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, color processing, and rendering. A spectral image processing algorithm is used to simulate the radiometric properties of a digital camera. In the algorithm, we take into consideration the spectral image and the transmittances of the light source, lenses, filters, and the quantum efficiency of a complementary metal-oxide semiconductor (CMOS) image sensor. The optical part is characterized by a multiple convolution between the different point spread functions optical components such as the 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, dynamic range, and analog to digital conversion. The reconstruction of the noisy blurred image is performed by blending different light exposed images in order to reduce the noise. Then, the image is filtered, deconvoluted, and sharpened to eliminate the noise and blur. Next, we have the color processing and rendering blocks interpolation, white balancing, color correction, conversion from XYZ color space to LAB color space, and, then, into the RGB color space, the color saturation and contrast.