Non-uniformity noise is common in infrared imagers, and is usually corrected through calibration, often by momentarily blocking the optical system with a relatively uniform temperature plate. The non-uniformity patterns also tend to drift and require periodic recalibration, necessitating occasional loss of video from the imager during the recalibration process. Microgrid polarimeters are especially sensitive to fixed-pattern noise because the polarization signal is acquired by differentiation of neighboring pixels. Scene-based algorithms attempt to alleviate the need for recalibration of the imager through image processing techniques. We introduce a new frequency-domain scene-based non-uniformity estimation and correction technique, and apply the technique to infrared and microgrid polarimeter imagery. The technique demonstrates promising results for shutter-assisted (recalibration) video, for microgrid polarization systems as well as most spatially modulated sensor systems.