Enhancing Demosaicking Algorithms using Loopy Propagation

Consumer-level digital cameras observe a single value at each pixel. The remaining two channels of a three-channel image are reconstructed through a process called demosaicking. This paper describes a methodology for enhancing current demosaicking methods. Using an iterative relaxation approach from probabilistic AI literature, our empirical results show that we can improve the results of the standard algorithms using monitored successive application of those algorithms. We apply the new technique to several algorithms: hue-based interpolation, gradient-based interpolation, and adaptive colour plan interpolation; and we show a significant improvement in mean-squared error over both RGB and CIE colour spaces using each of these algorithms.