Parallel Image Processing Using Incoherent Optical General Matrix Multiplication

Image filtering is essential to image processing and machine vision systems. To enhance the throughput, multiple filters are applied simultaneously using matrix-matrix multiplication. Here we experimentally demonstrate the use of a novel optical general matrix multiplication (OGeMM) scheme to apply several image kernels, namely Laplace, Gaussian, and Sobel horizontal and vertical, in parallel. The OGeMM uses incoherent laser and wavelength multiplexing, handles signed numbers, and enables single simultaneous data write and read for single-shot parallel image processing.

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Published
2025-05-20
DOI
https://doi.org/10.1109/pn66844.2025.11097126
Primary Topic
Neural Networks and Reservoir Computing
Type
article
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article

Parallel Image Processing Using Incoherent Optical General Matrix Multiplication

Farshid Ashtiani, Mohamad Hossein Idjadi
Neural Networks and Reservoir Computing
article

Parallel Image Processing Using Incoherent Optical General Matrix Multiplication

Farshid Ashtiani, Mohamad Hossein Idjadi
article en

Abstract

Image filtering is essential to image processing and machine vision systems. To enhance the throughput, multiple filters are applied simultaneously using matrix-matrix multiplication. Here we experimentally demonstrate the use of a novel optical general matrix multiplication (OGeMM) scheme to apply several image kernels, namely Laplace, Gaussian, and Sobel horizontal and vertical, in parallel. The OGeMM uses incoherent laser and wavelength multiplexing, handles signed numbers, and enables single simultaneous data write and read for single-shot parallel image processing.

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