POCS-Based Restoration of Bayer-Sampled Image Sequences

Spatial resolution of digital images are limited due to optical/sensor blurring and sensor site density. In single-chip digital cameras, the resolution is further degraded because such devices use a color filter array to capture only one spectral component at a pixel location. The process of estimating the missing two color values at each pixel location is known as demosaicking. Demosaicking methods usually exploit the correlation among color channels. When there are multiple images, it is possible not only to have better estimates of the missing color values but also to improve the spatial resolution further (using super-resolution reconstruction). Previously, we have proposed a demosaicking algorithm based on the projection onto convex sets (POCS) technique. In this paper, we improve the results of that algorithm adding a new constraint set based on the spatio-intensity neighborhood. We extend the algorithm to image sequences for multi-frame demosaicking and super resolution.