Changes in measured image irradiance have many physical causes and are the
primary cue for several visual processes such as edge detection and shape
from shading. Using physical models for CCD video cameras and material
reflectance, we quantify the variation in digitized pixel values that is
due to sensor noise and scene variation. This analysis forms the basis
of algorithms for camera characterization and calibration and for scene
description. Specifically, algorithms are developed for estimating the
parameters of camera noise and for calibrating a camera to remove the
effects of fixed pattern nonuniformity and spatial variation in dark
current. While these techniques have many potential uses, we describe in
particular how they can be used to estimate a measure of scene variation.
This measure is independent of image irradiance and can be used to
identify a surface from a single sensor band over a range of situations.
Experimental results confirm that the models presented in this paper are
useful for modeling the different sources of variation in real images
obtained from video cameras.