Automatic Underwater Image Enhancement using Improved Dark Channel Prior

Images taken under water are often of a monochromatic appearance, due to the physical interaction (absorption and reflection) between particles and light sources. Enhanced images with improved saturation, for which the monochromatic character has been corrected, are more suitable for generating 3D models and for identifying structures and materials by human experts. In this paper, we present an automatic method to identify the mean water color from a set of images. This mean color represents an average gray and is used to describe a new axis in CIELab color space. An extended color variance and a histogram equalization are simultaneously applied to the image. The main advantage of this method is the fully automatic enhancement process. An UUV (Unmanned Underwater Vehicle) can operate without providing a color reference scheme. The presented method was implemented in the software JEnhancer, which is freely available. JEnhancer was successfully tested in several documentation campaigns, and was integrated into the videogrammetric software pipeline Archaeo3D to produce 3D models from videos.

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