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Texture-sensitive superpixeling and adaptive thresholding for effective segmentation of sea ice floes in high-resolution optical images.

Chai, Yanmei; Ren, Jinchang; Hwang, Byongjun; Wang, Jian; Fan, Dan; Yan, Yijun; Zhu, Shiwei

Authors

Yanmei Chai

Jinchang Ren

Byongjun Hwang

Jian Wang

Dan Fan

Yijun Yan

Shiwei Zhu



Abstract

Efficient and accurate segmentation of sea ice floes from high-resolution optical (HRO) remote sensing images is crucial for understanding of sea ice evolutions and climate changes, especially in coping with the large data volume. Existing methods suffer from noise interference and the mixture of water and ice caused high segmentation error and less robustness. In this article, we propose a novel sea ice floe segmentation algorithm from HRO images based on texture-sensitive superpixeling and two-stage thresholding. First, sparse components are extracted from the HRO images using the robust principal component analysis (RPCA), and noise is removed by the bilateral filter. The enhanced image is obtained by combining the low-rank matrix and the sparse components. Second, a texture-sensitive simple linear iterative clustering (SLIC) superpixel algorithm is introduced for presegmentation of the enhanced HRO image. Third, a learning-based adaptive thresholding in the two stages is employed to generate the refined segmentation from the derived superpixels blocks. The efficacy of the proposed method is validated on two HRO images using visual assessment, quantitative evaluation (with seven metrics), and histogram comparison. The superior performance of the proposed method has demonstrated its efficacy for sea ice floe segmentation.

Citation

CHAI, Y., REN, J., HWANG, B., WANG, J., FAN, D., YAN, Y. and ZHU, S. 2021. Texture-sensitive superpixeling and adaptive thresholding for effective segmentation of sea ice floes in high-resolution optical images. IEEE journal of selected topics in applied earth observations and remote sensing [online], 14, pages 577-586. Available from: https://doi.org/10.1109/jstars.2020.3040614

Journal Article Type Article
Acceptance Date Nov 23, 2020
Online Publication Date Nov 25, 2020
Publication Date Jan 6, 2021
Deposit Date Jan 28, 2021
Publicly Available Date Jan 28, 2021
Journal IEEE Journal of selected topics in applied earth observations and remote sensing
Print ISSN 1939-1404
Electronic ISSN 2151-1535
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 14
Pages 577-586
DOI https://doi.org/10.1109/JSTARS.2020.3040614
Keywords Adaptive two-stage thresholding; High-resolutionoptical (HRO) image; Low-rank sparse representation; Sea ice floesegmentation; Texture-sensitive superpixeling
Public URL https://rgu-repository.worktribe.com/output/1148978

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