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An infrared small target detection algorithm based on high-speed local contrast method
- Source :
- Infrared Physics & Technology. 76:474-481
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- Small-target detection in infrared imagery with a complex background is always an important task in remote sensing fields. It is important to improve the detection capabilities such as detection rate, false alarm rate, and speed. However, current algorithms usually improve one or two of the detection capabilities while sacrificing the other. In this letter, an Infrared (IR) small target detection algorithm with two layers inspired by Human Visual System (HVS) is proposed to balance those detection capabilities. The first layer uses high speed simplified local contrast method to select significant information. And the second layer uses machine learning classifier to separate targets from background clutters. Experimental results show the proposed algorithm pursue good performance in detection rate, false alarm rate and speed simultaneously.
- Subjects :
- Learning classifier system
Infrared imagery
Infrared
Computer science
media_common.quotation_subject
02 engineering and technology
Small target
Condensed Matter Physics
01 natural sciences
Atomic and Molecular Physics, and Optics
Electronic, Optical and Magnetic Materials
Constant false alarm rate
010309 optics
Task (computing)
0103 physical sciences
Human visual system model
0202 electrical engineering, electronic engineering, information engineering
Contrast (vision)
020201 artificial intelligence & image processing
Algorithm
media_common
Subjects
Details
- ISSN :
- 13504495
- Volume :
- 76
- Database :
- OpenAIRE
- Journal :
- Infrared Physics & Technology
- Accession number :
- edsair.doi...........7acf5e5e1d27a36edeeee90c919fcbe1