  Microsatellites and drones are often equipped with digital cameras whose
sensing system is based on color filter arrays (CFAs), which define a pattern
of color filter overlaid over the focal plane. Recent commercial cameras have
started implementing RGBW patterns, which include some filters with a wideband
spectral response together with the more classical RGB ones. This allows for
additional light energy to be captured by the relevant pixels and increases the
overall SNR of the acquisition. Demosaicking defines reconstructing a
multi-spectral image from the raw image and recovering the full color
components for all pixels. However, this operation is often tailored for the
most widespread patterns, such as the Bayer pattern. Consequently, less common
patterns that are still employed in commercial cameras are often neglected. In
this work, we present a generalized framework to represent the image formation
model of such cameras. This model is then exploited by our proposed
demosaicking algorithm to reconstruct the datacube of interest with a Bayesian
approach, using a total variation regularizer as prior. Some preliminary
experimental results are also presented, which apply to the reconstruction of
acquisitions of various RGBW cameras.
