A novel light field compression framework with hybrid residue transform mechanism.

To meet the challenge of compressing the vast light field data, many prediction‐based algorithms achieve satisfactory results. Although these algorithms remove most redundancy through angular prediction, they rarely develop the suitable de‐correlation solutions for the prediction residue, leading to a large gap for higher compression performance. Therefore, this letter proposes a hybrid residue transform (HRT) mechanism to fully exploit the correlations in prediction residue for a three‐layer hierarchical light field compression. Specifically, the prediction residue is hierarchically generated from the authors' three‐layer structure. Besides, considering the high‐dimensional feature of light field residue, the high‐dimensional transforms, including 3D and 4D discrete cosine transforms, are alternately utilized to make the energy of the residue more compact. Experimental results demonstrate that the proposed method outperforms the state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]