Most mass-produced, commercially available and fielded military reflective imaging systems operate across broad swaths of the visible, near infrared (NIR), and shortwave infrared (SWIR) wavebands without any spectral selectivity within those wavebands. In applications that employ these systems, it is not uncommon to be imaging a scene in which the image contrasts between the objects of interest, i.e., the targets, and the objects of little or no interest, i.e., the backgrounds, are sufficiently low to make target discrimination difficult or uncertain. This can occur even when the spectral distribution of the target and background reflectivity across the given waveband differ significantly from each other, because the fundamental components of broadband image contrast are the spectral integrals of the target and background signatures. Spectral integration by the detectors tends to smooth out any differences. Hyperspectral imaging is one approach to preserving, and thus highlighting, spectral differences across the scene, even when the waveband integrated signatures would be about the same, but it is an expensive, complex, noncompact, and untimely solution. This paper documents a study of how the capability to selectively customize the spectral width and center wavelength with a hypothetical tunable fore-optic filter would allow a broadband reflective imaging sensor to optimize image contrast as a function of scene content and ambient illumination.