Compressed sensing (CS) breaks the limit of Nyquist sampling rate and provides a new method for information sampling. Compressed video sensing (CVS) introduces CS into video codec and decreases the burden of encoding. For three-dimensional video data, the cube-based CVS scheme is an intuitive method in that CS measurements can span the entire spatial and temporal extent of a video sequence. Unfortunately, the measuring of multiple frames in video cubes simultaneously requires complex calculation and expensive spatial costs, which is largely considered impractical to implement in a real device. In this paper, a novel compressed video sensing scheme that is exactly suitable for wireless multimedia sensor networks is proposed by changing the method of processing multiple frames in video cubes. At the encoder, sampling rate redistribution (SRR) algorithm increases the measurements contained in the first and last frames so that they can assist to reconstruct intermediate frames. At the decoder, all measurements are scrambled by global measurement scrambling (GMS) algorithm to make them similar to measurements of the global CS acquisition. The experimental results show that the proposed scheme effectively improves the decoding performance on the premise of realizable hardware devices.
['Yonghong Kuo', 'Yatian Gao', 'Xin Zhang', 'Jian Chen']
A new multiple frames decoding and frame wise measurement for compressed video sensing