针对水下图像颜色失真与模糊问题,提出了基于背景光估计与透射率优化的水下图像复原算法。该算法将透射率定义为直接分量透射率和后向散射分量透射率,有效提升成像模型的完整性。先对红色衰减分量进行补偿并重置直方图分布范围实现色彩均衡;基于亮度、梯度判别及色调判断选出最佳背景光点;再通过红色暗通道先验得到后向散射分量透射率,利用无退化像素点求得直接分量透射率;最后将两个透射率及所求背景光代入成像模型中以获得复原图像。实验结果表明,所提算法能够有效平衡图像的色度、饱和度及清晰度,视觉效果接近自然场景下的图像。

This study proposes an underwater image restoration algorithm based on background light estimation and transmittance optimization to address the problem of color distortion and blur of underwater image. The proposed algorithm defines the transmittance as direct and backscatter component transmittances, which effectively improve the integrity of the imaging model. First, the red attenuation component is compensated, and the histogram distribution range is reset to achieve color balance. Second, the best background light point is selected based on the brightness, gradient discrimination, and hue judgment. The transmittance of the backscatter component is then obtained through a red dark channel prior, and the direct component transmittance is obtained through a nondegenerate pixel point. Finally, the two transmittances and the background light are substituted into the imaging model to obtain a restored image. Experimental results show that the proposed algorithm can effectively balance the chroma, saturation, and sharpness of the image, and the visual effect is close to the image in the natural scene.