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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