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Two Adaptive Methods Based on Edge Analysis for Improved Concealing Damaged Coded Images in Critical Error Situations

机译:两种基于边缘分析的自适应方法在关键错误情况下改进隐藏图像的隐藏编码

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The original coded image signal can be affected when it is transmitted over error-prone networks. Error concealment techniques for compressed image or video attempt to exploit correctly received information to recover corrupted regions that are lost. If these regions have edges, most of these conventional approaches cause noticeable visual degradations, because they not consider the edge characteristics of images. The spatial error concealment methods cannot work well; especially over high burst error condition since a great of neighboring information have been corrupted or lost (called 'critical error situations'). This paper proposes two adaptive and effective methods to select the required support area, based on edge analysis using local geometric information, suited base functions and optimal expansion coefficients, in order to conceal the damaged macroblocks in critical error situations. Experimental results show that the proposed two approaches outperform existing methods by up to 7.9 dB on average.
机译:原始编码图像信号在易错网络上传输时可能会受到影响。用于压缩图像或视频的错误隐藏技术试图利用正确接收的信息来恢复丢失的损坏区域。如果这些区域具有边缘,则这些传统方法中的大多数会导致明显的视觉下降,因为它们没有考虑图像的边缘特征。隐藏空间误差的方法效果不佳;特别是在高突发错误情况下,因为大量相邻信息已损坏或丢失(称为“严重错误情况”)。本文基于使用局部几何信息的边缘分析,合适的基本函数和最佳扩展系数,提出了两种自适应有效的方法来选择所需的支撑区域,以便在关键错误情况下隐藏受损的宏块。实验结果表明,所提出的两种方法的平均性能比现有方法高出7.9 dB。

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