计算机工程 ›› 2019, Vol. 45 ›› Issue (2): 245-249.doi: 10.19678/j.issn.1000-3428.0050093

• 多媒体技术及应用 • 上一篇    下一篇

基于双稀疏优化的空域错误隐藏

严静文a,b,肖晶a,b,高戈a,b   

  1. 武汉大学 a.国家多媒体软件工程技术研究中心; b.计算机学院,武汉430072
  • 收稿日期:2018-01-15 出版日期:2019-02-15 发布日期:2019-02-15
  • 作者简介:严静文(1990—),女,硕士研究生,主研方向为音频信号处理;肖晶、高戈,副教授。
  • 基金项目:

    国家自然科学基金(61471271)。

Spatial Error Concealment Based on Coupled Sparse Optimization

YAN Jingwena,b,XIAO Jinga,b,GAO Gea,b   

  1. a.National Engineering Research Center for Multimedia Software; b.School of Computer,Wuhan University,Wuhan 430072,China
  • Received:2018-01-15 Online:2019-02-15 Published:2019-02-15

摘要:

现有空域错误隐藏算法通常利用线性插值或者常规稀疏表达恢复丢失像素,但线性插值在恢复不平滑图像时因邻域信息不一致导致恢复图像模糊,而常规稀疏表达因字典构建不当造成丢失像素重建效果较差。为此,提出一种改进的空域错误隐藏算法,采用动态阈值搜索潜在集合和模板集合提高字典构建精度,利用典型相关分析获得双稀疏优化的初值,通过稀疏重建恢复丢失像素。实验结果表明,与现有主流算法相比,该算法的峰值信噪比至少提高1.23 dB,具有较好的错误隐藏效果。

关键词: 空域错误隐藏, 线性插值, I帧丢失, 字典构建, 稀疏优化

Abstract:

Linear interpolation algorithm or conventional sparse representation algorithm are used to recover the lost pixels currently.However,linear interpolation restores image blur due to inconsistent neighborhood information when restoring unsmooth images.For the conventional sparse representation algorithm,improper dictionary construction will result in a poor recovered image quality.To solve these problem,an improved spatial error concealment algorithm is proposed.The proposed algorithm optimizes the process of potential set and template set search by means of dynamic threshold searching,which improves the precision of the constructed dictionary.It can obtain the value of double sparse optimization using Canonical Correlation Analysis(CCA),and recover lost pixels by sparse reconstruction.Experimental results show that the proposed algorithm improves the Peak Signal to Noise Ratio(PSNR) by at least 1.23 dB compared with the current mainstream algorithm,and has a good error hiding effect.

Key words: spatial error concealment, linear interpolation, I-frame loss, dictionary construction, sparse optimization

中图分类号: