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Video coding algorithm based on recovery techniques using mean field annealing

机译:基于恢复技术的平均场退火视频编码算法

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Abstract: Most of the existing video coding algorithms produce highly visible artifacts in the reconstructed images as the bit-rate is lowered. These artifacts are due to the information loss caused by the quantization process. Since these algorithms treat decoding as simply the inverse process of encoding, these artifacts are inevitable. In this paper, we propose an encoder/decoder paradigm in which both the encoder and decoder solve an estimation problem based on the available bitstream and prior knowledge about the source image and video. The proposed technique makes use of a priori information about the original image through a nonstationary Gauss-Markov model. Utilizing this mode, a maximum a posteriori (MAP) estimate is obtained iteratively using mean field annealing. The fidelity to the data is preserved by projecting the image onto a constraint set defined by the quantizer at each iteration. The performance of the proposed algorithm is demonstrated on an H.261-type video codec. It is shown to be effective in improving the reconstructed image quality considerably while reducing the bit-rate.!13
机译:摘要:随着比特率的降低,大多数现有的视频编码算法都会在重建的图像中产生高度可见的伪像。这些伪像归因于量化过程导致的信息丢失。由于这些算法将解码视为简单的编码逆过程,因此这些伪像是不可避免的。在本文中,我们提出了一种编码器/解码器范例,其中编码器和解码器都基于可用的比特流和有关源图像和视频的先验知识来解决估计问题。所提出的技术通过非平稳高斯-马尔可夫模型利用有关原始图像的先验信息。利用此模式,使用平均场退火迭代地获得最大后验(MAP)估计。通过在每次迭代中将图像投影到量化器定义的约束集上,可以保持数据的保真度。在H.261型视频编解码器上演示了该算法的性能。可以有效地显着提高重构图像的质量,同时降低比特率。13

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