Laser & Optoelectronics Progress, Volume. 62, Issue 10, 1028004(2025)

Remote-Sensing Image-Change Detection Based on Depth-Information Fusion

Jingyu Yang1,2、*, Yahui An1, Jianwu Dang1,2,3, Feng Wang4, and Jiuyuan Huo1
Author Affiliations
  • 1School of Electronics and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, Gansu , China
  • 2Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics & Image Processing, Lanzhou 730070, Gansu , China
  • 3National Virtual Simulation Experimental Teaching Center for Rail Transit Information and Control, Lanzhou Jiaotong University, Lanzhou 730070, Gansu , China
  • 4Gansu Luqiao Feiyu Transportation Facilities Co., Ltd., Lanzhou 730070, Gansu , China
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    References(37)

    [1] Liu Q, Cao L, Tian S et al. Structure-aware multiscale hybrid network for change detection of remote sensing images[J]. Laser & Optoelectronics Progress, 61, 1428008(2024).

    [5] Liu Y, Guo H T, Lu J et al. Remote sensing image change detection method based on adaptive boundary sensing[J]. Acta Optica Sinica, 44, 1828001(2024).

    [6] Yao Q F, Ning Y X, Du S W. Change detection of optical and synthetic aperture radar remote sensing images based on a domain adaptive neural network[J]. Laser & Optoelectronics Progress, 61, 1828001(2024).

    [9] Gu L, Xu S Q, Zhu L Q. Detection of building changes in remote sensing images via FlowS-Unet[J]. Acta Automatica Sinica, 46, 1291-1300(2020).

    [22] Rahaman N, Baratin A, Arpit D et al. On the spectral bias of neural networks[C], 5301-5310(2019).

    [25] Jähne B[M]. Digital image processing(2005).

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    Jingyu Yang, Yahui An, Jianwu Dang, Feng Wang, Jiuyuan Huo. Remote-Sensing Image-Change Detection Based on Depth-Information Fusion[J]. Laser & Optoelectronics Progress, 2025, 62(10): 1028004

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Sep. 24, 2024

    Accepted: Nov. 26, 2024

    Published Online: May. 8, 2025

    The Author Email: Jingyu Yang (yangjy@mail.lzjtu.cn)

    DOI:10.3788/LOP242039

    CSTR:32186.14.LOP242039

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