An improved video coding scheme for depth map sequences based on compressed sensing

Compressed Sensing (CS) is an emerging theory in signal processing. The CS framework suggests that the signal can be reconstructed from the sub-samples by some recovery algorithm when the signal is sparse. We propose an improved video coding scheme to compress the depth map by Total Variation (TV) minimization in the pixel domain from the quantized/dequantized transform coefficients due to the extremely sparse gradient of depth maps. We keep all the frequency coefficients to avoid introducing noise to the reconstruction results. The TV minimization solver is integrated into the standard encoder, and the proposed coding scheme chooses the optimal recovery method by using the Rate-distortion Optimization (RDO) method. The experimental results show that our proposed scheme is highly efficient for the depth map sequences.