Improving visibility and fidelity of underwater images using an adaptive restoration algorithm

When light is transmitted in water from a subject to an observer, it is scattered and absorbed by the unstable environment such as suspended particles and turbid water. Due to these phenomena, underwater images usually have poor quality including low contrast, blurring, darkness, and color diminishing. In this paper, we propose a new underwater image restoration algorithm that consists of two major phases: visibility restoration and fidelity restoration. In the first phase, underwater images are observed similar to haze images because they have the same problems of low contrast and color shifting. This motivated us to use the haze removal technique, namely, dark channel prior, to dehaze underwater images. Subsequently, in the second phase, we equalize the color mean in each RGB (red, green, blue) channel to balance the color. Then transform the color space from RGB to HSV (hue, saturation, value) color space to adjust S channel to make the image color more natural. Finally, we adjust V channel according to the brightness value of RGB to enhance the contrast. Preliminary results indicated that the proposed method effectively improved visibility and fidelity of underwater images.