Underwater Images Visibility Improving Algorithm with Weighted L1 Regularization

YANG Aiping; ZHANG Liyun; QU Chang; WANG Jian

doi:10.11999/JEIT160481

Volume 39 Issue 3

Mar. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(3): 626-633

YANG Aiping, ZHANG Liyun, QU Chang, WANG Jian. Underwater Images Visibility Improving Algorithm with Weighted L1 Regularization[J]. Journal of Electronics & 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 & Information Technology, 2017, 39(3): 626-633. doi: 10.11999/JEIT160481

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Underwater Images Visibility Improving Algorithm with Weighted L1 Regularization

doi: 10.11999/JEIT160481

1.
(School of Electronic Information Engineering, Tianjin University, Tianjin 300072, China)
2.

Funds:

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

Received Date: 2016-05-10
Rev Recd Date: 2016-10-31
Publish Date: 2017-03-19

Abstract

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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References(23)

References

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