A Two-Stage Approach for Underwater Image Enhancement Via Color-Contrast Enhancement and Trade-Off

The underwater imaging environment is very different from land, and some common land image enhancement methods are often not applicable to the underwater environment. This paper proposes a two-step underwater image enhancement method. White balance is a commonly used color correction method. In underwater environments, the traditional white balance method has certain limitations and results in severe color bias. This is caused by the faster attenuation of red light in underwater environments. We develop a new white balance method based on the assumption of the gray world method. A red correction module is embedded in the method, which is more suitable for underwater environments. For contrast correction, we design an illuminance correction method based on the Retinex model. The method significantly reduces the computational burden compared to traditional methods, while enhancing the brightness and contrast of the images. In addition, most of the current underwater image enhancement methods deal with color and contrast issues separately. However, these two factors influence each other, and processing them separately may lead to suboptimal results. Therefore, we investigate the relationship between color and contrast and propose a trade-off method. Our method integrates color and contrast within a histogram framework, achieving a balanced enhancement of both aspects. To avoid chance, we utilized four datasets, each containing 800 randomly selected images for metric testing. On the five non-referential metrics, three firsts and two seconds were ranked. Our method ranked second on two referenced metrics. Superior results were also achieved in runtime comparisons. Finally, we further demonstrate the superiority of our method through detailed demonstrations and ablation experiments.