@inproceedings{be36136910a2460e9964562cad1d4c72,
title = "A hierarchical structure features analysis technique to reduce registration noise for change detection on VHR images",
abstract = "This paper presents a hierarchical structure feature analysis technique, which is robust to registration noise for change detection in multioral very high spatial resolution (VHR) remote sensing images. To suppress the registration noise in 'difference images', the proposed technique extracts the structural features of the same local area from multioral images and then analyzes the similarity of these features. Specifically, this method consist two steps: first, the structural features is employed to obtain gross suppression of registration noise, so that the noise from the regions that have high similarity is eliminated; second, the remained noise is further suppressed using the local features with more spatial details. Experimental results obtained from multioral remote sensing images demonstrated the effectiveness of the proposed approach.",
keywords = "change detection, hierarchical structure feature, multitemporal images, registration noise, remote sensing",
author = "Chen Zhong and Bo Li and Qizhi Xu",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 3rd International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2014 ; Conference date: 11-06-2014 Through 14-06-2014",
year = "2014",
month = oct,
day = "16",
doi = "10.1109/EORSA.2014.6927894",
language = "English",
series = "3rd International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2014 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "276--279",
editor = "Qihao Weng and Paolo Gamba and George Xian and Guangxing Wang and Guangxing Wang and Jianjun Zhu",
booktitle = "3rd International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2014 - Proceedings",
address = "United States",
}