LFUID: Light Field-Based Underwater Image Formation, Restoration, and Real-World Dataset
Shijun Zhou, Yiming Su, Doneyue Wang, Weihong Ren, Jiandong Tian · IEEE Transactions on Industrial Informatics · 2025
Underwater imaging in turbid environments presents significant challenges for industrial applications due to optical distortions that severely degrade image quality. This article addresses the fundamental information deficit in traditional single-image restoration methods by introducing the first comprehensive Light Field Underwater Image Dataset, comprising 1356 images captured across diverse environments with 1820× 720× 14× 14× 3 resolution. We develop a novel physics-based image formation model that extends scattering principles to the 4-D light field domain, incorporating water attenuation coefficients and scattering properties while accounting for light field camera characteristics. Our model features three key components: an ambient underwater optical constant, a phase function for angular scattering, and a pixel position modulation function for spatial variations in backscatter. Based on this model, we propose a restoration algorithm that leverages complementary information across subaperture views. Experimental results demonstrate that our approach significantly outperforms state-of-the-art underwater image enhancement techniques across multiple metrics and diverse underwater scenes, establishing a promising new direction for underwater imaging applications.