一种基于声呐信息融合的水下图像增强方法

由于光在水中传输时的衰减和散射效应，使得光学成像细节丢失、对比度下降以及颜色偏移失真，导致水下图像雾化。因此在光线条件较为恶劣情况下，水下高性能相机对目标的有效捕捉范围较小，水下光学成像系统通常很难达到令人满意的成像效果。而声呐利用声波在水中传播衰减较小的特点可以进行更远距离的探测。因此，当水下目标距离光学探测设备较远而不能进行准确光学成像来捕捉目标时，可利用声呐采集得到的信息与光学图像进行融合，实现图像增强，提高成像效果。文章提出了一种基于声呐信息融合的水下图像增强方法，首先对水下光学图像分两步进行预处理，即基于暗通道先验模型的去雾增强和自适应图像增强，再使用声呐信息对水下图像进行局部增强，明显提高水下环境中所要探测目标的对比度与可识别度。

An underwater image enhancement method based on sonar information fusion

Due to the attenuation and scattering effects of light propagation in the water, the details of the optical imaging are severely lost, the contrast is reduced and the color shift is distorted, resulting in the atomization of underwater light image. Therefore, in the poor light conditions, the effective capture range of high-performance underwater cameras is relatively short, and the satisfactory imaging result is hard to obtain. Sonar uses sound wave to detect long distance target due to low attenuation of sound propagation in water. Therefore, when the underwater optical detection device cannot perform accurate optical imaging to capture the long distance target, the information collected by the sonar system can be used to fuse with the optical image information to enhance the image and improve the imaging effect. In this paper, an underwater image enhancement method based on sonar information fusion is proposed. First, the underwater optical image is preprocessed in the two steps, i. e. the dark channel prior model based defog enhancement and the adaptive image enhancement, and then the sonar information is used to locally enhance the underwater image and significantly improve the contrast and recognizability of the target to be detected in the underwater environments.