This paper concerns compressive sensing methods for overcoming the pixel-limited resolution of digital video imaging systems. Recent developments in coded aperture mask designs have led to the reconstruction of static images from a single, low-resolution, noisy observation image. Our methods apply these coded mask designs to each video frame and use compressive sensing optimization techniques for enhanced resolution digital video recovery. We demonstrate that further improvements can be attained by solving for multiple frames simultaneously, even when the total computation time budget is held fixed.
['Roummel F. Marcia', 'Rebecca Willett']
Compressive coded aperture video reconstruction