Unsupervised Change Detection in Multitemporal Multispectral Satellite Images: A Convex Relaxation Approach

Wei Cheng Zheng, Chia Hsiang Lin, Kuo Hsin Tseng, Chih Yuan Huang, Tang Huang Lin, Chia Hsiang Wang, Chong Yung Chi

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

Change detection (CD), enabled by multitemporal multispectral satellite imagery, has many important Earth observation missions such as land cover/use monitoring, for which we observe that change regions are relatively smaller than those caused by disaster (e.g., forest fire) with patterns typically composed of a number of smooth regions. These observations are considered in our new CD criterion, which can effectively mitigate the artifacts and speckle noise suffered by existing statistic-based and difference image (DI) analysis based methods. The proposed CD criterion amounts to a large-scale non-convex optimization, which is first reformulated using the convex relaxation trick with associated change map interpreted in the probability sense, followed by adopting an efficient convex solver known as alternating direction method of multipliers (ADMM). The resulted probabilistic change map would be more practical, and can be thresholded at 0.5 to yield the conventional binary-valued one. We also reveal a link between the proposed criterion and the DI-based criterion, and demonstrate the outstanding performance of our fully unsupervised CD algorithm qualitatively and quantitatively.

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主出版物標題2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1546-1549
頁數4
ISBN(電子)9781538691540
DOIs
出版狀態已出版 - 7月 2019
事件39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Yokohama, Japan
持續時間: 28 7月 20192 8月 2019

出版系列

名字International Geoscience and Remote Sensing Symposium (IGARSS)

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???event.eventtypes.event.conference???39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
國家/地區Japan
城市Yokohama
期間28/07/192/08/19

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