Hyper-spectral image processing applications on the SIMD Pixel Processor for the digital battlefield

Abstract

Future military scenarios will rely on advanced imaging sensor technology beyond the visible spectrum to gain total battlefield awareness. Real-time processing of these data streams requires tremendous computational workloads and I/O throughputs. This paper presents three applications for hyper-spectral data streams, vector quantization, region autofocus, and K-means clustering, on the SIMD Pixel Processor (SIMPil). In SIMPil, an image sensor array (focal plane) is integrated on top of a SIMD computing layer to provide direct coupling between sensors and processors, alleviating I/O bandwidth bottlenecks while maintaining low power consumption and portability. Simulation results with sustained operation throughputs of 500-1500 Gops/sec support real-time performance and promote focal plane processing on SIMPil.