In digital imaging applications, data are typically obtained via a spatial sub-sampling procedure implemented as a color filter array (CFA). CFA assigns a separate primary color to each pixel by placing a filter of that color over the pixel. The most well known CFA is the Bayer pattern which uses a checkerboard pattern with alternating rows of filters. The Bayer filter has twice as many green pixels as red or blue and takes advantage of the human eye's tendency to see green luminance as the strongest influence in defining image quality.

Despite its widespread use, the Bayer pattern imposes inherent limitations upon the design of interpolation and de-noising methods. In particular, the rectangular sub-sampling lattice associated with Bayer-patterned data induces spectral copies of the difference signals centered about the set of frequencies. Hence, by reducing allowable bandwidth, the Bayer spectral periodization "penalizes" the very horizontal and vertical features which are most likely to appear in typical "real world" images.

The proposed scheme, an alternative to the Bayer pattern, offers the potential to significantly reduce hardware complexity in a wide variety of applications, while at the same time improving output color image quality.