Complexity reduction using power-law based scheduling for exploiting spatial correlation in distributed video coding
In pixel-domain distributed video coding (DVC), due to the largely translational nature of motion, residue errors in the side-information frame are often clustered together. These clusterings can be exploited to reduce the number of syndrome bits required to successfully perform low density parity check (LDPC) decoding, and therefore improve the overall rate-distortion performance. We shall see that using alternate iterations of LDPC syndrome decoding and Baum-Welch channel estimation proves to be an efficient scheme for exploiting the spatial clustering of errors in pixel-domain DVC. In this paper we demonstrate that a sparser power-law based scheduling of the channel estimation iteration leads to significant reduction in estimation complexity (around 83% reduction) for a small loss in rate-distortion performance (less than 0.75 dB). This sparser scheduling of channel estimation iterations can potentially improve decoding delays.