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基于HSV透射率加权修正的机载视频去雾系统设计

王健 秦春霞 杨珂 任萍 郑洁 赵远鹏 陈贵锋

王健, 秦春霞, 杨珂, 任萍, 郑洁, 赵远鹏, 陈贵锋. 基于HSV透射率加权修正的机载视频去雾系统设计[J]. 西南交通大学学报, 2021, 56(1): 160-167, 205. doi: 10.3969/j.issn.0258-2724.20190985
引用本文: 王健, 秦春霞, 杨珂, 任萍, 郑洁, 赵远鹏, 陈贵锋. 基于HSV透射率加权修正的机载视频去雾系统设计[J]. 西南交通大学学报, 2021, 56(1): 160-167, 205. doi: 10.3969/j.issn.0258-2724.20190985
WANG Jian, QIN Chunxia, YANG Ke, REN Ping, ZHENG Jie, ZHAO Yuanpeng, CHEN Guifeng. Design of Airborne Video Dehazing System for UCAV Based on HSV Transmission Weighted Correction[J]. Journal of Southwest Jiaotong University, 2021, 56(1): 160-167, 205. doi: 10.3969/j.issn.0258-2724.20190985
Citation: WANG Jian, QIN Chunxia, YANG Ke, REN Ping, ZHENG Jie, ZHAO Yuanpeng, CHEN Guifeng. Design of Airborne Video Dehazing System for UCAV Based on HSV Transmission Weighted Correction[J]. Journal of Southwest Jiaotong University, 2021, 56(1): 160-167, 205. doi: 10.3969/j.issn.0258-2724.20190985

基于HSV透射率加权修正的机载视频去雾系统设计

doi: 10.3969/j.issn.0258-2724.20190985
基金项目: 国家自然科学基金(61671383);陕西省重点产业创新链项目(2018ZDCXL-GY-03-05,2019ZDLGY14-02-02,2019ZDLGY14-02-03)
详细信息
    作者简介:

    王健(1972—),男,副教授,博士,研究方向为无人机智能情报处理技术,无人机对地观测信息处理技术,多源信息智能处理技术,无人机对地观测三维可视化技术,E-mail:jianwang@nwpu.edu.cn

  • 中图分类号: TP368.1

Design of Airborne Video Dehazing System for UCAV Based on HSV Transmission Weighted Correction

  • 摘要: 针对无人机机载雾天实时获取图像降质的问题,设计一种基于HSV (hue,saturation,value)透射率加权修正的无人机视频去雾处理系统. 首先,根据机载低功耗实时去雾系统要求,完成去雾系统总体设计;其次,根据去雾系统视频采集需要,设计数字视频BT.656/BT.1120隔行和逐行处理、视频控制、指令接收处理、TS1601视频去雾算法处理、H.264视频压缩处理和组帧等功能;最后,重点介绍系统去雾处理算法和平台设计、去雾参数化处理等功能模块的设计实现,分别使用本系统方法和相关文献方法对典型含雾图像处理,采用方差函数、平均梯度函数、TenenGrad函数等3种清晰度评价函数并做归一化处理,以进行客观评价. 研究结果表明:根据HSV分量透射率加权修正的无人机机载图像去雾处理系统设计,具有功耗小、易实现和适应性强等特点;对典型含雾图像3处理后方差函数归一化分别提高46.87%、1.44%、12.83%,平均梯度函数归一化分别提高12.54%、9.26%、11.15%,TenenGrad函数归一化分别提高53.19%、3.60%、8.82%,测试算法整体运算时间分别提高4.74、5.41倍和5.46倍.

