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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publication2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1546-1549
Number of pages4
ISBN (Electronic)9781538691540
DOIs
Publication statusPublished - 2019 Jul
Event39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Yokohama, Japan
Duration: 2019 Jul 282019 Aug 2

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
CountryJapan
CityYokohama
Period19-07-2819-08-02

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All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

Cite this

Zheng, W. C., Lin, C. H., Tseng, K. H., Huang, C. Y., Lin, T. H., Wang, C. H., & Chi, C. Y. (2019). Unsupervised Change Detection in Multitemporal Multispectral Satellite Images: A Convex Relaxation Approach. In 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings (pp. 1546-1549). [8898598] (International Geoscience and Remote Sensing Symposium (IGARSS)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2019.8898598