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An Iterative Fusion Technique for Dynamic Side Information Refinement in Pixel Domain Distributed Video Coding

机译:像素域分布式视频编码中动态辅助信息细化的迭代融合技术

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摘要

Distributed video coding (DVC) technology has been considered to be capable of reducing the processing complexity of the encoder immensely, while majority of the computational overheads are taken over by the decoder. In the common DVC framework, the pictures are decoded using the Wyner-Ziv encoded bit stream received from the encoder and the side information estimated using previously decoded information. As a result, accuracy of the side information estimation is very critical in improving the coding efficiency. In this paper we propose a novel side information refinement technique for DVC using multiple side information streams and sequential motion compensation with luminance and chrominance information involving iterative fusion of parallel information streams. In the bit plane wise coding architecture, previously decoded higher order bit planes are incrementally used to perform the motion estimation jointly in luminance and chrominance spaces to estimate multiple redundant bit streams for iterative fusion to produce more improved side information for subsequent bit planes. Simulation results show significant objective quality gain can be achieved at the same bit rate by utilizing the proposed refinement algorithms.
机译:分布式视频编码(DVC)技术被认为能够极大地降低编码器的处理复杂性,而大部分计算开销则由解码器接管。在公共DVC框架中,使用从编码器接收的Wyner-Ziv编码位流对图片进行解码,并使用先前解码的信息估算辅助信息。结果,辅助信息估计的准确性对于提高编码效率非常关键。在本文中,我们提出了一种新颖的DVC辅助信息细化技术,该技术使用多个辅助信息流和具有亮度和色度信息的顺序运动补偿,涉及并行信息流的迭代融合。在按位平面编码结构中,先前解码的较高阶位平面被增量地用于在亮度和色度空间中共同执行运动估计,以估计多个冗余位流以进行迭代融合,从而为后续位平面产生更多改进的辅助信息。仿真结果表明,利用所提出的优化算法,可以在相同的比特率下获得显着的客观质量增益。

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