In-Situ Joint Light and Medium Estimation for Underwater Color Restoration

Abstract

The majority of Earth’s surface is situated in the deep sea and thus remains deprived of natural light. Such adverse underwater environments have to be explored with powerful camera-light systems. In order to restore the colors in images taken by such systems, we need to jointly estimate physically-meaningful optical parameters of the light as well as the water column. We thus propose an integrated in-situ estimation approach and a complementary surface texture recovery strategy, which also removes shadows as a by-product. As we operate in a scattering medium under inhomogeneous lighting conditions, the volumetric effects are difficult to capture in closed-form solutions. Hence, we leverage the latest progress in Monte Carlo-based differentiable ray tracing that becomes tractable through recent GPU RTX-hardware acceleration. Evaluations on synthetic data and in a water tank show that we can estimate physically meaningful parameters, which enables color restoration. The approaches could also be employed to other camera-light systems (AUV, robot, car, endoscope) operating either in the dark, in fog – or – underwater.