Block-recursive filtering for offset nonuniformity estimation in infrared imaging systems: Theory and implementation

In an earlier work, a recursive filter to compensate for the offset nonuniformity (NU) noise corrupting the output of infrared (IR) imaging system was presented. Such a filter was derived assuming an estimation time-window short enough so that the offset NU can be regarded as a constant corrupted by additive noise. In this paper, the assumption on the stationarity of the offset NU noise has been relaxed by characterizing the dynamics of the offset NU using a Gauss–Markov random process. Based upon this model, a recursive filter that uses blocks of IR data to estimate the offset NU has been derived. A rigorous theoretical analysis of the filter has been conducted in order to provide expressions for appropriately selecting the parameters of the filter. The ability of the block-recursive filter to compensate for NU noise has been tested using raw IR videos from different IR cameras. In addition, the filter has been implemented and tested on-line in a prototype spectrally tunable IR camera.