Title

Automatic Target Recognition Employing Signal Compression

Abstract

Quadratic correlation filters (QCFs) have been used successfully to detect and recognize targets embedded in background clutter. Recently, a QCF called the Rayleigh quotient quadratic correlation filter (RQQCF) was formulated for automatic target recognition (ATR) in IR imagery. Using training images from target and clutter classes, the RQQCF explicitly maximized a class separation metric. What we believe to be a novel approach is presented for ATR that synthesizes the RQQCF using compressed images. The proposed approach considerably reduces the computational complexity and storage requirements while retaining the high recognition accuracy of the original RQQCF technique. The advantages of the proposed scheme are illustrated using sample results obtained from experiments on IR imagery. © 2007 Optical Society of America.

Publication Date

7-20-2007

Publication Title

Applied Optics

Volume

46

Issue

21

Number of Pages

4702-4711

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1364/AO.46.004702

Socpus ID

34548577386 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/34548577386

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