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A novel multi-view image coding scheme based on view-warping and 3D-DCT

机译:一种基于视角变形和3D-DCT的新颖的多视角图像编码方案

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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.
机译:多视图图像和视频的有效压缩是一个开放而有趣的研究问题,最近几年一直吸引着学术界和工业界的关注。多摄像机采集系统产生的大量信息需要有效的编码算法,以减少传输的数据,同时在重构序列中获得良好的视觉质量。多视图编码的经典方法基于H.264 / AVC标准的扩展,但仍基于运动预测技术。在本文中,我们提出了一种新颖的方法,该方法试图同时考虑纹理和几何信息来充分利用同一场景的不同视图之间的冗余。所提出的方案使用基于深度信息的3D变形过程代替了运动预测阶段。在变形步骤之后,利用所有变形视图之间的强相关性,提供了所有变形视图的联合3D-DCT编码。最后,方便地对变换后的系数进行量化和熵编码。临时插值和编码策略也考虑了遮挡区域。使用该方法的初步版本执行的实验结果表明,在低比特率下,它在真实和合成数据集上均优于H.264 MVC编码方案。只要可获得准确的深度信息,高比特率的性能也是令人满意的。

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