Underwater image enhancement via variable contrast and saturation enhancement model

Since underwater optical imaging is affected by underwater light absorption and attenuation, the pixels of images distribute unevenly, and image structures are damaged to different degrees, leading to problems such as color distortion, low contrast, and blurred details. A single-color correction method cannot improve the contrast and details of images, and a single contrast enhancement method will cause image color distortion and local contrast over-enhanced and weak-enhanced. To deal with the problems simultaneously, this paper proposes an underwater image enhancement method based on variable contrast and saturation enhancement model and local contrast correction. Firstly, we design a white balance method based on pixel transformation to adjust the pixel distribution and further work out color distortion; Moreover, a variable contrast and saturation enhancement model is designed to recover the image structure and statistical characteristics effectively and further promote global contrast; Ultimately, contrast limited histogram equalization is adopted to perform local contrast correction, and then solve the over-enhanced and weak-enhanced. The enhancement results based on the synthetic and real underwater image data sets show that the proposed method is superior to some advanced qualitative and quantitative evaluation methods and effectively elevates visual effects.