Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation

Understand

This paper presents a novel method, Zero-Reference Deep Curve Estimation (Zero-DCE), which formulates light enhancement as a task of image-specific curve estimation with a deep network.

• Our method trains a lightweight deep network, DCE-Net, to estimate pixel-wise and high-order curves for dynamic range adjustment of a given image.
• The curve estimation is specially designed, considering pixel value range, monotonicity, and differentiability.
• Zero-DCE is appealing in its relaxed assumption on reference images, i.e., it does not require any paired or even unpaired data during training.