Efficient compression of multi-view images and videos is an open and interesting research issue that has been attracting the attention of both academic and industrial world during the last years. The considerable amount of information produced by multi-camera acquisition systems requires effective coding algorithms in order to reduce the transmitted data while granting good visual quality in the reconstructed sequence. The classical approach of multi-view coding is based on an extension of the H.264/AVC standard, still based on motion prediction techniques. In this paper we present a novel approach that tries to fully exploit the redundancy between different views of the same scene considering both texture and geometry information. The proposed scheme replaces the motion prediction stage with a 3D warping procedure based on depth information. After the warping step, a joint 3D-DCT encoding of all the warped views is provided, taking advantage of the strong correlation among them. Finally, the transformed coefficients are conveniently quantized and entropy coded. Occluded regions are also taken into account with ad-hoc interpolation and coding strategies. Experimental results performed with a preliminary version of the proposed approach show that at low bitrates it outperforms the H.264 MVC coding scheme on both real and synthetic datasets. Performance at high bitrates are also satisfactory provided that accurate depth information is available.
|Journal||Journal of Visual Communication and Image Representation|
|Publication status||Published - 2010|