Visibility Enhancement for Underwater Visual SLAM Based on Underwater Light Scattering Model

Younggun Cho, Ayoung Kim1

  • 1Seoul National University

Details

11:30 - 11:35 | Tue 30 May | Room 4311/4312 | TUB3.1

Session: Computer Vision 2

Abstract

This paper presents a real-time visibility enhancement algorithm for effective underwater visual simultaneous localization and mapping (SLAM). Unlike an aerial environment, an underwater environment contains larger particles and is dominated by a different image degradation model. Our method starts with a thorough understanding of underwater particle physics (e.g., forward, back, multiple scattering, and blur). Targeting underwater image enhancement in a realworld application, we include an artificial light model in the derivation. The proposed method is effective for both color and gray images with, substantial improvement in the process time compared to conventional methods. The proposed method is validated by using simulated synthetic images (color) and real-world underwater images (color and grayscale). Using two underwater image sets acquired from the same area but with different water turbidity, we evaluate the proposed visibility enhancement and resulting improvement in SLAM.