Automatic Color Correction for 3D Reconstruction of Underwater Scenes

Abstract

Mapping of underwater environments is a critical task for a range of activities from monitoring coral reef habitats to surveying submerged archaeological sites. While recent advances in methods for terrestrial mapping can achieve dense 3D reconstructions of scenes in real-time, there remains the challenge of transferring these methods to the underwater domain due to characteristic effects on propagation of light through the water column that violate the brightness constancy constraint used in terrestrial techniques. Current state-of-the-art methods for underwater 3D reconstruction exploit a physical model of light propagation underwater to account for such range-dependent effects as scattering and attenuation; however, these methods necessitate careful calibration of attenuation coefficients required by the physical model, or rely on rough estimates of these coefficients from prior lab experiments. The main contribution of this paper is to develop a novel method to achieve simultaneous estimation of attenuation coefficients for color correction during structure recovery of an underwater scene by integrating this estimation directly into the bundle adjustment step, which performs non-linear optimization. To validate the proposed method, an artificial scene is submerged in a pure water tank and surveyed with a stereo camera platform to simulate an underwater robotic survey in a controlled environment. The target structure is imaged in air with an RGB-D sensor to provide ground truth structure and color, and a color calibration board is place in the scene for further reference. Results show that the proposed method can automatically estimate a water-column aware model for color correction of underwater images simultaneously to 3D reconstruction of the submerged scene.