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Bit Allocation Algorithm With Novel View Synthesis Distortion Model for Multiview Video Plus Depth Coding

机译:新型视点合成失真模型的多视点视频加深度编码比特分配算法

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An efficient bit allocation algorithm based on a novel view synthesis distortion model is proposed for the rate-distortion optimized coding of multiview video plus depth sequences in this paper. We decompose an input frame into nonedge blocks and edge blocks. For each nonedge block, we linearly approximate its texture and disparity values, and derive a view synthesis distortion model, which quantifies the impacts of the texture and depth distortions on the qualities of synthesized virtual views. On the other hand, for each edge block, we use its texture and disparity gradients for the distortion model. In addition, we formulate a bit-rate allocation problem in terms of the quantization parameters for texture and depth data. By solving the problem, we can optimally divide a limited bit budget between the texture and depth data, in order to maximize the qualities of synthesized virtual views, as well as those of encoded real views. Experimental results demonstrate that the proposed algorithm yields the average PSNR gains of 1.98 and 2.04 dB in two-view and three-view scenarios, respectively, as compared with a benchmark conventional algorithm.
机译:针对多视点视频加深度序列的码率失真优化编码,提出了一种基于新型视点合成失真模型的高效比特分配算法。我们将输入帧分解为非边缘块和边缘块。对于每个非边缘块,我们线性地近似其纹理和视差值,并得出视图合成失真模型,该模型量化了纹理和深度失真对合成虚拟视图质量的影响。另一方面,对于每个边缘块,我们将其纹理和视差梯度用于失真模型。此外,我们根据纹理和深度数据的量化参数来制定比特率分配问题。通过解决该问题,我们可以在纹理数据和深度数据之间最佳地分配有限的比特预算,以使合成的虚拟视图以及编码的真实视图的质量最大化。实验结果表明,与基准常规算法相比,该算法在两视图和三视图方案中分别产生1.98和2.04 dB的平均PSNR增益。

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