Research On Nonuniformity Correction For Infrared Focal Plane Array Based On SoC

As the core component of infrared imaging system, the infrared focal plane arrays (IRFPA) is one kind of advanced infrared detector, which has both function of sensitive to infrared radiation and signal processing. A variety of infrared thermal imaging system based on IRFPA have been widely applied in many aspects of military andcivilian.However,because of the materials, technology, surrounding environment and other factors cause the nonuniformity of infrared focal plane arrays. The existence of nonuniformity greatly limits the performance of imaging systems, so we must perform nonuniformity correction for the IRFPA.In this paper, firstly discusses and contrasts several existing nonuniformity correction methods. calibration is simple,however,it must recalibration after surrounding environment has changed, while scene-based nonuniformity correction methods has the advantages of need no reference radiation source, recalibration and adaptive correction, so it will be the hotspot and focus.. It emphatically introduced the BP artificial neural network algorithm among scene-based nonuniformity correction algorithms. The parameters of classical BP correction algorithm is hard to choose, aimed at this shortcoming, this paper selects a modified BP algorithm - normalized BP artificial neural network algorithm as the ultimate correction algorithm.On the way of hardware implementation of the algorithm, this paper adopted the SOPC technology based on FPGA.FPGA is one kind of programmable logic device raised recently which has the features of fast speed and great flexibility, so using FPGA to carry out the nonuniformity correction has great advantages. this system uses Altera's stratix II EP2S60 DSP development board as hardware development platform, and then adopts the SOPC technology based on NiosⅡto build a nonuniformity correction system on this platform. Finally, research of simulation for normalized BP artificial neural network correction algorithm, discusses the different parameters related to correction results, and achieved all that we expected.