Visible-Infrared Image Fusion Based on Double- Density Wavelet and Thermal Exchange Optimization

Hao Guo; Jingyu Chen; Xuan Yang; Qingliang Jiao; Ming Liu

doi:10.1109/IAEAC50856.2021.9390665

Visible-Infrared Image Fusion Based on Double- Density Wavelet and Thermal Exchange Optimization

Hao Guo, Jingyu Chen, Xuan Yang, Qingliang Jiao, Ming Liu

Research output: Contribution to journal › Conference article › peer-review

5 Citations (Scopus)

Abstract

Infrared and visible image fusion has been a hot issue in image fusion. However, the parameters and result image have many proposed. In this paper, a novel visible infrared image fusion algorithm based on double-density wavelet and thermal exchange optimization is proposed. The pre-processed infrared and visible images are decomposed into detail layers and background layers by double-density wavelet transform. Thermal exchange optimization is used to estimate the number of layers and weight thresholds of decomposition. Experimental shows that both visual effects and quantitative analysis of proposed algorithm can get the best results.

Original language	English
Article number	9390665
Pages (from-to)	2151-2154
Number of pages	4
Journal	IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)
DOIs	https://doi.org/10.1109/IAEAC50856.2021.9390665
Publication status	Published - 2021
Externally published	Yes
Event	5th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2021 - Chongqing, China Duration: 12 Mar 2021 → 14 Mar 2021

Keywords

double-density wavelet
infrared image
thermal exchange optimization
visible image

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10.1109/IAEAC50856.2021.9390665

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title = "Visible-Infrared Image Fusion Based on Double- Density Wavelet and Thermal Exchange Optimization",

abstract = "Infrared and visible image fusion has been a hot issue in image fusion. However, the parameters and result image have many proposed. In this paper, a novel visible infrared image fusion algorithm based on double-density wavelet and thermal exchange optimization is proposed. The pre-processed infrared and visible images are decomposed into detail layers and background layers by double-density wavelet transform. Thermal exchange optimization is used to estimate the number of layers and weight thresholds of decomposition. Experimental shows that both visual effects and quantitative analysis of proposed algorithm can get the best results.",

keywords = "double-density wavelet, infrared image, thermal exchange optimization, visible image",

author = "Hao Guo and Jingyu Chen and Xuan Yang and Qingliang Jiao and Ming Liu",

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year = "2021",

doi = "10.1109/IAEAC50856.2021.9390665",

language = "English",

pages = "2151--2154",

journal = "IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)",

issn = "2689-6621",

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T1 - Visible-Infrared Image Fusion Based on Double- Density Wavelet and Thermal Exchange Optimization

AU - Guo, Hao

AU - Chen, Jingyu

AU - Yang, Xuan

AU - Jiao, Qingliang

AU - Liu, Ming

PY - 2021

Y1 - 2021

N2 - Infrared and visible image fusion has been a hot issue in image fusion. However, the parameters and result image have many proposed. In this paper, a novel visible infrared image fusion algorithm based on double-density wavelet and thermal exchange optimization is proposed. The pre-processed infrared and visible images are decomposed into detail layers and background layers by double-density wavelet transform. Thermal exchange optimization is used to estimate the number of layers and weight thresholds of decomposition. Experimental shows that both visual effects and quantitative analysis of proposed algorithm can get the best results.

AB - Infrared and visible image fusion has been a hot issue in image fusion. However, the parameters and result image have many proposed. In this paper, a novel visible infrared image fusion algorithm based on double-density wavelet and thermal exchange optimization is proposed. The pre-processed infrared and visible images are decomposed into detail layers and background layers by double-density wavelet transform. Thermal exchange optimization is used to estimate the number of layers and weight thresholds of decomposition. Experimental shows that both visual effects and quantitative analysis of proposed algorithm can get the best results.

KW - double-density wavelet

KW - infrared image

KW - thermal exchange optimization

KW - visible image

UR - http://www.scopus.com/inward/record.url?scp=85104604607&partnerID=8YFLogxK

U2 - 10.1109/IAEAC50856.2021.9390665

DO - 10.1109/IAEAC50856.2021.9390665

M3 - Conference article

AN - SCOPUS:85104604607

SN - 2689-6621

SP - 2151

EP - 2154

JO - IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

JF - IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

M1 - 9390665

T2 - 5th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2021

Y2 - 12 March 2021 through 14 March 2021

ER -

Visible-Infrared Image Fusion Based on Double- Density Wavelet and Thermal Exchange Optimization

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Keywords

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