SUN Shiwei, LIU Jinhu, MA Wenjun, WANG Xiaopeng. Adaptive optimization defogging algorithm based on linear model[J]. Journal of Applied Optics, 2020, 41(1): 114-119. DOI: 10.5768/JAO202041.0102008
Citation: SUN Shiwei, LIU Jinhu, MA Wenjun, WANG Xiaopeng. Adaptive optimization defogging algorithm based on linear model[J]. Journal of Applied Optics, 2020, 41(1): 114-119. DOI: 10.5768/JAO202041.0102008

Adaptive optimization defogging algorithm based on linear model

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  • Received Date: May 26, 2019
  • Revised Date: July 27, 2019
  • Available Online: March 30, 2020
  • Aiming at the problem of insufficient estimate of transmittance and atmospheric light in linear transformation algorithm, an adaptive optimization defogging algorithm based on linear model was proposed. First, the edge information model was used to enhance the detailed information of the initial transmittance image, so that the edge region details of the restored image were richer. Then, an adaptive optimization transmittance was obtained to better process the image including the depth of field region by the dark channel prior. Finally, the local atmospheric light estimate method was used instead of the quadtree method to avoid the inaccuracy of atmospheric light estimate, and the image was restored by combining with the physical model. The simulation experiment was carried out in matlab2014, and the experimental results show that the proposed algorithm has good validity and timeliness.
  • [1]
    WANG J Z, WANG W M, WANG R G, et al. CSPS: an adaptive pooling method for image classification[J]. IEEE Transactions on Multimedia,2016,18(6):1000-1010. doi: 10.1109/TMM.2016.2544099
    [2]
    WANG Wencheng, YUAN Xiaohui. Recent advances in image dehazing[J]. IEEE/CAA Journal of Automatica Sinica,2017,4(3):410-436. doi: 10.1109/JAS.2017.7510532
    [3]
    XU H T, ZHAI G T, WU X L, et al. Generalized equalization model for image enhancement[J]. IEEE Transactions on Multimedia,2014,16(1):68-82. doi: 10.1109/TMM.2013.2283453
    [4]
    代晴晴, 范之国, 宋强, 等. 全局参数自动估计的彩色图像偏振去雾方法[J]. 应用光学,2018,39(4):511-517.

    DAI Qingqing, FAN Zhiguo, SONG Qiang, et al. Polarization defogging method for color image based on automatic estimation of global parameters[J]. Journal of Applied Optics,2018,39(4):511-517.
    [5]
    TAN R T. Visibility in bad weather from a single image[C]. IEEE Conference on Computer Vision & Pattern Recognition, USA:IEEE, 2008
    [6]
    MENG G F, WANG Y, DUAN J Y, et al. Efficient image dehazing with boundary constraint and contextual regularization[C]. IEEE International Conference on Computer Vision.Australia:IEEE, 2013: 617-624.
    [7]
    禹晶, 李大鹏, 廖庆敏. 基于物理模型的快速单幅图像去雾方法[J]. 自动化学报,2011,37(2):143-149.

    YU Jing, LI Dapeng, LIAO Qingmin. Physical-based fast single fog removal[J]. Acta Automatica Sinica,2011,37(2):143-149.
    [8]
    HE K M, SUN J, TANG X O. Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence,2011,33(12):2341-2353.
    [9]
    WANG W C, YUAN X H, WU X J, et al. Fast image dehazing method based on linear transformation[J]. IEEE Transactions on Multimedia,2017,19(6):1142-1155. doi: 10.1109/TMM.2017.2652069
    [10]
    杨燕, 李一菲, 岳辉. 一种自适应线性透射率估计去雾算法[J]. 应用光学,2019,40(3):447-453.

    YANG Yan, LI Yifei, YUE Hui. Adaptive linear transmission estimation dehazing algorithm[J]. Journal of Applied Optics,2019,40(3):447-453.
    [11]
    HUANG S C, CHEN B H, WANG W J. Visibility restoration of single hazy images captured in real-world weather conditions[J]. IEEE Transactions on Circuits & Systems for Video Technology,2014,24(10):1814-1824.
    [12]
    SUN W, WANG H, SUN C H, et al. Fast single image haze removal via local atmospheric light veil estimation[J]. Computers & Electrical Engineering,2015,46:371-383.
    [13]
    HE K M, SUN J, TANG X O. Guided image filtering[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence,2013,35(6):1397-1409.
    [14]
    ZHU Q S, MAI J, SHAO L. A Fast single image haze removal algorithm using color attenuation prior[J]. IEEE Transactions on Image Processing,2015,24(11):3522-3533. doi: 10.1109/TIP.2015.2446191
    [15]
    ANCUTI C O, ANCUTI C, TIMOFTE R, et al. I-HAZE: a dehazing benchmark with real hazy and haze-free indoor images[J]. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops,2018,1804:754-762.
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