Modeling misregistration and related effects on multispectral classification

Abstract

Misregistration is but one of a group of parameters (noise, class separability, spatial transient response, field sizes) affecting the accuracy of multispectral classification. The entire group must be considered simultaneously. Any noise in the measurements (due to the scene, to the sensor, or to the analog/digital conversion) will cause a finite fraction of the measurements to fall outside of the classification limits, even within nominally uniform fields. For field boundaries, where the effects of misregistration are felt, additional pixels will be misclassified due to the mixture of materials in the pixels. Misregistration causes field borders in a given (set of) band(s) to be closer than expected to a given pixel, causing additional pixels to be misclassified. Simplified models of the various effects are used to gain conceptual understanding and to estimate the performance to be expected.