Abstract
The determination of the optimal change threshold is an essential step for very high-resolution (VHR) remote sensing change detection. Although a number of change threshold selection methods have been developed for various applications, no single method can be suitable for all cases. It is difficult for users to select an applicable change threshold selection method for their own purposes. To address this challenge, eight common-used change threshold selection methods were studied from their pros and cons as well as performance. First, a clear analysis of these eight threshold selection methods was presented from the perspective of their pros and cons. Second, four groups of comparative experiments were conducted using VHR remote sensing images from the perspectives of greyscale histogram distribution, scene complexity, greyscale histogram processing, and runtime, respectively. From the experimental results, it is clear that the Otsu method and the FST method are the highest accuracy method for detecting multi-temporal VHR remote sensing images. Considering the time cost, the FST method outperforms the Otsu method. This study could be helpful for researchers to select appropriate change threshold approach for various change detection applications.
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Acknowledgements
This paper is jointly funded by the National Natural Science Foundation of China (41801308 and 41930107); Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University (20S01); Doctoral Research Fund of Shandong Jianzhu University (XNBS1804), Key Laboratory of Land Satellite Remote Sensing Application Centre, Ministry of Natural Resources of the People’s Republic of China (KLSMNR-202105), and Science and Technology Support Program for Youth Innovation in Colleges and Universities of Shandong Province (2019KJG005). The authors would like to thank the editor and four anonymous reviewers for their valuable comments and suggestions.
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Communicated by: H. Babaie.
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Xing, H., Zhu, L., Chen, B. et al. A comparative study of threshold selection methods for change detection from very high-resolution remote sensing images. Earth Sci Inform 15, 369–381 (2022). https://doi.org/10.1007/s12145-021-00734-y
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DOI: https://doi.org/10.1007/s12145-021-00734-y