Video compressive sensing for overlapped encoded frames

摘要

This paper investigates a particular application of compressive sensing (CS) for reconstruction of video data cubes in temporal multiplexing scheme (TM) and focuses on exploring the after acquisition reconstruction process. We propose a new implementation based on weighted 3D total variation algorithm with residual based updating parameters under the alternating direction method of multipliers (ADMM) framework for video CS applications. This method enables a fast data reconstruction with higher resolution compared to the other bench mark methods and benefits from iterative updates on optimisation parameters. We explore the reconstruction quality of the proposed method by comparing the results to some of the state of the art algorithms used in video CS and discuss the calculation time needed to process the data. Last section of this paper investigates the behaviour of the algorithm while handling the large amount of data and explores the potentials of proposed scheme to capture longer video sequences.