The attenuation (sum of absorption and scattering), which is caused by the dense and non-uniform medium, generally leads to problems of color degradation and detail loss in underwater imaging. In this study, we describe an underwater image enhancement method based on adaptive attenuation-curve prior. This method uses color channel transfer (CCT) to preprocess the underwater images, light smoothing, and wavelength-dependent attenuation to estimate water light and obtain the attenuation ratio between color channels, and estimates and refines the initial relative transmission of the channel. Additionally, the method calculates the attenuation factor and saturation constraints of the three color channels and generates an adjusted reverse saturation map (ARSM) to address uneven light intensity, after which the image is restored through water light and transmission estimation. Furthermore, we applied white balance fusion globally guided image filtering (G-GIF) technology to achieve color enhancement and edge detail preservation in the underwater images. Comparison experiments showed that the proposed method obtained better color and de-hazing effects, as well as clearer edge details, relative to current methods.

Underwater images have great practical value in many fields such as underwater archeology, seabed mining, and underwater exploration. Due to the complex underwater environment, there are problems such as poor light, low contrast, and color degradation. Traditional underwater image processing methods cannot well achieve the goal of clear display under extreme conditions. This paper proposes a method for restoration and enhancement of underwater under-exposure images that protects edge details and enhances image color. Firstly, the underwater image was preprocessed, denoising with improved wavelet threshold function, defogging with the Multi-Scale Retinex Color Restoration (MSRCR) and guided filter method. Then, the method of adaptive exposure graph is used to enhance the under-exposure image. Finally, the deep learning algorithm combined with the Non-Subsampled Contour Transform (NSCT) technology is used to solve the problem of color degradation and edge texture weakening. Experiments show that compared with other underwater image processing methods, this method greatly improves the clarity of the image, enhances the color saturation and the edge texture details of the image, and has a better visual effect.