• Laser Journal
  • Vol. 45, Issue 4, 128 (2024)
LIN Jiao1 and HUO Jiuyuan1,2,3,*
Author Affiliations
  • 1School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
  • 2National Cryosphere Desert Data Center (NCDC), Lanzhou 730000, China
  • 3Lanzhou Ruizhiyuan Information Technology Co. LTD, Lanzhou 730070, China
  • show less
    DOI: 10.14016/j.cnki.jgzz.2024.04.128 Cite this Article
    LIN Jiao, HUO Jiuyuan. SAR image change detection method based on difference image construction and fusion[J]. Laser Journal, 2024, 45(4): 128 Copy Citation Text show less
    References

    [2] X. Jiang, G. Li, Y. Liu,, et al. Change detection in heterogeneous optical and SAR remote sensing images via deep homogeneous feature fusion[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 1551-1566.

    [4] X. Zhang, H. Su, C. Zhang, et al. Robust unsupervised small area change detection from SAR imagery using deep learning[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2021, 173: 79-94.

    [7] Dingle Robertson, McNairn, M. Jiao, et al. Monitoring autumn agriculture activities using Synthetic Aperture Radar (SAR) and coherence change detection[J]. Heliyon, 2023, 9(6): e17322.

    [8] B. Cui, Y. Zhang, L. Yan, et al. A SAR change detection method based on the consistency of single-pixel difference and neighborhood difference[J]. Remote Sensing Letters, 2019, 10(5): 488-495.

    [10] F. Gao, J. Dong, B. Li, et al. Automatic Change Detection in Synthetic Aperture Radar Images Based on PCANet[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(12): 1792-1796.

    [11] Z. Xu, Y. Zhou, and X. Jiang. An Unsupervised Neural Network For Change Detection in SAR images[J]. Asia-Pacific Conference on Synthetic Aperture Radar, 2021, 7: 1-5.

    [12] F Gao, X Wang, J Y Dong, et al. Synthetic aperture radar image change detection based on frequency domain analysis and random multigraphs[J]. Journal of Applied Remote Sensing. 2018, 12(1): 016010.

    [13] F. Gao, J. Dong, B. Li, et al. Change detection from synthetic aperture radar images based on neighborhood-based ratio and extreme learning machine[J]. Journal of Applied Remote Sensing, 2016, 10: 046019.

    [15] Barrie, G. The Use of Diffusion Filtering in SAR Shoreline Extraction Applied to Radarsat-2 Data[C]//IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022, 2602-2605.

    [16] B. Li, H. Peng, and J. Wang. A novel fusion method based on dynamic threshold neural P systems and nonsubsampled contourlet transform for multi-modality medical images[J]. Signal Processing, 2021, 178: 107793.

    [17] K. He, J. Sun, et al. Guided Image Filtering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6): 1397-1409.

    [18] Y. Gao, F. Gao, J. Dong, et al. Change Detection From Synthetic Aperture Radar Images Based on Channel Weighting-Based Deep Cascade Network[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, 12(11): 4517-4529.

    [19] U. H. Atasever and M. A. Gunen. Change Detection Approach for SAR Imagery Based on Arc-Tangential Difference Image and k-Means++[J]. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 1-5.

    [20] A. Goyal and T. Meenpal. Patch-Based Dual-Tree Complex Wavelet Transform for Kinship Recognition[J]. IEEE Transactions on Image Processing, 2021, 30: 191-206.

    LIN Jiao, HUO Jiuyuan. SAR image change detection method based on difference image construction and fusion[J]. Laser Journal, 2024, 45(4): 128
    Download Citation