Commercialization of spectral imaging for color reproduction will require low bandwidth but highly accurate spectral image acquisition systems. Self-adapting systems are proposed as potential solutions. Such systems perform spectral content analysis on an encountered scene, reacting to the analysis by configuring efficient high quality spectral reconstruction. An experiment is reported comparing scene-derived spectral estimation transforms to static global transforms in multi-channel imaging simulations. For noise-free simulations, the adaptive approach showed clear benefit in terms of colorimetric and spectral statistics. When noise was added, the adaptive method continued to be superior in terms of spectral evaluations, but colorimetric degradation for the adaptive approach exceeded that of the static. This provided additional evidence that spectral reconstruction methods should reference psychometrics as an integral part of spectral error management.