基于颜色失真去除与暗通道先验的水下图像复原

杨爱萍; 郑佳; 王建; 何宇清

doi:10.11999/JEIT150483

基于颜色失真去除与暗通道先验的水下图像复原

doi: 10.11999/JEIT150483

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, 61472274, 61201371)

计量
- 文章访问数: 2226
- HTML全文浏览量: 267
- PDF下载量: 2862
- 被引次数: 0
出版历程
- 收稿日期: 2015-04-28
- 修回日期: 2015-07-20
- 刊出日期: 2015-11-19

Underwater Image Restoration Based on Color Cast Removal and Dark Channel Prior

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

Funds:

The National Natural Science Foundation of China (61372145, 61472274, 61201371)

摘要

摘要: 水下图像成像过程与雾天图像虽然类似，但因水对光的选择性吸收和光的散射作用，水下图像存在颜色衰减并呈现蓝(绿)色基调，传统的去雾方法用于水下图像复原时效果欠佳。针对这类方法出现的缺点，该文根据先去除颜色失真后去除背景散射的思路，提出一种新的水下图像复原方法。结合光在水中的衰减特性，提出适用于水下图像的颜色失真去除方法，并利用散射系数与波长的关系修正各通道透射率；另外，该文改进的背景光估计方法可有效避免人工光源、白色物体、噪声等影响。实验结果证明，该文方法在恢复场景物体原本颜色和去除背景散射方面效果良好。
- 无损信息隐藏 /
- 广义整数变换 /
- 拓展 /
- 嵌入容量
Abstract: The imaging process of the underwater image is similar to the haze image. However, the dehazing methods fail when used in the underwater image restoration because of the color attenuation and blue (green) color tone, caused by the selective absorption of water and light scattering. Thus, this paper proposes a new approach for underwater images restoration based on the idea of removing backscattering after the color cast removal. Due to the attenuation of light in water, a color cast removal approach is proposed. The relationship between scattering coefficient and wavelength is used to obtain a more accurate transmission estimation for each color channel. In addition, an improved algorithm for background light estimation is presented, which can effectively avoid the influence of artificial light, white object and noise. Experimental results demonstrate the effectiveness of the proposed method in restoring the original color of the scene and removing the backscattering.
- Image processing /
- Color cast /
- Backscattering /
- Dark channel prior

HTML全文

参考文献(20)

Schettini R and Corchs S. Underwater image processing: state of the art of restoration and image enhancement methods[J]. EURASIP Journal on Advances in Signal Processing, 2010(1), 2010: 1-14.

Ancuti C, Ancuti C O, Haber T, et al.. Enhancing underwater images and videos by fusion[C]. IEEE Conference on Computer Vision and Pattern Recognition, Providence, USA, 2012: 81-88.

Fu Xue-yang, Zhuang Pei-xian, Huang Yue, et al.. A retinex- based enhancing approach for single underwater image[C]. IEEE International Conference on Image Processing, Paris, 2014: 4572-4576.

张问一, 胡东辉, 丁赤飚. 基于Goldstein滤波器的SAR海洋图像增强方法[J]. 电子与信息学报, 2012, 34(9): 2263-2267.

Zhang Wen-yi, Hu Dong-hui, and Ding Chi-biao. Enhancement of SAR ocean image based on Goldstein filter[J]. Journal of Electronics Information Technology, 2012, 34(9): 2263-2267.

Hou W L, Gray D J, Weidemann A D, et al.. Automated underwater image restoration and retrieval of related optical properties[C]. IEEE International Geoscience and Remote Sensing Symposium, Barcelona, 2007: 1889-1892.

Stephan T, Frhberger P, Werling S, et al.. Model based image restoration for underwater images[C]. SPIE Optical Metrology 2013. International Society for Optics and Photonics, Munich, 2013: 87911F-87911F-9.

Chiang J Y and Chen Ying-Ching. Underwater image enhancement by wavelength compensation and dehazing[J]. IEEE Transactions on Image Processing, 2012, 21(4): 1756-1769.

Li Yu-Jie, Lu Hui-min, Zhang Li-feng, et al.. Real-time visualization system for deep-sea surveying[J]. Mathematical Problems in Engineering, 2014, 2014: 1-10.

Jaffe J S. Computer modeling and the design of optimal underwater imaging systems[J]. IEEE Journal of Oceanic Engineering, 1990, 15(2): 101-111.

Jaffe J S. Underwater optical imaging: the past, the present, and the prospects[J]. IEEE Journal of Oceanic Engineering, 2014, 40(3): 683-700.

He Kai-ming, Sun Jian, and Tang Xiao-ou. Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12): 2341-2353.

Guo Jun-kai, Sung Chia-chi, and Chang Herng-hua. Improving visibility and fidelity of underwater images using an adaptive restoration algorithm[C]. IEEE OCEANS 2014, Taipei, China, 2014: 1-6.

Wen Hao-cheng, Tian Yong-hong, Huang Tie-jun, et al.. Single underwater image enhancement with a new optical model[C]. IEEE International Symposium on Circuits and Systems, Beijing, 2013: 753-756.

He Kai-ming, Sun Jian, and Tang Xiao-ou. Guided image filtering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6): 1397-1409.

Henke B, Vahl M, and Zhou Zhi-liang. Removing color cast of underwater images through non-constant color constancy hypothesis[C]. IEEE International Symposium on Image and Signal Processing and Analysis, Trieste, 2013: 20-24.

Zhao Xin-wei, Jin Tao, and Qu Song. Deriving inherent optical properties from background color and underwater image enhancement[J]. Ocean Engineering, 2015, 94(2): 163-172.

Gould R W, Arnone R A, and Martinolich P M. Spectral dependence of the scattering coefficient in case 1 and case 2 waters[J]. Applied Optics, 1999, 38(12): 2377-2383.

Li Fang, Wu Jin-yong, Wang Yi-ke, et al.. A color cast detection algorithm of robust performance[C]. IEEE International Conference on Advanced Computational Intelligence, Nanjing, 2012: 662-664.

Aydin T O, Mantiuk R, Myszkowski K, et al.. Dynamic range independent image quality assessment[J]. ACM Transactions on Graphics, 2008, 27(3): 1-10.

施引文献

资源附件(0)

访问统计