Algebraic nonuniformity correction for infrared imagery using a hexagonal coordinate scheme

Abstract

Infrared imagery, like almost any other two-dimensional (2D) imagery, have been traditionally sampled and acquired using a traditional rectangular grid. Therefore, nonuniformity correction (NUC) algorithms for infrared imaging systems which mitigate the most dominant, bias/offset portion of the nonuniformity were developed on the rectangular grid. However, it is well-known that hexagonal sampling grid captures more information in sampled data/imagery when compared to traditional rectangular sampling, and a hexagonal addressing scheme (HAS) for hexagonally-sampled imagery to convert imagery between the two different coordinate systems was developed. In this work, we build on prior work by Sakoglu et al. who developed bilinear interpolation equations between two image frames under the 2-D global motion of the scene or the camera, and apply this 2D algebraic NUC algorithm to hexagonally-sampled imagery directly in the HAS domain by utilizing simulated hexagonal sampling of real IR images.