基于改进U-Net的水下图像增强算法

Underwater image enhancement algorithm based on improved U-Net

针对水下退化图像存在颜色失真、模糊雾化、对比度低等问题,提出了一种新的基于改进U-Net的水下图像增强算法。设计一种新的残差注意力结构和边缘检测模块并将其引入到U-Net网络中,构建改进后的水下图像增强算法。实验结果表明,本文提出的算法在校正水下色偏和增强对比度方面均得到了很好的效果,IE值较原始图像平均提高了14.2%,UCIQE值较原始图像平均提高了24%。消融实验结果表明,本文提出的残差注意力结构、边缘检测模块和损失函数均对水下图像增强起到了积极的效果。

A new underwater image enhancement algorithm based on improved U-Net is proposed to address the problems of color distortion,fuzzy fogging,and low contrast in underwater degraded images.A new residual attention structure and edge detection module are designed and introduced into the U-Net network to construct the improved underwater image enhancement algorithm.The experimental results show that the algorithm proposed in this paper obtains good results in both correcting the underwater color bias and enhancing the contrast,with an average improvement of 14.2%in the IE value compared with the original image and an average improvement of 24%in the UCIQE value compared with the original image.The results of the ablation experiments show that the residual attention structure,edge detection module,and loss function proposed in this paper have positive effects on underwater image enhancement.