Journal
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
Volume 19, Issue -, Pages -Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2020.3037930
Keywords
Optical sensors; Optical imaging; Remote sensing; Radar polarimetry; Fractals; Sun; Atmospheric measurements; Adaptive local structure; graph; heterogeneous remote sensing; unsupervised change detection (CD)
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Funding
- Key Research and Development Program of Hunan Province of China [2016SK2016]
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This study proposes an unsupervised change detection method based on adaptive local structure consistency for heterogeneous remote sensing images. Experimental results demonstrate the effectiveness of the proposed method.
Change detection (CD) of heterogeneous remote sensing images is a challenging topic, which plays an important role in natural disaster emergency response. Due to the different imaging mechanisms of heterogeneous sensors, it is hard to directly compare the images. To address this challenge, we explore an unsupervised CD method based on adaptive local structure consistency (ALSC) between heterogeneous images in this letter, which constructs an adaptive graph representing the local structure for each patch in one image domain and then projects this graph to the other image domain to measure the change level. This local structure consistency exploits the fact that the heterogeneous images share the same structure information for the same ground object, which is imaging modality-invariant. To avoid heterogeneous data confusion, the pixelwise change image is calculated in the same image domain by graph projection. By comparing with some state-of-the-art methods, the experimental results show the effectiveness of the proposed ALSC-based CD method.
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