Underwater Organism Color Enhancement via Color Code Decomposition, Adaptation and Interpolation

TL;DR

This paper introduces ColorCode, a novel underwater image enhancement method that allows for controllable and interpolated color adjustments, surpassing existing fixed-color enhancement techniques in quality and flexibility.

Contribution

The paper presents a new approach that decomposes underwater images into color and content codes, enabling controllable and interpolated color enhancement with a Gaussian-constrained color code.

Findings

Outperforms existing methods in diverse, controllable, and realistic color enhancement.

Enables smooth color interpolation through continuous sampling of the color code.

Demonstrates superior results on benchmark datasets with quantitative and visual evaluations.

Abstract

Underwater images often suffer from quality degradation due to absorption and scattering effects. Most existing underwater image enhancement algorithms produce a single, fixed-color image, limiting user flexibility and application. To address this limitation, we propose a method called \textit{ColorCode}, which enhances underwater images while offering a range of controllable color outputs. Our approach involves recovering an underwater image to a reference enhanced image through supervised training and decomposing it into color and content codes via self-reconstruction and cross-reconstruction. The color code is explicitly constrained to follow a Gaussian distribution, allowing for efficient sampling and interpolation during inference. ColorCode offers three key features: 1) color enhancement, producing an enhanced image with a fixed color; 2) color adaptation, enabling controllable adjustments of long-wavelength color components using guidance images; and 3) color interpolation, allowing for the smooth generation of multiple colors through continuous sampling of the color code. Quantitative and visual evaluations on popular and challenging benchmark datasets demonstrate the superiority of ColorCode over existing methods in providing diverse, controllable, and color-realistic enhancement results. The source code is available at https://github.com/Xiaofeng-life/ColorCode.