Local Intensity Compensation using sparse representation with additional sparse dictionary

Abstract

The novel motion compensation called LIC (Local Intensity Compensation) predicts a current block using a linear combination of reference blocks. The weight coefficients of the LIC should be sparse in order to predict and to encode frames effectively. Sparse representation aims at obtaining the least possible number of non-zero coefficients and is a powerful solution for the LIC. Our previous work has proposed the LIC using sparse representation and has achieved high prediction accuracy. Video coding standards encode motion vectors and prediction errors of the macro blocks independently. The prediction errors are converted via DCT (Discrete Cosine Transform), and the quantized DCT coefficients are encoded. This means that the video coding standards predicts the current block using two steps, namely motion compensation and the DCT. Sparse representation is applied to optional basis vectors as reference blocks; thus, this study proposes a framework to conduct motion compensation and the DCT simultaneously by adding the DCT basis vectors into the sparse dictionary. Additionally, this study employs macro blocks generated using intra prediction because the intra prediction is also applied to the current block by neighbouring macro blocks. Experimental results demonstrate that the proposed method integrating the two steps shows high prediction accuracy.