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Laser & Optoelectronics Progress, Volume. 57, Issue 22, 221105(2020)

Deblurring Processing Method for Pixel Level Change Detection of SAR Images

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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    Figures&Tables (8)
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    References (16)
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    Figures & Tables(8)
    Mexico dataset. (a) Image from April 2000; (b) image from May 2002; (c) reference map

    Fig. 1. Mexico dataset. (a) Image from April 2000; (b) image from May 2002; (c) reference map

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    Ottawa dataset. (a) Image from May 1997; (b) image from August 1997; (c) reference map

    Fig. 2. Ottawa dataset. (a) Image from May 1997; (b) image from August 1997; (c) reference map

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    Difference maps of different algorithms on Mexico dataset. (a) Mean-ratio method; (b) neighborhood-ratio method; (c) proposed method

    Fig. 3. Difference maps of different algorithms on Mexico dataset. (a) Mean-ratio method; (b) neighborhood-ratio method; (c) proposed method

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    Change detection results of different algorithms on Mexico dataset. (a) Mean-ratio method; (b) neighborhood-ratio method; (c) proposed method

    Fig. 4. Change detection results of different algorithms on Mexico dataset. (a) Mean-ratio method; (b) neighborhood-ratio method; (c) proposed method

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    Difference maps of different algorithms on Ottawa dataset. (a) Mean-ratio method; (b) neighborhood-ratio method; (c) proposed method

    Fig. 5. Difference maps of different algorithms on Ottawa dataset. (a) Mean-ratio method; (b) neighborhood-ratio method; (c) proposed method

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    Change detection results of different algorithms on Ottawa dataset. (a) Mean-ratio method; (b) neighborhood-ratio method; (c) proposed method

    Fig. 6. Change detection results of different algorithms on Ottawa dataset. (a) Mean-ratio method; (b) neighborhood-ratio method; (c) proposed method

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    • Table 1. Quantitative analysis on change detection results of different algorithms on Mexico dataset

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      Table 1. Quantitative analysis on change detection results of different algorithms on Mexico dataset

      AlgorithmFNFPDCPCC /%Kappa
      Mean-ratio method350534504498197.910.91
      Neighborhood-ratio method457236044406897.540.89
      Proposed method30338774861098.740.95

    • Table 2. Quantitative analysis on change detection results of different algorithms on Ottawa dataset

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      Table 2. Quantitative analysis on change detection results of different algorithms on Ottawa dataset

      AlgorithmFNFPDCPCC /%Kappa
      Mean-ratio method372453249099.340.82
      Neighborhood-ratio method207948315099.070.78
      Proposed method54459281499.590.90
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    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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    Paper Information

    Category: Imaging Systems

    Received: Feb. 27, 2020

    Accepted: Apr. 23, 2020

    Published Online: Oct. 27, 2020

    The Author Email: Xiaoxia Wang (574978473@qq.com)

    DOI:10.3788/LOP57.221105

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology