Underwater image enhancement via integrated RGB and LAB color models

Abstract

Images taken underwater suffers from color shift and poor visibility because the light is absorbed and scattered when it travels through water. To handle the issues mentioned above, we propose an underwater image enhancement method via integrated RGB and LAB color models (RLCM). In the RGB color model, we first fully consider the leading causes of underwater image color shift, and then the poor color channels are corrected by dedicated fractions, which are designed via calculating the differences between the well and poor color channels. In the LAB color model, wherein the local contrast of the L channel is enhanced by a histogram with local enhancement and exposure cut-off strategy, whereas the difference between the A and B channels is traded-off by a gain equalization strategy. Besides, a normalized guided filtering strategy is incorporated into the histogram enhancement process to mitigate the effects of noise. Ultimately, the image is inverted from the LAB color model to the RGB color model, and a detail sharpening strategy is implemented in each channel to obtain a high-quality underwater image. Experiments on various real-world underwater images demonstrate that our method outputs better results with natural color and high visibility.