Improving the visual quality of AVC/H.264 by combining it with content adaptive depth map compression

Christian Keimel, K. Diepold, M. Sarkis
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引用次数: 3

Abstract

The future of video coding for 3DTV lies in the combination of depth maps and corresponding textures. Most current video coding standards, however, are only optimized for visual quality and are not able to efficiently compress depth maps. We present in this work a content adaptive depth map meshing with tritree and entropy encoding for 3D videos. We show that this approach outperforms the intra frame prediction of AVC/H.264 for the coding of depth maps of still images. We also demonstrate by combining AVC/H.264 with our algorithm that we are able to increase the visual quality of the encoded texture on average by 6 dB. This work is currently limited to still images but an extension to intra coding of 3D video is straightforward.
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提高AVC/H的视觉质量。264与内容自适应深度图压缩相结合
3DTV视频编码的未来在于深度图和相应纹理的结合。然而,目前大多数视频编码标准仅针对视觉质量进行了优化,而不能有效地压缩深度图。本文提出了一种基于三树和熵编码的3D视频内容自适应深度图网格划分方法。结果表明,该方法优于AVC/H的帧内预测。264用于对静止图像的深度图进行编码。我们还结合AVC/H进行了论证。使用我们的算法,我们能够将编码纹理的视觉质量平均提高6db。这项工作目前仅限于静止图像,但扩展到3D视频的内部编码是直截了当的。
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