UIALN: Enhancement for Underwater Image With Artificial Light

Since underwater images are seriously degraded due to the attenuation of light, artificial light (AL) is often used to assist photography in underwater. However, the normal underwater imaging process is changed by the AL. It is observed that the AL source typically alters the light condition to a large extent, resulting in non-uniform illumination of images. In addition, the color distortion of the area affected by AL is little because the AL close to the object suffers little attenuation. However, most existing underwater image enhancement algorithms ignore this phenomenon. In their results, the areas affected by AL tend to be over-enhanced or over-exposed and even affect the overall enhancement effect. To this end, we propose a novel underwater image enhancement algorithm (UIALN) based on luminance correction and AL area color self-guided restoration. The underwater image is converted into the LAB color space, where the AL and pseudo-blur effect on the L channel are removed based on the luminance correction network, and the color casts on the AB channels is removed by the guidance of the AL area. Specifically, a luminance correction network is first designed based on the retinex decomposition to correct luminance, where the uneven luminance caused by AL is corrected in the illumination layer decomposed by the L channel because AL is usually white light. After that, the AL area is detected by the difference between before and after luminance correction. Second, an AL area self-guidance network is designed to assist the restoration of the color channels AB. The color restoration module utilizes the internal characteristics of the image, where the characteristics of the AL area are utilized as the prior to make the color easy to be restored. In addition, to facilitate the training and testing of the algorithm, a method of synthetic underwater images with AL is proposed based on underwater image imaging model, and a new underwater image dataset with artificial light (UIDWAL) is provided. Experimental results show that our UIALN outperforms the existing state-of-the-art approaches for the enhancement of both synthetic and real underwater images with AL.