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Low Light Image Enhancement

Developed by keras-io
An algorithm for low-light image enhancement by estimating image-specific tone curves through deep neural networks
Downloads 37
Release Time : 3/2/2022

Model Overview

Zero-DCE is a deep learning method that enhances low-light images by estimating high-order tone curves without requiring reference images, preserving dynamic range and contrast.

Model Features

Reference-free Training
Does not require input/output image pairs for training; guided by reference-free loss functions
Dynamic Range Preservation
Preserves the dynamic range of images through high-order tone curve estimation
Contrast Retention
Retains contrast between adjacent pixels during enhancement
Lightweight Network
Uses a lightweight DCE-Net for pixel-level curve estimation

Model Capabilities

Low-light Image Enhancement
Dynamic Range Adjustment
Contrast Optimization

Use Cases

Image Processing
Night Photography Enhancement
Improves brightness and details in photos taken under low-light conditions
Example images show significant brightness improvement and detail recovery
Surveillance Video Enhancement
Enhances the quality of surveillance videos in low-light environments
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