Single underwater image restoration by blue green channels dehazing and red channel correction
Restoring underwater image from a single image is know to be ill posed, and some assumptions made in previous methods are not suitable for many situations. In this paper, we propose a method based on blue green channels dehazing and red channel correction for underwater image restoration. Firstly, blue green channels are recovered via dehazing algorithm based on an extension and modification of Dark Channel Prior algorithm. Then, red channel is corrected following the Gray World assumption theory. Finally, in order to resolve the problem which some recovered image regions may look too dim or too bright, an adaptive exposure map is built. Qualitative analysis demonstrates that our method significantly improves visibility and contrast, and reduces the effects of light absorption and scattering. For quantitative analysis, our results obtain best values in terms of entropy, local feature points and average gradient, which outperform three existing physical model available methods.
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)