A Residual Coefficients Pruning Algorithm in H.264

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A Residual Coefficients Pruning Algorithm in H.264

更新时间：2025-07-09

- A Residual Coefficients Pruning Algorithm in H.264
- Vol. 44, Issue 10, Pages: 52-56(2010)
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN919.8
- Online First：10 October 2010，
  
  Published：2010
- 稿件说明：
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A Residual Coefficients Pruning Algorithm in H.264[J]. 2010, 44(10): 52-56.
DOI：

A Residual Coefficients Pruning Algorithm in H.264[J]. 2010, 44(10): 52-56. DOI：

摘要

针对H.264残差系数编码中位置信息占用码率较多这一问题

提出了一种H.264残差系数修剪算法.该算法首先对视频序列进行预测、变换、量化以及扫描

然后对扫描后获得的残差系数进行线性分组

并采用率失真优化准则对残差系数分组进行修减

再在给定量化步长范围内计算每一个宏块在不同量化步长下的修剪结果

最后将率失真代价最小时对应的修剪剩余残差系数编码输出.实验结果表明

与H.264残差系数编码算法相比

该算法在相同码率下的峰值信噪比最多可以提高0.9 dB

在相同信噪比下最多可以节省17%的码率.该算法没有改变H.264的码流结构

与标准兼容.

Abstract

A pruning algorithm is proposed to reduce the encoding bits for the map information of residual coefficients in H.264. Video sequences are predicted

transformed

quantized

and scanned. Then residual coefficients obtained from scanning are divided into linear groups

and then the groups are pruned out using the rate-distortion optimization(RDO)sense. Furthermore

the pruning results of each macroblock with different quantization steplengths are calculated in a given range. Finally the remaining coefficients with the minimal rate-distortion cost are encoded and transformed. Experimental results show that the proposed algorithm has better RD performance than the residual coding method in H.264 at the relatively high bitrates. The proposed algorithm gains an 0.9 dB increase on the peak signal to noise ratio( PSNR)at the same bitrate

or equivalently

a 17% rate saving at the same PSNR. Moreover

the proposed algorithm does not change the bit-stream structure of H.264

and is compatible with the H.264 standard.

关键词

Keywords

references

XIONG Zixiang, RAMCHANDRAN K, ORCHARD M. Space-frequency quantization for wavelet image coding [J]. IEEE Transactions on Image Processing, 1997,6(5):677-693.

GLEICH D, PLANINSIC P, GERGIC B, et al. Progressive space frequency quantization for SAR data compression [J]. IEEE Transactions on Geoscience and Remote Sensing, 2002,40(1):3-10.

VELISAVLJEVIC V, BEFERULL-LOZANO B, VETTERLI M. Space-frequency quantization for image compression with directionlets [J]. IEEE Transactions on Image Processing, 2007,16(7):1761-1773.

SHOA A, SHIRANI S. Optimized atom position and coefficient coding for matching pursuit-based image compression [J]. IEEE Transactions on Image Processing, 2009, 18(12):677-693.

WIEGAND T, SCHWARZ H, JOCH A, et al. Rate-constrained coder control and comparison of video coding standards [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2003, 13(7):688-703.

毕厚杰. 新一代视频压缩编码标准——H.264/AVC [M]. 北京:人民邮电出版社, 2005.

WIEGAND T, SULLIVAN G, BJONTEGAARD G, et al. Overview of the H.264/AVC video coding standard [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2003,13(7):560-576.

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