LOW BIT-RATE COMPRESSION OF VIDEO AND LIGHT-FIELD DATA USING CODED SNAPSHOTS AND LEARNED DICTIONARIES

The method of coded snapshots has been proposed recently for compressive acquisition of video data to overcome the space-time trade-of inherent in video acquisition. The method involves modulation of the light entering the video camera at different time instants during the exposure period by means of a different and randomly generated code pattern at each of those time instants, followed by integration across time, leading to a single coded snapshot image. Given this image and knowledge of the random codes, it is possible to recon-struct the underlying video frames- by means of sparse cod-ing on a suitably learned dictionary. In this paper, we ap-ply a modified version of this idea, proposed formerly in the compressive sensing literature, to the task of compression of videos and light-field data. At low bit rates, we demonstrate markedly better reconstruction fidelity for the same storage costs, in comparison to JPEG2000 and MPEG-4 (H.264) on light-field and video data respectively. Our technique can cope with overlapping blocks of image data, thereby leading to suppression of block artifacts. 1