NDLI: Background clutter suppression and dim moving point targets detection using nonparametric method

Content Provider	IEEE Xplore Digital Library
Author	Askar, H. Xiaofeng Li Zaiming Li
Copyright Year	2002
Description	Author affiliation: Coll. of Inf. Sci. & Eng., Xinjiang Univ., Urumqi, China (Askar, H.)
Abstract	A nonparametric background clutter elimination method as an important counterpart of target detection procedures is presented. In our method, after the rejection of clutter, the original spatially correlated imaging sensor data are reduced to independent identical distribution random variables from pixel to pixel that the Gaussianity of residuals is not required while various detection methods strongly rely on it. In this case where the statistics of the residuals (targets or noise) are not known in sufficient details, the employment of a nonparametric detector is often desirable. For the continuity of problem solving, in the second part of this paper, we develop a kind of nonparametric detection algorithm based on track-before-detect method with the capability of detecting targets moving at various speeds. According to the central limit theorem, we derive a likelihood ratio decision rule on the basis of Neyman-Pearson criteria. Computer simulations based on infrared image data with artificially implanted point targets are used for checking the theoretical results.
Sponsorship	Chinese Inst. Commun Chinese Inst. Electron. Univ. Electron. Sci. & Technol. China
Starting Page	982
Ending Page	986
File Size	339496
Page Count	5
File Format	PDF
ISBN	0780375475
DOI	10.1109/ICCCAS.2002.1178952
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-06-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image sensors Employment Statistical distributions Object detection Detectors Gaussian distribution Random variables Problem-solving Detection algorithms Pixel
Content Type	Text
Resource Type	Article

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