Adaptive Cubic Spline Interpolation in CIELAB Color Space for Underwater Image Enhancement

Underwater images suffer from haze, blue/green tint, and color distortion, caused by attenuation and scattering of light. Existing methods for restoration depend on transmission maps to inverse the effects based on the underwater image formation model, and enhancement methods often result in unnatural colors. In this paper, we propose a method to adaptively estimate a color correction curve in the CIE L*a*b* color space for single image enhancement. Haze and blue-green tint in underwater images are removed through this process. We demonstrate improved canny edge detection on underwater images through enhancement. Results are evaluated and compared with state-of-art methods using standard underwater image datasets of coral reefs with marine populations and man-made concrete structures. Enhancement of underwater images finds its use in areas such as marine habitat mapping, improvement of 3D reconstruction of underwater scenes, and visual studies of marine life.