摘 要图像融合的主要目的是通过对多幅图像间的冗余数据的处理来提高图像的 可靠性,通过对多幅图像间的互补信息的处理来提高图像的清晰度。图像融合具 有扩大系统的工作范围、可靠性和性价比等优点。图像融合技术在遥感、医学、 自然资源勘探、地形地貌分析等领域占有非常重要的地位。本文的研究方向主要 是基于红外和可见光的图像融合技术，以及其对应的 LabVIEW 平台实现过程。72263

本论文的主要内容是介绍了与研究课题相关的背景知识或技术，主要包括图 像融合技术的概念和原理以及本文所采用的融合算法。简要介绍了图像融合的发 展历程以及红外和可见光的成像原理，并对两种图像的特征和区别等内容进行详 细阐述。

本文采用的是基于离散小波变换的图像融合算法，这种算法具有方向选择 性、正交性和分析数据量小等多种优良特性。本文针对算法存在不足的地方对比 改进，将其算法转换成图形化编程语言来实现数据的分析和处理。最后对实验所 得出的结果进行评价对比，方便判断算法所实现的图像融合的质量是否良好和对 算法的优化改进等工作。

该论文有图 16 幅，表 5 个，参考文献 28 篇。

毕业论文关键词: 图像融合 LabVIEW 红外图像 可见光

The Research of Image Fusion Technology Based on LabVIEW

Abstract The main purpose of image fusion is based on the redundant data between the many images processing to improve the reliability of image, through the process of complementary information between many images to improve image clarity。 Image fusion is on expanding our scope of work system, reliability and cost performance advantages。 Image fusion technology in remote sensing, medicine, natural resource exploration, topography analysis in areas such as occupies very important position。 The research direction of this paper is mainly based on infrared and visible  light image fusion technology, and its corresponding LabVIEW platform to achieve process。

The main content of this paper is to introduce the research topic related background knowledge or technology, mainly includes the concept and principle of image fusion technology and the fusion algorithm is adopted in this paper。 The development of image fusion is briefly introduced, and the imaging principle of infrared and visible light, and the features of two kinds of image and the difference between the content such as detailed in this paper。

The image fusion algorithm of this article is based on discrete wavelet transform。This algorithm has less directional selectivity, orthogonality, and analyze data, and other excellent features。 This article in view of the disadvantages of the algorithm is local contrast improvement, the algorithm converts graphical programming language to implement the data analysis and processing。 Finally the evaluation on the results of the experiments, it is concluded that contrast, convenient to judge the quality of the image fusion algorithm is implemented by are in good condition and the optimization of algorithm improvement, etc。

Key Words: Image fusion LabVIEW Infrared image Visible light

目 录

摘 要 I

Abstract II

目 录 III

图清单 IV

表清单 IV

1 绪论 1

1。1 引言