Acta Optica Sinica, Volume. 45, Issue 12, 1210001(2025)

Research on Thin Cloud Removal Based on Generative Adversarial Network with CBAM and Multi-Scale Attention

Yang Wang1, Guokun Chen1,2,3、*, Xingwu Duan4,5, Qingke Wen6,7, Jiatian Li1, and Zhen Zhang1,2,3
Author Affiliations
  • 1Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, Yunnan , China
  • 2Yunnan Key Laboratory of Quantitative Remote Sensing, Kunming 650093, Yunnan , China
  • 3Yunnan International Joint Laboratory for Integrated Sky-Ground Intelligent Monitoring of Mountain Hazards, Kunming 650093, Yunnan , China
  • 4Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, Yunnan , China
  • 5Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Yunnan University, Kunming 650500, Yunnan , China
  • 6Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
  • 7National Engineering Research Center for Geomatics, Beijing 100101, China
  • show less
    References(36)

    [4] Chen Y, Chen M L, He W et al. Thick cloud removal in multitemporal remote sensing images via low-rank regularized self-supervised network[J]. IEEE Transactions on Geoscience and Remote Sensing, 62, 5506613(2024).

    [7] Jiang H, Lü N, Yao L. HOT-transform based method to remove haze or thin cloud for Landsat 8 OLI satellite data[J]. Journal of Remote Sensing, 20, 620-631(2016).

    [12] Yu X Y, Pan J, Wang M et al. A curvature-driven cloud removal method for remote sensing images[J]. Geo-spatial Information Science, 27, 1326-1347(2024).

    [13] Li W B, Li Y, Chen D et al. Thin cloud removal with residual symmetrical concatenation network[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 153, 137-150(2019).

    [14] Zi Y, Xie F Y, Zhang N et al. Thin cloud removal for multispectral remote sensing images using convolutional neural networks combined with an imaging model[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 3811-3823(2021).

    [19] Xu M, Deng F R, Jia S et al. Attention mechanism-based generative adversarial networks for cloud removal in Landsat images[J]. Remote Sensing of Environment, 271, 112902(2022).

    [20] Zheng J H, Liu X Y, Wang X D. Single image cloud removal using U-Net and generative adversarial networks[J]. IEEE Transactions on Geoscience and Remote Sensing, 59, 6371-6385(2021).

    [21] Wang Z, Ma J, Guo Y et al. Cloud removal in multitemporal remote sensing imagery combining U-Net and spatiotemporal generative networks[J]. National Remote Sensing Bulletin, 28, 2089-2100(2024).

    [23] Zi Y, Xie F Y, Song X D et al. Thin cloud removal for remote sensing images using a physical-model-based CycleGAN with unpaired data[J]. IEEE Geoscience and Remote Sensing Letters, 19, 1004605(2021).

    [24] Li J, Wu Z C, Hu Z W et al. Thin cloud removal in optical remote sensing images based on generative adversarial networks and physical model of cloud distortion[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 166, 373-389(2020).

    [25] Tao L L, Wang Y Q. Reconstructing spectral information in cloud contaminated regions using object-oriented approach[J]. Transactions of the Chinese Society of Agricultural Engineering, 40, 216-223(2024).

    [27] Hu H, Li J T, A X H et al. Method for cloud removal from optical remote-sensing image based on latent diffusion model[J]. Acta Optica Sinica, 44, 1228009(2024).

    [34] Zheng Y, Zhan J H, He S F et al. Curricular contrastive regularization for physics-aware single image dehazing[C], 5785-5794(2023).

    Tools

    Get Citation

    Copy Citation Text

    Yang Wang, Guokun Chen, Xingwu Duan, Qingke Wen, Jiatian Li, Zhen Zhang. Research on Thin Cloud Removal Based on Generative Adversarial Network with CBAM and Multi-Scale Attention[J]. Acta Optica Sinica, 2025, 45(12): 1210001

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Image Processing

    Received: Feb. 5, 2025

    Accepted: Apr. 24, 2025

    Published Online: Jun. 23, 2025

    The Author Email: Guokun Chen (chengk@radi.ac.cn)

    DOI:10.3788/AOS250568

    CSTR:32393.14.AOS250568

    Topics