Paper
29 September 1995 Multispectra infrared sequential image processing for point target detection
George A. Lampropoulos, James F. Boulter
Author Affiliations +
Abstract
In this paper, we study the effects of orthogonalization on sequential, multisensor, and multispectral satellite images for CFAR point target detection incorporting fusion techniques. Although the K-L orthogonalization offers the best CFAR detection performance, it requires central fusion. A version of the G-S orthogonalization method, which preprocesses data in a pipeline form, offers a comparable CFAR detection to that of the K-L method. Point target CFAR detection is carried out by employing various fusion approaches on the orthogonal data. Sensor level fusion with quality information is shown to be preferable when the proposed sequential G-S orhtogonaltization is applied. The proposed CFAR approach is applied to dissimilar sensors and avoids overloading the communication channel transmitting only in the case of target detection. Trade-off studies and experimental results on real and simulated data are presented.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
George A. Lampropoulos and James F. Boulter "Multispectra infrared sequential image processing for point target detection", Proc. SPIE 2553, Infrared Spaceborne Remote Sensing III, (29 September 1995); https://doi.org/10.1117/12.221353
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Cited by 2 scholarly publications.
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KEYWORDS
Sensors

Target detection

Signal to noise ratio

Image fusion

Data fusion

Sensor fusion

Information fusion

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