title: A Real-Time Infrared Ultra-Spectral Signature Classification Method via Spatial Pyramid Matching.
abstract: The state-of-the-art ultra-spectral sensor technology brings new hope for high precision applications due to its high spectral resolution. However, it also comes with new challenges, such as the high data dimension and noise problems. In this paper, we propose a real-time method for infrared ultra-spectral signature classification via spatial pyramid matching (SPM), which includes two aspects. First, we introduce an infrared ultra-spectral signature similarity measure method via SPM, which is the foundation of the matching-based classification method. Second, we propose the classification method with reference spectral libraries, which utilizes the SPM-based similarity for the real-time infrared ultra-spectral signature classification with robustness performance. Specifically, instead of matching with each spectrum in the spectral library, our method is based on feature matching, which includes a feature library-generating phase. We calculate the SPM-based similarity between the feature of the spectrum and that of each spectrum of the reference feature library, then take the class index of the corresponding spectrum having the maximum similarity as the final result. Experimental comparisons on two publicly-available datasets demonstrate that the proposed method effectively improves the real-time classification performance and robustness to noise.
authors.affiliation: School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China. meixiaoguang@hust.edu.cn.
authors.forename: Xiaoguang
authors.initials: X
authors.lastname: Mei
authors.affiliation: Electronic Information School, Wuhan University, Wuhan 430072, China. mayong@whu.edu.cn.
authors.forename: Yong
authors.initials: Y
authors.lastname: Ma
authors.affiliation: School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China. changli@hust.edu.cn.
authors.forename: Chang
authors.initials: C
authors.lastname: Li
authors.affiliation: School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China. fanfan@hust.edu.cn.
authors.forename: Fan
authors.initials: F
authors.lastname: Fan
authors.affiliation: Electronic Information School, Wuhan University, Wuhan 430072, China. junhwong@whu.edu.cn.
authors.forename: Jun
authors.initials: J
authors.lastname: Huang
authors.affiliation: Electronic Information School, Wuhan University, Wuhan 430072, China. jiayima@whu.edu.cn.
authors.forename: Jiayi
authors.initials: J
authors.lastname: Ma
keywords: classification; spatial pyramid matching; ultra-spectral signature