Amer Khadidja Ould, Elbouz Marwa, Alfalou Ayman, Brosseau Christian, Hajjami Jaouad
Opt Express. 2019 Jan 21;27(2):621-643. doi: 10.1364/OE.27.000621.
Object identification in highly turbid optical media depends mainly on the quality of collected images. Underwater images acquired in a turbid environment are generally of very poor quality. Attenuation and backscattering of light by water, by materials dissolved in the water, and by particulate material are the main causes of the degradation of underwater images. It is therefore essential to improve the quality of such images to facilitate object identification. The focus of this paper is to report the principle and validation of a fast and effective method of improving the quality of underwater images. On the one hand, this method uses a polarimetric imaging optical system to reduce the effect of diffusion on the image acquisition. On the other hand, it is based on an optimized version of the dark channel prior (DCP) method that has received a great deal of attention for image dehazing. Results derived from images obtained in a controlled laboratory water tank environment with different turbidity conditions and images from tests using the proposed method at sea demonstrate an ability to significantly improve visibility and reduce runtime by a factor of about 50 for a 4K image when compared to conventional DCP methods.
在高度浑浊的光学介质中进行目标识别主要取决于采集图像的质量。在浑浊环境中获取的水下图像质量通常非常差。水、溶解在水中的物质以及颗粒物质对光的衰减和后向散射是水下图像质量下降的主要原因。因此，提高此类图像的质量以便于目标识别至关重要。本文的重点是报告一种快速有效的水下图像质量提升方法的原理及验证。一方面，该方法使用偏振成像光学系统来降低扩散对图像采集的影响。另一方面，它基于暗通道先验（DCP）方法的优化版本，该方法在图像去雾方面备受关注。在具有不同浑浊度条件的受控实验室水箱环境中获取的图像以及在海上使用所提出方法进行测试得到的图像结果表明，与传统DCP方法相比，对于4K图像，该方法能够显著提高能见度并将运行时间缩短约50倍。
