{"title":"基于分类似然空间的可见光波段VHR图像特异性变化检测","authors":"Feimo Li, Shuxiao Li, Cheng-Fei Zhu, Xiaosong Lan, Hongxing Chang","doi":"10.1109/ACPR.2015.7486530","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":240902,"journal":{"name":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","volume":"163 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Specific changes detection in visible-band VHR images using classification likelihood space\",\"authors\":\"Feimo Li, Shuxiao Li, Cheng-Fei Zhu, Xiaosong Lan, Hongxing Chang\",\"doi\":\"10.1109/ACPR.2015.7486530\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":240902,\"journal\":{\"name\":\"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)\",\"volume\":\"163 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACPR.2015.7486530\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPR.2015.7486530","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Specific changes detection in visible-band VHR images using classification likelihood space
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.