Reconstruction of bidirectional predicted residual for stereoscopic video based on compressed sensing

Abstract

As an effective method applied in video processing, compressed sensing(CS)[1] has gained wide interests. As we known, in traditional methods, if we want to recover a signal accurately from the samples, then the sampling rate has to be at least twice the maximum frequency present in the signal, which known as the Nyquist sampling rate. However, the sampling rate under the framework of compressed sensing can be much lower than the Nyquist sampling rate. As we will see in the remainder of this paper, CS asserts that we can recover certain signals from far few samples or measurements than traditional ways use. So as to save costs and improve efficiency, based on compressed sensing，we propose a reconstruction method for stereoscopic video codec. In our method, sparse residuals obtained by the block-based stereoscopic video processing and bidirectional prediction, are coded and reconstructed based on compressed sensing. Compared with other methods through simulation experiments, the proposed method reduces the sampling rate, and improves the quality of the reconstructed stereoscopic videos.