     

  • 图 1  机载视频去雾系统总体框图

    Figure 1.  Overall block diagram of airborne video dehazing system

    图 2  TS1601模块初始化流程

    Figure 2.  TS1601 module initialization process

    图 3  系统去雾控制实现流程

    Figure 3.  System control initialization process

    图 4  去雾平台实现流程

    Figure 4.  Software design process for platform initialization

    图 5  去雾前和去雾后处理效果对比

    Figure 5.  Comparison before and after dehazing

    图 6  文献方法和本文方法对含雾图像1到3 (从上到下)去雾前后效果对比

    Figure 6.  Comparison of 1-3 (top-down) images using proposed and other methods before and after dehazing

    表  1  图6去雾性能客观评价结果

    Table  1.   Objective evaluation results of dehazing performance for fig.6

    含雾图像性能指标原图文献[2]方法文献[3]方法文献[4]方法本文方法
    1方差函数0.330.5470.6450.7150.745
    平均梯度函数0.320.6980.7230.7540.798
    TenenGrad函数0.300.5050.6950.7430.705
    运算时间/ms42.47656.61187.12114.631
    2方差函数0.230.5320.7020.6420.742
    平均梯度函数0.250.6740.7650.7120.792
    TenenGrad函数0.270.6060.8660.7860.806
    运算时间/ms115.492115.481127.65415.654
    3方差函数0.120.4310.6240.5610.633
    平均梯度函数0.130.7970.8210.8070.897
    TenenGrad函数0.170.5640.8340.7940.864
    运算时间/ms121.834136.261137.25821.251
      注:表中黑体数据表示各项评价指标中的最优结果.
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  • HE Kaiming, SUN Jian, TANG Xiaoou, et al. Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12): 2341-2353. doi: 10.1109/TPAMI.2010.168
    HE Kaiming, SUN Jian, TANG Xiaoou, et al. Guided image filtering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6): 1397-1409. doi: 10.1109/TPAMI.2012.213
    BERMAN D, TREIBITZ T, AVIDAN S. Non-local image dehazing[C]//Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition. Los Alamitos: IEEE Computer Society Press, 2016: 1674-1682
    MENG G F, WANG Y, DUAN J Y, et al. Efficient image dehazing with boundary constraint and contextual regularization[C]//Proceedings of the IEEE International Conference on Computer Vision. Los Alamitos: IEEE Computer Society Press, 2013: 617-624.
    范新南,冶舒悦,史朋飞,等. 改进大气散射模型实现的图像去雾算法[J]. 计算机辅助设计与图形学学报,2019,31(7): 1148-1155.

    FAN Xinnan, YE Shuyue, SHI Pengfei, et al. An image dehazing algorithm based on improved atmospheric scattering model[J]. Journal of Computer-Aided Design & Computer Graphics, 2019, 31(7): 1148-1155.
    CHEN Xuesong, LU Haihua, CHENG Kaili, et al. Sequentially refined spatial and channel-wise feature aggregation in encoder-decoder network for single image dehazing[C]//IEEE International Conference on Image Processing. [S.l.]: IEEE, 2019: 2776-2780.
    HU Haimiao, ZHANG Hongda, ZHAO Zichen, et al. Adaptive single image dehazing using joint local-global illumination adjustment[J]. IEEE Transactions on Multimedia, 2020, 22(6): 1485-1495. doi: 10.1109/TMM.2019.2944260
    ZHAO D, XU L, YAN Y, et al. Multi-scale optimal fusion model for single image dehazing[J]. Signal Processing-Image Communication, 2019, 74: 253-265. doi: 10.1016/j.image.2019.02.004
    LIU P J, HORNG S J, LIN J S, et al. Contrast in haze removal:configurable contrast enhancement model based on dark channel prior[J]. IEEE Transactions on Image Processing, 2019, 5(28): 2212-2227.
    QIN M J, XIE F Y, W Li, et al. Dehazing for multi-spectral remote sensing images based on a convolutional neural network with the residual architecture[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11(5): 1645-1655.
    SINGH P, KOMODAKIS N. Cloud-gan: cloud removal for sentinel-2 imagery using a cyclic consistent generative adversarial networks[C]//IEEE International Geoscience and Remote Sensing Symposium. [S.l.]: IEEE, 2018: 1772-1775.
    DING J, YAN Z, WEI X, et al. Light-weight residual learning for single image dehazing[J]. Journal of Elec- tronic Imaging, 2019, 28(3): 033013.1-033013.13.
    周晓波,何魁华,周聪. 基于FPGA的图像高速去雾实时系统设计实现[J]. 电视技术,2018,42(4): 67-72.

