Parallel Algorithms For Automatic Target Identification Using CO2 Laser Radar Imagery

Arthur V. Forman Jr.; Daniel J. Sullivan

doi:10.1117/12.962382

6 December 1989 Parallel Algorithms For Automatic Target Identification Using CO₂ Laser Radar Imagery

Arthur V. Forman Jr., Daniel J. Sullivan

Proceedings Volume 1154, Real-Time Signal Processing XII; (1989) https://doi.org/10.1117/12.962382
Event: 33rd Annual Technical Symposium, 1989, San Diego, United States

Abstract

This paper describes a parallel implementation of algorithms for automatic target identification using a CO2 laser radar sensor, which provides pixel-registered visual, infrared, relative range and Doppler (motion) images. Images are preprocessed to remove artifacts and speckle and to detect edges. The processed images are then passed to a transformation which provides a representation independent of translation, rotation, and scaling of the input scene. The transformed image is designed to be input to a neural network to extract features representative of the targets. This paper also discusses three-dimensional transformation of range images for pattern matching and the implementation of algorithms in a single instruction, multiple data (SIMD) parallel architecture.

Citation Download Citation

Arthur V. Forman Jr. and Daniel J. Sullivan "Parallel Algorithms For Automatic Target Identification Using CO₂ Laser Radar Imagery", Proc. SPIE 1154, Real-Time Signal Processing XII, (6 December 1989); https://doi.org/10.1117/12.962382

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