Fusion of Infrared and Visible Images Based on Edge Feature and Adaptive PCNN in NSCT Domain

YAN Li; XIANG Tian-zhu

doi:10.3969/j.issn.0372-2112.2016.04.002

您当前的位置：

首页 >

文章列表页 >

Fusion of Infrared and Visible Images Based on Edge Feature and Adaptive PCNN in NSCT Domain

更新时间：2025-07-16

- Fusion of Infrared and Visible Images Based on Edge Feature and Adaptive PCNN in NSCT Domain
- Acta Electronica Sinica Vol. 44, Issue 4, Pages: 761-766(2016)
- 作者机构：
  
  1. 武汉大学测绘学院,湖北,武汉,430079
  2. 武汉大学测绘遥感信息工程国家重点实验室,湖北,武汉,430079
  3. 武汉大学测绘学院,湖北,武汉,430079
  4. 武汉大学测绘遥感信息工程国家重点实验室,湖北,武汉,430079
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.41271456)
- DOI：10.3969/j.issn.0372-2112.2016.04.002
  CLC： TP391.41
- Published Online：25 April 2016，
  
  Published：2016
- 稿件说明：
移动端阅览
YAN Li, XIANG Tian-zhu. Fusion of Infrared and Visible Images Based on Edge Feature and Adaptive PCNN in NSCT Domain[J]. Acta Electronica Sinica, 2016, 44(4): 761-766.
DOI：

YAN Li, XIANG Tian-zhu. Fusion of Infrared and Visible Images Based on Edge Feature and Adaptive PCNN in NSCT Domain[J]. Acta Electronica Sinica, 2016, 44(4): 761-766. DOI： 10.3969/j.issn.0372-2112.2016.04.002.

摘要

针对传统的基于多尺度变换的红外与可见光图像融合

对比度不高

边缘等细节信息保留不充分等问题

结合NSCT变换的多分辨率、多方向特性和PCNN全局耦合、脉冲同步激发等优点

提出一种基于NSCT变换结合边缘特征和自适应PCNN红外与可见光图像融合算法.对于低频子带

采用一种基于边缘的融合方法;对于高频方向子带

采用方向信息自适应调节PCNN的链接强度

使用改进的空间频率特征作为PCNN的外部激励

根据脉冲点火幅度融合子带系数.实验结果验证了该算法的有效性.

Abstract

To improve the contrast and preserve more image details in the fusion of infrared and visible images

a fusion method for infrared and visible images based on nonsubsampled contourlet transform (NSCT) combined with image edge feature and adaptive pulse coupled neural network (PCNN) is proposed.For the low frequency subband

the fusion is based on edges of images.For the high frequency subbands

the orientation information of each pixel in images is utilized as the linking strength

and a modified spatial frequency is adopted as the input to motivate the adaptive PCNN

and the fire amplitude is employed to determine the coefficients selection.Experimental results indicate the effectiveness of the proposed algorithm.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

The Nonsubsampled Contourlet Transform in Multisensor Images Fusion

Malware Detection Method Based on Multi-Dimensional Dynamic Weighted Alpha Image Fusion and Feature Enhancement

A Scene-Adaptive Dual-Branch Efficient Cattle Facial Recognition Algorithm

Dual-Channel Deep Image Prior for Image Denoising

MW-DAN: Multilevel Wavelet-Deep Aggregation Network for Hyperspectral Image Super-Resolution

Related Author

JIA Jian

JIAO Li-cheng

SUN Qiang

XIE Li-xia

WEI Chen-yang

YANG Hong-yu

HU Ze

CHENG Xiang

Related Institution

Institute of Intelligent Information Processing,Xidian University

Department of Mathematics,Northwest University

Institute of Intelligent Information ProcessingXidian UniversityXi’anShaanxi 710071China

Department of MathematicsNorthwest UniversityXi’anShaanxi 710069China

School of Computer Science and Technology, Civil Aviation University of China

⁰