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Subband-coded image reconstruction for lossy packet networks

机译:有损分组网络的子带编码图像重建

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Transmission of digital subband-coded images over lossy packet networks presents a reconstruction problem at the decoder. This paper presents two techniques for reconstruction of lost subband coefficients, one for low-frequency coefficients and one for high-frequency coefficients. The low-frequency reconstruction algorithm is based on inherent properties of the hierarchical subband decomposition. To maintain smoothness and exploit the high intraband correlation, a cubic interpolative surface is fit to known coefficients to interpolate lost coefficients. Accurate edge placement, crucial for visual quality, is achieved by adapting the interpolation grid in both the horizontal and vertical directions as determined by the edges present. An edge model is used to characterize the adaptation, and a quantitative analysis of this model demonstrates that edges can be identified by simply examining the high-frequency bands, without requiring any additional processing of the low-frequency band. High-frequency reconstruction is performed using linear interpolation, which provides good visual performance as well as maintains properties required for edge placement in the low-frequency reconstruction algorithm. The complete algorithm performs well on loss of single coefficients, vectors, and small blocks, and is therefore applicable to a variety of source coding techniques.
机译:通过有损分组网络的数字子带编码图像的传输在解码器处提出了重构问题。本文提出了两种重建丢失的子带系数的技术,一种用于低频系数,一种用于高频系数。低频重建算法基于分层子带分解的固有属性。为了保持平滑度并利用高带内相关性,三次插值曲面适合已知系数以插值丢失的系数。精确的边缘放置对于视觉质量至关重要,这是通过在水平方向和垂直方向上调整插值网格来实现的,该插值网格由存在的边缘确定,可以实现水平显示。使用边缘模型来表征适应性,对该模型的定量分析表明,可以通过简单地检查高频频带来识别边缘,而无需对低频频带进行任何其他处理。高频重构是使用线性插值执行的,它提供了良好的视觉效果,并保持了低频重构算法中边缘放置所需的属性。完整的算法在单个系数,向量和小块丢失方面表现良好,因此可应用于多种源编码技术。

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