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.
Chai
S M
SM
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0250, USA. sek@ece.gatech.edu
Gentile
A
A
Lugo-Beauchamp
W E
WE
Fonseca
J
J
Cruz-Rivera
J L
JL
Wills
D S
DS