A modular clutter rejection technique for FLIR imagery using region-based principal component analysis

被引：1
|
作者：
Rizvi, SA [1 ]
Saadawi, TN [1 ]
Nasrabadi, NM [1 ]
机构：
[1] CUNY Coll Staten Isl, Dept Engn Sci & Phys, Staten Isl, NY 10314 USA
来源：
2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL II, PROCEEDINGS | 2000年
关键词：
D O I：
10.1109/ICIP.2000.899456
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper(1), a modular clutter rejection technique using region-based principal component analysis (PCA) is proposed. Our modular clutter rejection system uses dynamic ROI extraction to overcome the problem of poorly centered targets. In dynamic ROI extraction, a representative ROI is moved in several directions with respect to the center of the potential target image to extract a number of ROIs. Each module in the proposed system applies region-based PCA to generate the feature vectors, which are subsequently used to decide about the identity of the potential target. We also present experimental results using real-life data evaluating and comparing the performance of the clutter rejection systems with static and dynamic ROI extraction.
引用
收藏
页码：475 / 478
页数：4
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