The goal of this paper is to simulate the functionality of a digital camera system. The simulations cover the conversion
from light to numerical signal and the color processing and rendering. We consider the image acquisition system to be
linear shift invariant and axial. The light propagation is orthogonal to the system. We use a spectral image processing
algorithm in order to simulate the radiometric properties of a digital camera. In the algorithm we take into consideration
the transmittances of the: light source, lenses, filters and the quantum efficiency of a CMOS (complementary metal oxide
semiconductor) sensor. The optical part is characterized by a multiple convolution between the different points spread
functions of the optical components. We use a Cooke triplet, the aperture, the light fall off and the optical part of the
CMOS sensor. The electrical part consists of the: Bayer sampling, interpolation, signal to noise ratio, dynamic range,
analog to digital conversion and JPG compression. We reconstruct the noisy blurred image by blending different light
exposed images in order to reduce the photon shot noise, also we filter the fixed pattern noise and we sharpen the image.
Then we have the color processing blocks: white balancing, color correction, gamma correction, and conversion from
XYZ color space to RGB color space. For the reproduction of color we use an OLED (organic light emitting diode)
monitor. The analysis can be useful to assist students and engineers in image quality evaluation and imaging system
design. Many other configurations of blocks can be used in our analysis.