A new performance metric, the two-dimensional （2D） contrast threshold surface, is proposed to charac- terize the systematic performance of a multi-spectral imaging sensor. Specifically, how to measure this performance metric is presented based on the discriminations of a set of sine-wave test patterns with dif- ferent radiance magnitudes and spectral properties. The theoretical model for predicting the 2D contrast threshold surface is derived based on an analytical description of the effective contrast between the test pattern and its background, in which the impacts of fusion algorithms on the 2D contrast threshold surface are also discussed using the minimum threshold match criteria. Preliminary simulation results show that this model can be used to quantitatively characterize spatial frequencies on the contrast thresholds required test patterns through a multi-spectral imaging sensor. the real influence of the spectral differences and for the observer to just resolve the images of thetest patterns through a multi-spectral imaging sensor.
