Focal-plane processing architectures for real-time hyperspectral image processing.


Real-time image processing requires high computational and I/O throughputs obtained by use of optoelectronic system solutions. A novel architecture that uses focal-plane optoelectronic-area I/O with a fine-grain, low-memory, single-instruction-multiple-data (SIMD) processor array is presented as an efficient computational solution for real-time hyperspectral image processing. The architecture is evaluated by use of realistic workloads to determine data throughputs, processing demands, and storage requirements. We show that traditional store-and-process system performance is inadequate for this application domain, whereas the focal-plane SIMD architecture is capable of supporting real-time performances with sustained operation throughputs of 500-1500 gigaoperations/s. The focal-plane architecture exploits the direct coupling between sensor and parallel-processor arrays to alleviate data-bandwidth requirements, allowing computation to be performed in a stream-parallel computation model, while data arrive from the sensors.

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@article{Chai2000FocalplanePA, title={Focal-plane processing architectures for real-time hyperspectral image processing.}, author={Sek M. Chai and Aniello Gentile and Wilfredo E. Lugo-Beauchamp and J. Fonseca and Jos{\'e} Cruz-Rivera and D. Scott Wills}, journal={Applied optics}, year={2000}, volume={39 5}, pages={835-49} }