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Sparse Recovery-Based Error Concealment

机译:基于稀疏恢复的错误隐藏

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摘要

Image and video transmission over heterogeneous networks may encounter packet loss due to the channel impairments, leading to quality degradation of the received image. In this paper, a novel robust image transmission system is proposed by casting the error concealment challenge into a sparse recovery framework. To this purpose, a robust encoder is carefully designed in order to mitigate the negative effects of the packet loss. After wavelet decomposition, a quadtree structure of the wavelet coefficients is used to rearrange them into independent partitions. Random linear combinations of coefficients for each partition are then adopted to provide a high error recovery capability. This linear process coupled with a simple packetization process introduces more robustness and error resilience into the transmission system. At the receiver side, the tree-sparse structure of the wavelet coefficients is explicitly exploited in order to model the error recovery problem as a sparse recovery framework. This is achieved by adaptation of a well-known iterative sparse reconstruction algorithm to the defined tree structure built in the wavelet domain. Compared with the state-of-the-art error concealment algorithms, experimental results show that the proposed method has better reconstruction performance in terms of objective and subjective evaluations over a range of packet loss rates, and ensure that a high-quality image can be recovered for the high packet loss scenarios.
机译:异构网络上的图像和视频传输可能会由于通道受损而导致数据包丢失,从而导致接收到的图像质量下降。在本文中,通过将错误隐藏挑战转换为稀疏恢复框架,提出了一种新颖的鲁棒图像传输系统。为此目的,精心设计了鲁棒的编码器,以减轻分组丢失的负面影响。小波分解后,小波系数的四叉树结构用于将它们重新排列为独立的分区。然后采用每个分区的系数的随机线性组合,以提供较高的错误恢复能力。这种线性过程与简单的打包过程相结合,将更强的鲁棒性和错误恢复能力引入了传输系统。在接收机端,显式地利用小波系数的树稀疏结构,以便将错误恢复问题建模为稀疏恢复框架。这是通过将众所周知的迭代稀疏重建算法适配到在小波域中构建的已定义树结构来实现的。与最新的错误隐藏算法相比,实验结果表明,该方法在丢包率范围内的客观评估和主观评估方面具有更好的重建性能,并确保可以得到高质量的图像。针对高丢包率情况进行了恢复。

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