Abstract:

To improve the quality of video frame image-reconstruction in the distributed compressive video sensing(DCVS) system, the continuous real-time video transmission is used as scenarios, an decoding algorithm based on the double sparse dictionary is proposed. Side information(SI) is generated by the adjacent key-frame. Separate sub-bands with different scales of the sample images under wavelet domain, then use the K-SVD algorithm to get different redundant dictionaries with multi-scale properties. Finally, these dictionaries and gradient pursuit for sparse reconstruction(GPSR) algorithm are combined to reconstruct the non-key frames. Simulation results show that at the same compression ratio, the peak signal to noise ratio (PSNR) of the proposed method can obtain more than 0.5~1.5 dB gain than traditional methods.