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.