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

机译:通过将其与内容自适应深度图压缩相结合来提高AVC / H.264的视觉质量

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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.
机译:3DTV视频编码的未来在于深度图和相应纹理的组合。但是,大多数当前的视频编码标准仅针对视觉质量进行了优化,无法有效地压缩深度图。我们在这项工作中展示了针对3D视频的三叉树和熵编码的内容自适应深度图网格划分。我们表明,这种方法的性能优于AVC / H.264的帧内预测,​​用于静态图像的深度图编码。通过将AVC / H.264与我们的算法结合,我们还证明了我们能够将编码纹理的视觉质量平均提高6 dB。目前,这项工作仅限于静止图像,但是对3D视频的帧内编码的扩展很简单。

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