华南理工大学学报(自然科学版) ›› 2015, Vol. 43 ›› Issue (5): 1-7.doi: 10.3969/j.issn.1000-565X.2015.05.001

• 电子、通信与自动控制 •    下一篇

DVC 中基于残差子带分组的自适应噪声模型估计

杨春玲 吴娟 郑伯伟   

  1. 华南理工大学 电子与信息学院,广东 广州 510640
  • 收稿日期:2014-12-08 修回日期:2015-02-09 出版日期:2015-05-25 发布日期:2015-05-07
  • 通信作者: 杨春玲(1970-),女,博士,教授,主要从事图像/视频压缩研究. E-mail:eeclyang@scut.edu.cn
  • 作者简介:杨春玲(1970-),女,博士,教授,主要从事图像/视频压缩研究.
  • 基金资助:

    国家自然科学基金资助项目(61471173,60972135)

Adaptive Noise Model Estimation Based on Residual Sub-Band Grouping in DVC

Yang Chun-ling Wu Juan Zheng Bo-wei   

  1. School of Electronic and Information Engineering,South China University of Technology,Guangdong 510640,Guangdong,China
  • Received:2014-12-08 Revised:2015-02-09 Online:2015-05-25 Published:2015-05-07
  • Contact: 杨春玲(1970-),女,博士,教授,主要从事图像/视频压缩研究. E-mail:eeclyang@scut.edu.cn
  • About author:杨春玲(1970-),女,博士,教授,主要从事图像/视频压缩研究.
  • Supported by:
    Supported by the National Natural Science Foundation of China(61471173,60972135)

摘要: 为提高噪声模型的估计精度,改善系统率失真性能,文中提出了一种基于残差子带分组聚类的自适应噪声模型估计方法. 首先根据频率高低对残差子带进行分组,然后由组内子带残差样本生成特征矢量,进而利用改进的模糊 c-均值聚类算法对当前解码子带进行聚类,最后计算出每类残差系数的噪声参数. 实验结果表明,相比于相邻子带聚类-方差估计算法,文中所提算法能够更加准确地匹配残差分布特征,率失真性能平均提升0.60dB,且解码时间平均节省 40.59%.

关键词: 分布式视频压缩, 残差子带聚类, 相关性, 噪声模型估计

Abstract: In order to improve the estimation accuracy of noise model and the rate-distortion performance of the sys-tem,an adaptive noise model estimation method on the basis of residual sub-band grouping is proposed. In this method,firstly,residual sub-bands are grouped according to their frequencies. Secondly,feature vectors are generated from the residual coefficients of all sub-bands in the same group. Then,the coefficients in each sub-band are clustered into different classes by means of improved fuzzy c-means clustering. Finally,the noise para-meters of each class of residual coefficients are estimated successfully. Experimental results show that,in compari-son with the method on the basis of adjacent sub-band clustering and variance estimation,the proposed method matches the residual distribution characteristics more accurately,improves the average rate-distortion performance by 0. 60dB,and saves the decoding time by 40. 59%.

Key words: distributed video compression, residual sub-band clustering, correlation, noise model estimation

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