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基于水下成像模型的图像清晰化算法

杨爱萍 曲畅 王建 张莉云

杨爱萍, 曲畅, 王建, 张莉云. 基于水下成像模型的图像清晰化算法[J]. 电子与信息学报, 2018, 40(2): 298-305. doi: 10.11999/JEIT170460
引用本文: 杨爱萍, 曲畅, 王建, 张莉云. 基于水下成像模型的图像清晰化算法[J]. 电子与信息学报, 2018, 40(2): 298-305. doi: 10.11999/JEIT170460
Underwater Image Visibility Restoration Based on Underwater Imaging Model[J]. Journal of Electronics & Information Technology, 2018, 40(2): 298-305. doi: 10.11999/JEIT170460
Citation: Underwater Image Visibility Restoration Based on Underwater Imaging Model[J]. Journal of Electronics & Information Technology, 2018, 40(2): 298-305. doi: 10.11999/JEIT170460

基于水下成像模型的图像清晰化算法

doi: 10.11999/JEIT170460
基金项目: 

国家自然科学基金(61372145, 61472274)

Underwater Image Visibility Restoration Based on Underwater Imaging Model

Funds: 

The National Natural Science Foundation of China (61372145, 61472274)

  • 摘要: 受水下场景中有机物和悬浮颗粒的影响,水下图像存在对比度低、颜色失真和细节丢失等问题。同时,水下场景中通常有人工光源存在,造成图像光照不均。传统基于图像去雾的方法用于水下图像复原时效果欠佳,为充分考虑水对光的吸收和散射作用,近期提出了新的水下成像模型和图像复原方法。但是这些方法未考虑红通道影响,导致估计的散射比偏大;另外,也未考虑人工光源的影响,导致估计的背景光过大。针对这些问题,该文提出一套有效的水下图像清晰化方案。首先,通过设置阈值确定是否将红通道信息用于暗通道计算,并将反映人工光源影响的饱和度指标用于散射比估计,以减小人工光源的影响。由此,提出了基于红通道预判和饱和度指标的暗通道计算方法。然后,根据三通道衰减系数比估计每个通道的透射率,可弥补目前很多方法假设蓝绿通道透射率一致的缺陷。最后,利用Shades of Gray算法估计环境光,并结合新的水下成像模型得到复原图像。实验结果表明,该文算法可显著提升图像的对比度,得到颜色自然、细节清晰的复原图像。
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出版历程
  • 收稿日期:  2017-05-15
  • 修回日期:  2017-11-02
  • 刊出日期:  2018-02-19

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