Compressive sampling and wavelet-based multi-view image compression scheme

A multi-view image codec using a disparity compensated lifting based wavelet transform and `compressive sampling (CS)` is presented. The input images are de-correlated into their sub-bands, using disparity compensated view filtering lifting based wavelet transforms. A wavelet transform is then applied to the baseband view, de-composing it into its sub-bands. High-frequency sub-bands are separately hard threshold. Wavelet-weights for high-frequency sub-bands are calculated and used to adjust threshold values for different sub-bands. The CS algorithm is then employed to generate measurements for each resulting sub-band. In the decoder side, the Basis Pursuit method is used to recover the high-frequency sub-bands. Results indicate that the proposed codec significantly outperforms the state-of-the-art CS-based multi-view image codecs.