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Sequential error concealment via canonical correlation analysis

机译:通过规范相关分析隐藏顺序错误

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In this paper, we propose a new error concealment algorithm for video/image based on canonical correlation analysis (CCA). Motivated by the Intra prediction in H.264/AVC, it is reasonable to assume that there is a strong spatial correlation relationship between the lost regions and their known adjacent regions. Based on the above idea, we use CCA to estimate a correlation projection matrix which utilizes the loss of macro block adjacent spatial information, then we use the projection matrix and the adjacent region to estimate missing pixel area. In addition, in order to use the spatial information efficiently, we apply the neighbor-embedding-type weight into the aforementioned CCA model. Experimental results demonstrate that the proposed method improves the subjective and objective image quality to a large extent in comparison with other existing methods.
机译:在本文中,我们提出了一种基于规范相关分析(CCA)的视频/图像错误隐藏算法。根据H.264 / AVC中的帧内预测,​​可以合理地假设丢失的区域与其已知的相邻区域之间存在很强的空间相关关系。基于上述思想,我们利用CCA来估计相关投影矩阵,该矩阵利用宏块相邻空间信息的损失,然后利用投影矩阵和相邻区域来估计丢失的像素区域。另外,为了有效地利用空间信息,我们将邻居嵌入类型权重应用于上述CCA模型。实验结果表明,与其他现有方法相比,该方法在很大程度上改善了主观和客观图像质量。

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