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

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

1.
(天津大学电子信息工程学院天津 300072) ②(国家海洋技术中心天津 300112)

基金项目:

国家自然科学基金(61372145, 61201371)

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- 被引次数: 0
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

Underwater Images Visibility Improving Algorithm with Weighted L1 Regularization

1.
(School of Electronic Information Engineering, Tianjin University, Tianjin 300072, China)

Funds:

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

摘要

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。
- 图像处理 /
- 颜色校正 /
- 透射率 /
- 加权L1正则化 /
- 自适应Gamma校正
Abstract: Due to the absorption and scattering when light is traveling in water, there are two major problems of underwater imaging: color distortion and low contrast. Traditional enhancement and restoration methods can not handle these problems very well, so, this paper proposes a new approach based on the underwater optical imaging model and a Retinex-based enhancing approach. Firstly, a simple color correction method based on statistical method is adopted to address the color distortion. Then the adaptive Wiener filter is used to optimize the initial transmission map with the boundary constraints. In order to make the result more naturalness, a weighted L1 regularization model is proposed to enhance the luminance layer. Finally, an adaptive Gamma correction operation is adopted for post-processing. Experimental results demonstrate the effectiveness of the proposed method in restoring the original color of the scene and enhancing image contrast and the visibility.
- Image processing /
- Color correction /
- Transmission map /
- Weighted L1 regularization model /
- Adaptive Gamma correction

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参考文献(23)

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