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基于雾线先验的时空关联约束视频去雾算法

姚婷婷 梁越 柳晓鸣 胡青

姚婷婷, 梁越, 柳晓鸣, 胡青. 基于雾线先验的时空关联约束视频去雾算法[J]. 电子与信息学报, 2020, 42(11): 2796-2804. doi: 10.11999/JEIT190403
引用本文: 姚婷婷, 梁越, 柳晓鸣, 胡青. 基于雾线先验的时空关联约束视频去雾算法[J]. 电子与信息学报, 2020, 42(11): 2796-2804. doi: 10.11999/JEIT190403
Tingting YAO, Yue LIANG, Xiaoming LIU, Qing HU. Video Dehazing Algorithm via Haze-line Prior with Spatiotemporal Correlation Constraint[J]. Journal of Electronics & Information Technology, 2020, 42(11): 2796-2804. doi: 10.11999/JEIT190403
Citation: Tingting YAO, Yue LIANG, Xiaoming LIU, Qing HU. Video Dehazing Algorithm via Haze-line Prior with Spatiotemporal Correlation Constraint[J]. Journal of Electronics & Information Technology, 2020, 42(11): 2796-2804. doi: 10.11999/JEIT190403

基于雾线先验的时空关联约束视频去雾算法

doi: 10.11999/JEIT190403
基金项目: 中央高校基本科研业务费专项资金(3132020208),国家自然科学基金(31700742)
详细信息
    作者简介:

    姚婷婷:女,1988年生,讲师,研究方向为计算机视觉与图像处理等

    梁越:男,1996年生,硕士生,研究方向为雾天视频处理

    柳晓鸣:男,1959年生,教授,研究方向为海上交通电子信息处理、雷达信号处理等

    胡青:男,1978年生,教授,研究方向为海事信息传输、自动识别系统等

    通讯作者:

    姚婷婷 ytt1030@dlmu.edu.cn

  • 1) SfM算法程序可以从网址: http://ccwu.me/vsfm/获得
  • 中图分类号: TN911.73, TP391

Video Dehazing Algorithm via Haze-line Prior with Spatiotemporal Correlation Constraint

Funds: The Fundamental Research Funds for the Central Universities (3132020208), The National Natural Science Foundation of China (31700742)
  • 摘要: 现有视频去雾算法由于缺少对视频结构关联约束和帧间一致性分析,容易导致连续帧去雾结果在颜色和亮度上存在突变,同时去雾后的前景目标边缘区域也容易出现退化现象。针对上述问题,该文提出一种基于雾线先验的时空关联约束视频去雾算法,通过引入每帧图像在空间邻域中具有的结构关联性和时间邻域中具有的连续一致性,提高视频去雾算法的求解准确性和鲁棒性。算法首先使用暗通道先验估计每帧图像的大气光向量,并结合雾线先验求取初始透射率图。然后引入加权最小二乘边缘保持平滑滤波器对初始透射率图进行空间平滑,消除奇异点和噪声对估计结果的影响。进一步利用相机参数刻画连续帧间透射率图的时序变化规律,对独立求取的每帧透射率图进行时序关联修正。最后根据雾图模型获得最终的视频去雾结果。定性和定量的对比实验结果表明,该算法下视频去雾结果的帧间过渡更加自然,同时对每一帧图像的色彩还原更加准确,图像边缘的细节信息显示也更加丰富。
  • 图  1  雾线示意图

