NDLI: Aircraft discrimination in high resolution SAR images based on texture analysis

Content Provider	IEEE Xplore Digital Library
Author	Liping Zhang Chao Wang Hong Zhang Bo Zhang
Copyright Year	2010
Description	Author affiliation: Digital Earth Lab., Center for Earth Observation and Digital Earth , Chinese Academy of Sciences, Beijing, China (Liping Zhang; Chao Wang; Hong Zhang; Bo Zhang)
Abstract	Target discrimination is the key step of automatic target detection in synthetic aperture radar (SAR) images. Aiming at the issue of aircraft discrimination in high resolution SAR images, a novel discrimination method is proposed with using texture features. First of all the method of gray level co-occurrence matrix is used to generate eight discrimination texture features: mean, variance, deficit moment, inertia moment, entropy, angular second moment, relevance and non-similarity and then forming a feature vector. Differing with the common method of extracting the holistic texture features of image to represent the target, the texture features of each pixel are extracted and the feature vectors of all pixels are used to represent the target. Then J-M distance is used to measure the different targets, and supervised training method is applied to achieve the parameters of discrimination rule. Finally, suspected targets are discriminated to different classes by the trained discrimination rule and large numbers of false alarms are eliminated efficiently. The experiments show that the aircraft has small distance to other aircrafts while large difference to false alarms, so this discrimination method has high accuracy with excellent applicability.
Starting Page	118
Ending Page	121
File Size	783303
Page Count	4
File Format	PDF
ISBN	9781424451920
ISSN	19483422
DOI	10.1109/CAR.2010.5456757
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image resolution Geoscience texture feature target discrimination Image texture analysis Robotics and automation synthetic aperture radar Image analysis J-M Distance Object detection Aircraft Synthetic aperture radar Pixel Backscatter
Content Type	Text
Resource Type	Article

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