Journal of Infrared and Millimeter Waves, Volume. 40, Issue 3, 369(2021)

Detection of building area with complex background by night light remote sensing

Hai LI1, Yang LI2, and Zheng-Rong ZUO1、*
Author Affiliations
  • 1National Key Laboratory of Multi-spectral Information Processing Technology, Huazhong University of Science and Technology, Wuhan 430074, China
  • 2Institute of Robotics, Shanghai Jiaotong University, Shanghai 200240, China
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    Figures & Tables(21)
    Buildings are characterized by visible light remote sensing in night light remote sensing images(a) Local structural similarity(b) Remote context
    Flow chart of detection network
    Four kinds of Classification network structure W
    Prior box matching correction
    4 kinds of network detectors
    Sampling point graph of deformable convolution with unit number 9 passing through 3 layers
    Structure comparison between GC module and CGC module
    Two CGC connection modes
    RGB remote sensing picture and night light remote sensing picture(a) RGB of 123 object, (b)RGB of 4 object, (c) Sensing of 123 object, (d) Sensing of 4 object
    Sample picture of luminous remote sensing data set(object and category are marked in the picture)
    Network detection image(a)No module added(b)Add CGC2 module
    Different networks’ P-R curve
    Different networks’ F-measure
    • Table 1. Hidden layer characteristics of different networks

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      Table 1. Hidden layer characteristics of different networks

      输入A网络B网络D网络
    • Table 2. Attention graphs of different global semantic modules

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      Table 2. Attention graphs of different global semantic modules

      原图输入GC模块CGC连接方式1CGC连接方式2
    • Table 3. All categories in the data set

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      Table 3. All categories in the data set

      类别(单位)12345
      数量/个52831138278227166
      平均边长/像素721601010318269
      平均PSNR/dB19.2619.8921.1721.7123.24
    • Table 4. The performance of 4 kinds of networks on the night light remote sensing data set

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      Table 4. The performance of 4 kinds of networks on the night light remote sensing data set

      分类网络参数量(107mAP

      A

      B

      C

      D

      2.563 750 4

      2.522 928 0

      2.191 003 2

      0.636 686 4

      0.387 9

      0.389 6

      0.419 9

      0.404 0

    • Table 5. Adding expansion convolution in different stages

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      Table 5. Adding expansion convolution in different stages

      阶段数56781-8
      mAP0.400 90.401 30.400 80.401 20.400 8
    • Table 6. Add GC module in different stages

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      Table 6. Add GC module in different stages

      阶段数45671-7
      mAP0.408 90.406 30.409 10.413 70.416 7
    • Table 7. Comparison of ablation experiments of D-network modules

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      Table 7. Comparison of ablation experiments of D-network modules

      实验CNECNDCNSSD匹配GE 匹配GCCGC1CGC2mAP
      10.383 3
      20.387 6
      30.398 2
      40.404 0
      50.400 8
      60.416 7
      70.424 5
      80.429 6
    • Table 8. Different network detection effects

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      Table 8. Different network detection effects

      网络12345mAP帧数
      Yolov30.2640.3440.3980.3490.4350.35806.7
      Fcos0.2780.3510.4230.3950.4800.38545.6
      Faster R-CNN0.2870.3910.6010.2810.4140.39494.3
      D0.3020.3500.4570.4010.5100.404016.7
      CGC-D0.3970.3630.4670.4070.5140.429614.3
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    Hai LI, Yang LI, Zheng-Rong ZUO. Detection of building area with complex background by night light remote sensing[J]. Journal of Infrared and Millimeter Waves, 2021, 40(3): 369

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    Paper Information

    Category: Research Articles

    Received: Apr. 5, 2020

    Accepted: --

    Published Online: Sep. 9, 2021

    The Author Email: Zheng-Rong ZUO (zhrzuo@hust.edu.cn)

    DOI:10.11972/j.issn.1001-9014.2021.03.014

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