Color Demosaicing by Estimating Luminance and Opponent Chromatic Signals in the Fourier Domain

We propose a new method for color demosaicing based on a mathematical model of spatial multiplexing of color. We demonstrate that a one-color per pixel image can be written as the sum of luminance and chrominance. In case of a regular arrangement of colors, such as with the Bayer color filter array (CFA), luminance and chrominance are well localized in the spatial frequency domain. Our algorithm is based on selecting the luminance and chrominance signal in the Fourier domain. This simple and efficient algorithm gives good results, comparable with the Bayesian approach to demosaicing. Additionally, this model allows us to demonstrate that the Bayer CFA is the most optimal arrangement of three colors on a square grid. Visual artifacts of the reconstruction can be clearly explained as aliasing between luminance and chrominance. Finally, this framework also allows us to control the trade-off between algorithm efficiency and quality in an explicit manner.