Underwater images always suffer from low contrast and inaccurate colors due to scattering and absorption by particles when the target light propagates through turbid water. In this paper, we first found that a lot of intensity space is occupied by fewer pixels, called ‘tails’, on both sides of the histograms for the red, green and blue channels of the image. Based on this histogram attenuation prior and taking account of the advantage of a polarization filter we proposed an effective polarimetric recovery method to enhance the underwater image quality, which includes a specially designed histogram processing method, named ‘cut-tail histogram stretching’. This processing overcomes the limitation of traditional histogram-based methods and can further improve the restoration performance. The experimental results corresponding to underwater scenes with different turbidities and colors show that the proposed method can simultaneously enhance the image contrast and reduce the color distortion to some extent, and thus realize clear underwater vision.

当目标光通过浑浊的水中传播时，由于颗粒的散射和吸收，水下图像始终会遭受低对比度和色彩不准确的困扰。在本文中，我们首先发现，在图像的红色，绿色和蓝色通道的直方图的两侧，很多强度空间被较少的像素（称为“尾巴”）占用。基于这种直方图衰减的先验，并考虑到偏振滤光片的优势，我们提出了一种有效的极化恢复方法来增强水下图像质量，其中包括专门设计的直方图处理方法，称为“切尾直方图拉伸”。该处理克服了传统的基于直方图的方法的局限性，可以进一步提高恢复性能。