    图  2  本文算法总体框图

    图  3  同一帧各阶段透射率图对比

    图  4  视频Ship和Beach连续帧下去雾结果对比

    图  5  单帧图像去雾结果对比

    表  1  各算法在不同评价指标下的性能对比

    视频集算法VCMSSIMHCC信息熵UQI
    Bali文献[16]算法47.7398±4.35020.6614±0.0459–0.3173±0.04856.8571±0.16410.5923±0.0425
    文献[17]算法30.1254±5.62770.5526±0.0215–0.2960±0.03267.3794±0.07920.4669±0.0225
    文献[19]算法41.6247±4.94480.8693±0.0041–0.0813±0.05817.5121±0.04470.8061±0.0086
    文献[20]算法37.4402±4.02380.6221±0.0214–0.1968±0.10616.5753±0.14450.5889±0.0335
    文献[21]算法49.7812±4.47820.7001±0.1116–0.0312±0.06397.5413±0.05720.8819±0.0101
    本文算法51.3852±6.32230.6679±0.0249–0.2532±0.02517.9253±0.13220.8938±0.0285
    Blenheim文献[16]算法35.5897±2.20010.8686±0.01290.0667±0.01656.5025±0.19670.7960±0.0258
    文献[17]算法37.5815±1.62240.8260±0.03660.4688±0.09457.0697±0.09030.7661±0.0373
    文献[19]算法26.0153±1.92590.9123±0.00350.4406±0.02317.0390±0.07160.8332±0.0209
    文献[20]算法18.2786±2.27690.8215±0.02620.2759±0.03396.4305±0.06020.7721±0.0449
    文献[21]算法64.9899±1.78270.6632±0.00940.0377±0.01356.2305±0.16370.7239±0.0108
    本文算法40.0056±0.91160.9764±0.00220.7940±0.09697.4379±0.04340.9549±0.0131
    Playground文献[16]算法50.2886±6.46190.8954±0.0129–0.0276±0.02495.9694±0.45800.9021±0.0123
    文献[17]算法31.9030±8.12110.7788±0.05750.0115±0.11777.4964±0.09110.7529±0.0703
    文献[19]算法43.6243±3.56590.9205±0.00860.1664±0.05197.2406±0.10600.8967±0.0142
    文献[20]算法35.5237±3.24260.7807±0.0182–0.1450±0.05956.9652±0.09300.7728±0.0309
    文献[21]算法51.8038±5.38900.6917±0.0258–0.0457±0.04176.8567±0.20890.8213±0.0204
    本文算法54.4761±10.97460.9546±0.02300.0587±0.05067.1156±0.17210.9379±0.0421
    Stele文献[16]算法30.7638±15.73690.3649±0.02880.4263±0.12346.8163±0.08280.7349±0.0476
    文献[17]算法44.2502±3.14280.7392±0.01990.0577±0.04437.1132±0.08280.7665±0.0296
    文献[19]算法51.0145±5.45310.8529±0.01090.3319±0.08466.5512±0.14770.7671±0.0174
    文献[20]算法40.8246±4.81870.8214±0.01570.2711±0.10346.2814±0.12420.7805±0.0233
    文献[21]算法75.7723±3.88980.5875±0.01660.0227±0.04197.3425±0.10650.7881±0.0252
    本文算法29.9452±3.07790.9045±0.02220.4791±0.11637.9275±0.09330.8580±0.0361
    Motocycle文献[16]算法35.9520±15.95570.6854±0.0389–0.0101±0.02546.9864±0.05070.5594±0.0292
    文献[17]算法49.8669±5.50660.7500±0.03240.3960±0.08827.4345±0.05830.8401±0.0319
    文献[19]算法33.4659±11.35330.8693±0.00470.2797±0.04757.0304±0.06460.8535±0.0114
    文献[20]算法25.9303±7.02410.3705±0.0650–0.3172±0.31565.7929±0.38120.1670±0.0547
    文献[21]算法69.1006±4.91470.5231±0.01460.0111±0.02997.6674±0.10620.7442±0.0219
    本文算法52.0758±8.09320.7720±0.02810.5653±0.08967.2598±0.09920.8955±0.0261
    Ship文献[16]算法38.8112±11.48190.7648±0.11410.0505±0.18177.5924±0.13690.6952±0.1243
    文献[17]算法33.9529±3.17270.8063±0.01620.0147±0.05517.5878±0.07910.7969±0.0267
    文献[19]算法35.1544±10.51720.8396±0.01040.0313±0.04497.5395±0.04310.7682±0.0134
    文献[20]算法33.8128±3.75080.5602±0.0496–0.3243±0.02126.8355±0.15860.3912±0.0669
    文献[21]算法53.0535±4.76260.6343±0.0167–0.1062±0.00996.8996±0.10230.7783±0.0097
    本文算法46.0955±3.61690.8365±0.01250.2137±0.08637.8230±0.01310.7985±0.0206
    Beach文献[16]算法16.2818±4.70950.9786±0.00960.7025±0.08647.3837±0.04570.9702±0.0133
    文献[17]算法38.2337±5.43350.7396±0.0096–0.2957±0.03717.4769±0.08440.6582±0.0159
    文献[19]算法9.4401±2.48710.8823±0.00500.0043±0.04547.4627±0.02370.8078±0.0062
    文献[20]算法22.7816±3.32440.4762±0.4821–0.3919±0.02076.4422±0.20080.2868±0.0615
    文献[21]算法32.7816±8.85430.7221±0.02070.0181±0.00827.4134±0.08510.8845±0.0031
    本文算法28.2158±5.86220.9802±0.01540.8117±0.08817.8108±0.02400.9415±0.0197
    下载: 导出CSV

    表  2  各算法计算效率对比

    算法文献[16]算法文献[17]算法文献[19]算法文献[20]算法文献[21]算法本文算法
    时间(s)182.26541.09850.10761.82500.26011.0502
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-06-05
  • 修回日期:  2020-06-22
  • 网络出版日期:  2020-07-17
  • 刊出日期:  2020-11-16

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