Knowledge Commons of Institute of Automation,CAS
Simultaneous change region and pattern identification for VHR images | |
Huo LG(霍雷刚)1,2; Huo CL(霍春雷)1; Huo CL(霍春雷) | |
2016-07 | |
会议名称 | IEEE International Geoscience and Remote Sensing Symposium |
会议录名称 | IEEE International Geoscience and Remote Sensing Symposium |
会议日期 | 2016.7.10-2016.7.15 |
会议地点 | 北京 |
摘要 | Very high resolution images are promising for detecting change regions and identifying change patterns. However, the low overall separability makes it difficult to discriminate change features. In this paper, a framework is proposed to simultaneously detect change regions and identify change patterns. A supervised approach is illustrated within this framework, which is aimed at reducing the overlaps between change classes by capturing the interclass difference and the intraclass similarity. Experiments demonstrate the effectiveness of the proposed approach. |
关键词 | Change Detection Change Pattern Feature Classification Feature Transformation Distance Tuning. |
收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/12336 |
专题 | 多模态人工智能系统全国重点实验室_先进时空数据分析与学习 |
通讯作者 | Huo CL(霍春雷) |
作者单位 | 1.Guangxi Teachers Education University 2.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Huo LG,Huo CL,Huo CL. Simultaneous change region and pattern identification for VHR images[C],2016. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Simultaneous change (1343KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论