Optimizing Codes for Source Separation in Compressed Video Recovery and Color Image Demosaicing

There exist several applications in image processing (eg: video compressed sensing [8] and color image demosaicing) which require separation of constituent images given measurements in the form of a coded superposition of those images. Physically practical code patterns in these applications are non-negative and do not obey the nice coherence properties of other patterns such as Gaussian codes, which can adversely affect reconstruction performance. The contribution of this paper is to design code patterns for video compressed sensing and demosaicing by minimizing the mutual coherence given a fixed dictionary. Our method explicitly takes into account the special structure of those code patterns as required by these applications: (1) non-negativity, (2) block-diagonal nature, and (3) circular shifting. In particular, the last property enables for accurate patchwise reconstruction.