ABBD: accumulated band-wise binary distancing for unsupervised parameter-free hyperspectral change detection.

Li, Yinhe; Ren, Jinchang; Yan, Yijun; Ma, Ping; Assaad, Maher; Gao, Zhi

Abstract

As a fundamental task in remote sensing earth observation, hyperspectral change detection (HCD) aims to identify the changed pixels in bi-temporal hyperspectral images (HSIs). However, the water-absorption effect, poor weather conditions, noise and inconsistent illumination as well as lack of accurate ground truth has made HCD particularly challenging. To tackle these challenges, a novel Accumulated Band-wise Binary Distancing (ABBD) model was proposed for unsupervised parameter-free HCD. Rather than relying on the absolute pixel difference with thresholding in conventional approaches, the binary distancing only indicated whether a pixel was changed or not in a certain band, which could alleviate the adverse effects of noise-induced inconsistency of measurement. The band-wise binary distance map is then accumulated to form a grayscale change map, on which the simple k-means was applied for a final binary decision-making. Experiments on three publicly available datasets have validated the superiority of our approach, which has yielded comparable or slightly better results in comparison to a few state-of-the-art methods including several deep learning models.

Citation

LI, Y., REN, J., YAN, Y., MA, P., ASSAAD, M. and GAO, Z. 2024. ABBD: accumulated band-wise binary distancing for unsupervised parameter-free hyperspectral change detection. IEEE journal of selected topics in applied earth observations and remote sensing [online], 17, pages 9880-9893. Available from: https://doi.org/10.1109/JSTARS.2024.3407212

• Journal Article Type: Article
• Acceptance Date: May 21, 2024
• Online Publication Date: May 30, 2024
• Publication Date: Dec 31, 2024
• Deposit Date: Jun 3, 2024
• Publicly Available Date: Jun 3, 2024
• 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 (IEEE)
• Peer Reviewed: Peer Reviewed
• Volume: 17
• Pages: 9880-9893
• DOI: https://doi.org/10.1109/jstars.2024.3407212
• Keywords: Hyperspectral image (HSI); Unsupervised change detection; Accumulated band-wise binary distancing (ABBD); Parameter-free
• Public URL: https://rgu-repository.worktribe.com/output/2363686