Improved Retinex-Theory-Based Low-Light Image Enhancement Algorithm
Researchers working on image processing have had a hard time handling low-light images due to their low contrast, noise, and brightness. This paper presents an improved method that uses the Retinex theory to enhance low-light images, with a network model mainly composed of a Decom-Net and an Enhance...
Main Authors: | Jiarui Wang, Hanjia Wang, Yu Sun, Jie Yang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-07-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/14/8148 |
Similar Items
-
Low-Light Image Enhancement Algorithm Based on Deep Learning and Retinex Theory
by: Chenyu Lei, et al.
Published: (2023-09-01) -
Low-Light Image Enhancement Method Based on Retinex Theory by Improving Illumination Map
by: Xinxin Pan, et al.
Published: (2022-05-01) -
Low-Light Mine Image Enhancement Algorithm Based on Improved Retinex
by: Feng Tian, et al.
Published: (2024-03-01) -
Low-Light Image Enhancement Based on Constraint Low-Rank Approximation Retinex Model
by: Xuesong Li, et al.
Published: (2022-08-01) -
Retinex-Based Fast Algorithm for Low-Light Image Enhancement
by: Shouxin Liu, et al.
Published: (2021-06-01)