A New Class of Color Filter Arrays with Optimal Sensing Properties

Digital color cameras acquire color images by means of a sensor on which a color filter array (CFA) is overlaid. The Bayer CFA dominates the consumer market, but few attention has been directed to the design of alternative CFAs in the literature. Recent works of Hirakawa et al. introduced new insights in this field, by focusing on the spectral properties of CFAs and operating directly in the Fourier domain. However, this new paradigm is generic and leaves open questions about the optimization of the many available parameters. In this work, we investigate the link between them and the light sensitivity and color discrimination capabilities of the CFA. Indeed, these characteristics determine the quality of the whole imaging pipeline, since they directly control its sensitivity to noise. By optimizing the key parameters, we obtain a class of new CFAs with optimal properties, in which the shortest 2 × 3 pattern shows up as the best compromise. Moreover, a simple and efficient linear demosaicking algorithm is associated to these CFAs, that fully exploits their spectral properties. Practical experiments confirm the superiority of our new design.