CNN Color Demosaicking Generalizes for any CFA

A convolutional neural network is trained in auto/hetero-associative mode for reconstructing RGB components from a randomly mosaicked color image. The was shown to perform equally well when images are sampled periodically or with different random mosaic. Therefore, this model able generalize on every type of filter array. We attribute property universal demosaicking the learning statistical structure independently mosaic pattern arrangement.