DocumentCode :
2610320
Title :
FPGA-based Neural Network for Nonuniformity Correction on Infrared Focal Plane Arrays
Author :
Celedón, Nicolás ; Redlich, Rodolfo ; Figueroa, Miguel
Author_Institution :
Dept. of Electr. Eng., Univ. of Concepcion, Concepcion, Chile
fYear :
2012
fDate :
5-8 Sept. 2012
Firstpage :
193
Lastpage :
200
Abstract :
Despite recent technological advances which improve their performance and reduce their cost, Focal Plane Arrays for infrared imagers suffer from spatial nonuniformity that renders their output unusable unless a suitable correction method is applied. This paper describes an embedded hardware implementation of Scribner´s algorithm for online nonuniformity correction. Our implementation on a Xilinx Spartan XC3S1200E FPGA achieves a throughput of more than 130 frames per second on 320x240-pixel IR video, which greatly exceeds real-time requirements. The power consumption of our system is 329mW, which is two orders of magnitude smaller than a software implementation of the algorithm on a traditional processor, and can be greatly reduced with a custom-VLSI implementation of the architecture.
Keywords :
field programmable gate arrays; focal planes; infrared imaging; neural chips; FPGA-based neural network; Scribner algorithm; VLSI; Xilinx Spartan XC3S1200E FPGA; infrared focal plane arrays; infrared imagers; online nonuniformity correction method; pixel IR video; power 329 mW; power consumption; Cameras; Field programmable gate arrays; Hardware; Neural networks; Noise; Random access memory; Streaming media; Field-programmable gate array; Neural network; Nonuniformity correction; Smart IR camera;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital System Design (DSD), 2012 15th Euromicro Conference on
Conference_Location :
Izmir
Print_ISBN :
978-1-4673-2498-4
Type :
conf
DOI :
10.1109/DSD.2012.64
Filename :
6386892
Link To Document :
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