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Laser & Optoelectronics Progress, Volume. 57, Issue 20, 201006(2020)

Shadow Compensation of High-Resolution Remote Sensing Images Based on Improved Logarithmic Transformation and Local Enhancement

Yuanyuan Feng1, Xianjun Gao1,2、*, Yuanwei Yang1,2, and Fan Deng1
Author Affiliations
  • 1School of Geoscience, Yangtze University, Wuhan, Hubei 430100, China
  • 2State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei 430079, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (12)
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    References (15)
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    Figures & Tables(12)
    Influence of parameter V on logarithmic transformation curve

    Fig. 1. Influence of parameter V on logarithmic transformation curve

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    Influence of parameter V on compensation result. (a) Original image; (b) shadow detection result; (c) compensation effect when V = 0.5; (d) compensation effect when V = 1; (e) compensation effect when V=2.5; (f) compensation effect when V=3

    Fig. 2. Influence of parameter V on compensation result. (a) Original image; (b) shadow detection result; (c) compensation effect when V = 0.5; (d) compensation effect when V = 1; (e) compensation effect when V=2.5; (f) compensation effect when V=3

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    Compensation results from three methods. (a) Original image; (b) logarithmic transformation result; (c) local compensation result; (d) joint compensation result

    Fig. 3. Compensation results from three methods. (a) Original image; (b) logarithmic transformation result; (c) local compensation result; (d) joint compensation result

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    Acquisition diagram of similarity pairs during automatic compensation

    Fig. 4. Acquisition diagram of similarity pairs during automatic compensation

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    Comparison among compensation results of urban image 1. (a) Original image; (b) selected area of detail comparison map; (c) compensation result by Wallis method; (d) local compensation effect; (e) compensation result by original logarithmic transformation; (f) compensation result by proposed method;(g) detail of compensation result by original logarithmic transformation; (h) detail of compensation result by proposed method

    Fig. 5. Comparison among compensation results of urban image 1. (a) Original image; (b) selected area of detail comparison map; (c) compensation result by Wallis method; (d) local compensation effect; (e) compensation result by original logarithmic transformation; (f) compensation result by proposed method;(g) detail of compensation result by original logarithmic transformation; (h) detail of compensation result by proposed method

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    Comparison among compensation results of urban image 2. (a) Original image; (b) selected area of detail comparison map; (c) compensation result by Wallis method; (d) local compensation effect;(e) compensation result by original logarithmic transformation; (f) compensation result by proposed method;(g) detail of compensation result by original logarithmic transformation; (h) detail of compensation result by proposed method

    Fig. 6. Comparison among compensation results of urban image 2. (a) Original image; (b) selected area of detail comparison map; (c) compensation result by Wallis method; (d) local compensation effect;(e) compensation result by original logarithmic transformation; (f) compensation result by proposed method;(g) detail of compensation result by original logarithmic transformation; (h) detail of compensation result by proposed method

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    Comparison among compensation results of urban image 3. (a) Original image; (b) selected area of detail comparison map; (c) compensation result by Wallis method; (d) local compensation effect;(e) compensation result by original logarithmic transformation; (f) compensation result by proposed method;(g) detail of compensation result by original logarithmic transformation; (h) detail of compensation result by proposed method

    Fig. 7. Comparison among compensation results of urban image 3. (a) Original image; (b) selected area of detail comparison map; (c) compensation result by Wallis method; (d) local compensation effect;(e) compensation result by original logarithmic transformation; (f) compensation result by proposed method;(g) detail of compensation result by original logarithmic transformation; (h) detail of compensation result by proposed method

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    Comparison among shadow compensation results of building image. (a) Original image; (b) compensation result by Wallis method; (c) local compensation result;(d) compensation result by original logarithmic transformation; (e) compensation result by the proposed method

    Fig. 8. Comparison among shadow compensation results of building image. (a) Original image; (b) compensation result by Wallis method; (c) local compensation result;(d) compensation result by original logarithmic transformation; (e) compensation result by the proposed method

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    • Table 1. Experimental data of logarithmic transformation

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      Table 1. Experimental data of logarithmic transformation

      IndexOriginal valueof shadedareaNon-shadedareatarget valueCompensationeffect whenV=0.5Compensationeffect whenV=1Compensationeffect whenV=2.5Compensationeffect whenV=3
      Meanbrightness35.681361.525813.732626.502960.269570.3108
      Meangradient5.915710.78432.82134.34338.62239.9473

    • Table 2. Image quality under each compensation method

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      Table 2. Image quality under each compensation method

      IndexOriginal value ofshaded areaNon-shaded areatarget valueLogarithmictransformation resultLocalcompensation resultJoint compensationresult
      Mean brightness35.681361.325887.009643.882661.1334
      Mean gradient5.915710.51437.132811.921210.0059

    • Table 3. Evaluation of shadow compensation results

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      Table 3. Evaluation of shadow compensation results

      ImageIndexOriginal valueof shadedareaNon-shadedarea targetvalueCompensationresult byWallismethodLocalcompensationresultCompensationresult by originallogarithmictransformationCompensationresult byproposedmethod
      1Meanbrightness32.759257.351242.914242.881048.974657.3512
      Mean gradient4.51167.27903.54628.63966.36768.9232
      2Meanbrightness50.566086.866872.685065.150173.004986.2285
      Meangradient7.655715.25376.192313.137610.018114.0568
      3Meanbrightness29.102953.779437.563043.712549.775753.2503
      Meangradient4.62649.13614.95758.80155.95488.4537
      4Meanbrightness50.101998.879171.491675.148179.716195.5914
      Meangradient6.015510.16747.68679.56547.962010.0674

    • Table 4. Operation performance

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      Table 4. Operation performance

      ImageImage size /(pixel×pixel )Number of shaded pixelsCompensation time /s
      Urban image 1863×5851665411.13
      Urban image 2884×6132120221.62
      Urban image 3622×6381094381.01
      Building image257×26696070.25
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    Yuanyuan Feng, Xianjun Gao, Yuanwei Yang, Fan Deng. Shadow Compensation of High-Resolution Remote Sensing Images Based on Improved Logarithmic Transformation and Local Enhancement[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201006

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    Paper Information

    Category: Image Processing

    Received: Jan. 19, 2020

    Accepted: Feb. 24, 2020

    Published Online: Oct. 13, 2020

    The Author Email: Gao Xianjun (junxgao@whu.edu.cn)

    DOI:10.3788/LOP57.201006

    Topics

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