自适应水下图像增强算法

Adaptive Underwater Image Enhancement Algorithm

针对水下图像因成像环境造成的色彩失真、对比度下降、模糊等问题,提出一种自适应水下图像增强算法。首先,基于Lab色彩空间的局部色偏和全局色偏对衰减颜色进行色彩补偿,再利用灰度世界算法恢复水下图像的色彩平衡。其次,使用自动色阶和伽马校正方法调整各通道信息,以获得高动态范围、高照度的图像。最后,通过反锐化掩膜方法获得高频信息并增强图像细节,从而获得清晰的水下图像。所提算法利用图像的色偏、均方差等统计信息,实现了自适应处理。实验结果表明,所提算法能有效去除水下图像色偏,提高图像对比度与清晰度,提升视觉效果。较之其他算法,其在处理效果及时间上均有优势。

A selfadaptive underwater image enhancement algorithm is proposed to address the issues of color distortion,decreased contrast,and blurring caused by the imaging environment in underwater images.First,based on the local and global color biases in the Lab color space,color compensation is applied to attenuated colors,and thereafter the grayscale world algorithm is used to restore the color balance of underwater images.Second,automatic color scale and gamma correction methods are used to adjust the information of each channel to obtain images with high dynamic range and high illumination.Finally,highfrequency information is obtained through the antisharpening mask method,and image details are enhanced to obtain clear underwater images.The proposed algorithm utilizes statistical information,such as the color deviation and mean square deviation of the image,to achieve adaptive processing.The experimental results show that the proposed algorithm can effectively remove color deviation from underwater images,improve image contrast and clarity,and enhance visual effects.Compared with other algorithms,it has advantages in processing efficiency and time.