Abstract
To deal with the issue of poor visibility caused by water
turbidity during the operation of underwater robotics, we propose an
attenuation prior formation model-guided enhancement algorithm for
turbid underwater images. Specifically, we establish an imaging model
suitable for turbid water by studying the influence of water turbidity
on light attenuation and transmission. For this model, we first propose
a scoring formula that takes into account multiple prior knowledge to
estimate the global background light with the help of hierarchical
searching technique. Then, we make full use of the advantages of
different scale neighborhoods in image restoration, and propose an
adaptive multi-scale weighted fusion transmission estimation method to
balanc e brightness and contrast. In addition, to correct the color of
the images with a natural appearance, a variation of white balance is
introduced as post-processing. Extensive experiments on two image
datasets show that our algorithm achieves better results than
state-of-the-art methods.
