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基于多子块协同单尺度Retinex的浓雾图像增强

高原原 胡海苗

高原原, 胡海苗. 基于多子块协同单尺度Retinex的浓雾图像增强[J]. 北京航空航天大学学报, 2019, 45(5): 944-951. doi: 10.13700/j.bh.1001-5965.2018.0528
引用本文: 高原原, 胡海苗. 基于多子块协同单尺度Retinex的浓雾图像增强[J]. 北京航空航天大学学报, 2019, 45(5): 944-951. doi: 10.13700/j.bh.1001-5965.2018.0528
GAO Yuanyuan, HU Haimiao. Foggy image enhancement based on multi-block coordinated single-scale Retinex[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(5): 944-951. doi: 10.13700/j.bh.1001-5965.2018.0528(in Chinese)
Citation: GAO Yuanyuan, HU Haimiao. Foggy image enhancement based on multi-block coordinated single-scale Retinex[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(5): 944-951. doi: 10.13700/j.bh.1001-5965.2018.0528(in Chinese)

基于多子块协同单尺度Retinex的浓雾图像增强

doi: 10.13700/j.bh.1001-5965.2018.0528
基金项目: 

国家自然科学基金 61801448

详细信息
    作者简介:

    高原原  女, 博士研究生, 工程师。主要研究方向:图像处理

    胡海苗  男, 副教授。主要研究方向:图像处理

    通讯作者:

    高原原. E-mail:gyy002005@163.com

  • 中图分类号: TP391

Foggy image enhancement based on multi-block coordinated single-scale Retinex

Funds: 

National Natural Science Foundation of China 61801448

More Information
  • 摘要:

    针对现有算法增强雾气分布不均匀的浓雾图像效果不理想的问题,提出了一种基于多子块协同单尺度Retinex的浓雾图像增强算法。该算法不同于传统的利用全局统计量获取动态截断值的Retinex算法,首先将图像划分为多个子块,计算出适合不同浓度雾气的动态截断值;然后,利用动态截断值对高频细节信息进行动态范围调整,得到多幅局部最优的图像;最后,融合多幅局部最优图像生成高质量的结果,从而实现浓雾图像每个区域细节的增强。实验结果表明,所提算法能够有效去除不均匀浓雾,并保证去雾后图像的亮度保持在适合人眼观察的范围。

     

  • 图 1  单尺度Retinex处理结果

    Figure 1.  Processed result of single-scale Retinex

    图 2  利用不同局部均值统计拉伸量化后结果

    Figure 2.  Stretched quantization result using different local mean statistics

    图 3  基于多子块协同的单尺度Retinex算法流程

    Figure 3.  Flowchart of multi-block coordinated single-scale Retinex algorithm

    图 4  去雾效果对比示例1

    Figure 4.  Example 1 of defogged result comparison

    图 5  去雾效果对比示例2

    Figure 5.  Example 2 of defogged result comparison

    图 6  去雾效果对比示例3

    Figure 6.  Example 3 of defogged result comparison

    表  1  图 4去雾后客观指标评价结果

    Table  1.   Objective indicator evaluation results of defogged images in Fig. 4

    图像编号 h e γ
    图 4(b) 6.57 284.20 8.42
    图 4(c) 6.92 56.96 3.82
    图 4(d) 7.38 247.70 7.07
    图 4(e) 5.43 8.87 2.21
    图 4(f) 7.24 286.73 9.47
    下载: 导出CSV

    表  2  图 5去雾后客观指标评价结果

    Table  2.   Objective indicator evaluation results of defogged images in Fig. 5

    图像编号 h e γ
    图 5(b) 6.23 2.38 4.60
    图 5(c) 6.94 1.36 1.89
    图 5(d) 7.11 0.10 3.03
    图 5(e) 7.46 0.51 1.67
    图 5(f) 6.38 4.35 6.18
    下载: 导出CSV

    表  3  图 6去雾后客观指标评价结果

    Table  3.   Objective indicator evaluation results of defogged images in Fig. 6

    图像编号 h e γ
    图 6(b) 6.59 248.67 7.48
    图 6(c) 6.46 283.46 3.47
    图 6(d) 7.53 281.39 6.78
    图 6(e) 5.43 9.39 1.37
    图 6(f) 7.37 358.36 13.13
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-09-06
  • 录用日期:  2018-10-17
  • 刊出日期:  2019-05-20

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