基于二维经验模式分解（BEMD）的显微图像融合算法的研究
本课题考虑利用二文经验模式分解（BEMD）对多层面的源图像序列进行分解，建立各源图像的本征模式函数（IMF）序列，进而对源图像的IMF序列进行融合处理，最终得到完整的融合图像
关键词 二文经验模式分解 IMF分量 显微图像 图像融合 毕业设计说明书（论文）外文摘要
Title The Research of Microscopic Image Fusion Algorithm Base on The Two Dimensional Empirical Mode Decomposition
Abstract
When people use microscope biomedical analysis or industrial sample surface inspection process， often need to complete a microscopic sample clear observation of the object surface information. However, due to the surface of the work piece sample or uneven and microscopic system optical equipment limited depth of field, make the observations be amplified at the same time only focus on a single object plane, namely, single clear. But a single level focus of image often can not provide information for operators. Therefore, the operation personnel must adjust microscope from the height that many times to get more focus image sequence. To reach the surface of the sample or the complete understanding. However, this regulation will result in the complete image information can not be real samples. Therefore, the detected object image fusion of multi-leve, resulting in a two-dimensional focal clear image of the microstructure of the surface is particularly important.
The topics to consider the use of double dimensional empirical mode decomposition (BEMD) decomposition of multidimensional source image sequence. To establish the sequence of each source image of the intrinsic mode functions (IMF), thus the IMF source image sequence fusion, and finally complete the integration of image.
Keywords Two-dimensional empirical mode decomposition;IMF component; Microscopic image; Image fusion
目 次
第一章 绪论 1
1.1 课题研究的背景及意义 1
1.2 国内外研究现状 1
1.3 图像融合技术概要 3
1.4本文的主要研究内容 5
第二章 多聚焦图像融合方法 6
2.1 多聚焦图像融合方法概述 6
2.2 多聚焦图像融合算法 8
2.3 本章小结 12
第三章 经验模式分解相关内容的介绍 13
3.1 经验模式分解（EMD） 13
3.2 IMF分量函数 13
3.3 二文经验模式分解（BEMD） 14
3.4 本章小结 15
第四章 基于二文经验模式分解的显微图像融合 15
4.1 融合规则 15
4.2操作步骤 17
4.3 结果分析 26
4.4 本章小结 26
总结与展望 27