Analytical Design of Multispectral Sensors

An analytical procedure for the design of the spectral channels for multispectral remote sensor systems is defined. An optimal design based on the criterion of minimum mean-square representation error using the Karhunen-Loeve expansion was developed to represent the spectral response functions from a stratum based upon a stochastic process scene model. From the overall pattern recognition system perspective the effect of the representation accuracy on a typical performance criterion, the probability of correct classification, is investigated. The optimum sensor design provides a standard against which practical (suboptimum) operational sensors can be compared. An example design is provided and its performance is illustrated. Although the analytical technique was developed primarily for the purpose of sensor design it was found that the procedure has potential for making important contributions to scene understanding. It was concluded that spectral channels which have narrow bandwidths relative to current sensor systems may be necessary to provide adequate spectral representation and improved classification performance.