改进的基于小波变换的图像融合技术

数学理论与应用 ›› 2021, Vol. 41 ›› Issue (1): 58-.

改进的基于小波变换的图像融合技术

杨当福¹,刘圣军^1,2 ,姜源弘¹, 刘新儒^1,*

1. 中南大学数学与统计学院，长沙，410083; 2.中南大学高性能复杂制造国家重点实验室，长沙，410083

出版日期:2021-03-30 发布日期:2021-08-10
通讯作者: Xinru Liu, Male, Changsha, Hunan, Associate Professor, PhD；E−mail：liuxinru@csu.edu.cn

An Improved Image Fusion Method Based on Wavelet Transform

1. School of Mathematics and Statistics, Central South University, Changsha 410083, China； 2.State Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083, China

Online:2021-03-30 Published:2021-08-10
Supported by:
The research is supported by the National Natural Science Foundation of China (Grant No. 61572527); the Hunan Science Fund for Distinguished Young Scholars (Grant No. 2019JJ20027); the Hunan R\&D Program (Grant No. 2017NK2383); Mathematics and Interdisciplinary Sciences Project of Central South University

摘要/Abstract

摘要： 图像融合旨在构建更适合人类和机器感知的图像。在遥感应用中，高分辨率全色（PAN）图像和低分辨率多光谱（MS）图像的融合一直是一个问题，并引起了广泛关注。本文提出了一种基于小波变换的PAN和MS图像融合算法。在两个图像上执行小波变换后，使用边缘强度因子（EIF）将PAN图像的低频成分融合到MS图像的低频成分中。然后，基于最大局部标准偏差标准（MLSTD）对图像的高频成分进行融合以获得高频特征。最后，通过小波逆变换，从融合后的低频和高频分量中获得高分辨率和多光谱的融合图像。实例说明融合图像很好地配备了所需的特征，并且所提出的算法比几种经典方法具有更好的性能。

关键词: 图像融合 , 小波变换 , 边缘强度因子 , 局域标准差

Abstract: Image fusion aims to construct images that are more appropriate and understandable for human and machine perception. In remote sensing applications, the fusion of the high-resolution panchromatic (PAN) image and the low-resolution multi-spectral (MS) image has always been a problem and has drawn much attention. In this paper, we proposed a PAN and MS image fusion algorithm based on wavelet transform. After performing a wavelet transform on both images, the PAN image's low-frequency component is fused into the MS image's low-frequency component using the edge intensity factor (EIF). Then, the high-frequency components of images are fused to obtain high-frequency features based on the maximum local standard deviation criterion (MLSTD). Finally, the high-resolution and multi-spectral fused image can be obtained by wavelet inverse transform from the fused low-frequency and high-frequency components. Examples illustrated that the fused images are well equipped with desired features, and the proposed algorithm performs better than several classics methods.

Key words: Image fusion , Wavelet transform , Edge intensity factor , Local standard deviation

杨当福, 刘圣军, 姜源弘, 刘新儒. 改进的基于小波变换的图像融合技术[J]. 数学理论与应用, 2021, 41(1): 58-.