A new approach for discrimination of objects on hyperspectral images

被引：30
作者：
Kucheryavskiy, Sergey [1 ]
机构：
[1] Aalborg Univ, Dept Biotechnol Chem & Environm Engn, Esbjerg, Denmark
来源：
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 2013年 / 120卷
关键词：
Multivariate image analysis; Hyperspectral imaging; Classification; CLASSIFICATION; QUALITY;
D O I：
10.1016/j.chemolab.2012.11.009
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new approach for discrimination of objects on hyperspectral images, which combines state-of-art image processing methods and multivariate image analysis, is proposed. The basic idea of the approach is to build a joint principal component space for all objects' pixels, detect patterns, pixels from a particular object shared in this space, and use quantitative evaluation of the patterns as the objects' features. The approach was particularly developed for dealing with challenging cases, when objects from different classes have many similar pixels. It has been tested on several real cases and showed very promising results. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码：126 / 135
页数：10
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