Ranking color correction algorithms using cluster indices

In the field of underwater imaging it is often necessary to pre-process images to homogenize image quality across a whole image transect and to compensate variations in imaging conditions. A variety of pre-processing methods have been developed in recent years to overcome different problems occurring in underwater imaging, hence performing different on different image sets. Protocols for an objective comparison and scoring of those methods are needed. Here we show how to use cluster indices to rank the differently methods regarding their performances on different image sets. Our results show different rankings for four preprocessing methods for two chosen sets of benthic images from the deep seafloor.