• Laser & Optoelectronics Progress
  • Vol. 57, Issue 22, 221105 (2020)
Min Gao, Xiaoxia Wang*, Fengbao Yang, and Zongjun Zhang
Author Affiliations
  • School of Information and Communication Engineering, North University of China, Taiyuan, Shanxi 030051, China
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    DOI: 10.3788/LOP57.221105 Cite this Article Set citation alerts
    Min Gao, Xiaoxia Wang, Fengbao Yang, Zongjun Zhang. Deblurring Processing Method for Pixel Level Change Detection of SAR Images[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221105 Copy Citation Text show less
    References

    [1] Sui H G, Feng W Q, Li W Z et al. Review of change detection methods for multi-temporal remote sensing imagery[J]. Geomatics and Information Science of Wuhan University, 43, 1885-1898(2018).

    [2] Huang C X, Yin J J, Yang J. Polarimetric SAR change detection with l1-norm principal component analysis[J]. Systems Engineering and Electronics, 41, 2214-2220(2019).

    [3] Jin Q H, Wang Y P, Yang J Y. Remote sensing image change detection based on density attraction and multi-scale and multi-feature fusion[J]. Laser & Optoelectronics Progress, 56, 121003(2019).

    [4] Baik H, Son Y, Kim K. Detection of liquefaction phenomena from the 2017 Pohang (Korea) earthquake using remote sensing data[J]. Remote Sensing, 11, 2184(2019).

    [5] Perbet P, Fortin M, Ville A et al. Near real-time deforestation detection in Malaysia and Indonesia using change vector analysis with three sensors[J]. International Journal of Remote Sensing, 40, 7439-7458(2019).

    [6] Shimizu K, Ota T, Mizoue N. Detecting forest changes using dense landsat 8 and sentinel-1 time series data in tropical seasonal forests[J]. Remote Sensing, 11, 1899(2019).

    [7] Zhang Q Y, Li Z, Peng D L. Detecting land use change by object-oriented change vector analysis (OCVA)[J]. Journal of China Agricultural University, 24, 166-174(2019).

    [8] Wu Y Q, Cao Z Q, Tao F X. Change detection of multi-temporal remote sensing images based on Contourlet transform and ICA[J]. Chinese Journal of Geophysics, 59, 1284-1292(2016).

    [9] Wang S N, Jiao L C, Yang S Y. SAR images change detection based on spatial coding and nonlocal similarity pooling[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9, 3452-3466(2016).

    [10] Inglada J, Mercier G. A new statistical similarity measure for change detection in multitemporal SAR images and its extension to multiscale change analysis[J]. IEEE Transactions on Geoscience and Remote Sensing, 45, 1432-1445(2007).

    [11] Gong M G, Cao Y, Wu Q D. A neighborhood-based ratio approach for change detection in SAR images[J]. IEEE Geoscience and Remote Sensing Letters, 9, 307-311(2012).

    [12] Ma J J, Gong M G, Zhou Z Q. Wavelet fusion on ratio images for change detection in SAR images[J]. IEEE Geoscience and Remote Sensing Letters, 9, 1122-1126(2012).

    [13] Su Q, Yang J Y, Wang Y P. Synthetic aperture radar image change detection based on intuitionistic fuzzy C-core mean clustering algorithm[J]. Laser & Optoelectronics Progress, 56, 192805(2019).

    [14] Mu C H, Huo L L, Liu Y et al. Change detection for remote sensing images based on wavelet fusion and PCA-kernel fuzzy clustering[J]. Acta Electronica Sinica, 43, 1375-1381(2015).

    [15] Zhang Q C, Tong G F, Li Y et al. River detection in remote sensing images based on multi-feature fusion and soft voting[J]. Acta Optica Sinica, 38, 0628002(2018).

    [16] Zhao Z G, Xiong C H, Wang K et al[M]. Conceptions, methods and applications on information fusion, 283(2012).

    Min Gao, Xiaoxia Wang, Fengbao Yang, Zongjun Zhang. Deblurring Processing Method for Pixel Level Change Detection of SAR Images[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221105
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