Spatio-Chromatic PCA of a Mosaiced Color Image

In this paper, we analyze whether Principal Component Analysis (PCA) is an appropriate tool for estimating spatial information in spatio-chromatic mosaiced images. Ruderman et al. [1] have shown that the spatio-chromatic principal components of cone images contain first spatial information, followed by blue minus yellow and red minus green. However, their analysis is based on fully defined spatio-chromatic images. In case of a reduced spatio-chromatic set with a single chromatic value per pixel, such as present in the retina or in CFA images, we found that PCA is not an appropriate tool for estimating spatial information. By extension, we discuss that the relation between natural image statistics and the visual system does not remain valid if we take into account the spatio-chromatic sampling by cone photoreceptors.