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.
© 2000 Optical Society of America
(100.0100) Image processing : Image processing
(100.2000) Image processing : Digital image processing
(100.2550) Image processing : Focal-plane-array image processors
(110.0110) Imaging systems : Imaging systems
Sek M. Chai, Antonio Gentile, Wilfredo E. Lugo-Beauchamp, Javier Fonseca, José L. Cruz-Rivera, and D. Scott Wills, "Focal-Plane Processing Architectures for Real-Time Hyperspectral Image Processing," Appl. Opt. 39, 835-849 (2000)