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Evaluation of binary-phase-only filters for distortion-invariant pattern recognition
The paper examines the performance of fSDF (filter synthetic discriminant function) binary-phase-only filters (BPOFs) for images in the distortion-range that were not members of the training set. Consideration is given to the nature of the tradeoff between the extent of the distortion range and the correlator performance for fSDF-BPOFs, and to the probable constraints this tradeoff will impose on a realized optical correlator.
Optical processing and Space Station automation
Optical information processing research aimed at Space Station automation applications is reviewed. The emphasis of the NASA Ames Research Center program is on intelligent optical pattern recognition and optical control processing. Attention is given to the primary functions of an overall scene understanding system: distortion-invariant optical feature generation, dimensionality reduction, object classification, and contextual information processing. A method of using synthetic discriminant functions to facilitate learning in a high-speed optical correlator is described. A discussion is presented of candidate analog and digital architectures for the optical implementation of state-estimation algorithms needed for the control of high-dimension dynamic systems. The multivariate system chosen for the optical control technology demonstration - a segmented, adaptive mirror and interferometrically based wavefront sensor - is also described.
Photonic processing at NASA Ames Research Center
The Photonic Processing group is engaged in applied research on optical processors in support of the Ames vision to lead the development of autonomous intelligent systems. Optical processors, in conjunction with numeric and symbolic processors, are needed to provide the powerful processing capability that is required for many future agency missions. The research program emphasizes application of analog optical processing, where free-space propagation between components allows natural implementations of algorithms requiring a large degree of parallel computation. Special consideration is given in the Ames program to the integration of optical processors into larger, heterogeneous computational systems. Demonstration of the effective integration of optical processors within a broader knowledge-based system is essential to evaluate their potential for dependable operation in an autonomous environment such as space. The Ames Photonics program is currently addressing several areas of interest. One of the efforts is to develop an optical correlator system with two programmable spatial light modulators (SLMs) to perform distortion invariant pattern recognition. Another area of research is optical neural networks, also for use in distortion-invariant pattern recognition.
Optical information processing for NASA's space exploration
The development status of optical processing techniques under development at NASA-JPL, NASA-Ames, and NASA-Johnson, is evaluated with a view to their potential applications in future NASA planetary exploration missions. It is projected that such optical processing systems can yield major reductions in mass, volume, and power requirements relative to exclusively electronic systems of comparable processing capabilities. Attention is given to high-order neural networks for distortion-invariant classification and pattern recognition, multispectral imaging using an acoustooptic tunable filter, and an optical matrix processor for control problems.
Optical pattern recognition III; Proceedings of the Meeting, Orlando, FL, Apr. 21, 22, 1992
Consideration is given to transitioning of optical processing into systems (TOPS), optical correlator hardware, phase-only optical correlation filters, optical distortion-invariant correlation filters, and optical neural networks. Particular attention is given to a test target for optical correlators, a TOPS electronic warfare channelizer program, a portable video-rate optical correlator, a joint transform correlator employing electron trapping materials, a novelty filtered optical correlator using a photorefractive crystal, a comparison of correlation performance of smart ternary phase-amplitude filters with gray-scale and binary input scenes, real-time distortion-tolerant composite filters for automatic target identification, landscaping the correlation surface, fast designing of a circular harmonic filter using simulated annealing, feature-based correlation filters for distortion invariance, automatic target recognition using a feature-based optical neural network, and a holographic inner-product processor for pattern recognition.