SBNUC based on Constant Statistics for VOx uncooled IRFPA and implementation with FPGA

The quality of infrared imaging system was limited by the non-uniformity (NU) in the Infrared Focal Plane Array(IRFPA), especially in the uncooled infrared imaging system. Scene based non-uniformity correction (SBNUC) algorithms are widely concerned since they only need the readout infrared data captured by the imaging system during its normal operation. However, there still exists the problem of ghost artifact in the algorithms, and their performance is noticeably degraded when the methods are applied over scenes with lack of motion. In addition, most SBNUC algorithms are difficult to be implemented in the hardware. In this paper, to reduce the fringe NU in uncooled VOx IRFPA we present a simple and effective SBNUC method based on Constant Statistics in which the fringe NU is reduced by balancing the statistics of the vertical channels. Through analyzing the reason of ghost artifact being brought in in the SBNUC algorithms, our algorithm successfully reduce the ghost artifact that plagues SBNUC algorithms through the use of optimization techniques in the parameter estimation. The advantage of the algorithm lies in its simplicity and low computational complexity. Our algorithm is implemented on a FPGA hardware platform with XC5VSX50T as the kernel processor, the raw infrared data are provided by an uncooled infrared focal plane array of VOx which has fringe NU. Our processing system reaches high correction levels, fringe NU being reduced, the ghost artifact being decreased, which can lay a technical foundation for the following study and applications of high performance thermal imaging system.