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Dynamic algorithm for correlation noise estimation in distributed video coding

机译:分布式视频编码中相关噪声估计动态算法

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Low complexity encoders at the expense of high complexity decoders are advantageous in wireless video sensor networks. Distributed video coding (DVC) achieves the above complexity balance, where the receivers compute Side information (SI) by interpolating the key frames. Side information is modeled as a noisy version of input video frame. In practise, correlation noise estimation at the receiver is a complex problem, and currently the noise is estimated based on a residual variance between Pixels of the key frames. Then the estimated (fixed) variance is used to calculate the bit-metric values. In this paper, we have introduced the new variance estimation technique that rely on the bit pattern of each pixel, and it is dynamically calculated over the entire motion environment which helps to calculate the soft-value information required by the decoder. Our result shows that the proposed bit based dynamic variance estimation significantly improves the peak signal to noise ratio (PSNR.)performance.
机译:在无线视频传感器网络中,低复杂性解码器的低复杂性编码器是有利的。分布式视频编码(DVC)通过内插关键帧来实现上述复杂性平衡,其中接收器计算侧信息(SI)。侧面信息被建模为输入视频帧的嘈杂版本。实际上,接收器处的相关噪声估计是复杂的问题,并且当前基于关键帧的像素之间的剩余方差来估计噪声。然后,估计(固定)方差用于计算比特度量值。在本文中,我们介绍了依赖于每个像素的位模式的新方差估计技术,并且在整个运动环境中动态地计算,有助于计算解码器所需的软值信息。我们的结果表明,所提出的基于比特的动态方差估计显着提高了峰值信噪比(PSNR。)性能。

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