Paper
9 April 2007 System issues of developing grayscale optical correlator for ATR applications
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Abstract
We have been developing Grayscale Optical Correlator (GOC) and exploring a variety of automatic target recognition (ATR) applications to take advantage of the inherent performance advantages of the GOC parallel processing, high-speed, vast parallelism and high-speed [1-4]. To date, we have built compact 512 x 512, 1000 fps GOC systems and tested/demonstrated for field ATR experiments. We have also worked with our industrial partners to develop a 1024 x 1024 Ferroelectric Spatial Light Modulator (FLCSLM) to meet the challenging applications demanding larger input scene Field-of-View (FOV) and higher resolution. In this paper, two major system issues that we have encountered during the development efforts for real-world applications will be discussed. These include: 1) SLM dynamic range limitations and 2) ATR performance for CAD/CAC, computer-aided detection & classification (CAD/CAC) applications. Our simulation study has shown that the current 8-bit dynamic range possessed by the FLCSLM is adequate for both the input image and the correlation filter encodings. We will also describe the addition of a neural network (NN) post-processor to greatly decrease the false positive detection rate while retaining the high positive detection rate obtained by the by the GOC. Experimental results demonstrating the high-performance of the fused GOC and NN processor will be provided.
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Tien-Hsin Chao and Thomas Lu "System issues of developing grayscale optical correlator for ATR applications", Proc. SPIE 6574, Optical Pattern Recognition XVIII, 657405 (9 April 2007); https://doi.org/10.1117/12.723632
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KEYWORDS
Target detection

Automatic target recognition

Optical correlators

Image filtering

Spatial light modulators

Image processing

Neural networks

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