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改进多尺度结构化融合的红外与可见光图像融合

龙志亮 邓月明 谢竞 王润民

光学精密工程2024,Vol.32Issue(7):1101-1110,10.
光学精密工程2024,Vol.32Issue(7):1101-1110,10.DOI:10.37188/OPE.20243207.1101

改进多尺度结构化融合的红外与可见光图像融合

Infrared and visible images fusion based on improved multi-scale structural fusion

龙志亮 1邓月明 1谢竞 1王润民1

作者信息

  • 1. 湖南师范大学 信息科学与工程学院,湖南 长沙 410081
  • 折叠

摘要

Abstract

Under low-light conditions,the fusion of infrared and visible images often results in images with poor contrast,lacking in detail,and requiring a lengthy processing time.To address these issues,this pa-per introduces an enhanced multi-scale structural fusion approach.Initially,it improves the low-light visi-ble image using a dynamic range compression enhancement algorithm.Subsequently,through a multi-scale structural image decomposition method,it separates the enhanced visible and infrared images into their low-frequency and high-frequency components.For image fusion,the low-frequency components of both image types are merged using a technique based on the root mean square error coefficient.The high-fre-quency components are initially fused in a straightforward manner,followed by an optimized fusion using a self-adaptive weight adjustment based on image information entropy.Afterward,by reversing the multi-scale structural decomposition,the fused low and high-frequency components are combined to form a com-plete image.To further enhance the image contrast,a regional pixel enhancement algorithm based on gray level classification is introduced.The effectiveness of this method is compared with nine conventional infra-red and visible image fusion techniques,both qualitatively and quantitatively,using TNO and CVC-14 da-tasets.The proposed method demonstrates superior performance in terms of average gradient,cross entro-py,edge intensity,standard deviation,and spatial frequency,along with an improved overall visual quali-ty.This confirms that the images produced by the proposed method exhibit enhanced detail,clarity,con-trast,and are processed more quickly.

关键词

图像处理/多尺度结构化融合/动态范围压缩/均方根误差/信息熵/对比度

Key words

image processing/multi-scale structural fusion/dynamic range compression/root mean square error/information entropy/contrast

分类

信息技术与安全科学

引用本文复制引用

龙志亮,邓月明,谢竞,王润民..改进多尺度结构化融合的红外与可见光图像融合[J].光学精密工程,2024,32(7):1101-1110,10.

基金项目

国家自然科学基金资助项目(No.62072175) (No.62072175)

湖南省教育厅科学研究资助项目(No.21C0008) (No.21C0008)

湖南省教育厅重点基金资助项目(No.21A0052) (No.21A0052)

长沙市重点研发计划资助项目(No.kq2004050) (No.kq2004050)

光学精密工程

OA北大核心CSTPCD

1004-924X

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