Acta Optica Sinica, Volume. 39, Issue 12, 1228004(2019)

Analysis and Removal of Stripe Noise in AGRI Remote-Sensing Images

Wenli Li1,2, Kai Li1,2, Di Peng1,2, and Changpei Han2、*
Author Affiliations
  • 1University of Chinese Academy of Sciences, Beijing 100049
  • 2Key Laboratory of Infrared Detection and Imaging Technology, Chinese Academy of Sciences, Shanghai 200083, China
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    Figures & Tables(11)
    RSR of different pixels of detector in AGRI at 13.5 μm
    AGRI local remote sensing images affected by stripe noise. (a) 5.8 μm band; (b) 6.9 μm band; (c) 13.5 μm band
    Sub-images of four pixels of detector in AGRI at 13.5 μm band. (a) Sub-image of No. 1 pixel; (b) sub-image of No. 2 pixel; (c) sub-image of No. 3 pixel; (d) sub-image of No. 4 pixel
    Gradient maps of images with stripes in different directions. (a) Vertical direction; (b) horizontal direction
    Partial image extracted from original image at 13.5 μm band and images after removing stripes by different methods. (a) Original image; (b) HM; (c) WFAF; (d) SSGE; (e) UTV; (f) proposed method
    Original image at 13.5 μm band and longitudinal mean power spectra of images processed by different methods. (a) Original image; (b) HM; (c) WFAF; (d) SSGE; (e) UTV; (f) proposed method
    Original image at 13.5 μm band and longitudinal mean values of images processed by different methods. (a) Original image; (b) HM; (c) WFAF; (d) SSGE; (e) UTV; (f) proposed method
    Original image at 13.5 μm band and longitudinal mean values of images processed by different methods
    • Table 1. NR of each band after processing by different methods

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      Table 1. NR of each band after processing by different methods

      Band /μmNR
      OriginalHMWFAFSSGEUTVProposed method
      5.811.7681.8051.8092.1913.334
      6.911.7041.6691.6691.7832.408
      13.511.6792.0752.0792.4463.264
    • Table 2. ICV of each band after processing by different methods

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      Table 2. ICV of each band after processing by different methods

      Band /μmICV
      SampleOriginalHMWFAFSSGEUTVProposed method
      Area 116.2618.1620.0120.8524.3626.18
      5.8Area 235.6454.8360.2257.6456.1761.69
      Area 365.01120.59131.73121.63133.57154.18
      Area 113.7413.5213.213.1215.5822.86
      6.9Area 252.28112.7685.1291.79118.78140.14
      Area 358.33153.94146.72152.75167.96217.56
      Area 116.9517.519.8320.7721.6626.61
      13.5Area 247.9468.2693.97100.68100.52114.19
      Area 349.9980.792.6186.0291.86137.38
    • Table 3. MRD of each band after processing by different methods

      View table

      Table 3. MRD of each band after processing by different methods

      Band /μmMRD
      SampleOriginalHMWFAFSSGEUTVProposed method
      Area 101.6393.2123.6145.9162.235
      5.8Area 201.5792.4842.6213.9112.379
      Area 301.4821.1621.1912.2411.136
      Area 101.9553.7623.7033.6912.303
      6.9Area 202.6326.5636.6478.1776.104
      Area 301.8382.7602.9573.2192.700
      Area 101.2272.6872.8493.3073.003
      13.5Area 201.1872.7512.5542.2012.083
      Area 301.4071.6871.7971.9051.680
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    Wenli Li, Kai Li, Di Peng, Changpei Han. Analysis and Removal of Stripe Noise in AGRI Remote-Sensing Images[J]. Acta Optica Sinica, 2019, 39(12): 1228004

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jul. 5, 2019

    Accepted: Aug. 30, 2019

    Published Online: Dec. 6, 2019

    The Author Email: Changpei Han (wenuestc986@163.com)

    DOI:10.3788/AOS201939.1228004

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