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Cross-scale Heterogeneous Convolution Change Detection Based on Spatial-Spectral Information Fusion for Remote Sensing Imagery

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Advances in Computational Intelligence Systems (UKCI 2024)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1462))

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Abstract

Change Detection in remote sensing images typically aims to accurately determine any significant land surface changes, based on acquired multi-temporal image data, being a pivotal task in remote sensing image processing. Recently, deep learning has been widely applied in machine vision with remarkable potential demonstrated for performing change detection in images. Current multi-scale feature fusion methods, while enhancing algorithm performance, often introduce a significant number of redundant parameters, thereby increasing model complexity. This paper presents a novel approach to addressing this challenge. A cross-scale heterogeneous convolution change detection method is proposed. It strengthens the perception of multi-scale information without adding excessive redundant parameters, mitigating the detail-blurring issues caused by fusion. By integrating scale perception with spatial-spectral information aggregation, the proposed approach effectively alleviates scale sensitivity issues, improving change detection performance in complex multi-scale environments. This is showcased by comparative experiments on a challenging real-world dataset with seven existing high-performing methods, the proposed method achieved an F1-score of 84.15% and an IoU of 72.64%, demonstrating the advancement of the proposed method.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Faculty of Business and Physical Sciences, Aberystwyth University, Aberystwyth, SY23 3DB, UK

    Xuan Hou, Jinle Lin, Changjing Shang & Qiang Shen

Authors
  1. Xuan Hou
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  2. Jinle Lin
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  3. Changjing Shang
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  4. Qiang Shen
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Corresponding author

Correspondence to Changjing Shang .

Editor information

Editors and Affiliations

  1. School of Computing, Ulster University, Belfast, UK

    Huiru Zheng

  2. School of Computing, Ulster University, Belfast, UK

    David Glass

  3. School of Computing, Ulster University, Belfast, UK

    Maurice Mulvenna

  4. School of Computing, Ulster University, Belfast, UK

    Jun Liu

  5. School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast, UK

    Hui Wang

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Hou, X., Lin, J., Shang, C., Shen, Q. (2024). Cross-scale Heterogeneous Convolution Change Detection Based on Spatial-Spectral Information Fusion for Remote Sensing Imagery. In: Zheng, H., Glass, D., Mulvenna, M., Liu, J., Wang, H. (eds) Advances in Computational Intelligence Systems. UKCI 2024. Advances in Intelligent Systems and Computing, vol 1462. Springer, Cham. https://doi.org/10.1007/978-3-031-78857-4_1

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