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基于主成分分析-二阶导数光谱成像的红外显微图像分析
引用本文:杨秀坤,钟明亮,景晓军,张尚迪. 基于主成分分析-二阶导数光谱成像的红外显微图像分析[J]. 光学学报, 2012, 32(7): 711001-114
作者姓名:杨秀坤  钟明亮  景晓军  张尚迪
作者单位:杨秀坤:哈尔滨工程大学信息与通信工程学院, 黑龙江 哈尔滨 150001
钟明亮:哈尔滨工程大学信息与通信工程学院, 黑龙江 哈尔滨 150001北京邮电大学信息与通信工程学院, 北京 100876
景晓军:北京邮电大学信息与通信工程学院, 北京 100876
张尚迪:哈尔滨工程大学信息与通信工程学院, 黑龙江 哈尔滨 150001
基金项目:国家自然科学基金(61143008)和黑龙江省自然科学基金(ZD200915)资助课题。
摘    要:红外显微成像技术将红外光谱技术和显微技术相结合,不仅可以提供测试样品的光谱信息而且能够提供测试样品的空间分布信息。然而复杂样品的红外显微图像谱峰重叠严重,无法直接获得目标组分的分布信息。将因子分析与光谱分离技术相结合提出了主成分分析-二阶导数光谱成像方法。通过兔子动脉红外显微图像中胆固醇分布的成像实验,验证该方法的可行性和有效性。实验结果表明,该方法可以提高光谱分辨率,挖掘隐藏于重叠谱峰中的有用信息,是一种有效的红外显微图像分析方法。

关 键 词:显微  红外显微成像  主成分分析  二阶导数  光谱成像
收稿时间:2012-01-09

FTIR Microscopic Image Analysis Based on Principal Component Analysis-2nd Derivative Spectral Imaging
Yang Xiukun,Zhong Mingliang,Jing Xiaojun,Zhang Shangdi. FTIR Microscopic Image Analysis Based on Principal Component Analysis-2nd Derivative Spectral Imaging[J]. Acta Optica Sinica, 2012, 32(7): 711001-114
Authors:Yang Xiukun  Zhong Mingliang  Jing Xiaojun  Zhang Shangdi
Affiliation:1 College of Information and Communication Engineering,Harbin Engineering University,Harbin,Heilongjiang 150001,China 2 School of Information and Communication Engineering,Beijing University of Posts and Telecommunication,Beijing 100876,China
Abstract:Fourier transform infrared spectroscopy (FTIR) microscopic imaging technology combines infrared ray spectroscopy with microscopy, so that not only spectral information but also space distribution of sample can be provided. However, because severe peak overlapping exists in the FTIR microscopic image of complex samples, distribution information of the target chemical compound cannot be displayed directly. To overcome the drawbacks, a method of principal component analysis-2nd derivative spectral imaging, combining factor analysis and the spectral unmixing technology is developed. Image analysis of distribution of cholesterol in rabbit arteries with FTIR microscopic imaging technology verifies the feasibility and effectiveness of the proposed method. The experimental results show that the proposed method is an effective method to improve the spectral resolution and find the useful information hidden in overlapping spectral peak.
Keywords:microscopy  Fourier transform infrared spectroscopy microscopic imaging  principal component analysis  2nd derivative  spectral imaging
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