In this paper, we introduce the Skellam distribution as
a sensor noise model for CCD or CMOS cameras. This is
derived from the Poisson distribution of photons that deter-
mine the sensor response. We show that the Skellam dis-
tribution can be used to measure the intensity difference of
pixels in the spatial domain, as well as in the temporal do-
main. In addition, we show that Skellam parameters are
linearly related to the intensity of the pixels. This property
means that the brighter pixels tolerate greater variation of
intensity than the darker pixels. This enables us to decide
automatically whether two pixels have different colors. We
apply this modeling to detect the edges in color images.
The resulting algorithm requires only a confidence interval
for a hypothesis test, because it uses the distribution of im-
age noise directly. More importantly, we demonstrate that
without conventional Gaussian smoothing the noise model-
based approach can automatically extract the fine details of
image structures, such as edges and corners, independent
of camera setting.