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基于加权L1正则化的水下图像清晰化算法

杨爱萍 张莉云 曲畅 王建

杨爱萍, 张莉云, 曲畅, 王建. 基于加权L1正则化的水下图像清晰化算法[J]. 电子与信息学报, 2017, 39(3): 626-633. doi: 10.11999/JEIT160481
引用本文: 杨爱萍, 张莉云, 曲畅, 王建. 基于加权L1正则化的水下图像清晰化算法[J]. 电子与信息学报, 2017, 39(3): 626-633. doi: 10.11999/JEIT160481
YANG Aiping, ZHANG Liyun, QU Chang, WANG Jian. Underwater Images Visibility Improving Algorithm with Weighted L1 Regularization[J]. Journal of Electronics and Information Technology, 2017, 39(3): 626-633. doi: 10.11999/JEIT160481
Citation: YANG Aiping, ZHANG Liyun, QU Chang, WANG Jian. Underwater Images Visibility Improving Algorithm with Weighted L1 Regularization[J]. Journal of Electronics and Information Technology, 2017, 39(3): 626-633. doi: 10.11999/JEIT160481

基于加权L1正则化的水下图像清晰化算法

doi: 10.11999/JEIT160481
基金项目: 

国家自然科学基金(61372145, 61201371)

Underwater Images Visibility Improving Algorithm with Weighted L1 Regularization

Funds: 

The National Natural Science Foundation of China (61372145, 61201371)

  • 摘要: 水体对光能量有较强的吸收和散射作用,造成水下图像颜色失真,对比度下降。传统的图像增强方法和复原方法处理水下图像时各有不足,该文结合水下成像物理模型和基于Retinex理论的图像增强算法,提出水下图像清晰化方案。首先,基于图像统计特性给出一种简单的颜色校正方法,以去除颜色失真;在水下图像成像理论框架下,利用边界约束求得初始透射率,再使用自适应维纳滤波进行优化;在此基础上,提出加权L1正则化模型对亮度层进行增强,最后再进行自适应Gamma校正。实验结果表明,算法可以有效去除颜色失真,而且能够大幅提升图像的对比度和清晰度。
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出版历程
  • 收稿日期:  2016-05-10
  • 修回日期:  2016-10-31
  • 刊出日期:  2017-03-19

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