Adaptive target detection in forward-looking infrared imagery using the eigenspace separation transform and principal component analysis

S. Susan Young; Heesung Kwon; Sandor Z. Der; Nasser M. Nasrabadi

doi:10.1117/1.1768534

1 August 2004 Adaptive target detection in forward-looking infrared imagery using the eigenspace separation transform and principal component analysis

S. Susan Young, Heesung Kwon, Sandor Z. Der, Nasser M. Nasrabadi

Author Affiliations +

Optical Engineering, Vol. 43, Issue 8, (August 2004). https://doi.org/10.1117/1.1768534

Abstract

An adaptive target detection algorithm for forward-looking infrared (FLIR) imagery is proposed, which is based on measuring differences between structural information within a target and its surrounding background. At each pixel in the image a dual window is opened, where the inner window (inner image vector) represents a possible target signature and the outer window (consisting of a number of outer image vectors) represents the surrounding scene. These image vectors are then preprocessed by two directional highpass filters to obtain the corresponding image gradient vectors. The target detection problem is formulated as a statistical hypotheses testing problem by mapping these image gradient vectors into two linear transformations, P₁ and P₂, via principal component analysis (PCA) and eigenspace separation transform (EST), respectively. The first transformation P₁ is only a function of the inner image gradient vector. The second transformation P₂ is a function of both the inner and outer image gradient vectors. For the hypothesis H₁ (target), the difference of the two functions is small. For the hypothesis H₀ (clutter), the difference of the two functions is large. Results of testing the proposed target detection algorithm on two large FLIR image databases are presented.

©(2004) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

S. Susan Young, Heesung Kwon, Sandor Z. Der, and Nasser M. Nasrabadi "Adaptive target detection in forward-looking infrared imagery using the eigenspace separation transform and principal component analysis," Optical Engineering 43(8), (1 August 2004). https://doi.org/10.1117/1.1768534

Published: 1 August 2004

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