What Affects Decoding Complexity of Distributed Video Codec Based on Turbo Code

Sheng Fang, Yongquan Liang, Shenyuan Li
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引用次数: 3

Abstract

The distributed video coding (DVC) is a new coming video compression technology that utilizes a different computing complexity mode from the traditional video codec. As a new paradigm there are some fundamental and hard questions in DVC that are not sufficiently addressed, for example the complexity balance between DVC encoder and decoder. This will be an important factor for some promising real time applications. In this context, this paper studies the factors which affect the decoding complexities of turbo code based DVC, especially focuses on quantization, side information and turbo code bit rates. Analyzing and simulation results show that precise side information will decrease the turbo decoding complexity, large reductions in computations can be traded against relatively small increases in bit rate, and uniform quantizer possesses the advantage than the non-uniform quantizer in computation load at a expense of a little decrease in rate distortion performance.
影响基于Turbo码的分布式视频编解码器解码复杂度的因素
分布式视频编码(DVC)是一种新兴的视频压缩技术,它采用了一种不同于传统视频编解码器的计算复杂度模式。DVC作为一种新的编码范式,存在着一些基础性和难点性的问题,如编码器和解码器之间的复杂性平衡问题,目前还没有得到充分的解决。对于一些有前途的实时应用程序来说,这将是一个重要的因素。在此背景下,本文研究了影响基于DVC的turbo码译码复杂度的因素,重点研究了量化、侧信息和turbo码比特率。分析和仿真结果表明,精确的侧信息可以降低turbo解码的复杂度,大大减少计算量可以换来相对较小的比特率增加,均匀量化器比非均匀量化器在计算量方面具有优势,但速率失真性能略有下降。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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