    ZHOU Xiaobo, HE Kuijua, ZHOU Cong, et al. Design and implementation of high-speed real-time image dehazing system based on FPGA[J]. Video Engineering, 2018, 42(4): 67-72.
    张海斌. 基于Zynq实时视频图像去雾系统的设计[D]. 上海: 上海师范大学, 2018.
    匡娇娇,张瑞珏,王慧芳. 改进的暗通道去雾算法在多核DSP上的并行实现[J]. 武汉大学学报(理学版),2016,62(6): 519-524.

    KUANG Jiaojiao, ZHANG Ruijue, WANG Huifang, et al. Parallel implementaiton of improved dark channel dehazing algorithm on multicores DSP[J]. Journal of Wuhan University of Technology (Natural Science Edition), 2016, 62(6): 519-524.
    ZHANG B, WEI J. Hardware implementation for haze removal with adaptive filtering[J]. IEEE Access, 2019, 7(11): 142498-142506.
    Techwell Corporation. Data sheet of TW9912[M/OL]. [S.l.]: Techwell Corporation, 2011[2019-10-08]. http://www.techwelllinc.com.
    Semtech Corporation. Gennum corporation GS2971 data sheet[M/OL]. [S.l.]: Semtech Corporation, 2009[2019-10-08]. http://www.semtech.com.
    Surveillance Semiconductor. TS1601 3D HD video enhance processor product datasheet[M/OL]. [S.l.]: Surveillance Semiconductor, 2012[2019-10-08]. http://www.tssic.com.
    NXP Semiconductors. i.MX6 dual/6 quad multimedia applications processor reference manual[M/OL]. Freescale: NXP Semiconductors, 2012[2019-10-08]. http://www.nxp.com.cn.
    王健,辛向龙,张修飞. 基于i.MX6无人机视频码率受控的压缩系统设计[J]. 火力与指挥控制,2016,41(11): 148-152. doi: 10.3969/j.issn.1002-0640.2016.11.034

    WANG Jian, XIN Xianglong, ZHANG Xiufei. Design of the embedded video process system based on i.MX6[J]. Fire Control & Command Control, 2016, 41(11): 148-152. doi: 10.3969/j.issn.1002-0640.2016.11.034
    王健,秦春霞,杨珂,等. 无人机机载视频去雾系统设计[J]. 计算机测量与控制,2020,28(6): 135-139.

    WANG Jian, QIN Chunxia, YANG Ke, et al. Design of the airborne video demisting system for UCAV[J]. Computer Measurement & Control, 2020, 28(6): 135-139.
    耿威. 基于视频图像的雾天能见度检测方法研究与实现[D]. 南京: 东南大学, 2013.
    李雪,江旻珊. 光学显微成像系统图像清晰度评价函数的对比[J]. 光学仪器,2018,40(1): 28-38.

    LI Xue, Jiang Minshan. Comparison of sharpness function based on microscope[J]. Optical Instruments, 2018, 40(1): 28-38.
    WANG Zhou, BOVIK A C, SHEIKH H R, et al. Image quality assessment:from error visibility to structural similarity[J]. IEEE Transactions on Image Processing, 2004, 13(4): 600-612. doi: 10.1109/TIP.2003.819861
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出版历程
  • 收稿日期:  2019-10-12
  • 修回日期:  2020-03-16
  • 网络出版日期:  2020-04-08
  • 刊出日期:  2021-02-01

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