Infrared and visible light images fusion based on frequency transformation enhancement

ZHANG Dandan

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Infrared and visible light images fusion based on frequency transformation enhancement

Optical Image Processing | 更新时间：2026-05-20

- Infrared and visible light images fusion based on frequency transformation enhancement
- OPTICAL TECHNIQUE Vol. 52, Issue 3, Pages: 378-384(2026)
- 作者机构：
  
  南昌工学院信息与人工智能学院，江西南昌 330108
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.41
- Received：25 January 2026，
  
  Revised：2026-02-28，
  
  Accepted：10 March 2026，
  
  Published：20 May 2026
- 稿件说明：
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张丹丹.基于频次变换增强的红外与可见光图像融合[J].光学技术,2026,52(03):378-384.

ZHANG Dandan.Infrared and visible light images fusion based on frequency transformation enhancement[J].OPTICAL TECHNIQUE,2026,52(03):378-384.
张丹丹.基于频次变换增强的红外与可见光图像融合[J].光学技术,2026,52(03):378-384. DOI：

ZHANG Dandan.Infrared and visible light images fusion based on frequency transformation enhancement[J].OPTICAL TECHNIQUE,2026,52(03):378-384. DOI：

摘要

为了克服现有图像融合方法在提取图像特征与特征融合上的不足，提出了一种基于频次变换增强的红外与可见光图像融合方法。其中，提出一种基于像素频次变换映射的对比度增强方法，用以改善图像的效果，凸显场景信息；根据对红外与可见光图像成像原理的分析，提出一种基于亮度和局部对比度的图像特征权重的定义；对红外与可见光图像及其对应的特征权重图执行多尺度金字塔分解，然后对各尺度下对应的图像层进行线性加权融合，最后对线性加权融合的图像金字塔进行重构，以此得到最终的融合图像。根据视觉效果、互信息、空间频率和视觉信息保真度，用实验验证提出方法的融合效果。实验结果显示，提出方法融合的图像，视觉效果更好，对应的互信息、空间频率和视觉信息保真度比部分现有方法高出10.45%、5.51%和9.99%以上。因此，该方法在视觉任务中能实现更优的图像融合。

Abstract

To overcome the shortcomings of existing image fusion methods in extracting image features and feature fusion

an infrared and visible light images fusion method based on frequency transformation enhancement is proposed. Therein

a contrast enhancement method based on pixel frequency transformation and mapping is proposed to improve the effect of images

highlighting the scene information. According to the analysis of the imaging principles of infrared and visible light images

a definition of image feature weight based on brightness and local contrast is proposed. Multi-scale pyramid decomposition is performed on the infrared and visible light images and their corresponding feature weight maps

then linear weighted fusion is performed on the image layers corresponding to each scale

and finally the linearly weighted fused image pyramid is reconstructed to obtain the final fused image. The fusion effect of the proposed method is verified experimentally based on visual effects

mutual information

spatial frequency

and visual information fidelity. The experimental results show that the proposed method shows better visual effect in the fused image

and the corresponding mutual information

spatial frequency

and visual information fidelity are 10.45%

5.51%

and 9.99% higher than those of some existing methods. Therefore

the proposed method can achieve superior image fusion in visual tasks.

关键词

Keywords

references

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