【作者】 闫胜武；

【导师】 李柏年；

【作者基本信息】 兰州大学 ， 电路与系统， 2012， 硕士

【摘要】 图像融合技术是由信息融合技术发展而来的,其根本方法就是对多个传感器采集的原始图像,使用特定的融和模型,融合生成一幅新的融和图像。融合后的图像不仅具有原始图像的大部分信息,而且更符合人眼的视觉习惯和机器感知,能对特定场景进行更全面、更精确地描述。近年以来,图像融合技术己经成为了一个重要研究领域,应用十分广泛。图像融合按层次分类,可分为像素级融合、特征级融合、决策级融合,其中像素级融合是基础。本文主要探讨像素级图像融合技术。本文根据图像融合技术的研究背景与现状,简要介绍了图像融合中的一些基础问题,并对像素级图像融合方法展开了研究,主要完成的工作如下：(1)本文简要说明图像融合技术的应用范围、研究现状、发展前景和困难,指出图像融合的意义和重要性,并在此基础上,对图像融合的预处理阶段的图像增强和图像配准操作做了介绍。(2)阐述了图像融合的步骤,探讨了图像融合的主观、客观质量评价标准,并对评价指标的选取问题,给出了简要说明；综合分析、介绍了小波变换理论及其在图像融合方面的应用。(3)对比研究了常用的图像融合方法,根据常用融合方法做了大量仿真试验；对照仿真试验结果,指出了其中的不足,在此基础上对基于区域能量融合算法的小波融合算法进行了改进。该方法利用小波分解,将源图像分解成低频和高频两个部分,对低频部分,采用了自适应加权系数；高频部分采用局部能量与加权相结合的融合方法。利用左、右聚焦图像和红外图像、可见光图像进行了仿真实验,并运用图像客观评价指标验证该方法的可行性更多还原

【Abstract】 Image fusion is evolved by information fusion, such process generates a single image which contains a more accurate description of the scene than any of the individual source images. This fused image should be more useful for human visual or machine perception, and it could be more accurate and more comprehensive description of the certain image scene through the processing of redundant information and complementary information of the source image. In recent years, image fusion has become a very important research field of many subjects and has been widely used.According to hierarchical classification, image fusion falls into the following three categories:pixel level fusion, feature level fusion, and decision level fusion. The basis is pixel level, and pixel level fusion is the object of study in this paper.This paper according to the image fusion technology’s background and status, gave some of the basic issues on the image fusion, and discuss the methods of pixel-level image fusion, the main work is as follows:(1) This paper gives a brief description of the image fusion technology’s range of applications, study of the current situation and development prospects and difficulties, and pointed out that images the meaning and importance, and on this basis, the images of the pre-processing stage of image enhancement and image registration method.(2) Explain the steps and comparative study of image fusion methods commonly used discussion on image fusion of subjective and objective quality evaluation criteria and the selection of evaluation index, and gives a brief description; Comprehensive analysis, introduction to the theory and its application in image fusion based on wavelet transform.(3) According to the common fusion methods to do a lot of simulation test, control simulation test results, pointed out that the lack of discussion on image fusion, and improved a method which based on regional local average gradient fusion with Wavelet Decomposition method. The method using Wavelet Decomposition of the original image for low frequency and high frequency sections, for low frequency section, using a weighted coefficient; high frequency part of the use of "local average gradient" fusion methods. Using visible light, infrared images left and focus image focus image and right carried out simulation experiments, using objective evaluation to verify the feasibility of the method.更多还原