Multi-spectral demosaicing: A joint-sparse elastic-net formulation

This work proposes techniques for demosaicing multi-spectral images obtained from a single sensor architecture. This is a new problem. Compressed Sensing (CS) based formulations can recover images by exploiting the sparsity of the images in the wavelet domain. In this work, we improve upon existing techniques by accounting for the hierarchical (tree-structured) correlation that exists among the wavelet coefficients of piecewise smooth signals. For a single image, this turns out to be an elastic -net problem. Since our problem involves multi-spectral images, the proposed formulation leads to a joint-sparse elastic-net optimization problem which is solved via Split Bregman type algorithm. Our proposed improvement yields considerably better recovery results compared to existing techniques.