D. H. Kim

City College of New York

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George Eichmann

City College of New York

A. Kostrzewski

City College of New York

Andrew A. Kostrzewski

Physical Optics Corporation

Gernot Eichmann

University of Graz

Y. Li

State Key Laboratory of Remote Sensing Science

Byung-Ho Ha

Inje University Busan Paik Hospital

Y. Li

City College of New York

Y. Li

City College of New York

Cooperative Institutions

City College of New York

City College

City University of New York

York College, City University of New York

Physical Optics Corporation

Bellingham Technical College

International Society for Optics and Photonics

Roma Tre University

Combat Capabilities Development Command Soldier Center

Clemson University

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Optoelectronic content addressable memory-based modified signed digit arithmetic

Annual Meeting Optical Society of America (1989)

Y. Li D. H. Kim A. Kostrzewski George Eichmann

The modified signed digit (MSD) number system offers inherent low interdigit dependence for arithmetic processing. Recently, using both optical logic and memory based approaches, various optical MSD arithmetic schemes were proposed. For the logic based optical MSD arithmetic, an existing approach implements a three-stage processing algorithm with either a symbolic substitution processor or some binary logic elements, such as bistable etalons. Because of the use of multiple processing stages, the required computing energy and its speed is sacrificed. The optical memory based approach, on the other hand, utilizes a single-stage content addressable memory (CAM) for a fast MSD arithmetic. However, the existing holographic CAM is difficult to implement. In this talk, a new nonholographic CAM scheme for a single-stage MSD addition processing is proposed and demonstrated. A position encoded 18 × 56 pixel CAM mask is used in an angularly multiplexed geometry for a parallel CAM matching operation. Electronic logic inverters are used as the output devices.

Arithmetic logic unit

10.1364/oam.1989.tumm3

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Real time programmable optical morphological filter

Annual Meeting Optical Society of America (1989)

Y. Li A. Kostrzewski D. H. Kim George Eichmann

Morphological filtering (MF), a form of nonlinear image processing, has recently been applied to optical image processing. Among the MF processing capabilities are the noise removal, median filtering, edge detection, and skeletonization. For an electronic MF implementation, a time-consuming 2-D image correlation is performed. Although an electronic special-purpose cellular processor can be used for MF processing, its processing and interconnect complexity is large. On the other hand, using free-space optics, both coherent and incoherent optical MF have been suggested. The existing optical MF approaches have drawbacks, such as their lack of programmability, employing a less-compact architecture, etc. In this talk, a new liquid crystal TV (LCTV) based compact, real time programmable optical MF is proposed and described. Using a LCTV addressed lenslet array that serves as a structuring element and a projection lens followed by an electronic threshold processor, this new compact optical device experimentally demonstrates its capability of performing real time image dilation, erosion, and noise clean-up operations.

Structuring element

Skeletonization

10.1364/oam.1989.thx1

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Parallel Optical Pyramidal Image Processing

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1988)

Gernot Eichmann Andrew A. Kostrzewski Byung-Ho Ha D. H. Kim Y. Li

Pyramidal processing is a form of multiresolution image analysis in which a primary image is decomposed into a set of different resolution image copies. Pyramidal processing aims to extract and interpret significant features of an image appearing at different resolutions. Digital pyramidal image processing, because of the large number of convolution type operations, is time-consuming. On the other hand, optical pyramidal processors, because of their ease in performing convolution operation, are preferable in real-time image understanding applications. Two methods of optical pyramidal image generation, a Fourier spectrum filtering based, and a local averaging using 2D lens array, are presented. Preliminary experimental results for optical Gaussian, Laplacian and other fivadtree pyramidal image processing are shown. Experimental results, using commercial lifiuid crystal TVs, for a real-time pyramid image generation are presented.

Pyramid (geometry)

Convolution (computer science)

10.1117/12.947053

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