A 16-band plenoptic camera allows for the rapid exchange of filter sets via a 4x4 filter array on the lens’s front aperture thus allowing an operator to quickly adapt to a different locale or threat intelligence. Typically, such a system incorporates a default set of 16 equally spaced, non-overlapping, flat-topped filters. Knowing the operating theater or the likely targets of interest it becomes advantageous to tune the filters; we propose a differential evolution approach to search over a set of commercial off-the-shelf (COTS) filters for an optimal collection of filters. We examine two independent tasks: general spectral sensing and target detection. For general spectral sensing, we utilize compressive sensing and find filters that generate codings which minimize the reconstruction error. For target detection, we select filters to optimize the separation between the background and a set of targets. We compare the results obtained using the selected COTS filters to the default filter set and full spectral resolution hyperspectral (HS) filter set for target detection and general spectral sensing on a previously obtained HS image.