基于红色暗通道先验和逆滤波的水下图像复原

Underwater Image Restoration Based on Red-Dark Channel Prior and Inverse Filtering

为提升水下图像的视觉效果,提出了基于红色暗通道先验(RDCP)和逆滤波的水下图像复原算法。该算法首先简化Jaffe-Mc Glamery水下光学成像模型,在此基础上,利用RDCP消除水下成像过程中后向散射引起的图像雾化效果;然后结合各通道透射率图与光学传递函数的数学关系,采用逆滤波去除前向散射分量;最后采用基于高斯分布的线性拉伸提高图像对比度。使用该算法与几种主流的水下图像处理算法对多种水下环境拍摄得到的图像进行处理,并计算信息熵等客观评价指标。实验结果表明,该算法能够更好地平衡图像的色度、对比度及饱和度,视觉效果更接近自然场景下的图像。

In order to improve the visual effect of underwater images, an underwater image restoration algorithm based on red-dark channel prior （RDCP） and inverse filtering is proposed. Firstly, the Jaffe-McGlamery underwater optical imaging model is simplified. On this basis, the RDCP is used to eliminate the foggy appearance of images resulting from backward scattering during the imaging process. Secondly, considering the mathematic relation between the transmission map of each channel and optical transfer function, inverse filtering is applied to remove the forward scattering component. Finally, the proposed algorithm adopts linear stretch based on Gaussian distribution to improve image contrast. The proposed algorithm and several main underwater image processing algorithms are employed in processing underwater images captured in various underwater environments, and the information entropy and other objective evaluation factors are calculated. The experimental results prove that the proposed algorithm has superiority for balancing the color, contrast and saturation of the images, and the visual effects are more similar to images captured in natural settings.