频次均衡分布与边缘优化的红外图像增强

王荣福

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频次均衡分布与边缘优化的红外图像增强

光学图像处理 | 更新时间：2026-05-20

- 频次均衡分布与边缘优化的红外图像增强
- Infrared image enhancement based on balanced distribution of frequency and edge optimization
- 光学技术 2026年52卷第3期页码：361-367
- 作者机构：
  
  广东科技学院计算机学院，广东东莞 523083
- 作者简介：
  
  王荣福（1979— ），男，副教授，硕士，从事计算机图形学和物联网方面的研究。447019622@qq.com
- 基金信息：
  
  教育部产学合作协同育人项目(230805211152352);东莞市社会发展科技项目(20221800905782)
- DOI：
  中图分类号： TN211
- 收稿：2026-02-25，
  
  修回：2026-04-17，
  
  纸质出版：2026-05-20
- 稿件说明：
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王荣福.频次均衡分布与边缘优化的红外图像增强[J].光学技术,2026,52(03):361-367.

WANG Rongfu.Infrared image enhancement based on balanced distribution of frequency and edge optimization[J].OPTICAL TECHNIQUE,2026,52(03):361-367.
王荣福.频次均衡分布与边缘优化的红外图像增强[J].光学技术,2026,52(03):361-367. DOI：

WANG Rongfu.Infrared image enhancement based on balanced distribution of frequency and edge optimization[J].OPTICAL TECHNIQUE,2026,52(03):361-367. DOI：

摘要

为了克服红外图像增强方法的缺陷，进一步改善红外图像的效果，提出了频次均衡分布与边缘优化的红外图像增强方法。统计图像像素在各个灰度级上分布的频次，然后对频次序列进行指数变换，以适当地降低低频次与高频次的差距；另外，调整部分较小的灰度级频次，以避免对应的灰度级被合并；最后根据频次对图像的像素值进行均衡映射，以此改善红外图像的亮度和对比度。进一步地，提出一种方向边缘算子，用它提取八个方向的边缘图像，然后对均衡映射后的图像进行边缘优化，以强化边缘和纹理的显著性特征。实验结果显示，经本文方法处理后的红外图像，边缘和纹理特征较清晰，图像质量指标平均梯度和信息熵优于增强性能较好的现有方法，分别高出1.96%和0.55%以上，因此，方法可以更好地应用于红外图像应用领域。

Abstract

Be aimed at the defects of infrared image enhancement methods and further improve the effect of infrared images

an infrared image enhancement method based on balanced distribution of frequency and edge optimization is proposed. It computes the frequency of image pixels for each gray level

and performs exponential transformation on the frequency sequence to appropriately reduce the difference between low frequency and high frequency. In addition

it adjusts the frequencies of certain low-frequency gray levels to avoid being merged. Finally

the pixel values of the image are mapped equally according to the frequency

so as to improve the brightness and contrast of the infrared image. Furthermore

a directional edge operator is proposed to extract edge images in eight directions

and then the edge of the equally mapped image is optimized to highlight the salient features of the edge and texture. The experimental results show that for the infrared image processed by the proposed method

its edge and texture features are clearer

the average gradient and information entropy of image quality indicators are better than the existing methods with better enhancement performance

which are 1.96% and 0.55% higher respectively. Therefore

the method in this paper can be better applied to infrared image applications.

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references

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