Open AccessUnderwater image restoration via depth map and illumination estimation based on a single image
Author(s) -
Jingchun Zhou,
Tongyu Yang,
Wenqi Ren,
Dan Zhang,
Weishi Zhang
Publication year - 2021
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.427839
Subject(s) - underwater , artificial intelligence , computer science , computer vision , image restoration , color correction , robustness (evolution) , distortion (music) , depth map , pixel , image formation , color image , image (mathematics) , image processing , optics , geology , physics , amplifier , computer network , biochemistry , oceanography , chemistry , bandwidth (computing) , gene
For the enhancement process of underwater images taken in various water types, previous methods employ the simple image formation model, thus obtaining poor restoration results. Recently, a revised underwater image formation model (i.e., the Akkaynak-Treibitz model) has shown better robustness in underwater image restoration, but has drawn little attention due to its complexity. Herein, we develop a dehazing method utilizing the revised model, which depends on the scene depth map and a color correction method to eliminate color distortion. Specifically, we first design an underwater image depth estimation method to create the depth map. Subsequently, according to the depth value of each pixel, the backscatter is estimated and removed by the channel based on the revised model. Furthermore, we propose a color correction approach to adjust the global color distribution of the image automatically. Our method only uses a single underwater image as input to eliminate lightwave absorption and scattering influence. Compared with state-of-the-art methods, both subjective and objective experimental results show that our approach can be applied to various real-world underwater scenes and has better contrast and color.