LAUSR

Underwater images have different color casts due to different attenuation conditions, such as bluish, greenish, and yellowish. In addition, due to floating particles and special illumination, underwater images have problems such as the lack of detail and unnecessary noise. To handle the above problems, this paper proposes a new, to the best of our knowledge, three-step adaptive enhancement method. For the first step, adaptive color correction, the three channels are adjusted based on the intermediate color channel, which is calculated by considering the positional relationship of the histogram distribution. For the second step, denoise and restore details, we first transform the space to hue, saturation, value (HSV), a detailed restoration method based on the edge-preserving decomposition that restores the lost detail while removing the influence of some noise. For the third step, we improve the global contrast. Still in the HSV space, a simple linear stretch strategy is applied to the saturation channel. Experiments on the standard underwater image enhancement benchmark data set have proved that our method yields more natural colors and more valuable detailed information than several state-of-the-art methods. In addition, our method also improves the visibility of underwater images captured by low-light scenes and different hardware cameras.