A Low‑Light Image Enhancement Algorithm Using Two‑Stage Hybrid Strategy

XU Shao-ping; CHEN Xiao-guo; LI Fen; LIN Zhen-yu; CHEN Xiao-jun

doi:10.12263/DZXB.20201018

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A Low‑Light Image Enhancement Algorithm Using Two‑Stage Hybrid Strategy

PAPERS | 更新时间：2025-12-08

- A Low‑Light Image Enhancement Algorithm Using Two‑Stage Hybrid Strategy
- ACTA ELECTRONICA SINICA Vol. 49, Issue 11, Pages: 2166-2170(2021)
- 作者机构：
  
  南昌大学信息工程学院，江西南昌 330031
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20201018
  CLC： TP391.41
- Received：13 September 2020，
  
  Revised：2021-03-31，
  
  Published：25 November 2021
- 稿件说明：
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徐少平,陈孝国,李芬等.采用两阶段混合策略实现的低照度图像增强算法[J].电子学报,2021,49(11):2166-2170.

XU Shao-ping,CHEN Xiao-guo,LI Fen,et al.A Low‑Light Image Enhancement Algorithm Using Two‑Stage Hybrid Strategy[J].ACTA ELECTRONICA SINICA,2021,49(11):2166-2170.
徐少平,陈孝国,李芬等.采用两阶段混合策略实现的低照度图像增强算法[J].电子学报,2021,49(11):2166-2170. DOI： 10.12263/DZXB.20201018.

XU Shao-ping,CHEN Xiao-guo,LI Fen,et al.A Low‑Light Image Enhancement Algorithm Using Two‑Stage Hybrid Strategy[J].ACTA ELECTRONICA SINICA,2021,49(11):2166-2170. DOI： 10.12263/DZXB.20201018.

摘要

在深入分析现有各主流低照度图像增强(Low Light Image Enhancement

LLIE)算法的基础上，提出了一种采用两阶段混合策略实现的低照度图像增强(Hybrid LLIE

HLLIE)算法.具体地，在第一阶段，对于给定的低照度图像，利用互补效果较好的Fu和Ying两个主流LLIE算法分别对其进行增强预处理，所得到的两张增强后图像称为初步增强图像；在第二阶段，将所得到的两张初步增强图像输入到预先训练好的多通道浅层卷积神经网络(Multi‑channel Shallow Convolution Neural Network

MSCNN)模型中，由MSCNN模型将两张初步增强图像优化组合为一张具有更高图像质量的最终增强图像.实验结果表明：与各主流LLIE算法相比，所提出的HLLIE算法在各个客观图像质量评价指标上有显著优势，人工主观评价亦能证实这一点.

Abstract

After carefully analyzing the characteristics of existing low light image enhancement (LLIE) algorithms

we proposed a hybrid LLIE (HLLIE) algorithm with two-stage hybrid strategy. Specifically

in the first stage

for a given low-light image

we chose the complementary LLIE algorithms

i.e.

Fu and Ying

to enhance the low-light image

respectively. In the second stage

the two preliminary enhanced images were used as the inputs of the multi-channel shallow convolution neural network (MSCNN)

and then the pre-trained MSCNN conducted optimal combination of the two preliminary enhanced images to achieve further enhancement regarding the image quality. The experimental results show that

compared with the state-of-the-art LLIE algorithms

the HLLIE algorithm has obvious advantages in terms of the objective image quality metrics on the low-light images

and the subjective evaluation also can confirm this.

关键词

Keywords

references

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