NeuroPump: Simultaneous Geometric and Color Rectification for Underwater Images
Journal:
arXiv
Published Date:
Dec 20, 2024
Abstract
Underwater image restoration aims to remove geometric and color distortions
due to water refraction, absorption and scattering. Previous studies focus on
restoring either color or the geometry, but to our best knowledge, not both.
However, in practice it may be cumbersome to address the two rectifications
one-by-one. In this paper, we propose NeuroPump, a self-supervised method to
simultaneously optimize and rectify underwater geometry and color as if water
were pumped out. The key idea is to explicitly model refraction, absorption and
scattering in Neural Radiance Field (NeRF) pipeline, such that it not only
performs simultaneous geometric and color rectification, but also enables to
synthesize novel views and optical effects by controlling the decoupled
parameters. In addition, to address issue of lack of real paired ground truth
images, we propose an underwater 360 benchmark dataset that has real paired
(i.e., with and without water) images. Our method clearly outperforms other
baselines both quantitatively and qualitatively. Our project page is available
at: https://ygswu.github.io/NeuroPump.github.io/.
