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
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