An Adaptive Image Enhancement Algorithm Based on Human Visual Properties

Yuan Xiaosong; Wang Xiutan; Wang Xiqin

您当前的位置：

首页 >

文章列表页 >

An Adaptive Image Enhancement Algorithm Based on Human Visual Properties

更新时间：2025-12-08

- An Adaptive Image Enhancement Algorithm Based on Human Visual Properties
- Acta Electronica Sinica Issue 4, (1999)
- 作者机构：
  
  清华大学电子工程系
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.4
- Published：1999
- 稿件说明：
移动端阅览
[1]袁晓松,王秀坛,王希勤.基于人眼视觉特性的自适应的图像增强算法的研究[J].电子学报,1999(04):64-66.

Yuan Xiaosong, Wang Xiutan, Wang Xiqin. An Adaptive Image Enhancement Algorithm Based on Human Visual Properties[J]. Acta Electronica Sinica, 1999, (4).
[1]袁晓松,王秀坛,王希勤.基于人眼视觉特性的自适应的图像增强算法的研究[J].电子学报,1999(04):64-66. DOI：

Yuan Xiaosong, Wang Xiutan, Wang Xiqin. An Adaptive Image Enhancement Algorithm Based on Human Visual Properties[J]. Acta Electronica Sinica, 1999, (4). DOI：

摘要

本文提出了一种基于人眼视觉特性的自适应的图像增强算法，这种算法是对基于ＬＩＰ模型的Ｌｅ图像增强算法的改进．该算法能够有效地增强整个图像的对比度，增大图像的动态范围，并且依据人眼视觉特性，增强图像的边缘而不明显地增大噪声．这种算法容易实现，适用于实时系统的应用．几种算法实验结果的比较和分析，表明了这种算法的有效性．

Abstract

This paper describes an adaptive image enhancement algorithm based on human visual properties

which is an improved version of Lee’s image enhancement algorithm based on the LIP model.The algorithm can improve the overall contrast of an image and expand the dynamic range.According to the HVS

it can sharpen the image edges and avoid much enhancement of noise.The algorithm is easy to implement

and suitable for real time applications.Experimental results of the proposed algorithm and other algorithms are compared and analyzed to illustrate the effectiveness of the proposed method.

关键词

Keywords

references

Views

816

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Image Enhancement via Content Semantic-Aware Multimodal Fusion

Progressive Edge-Aware Interactive Network for Multi-Degraded Low-Light Image Enhancement

Quality Assessment of Light Field Images Based on Contrastive Visual-Textual Model

Large Dynamic Range Microwave Photonic I/Q Down-Conversion System Based on PDM-DPMZM

Infrared Image Enhancement Based on Multi-Scale Cyclic Convolution and Multi-Clustering Space

Related Author

ZHU Han-cheng

LIU Xin-yu

YAO Rui

SHAO Zhi-wen

ZHOU Yong

LI Lei-da

LI Yue-zhou

NIU Yu-zhen

Related Institution

School of Computer Science and Technology / School of Artificial Intelligence, China University of Mining and Technology

Mine Digitization Engineering Research Center of the Ministry of Education

School of Artificial Intelligence, Xidian University

College of Computer and Data Science, Fuzhou University

College of Photonic and Electronic Engineering, Fujian Normal University

⁰