期刊文献+

噪声信道下保护图像感兴趣区的多描述编码 被引量:1

Multiple description coding for protecting regions of interest in images over noisy channels
在线阅读 下载PDF
导出
摘要 将感兴趣区编码和多描述编码相结合,提出一种噪声信道下保护图像感兴趣区的多描述编码方法。该方法将图像分为感兴趣区和背景区,并采用多描述编码方法,将感兴趣区和背景区码流编码成多个描述。同时对感兴趣区和背景区描述码流采用不同的冗余树分配方案,以进一步增强图像感兴趣区的抗分组丢失能力。实验证明,该方法即使在信道拥塞较为严重的情况下,也能为图像的感兴趣区提供令人满意的重建质量。 This paper proposed a new multiple description coding for protecting regions of interest in images over noisy channels by combining the advantages of multiple description coding and regions of interest coding.The SPIHT algorithm was used to generate multiple description streams,and divided these description streams into regions of interest streams and background streams.For the protection of the regions of interest,the method assigned different redundant trees to the two kinds streams,the full coding trees were assigned as the redundant tress of the regions of interest streams,the partial coding trees were assigned as the redundant tress of the background streams.Experiment results show that the method can further increase the reconstructed quality of the ROI over noisy channels compared with other ROI multiple description coding methods.
出处 《计算机应用研究》 CSCD 北大核心 2010年第11期4345-4347,共3页 Application Research of Computers
基金 国家自然科学基金资助项目(60572011)
关键词 噪声信道 感兴趣区 多描述编码 noisy channels regions of interest multiple description coding
  • 相关文献

参考文献12

二级参考文献159

  • 1陈婧,蔡灿辉,丁润涛.X树非平衡保护多描述编码[J].电子与信息学报,2005,27(12):1973-1977. 被引量:5
  • 2Mohr A. E. , Riskin E. A. , Ladner R.. Generalized multiple description coding through unequal forward error protection.In.. Proceedings of ICIP, Kobe, Japan, 1999, 1:411-415.
  • 3Goyal V. K. , Kovacevic J. , Arean R. , Vetterli M.. Multiple description transform coding of images. In: Proceedings of ICIP, Chicago, USA, 1998, 1:674-678.
  • 4Jiang W, , Ortega A.. Multiple description coding via polyphase transform and selective quantization. In: Proceedings of SPIE: Visual Communications and Image Processing, Denver,Colorado, USA, 1999, 3653(2): 998-1008.
  • 5Rauschenbach U.. The rectangular fish eye view as an efficient method for the transmission and display of large images. In:Proceedings of ICIP, Kobe, Japan, 1999, 3:115-119.
  • 6Chai D, , Ngan K, N, , Bouzerdoum A.. Foreground/Background bit allocation for Region Of Interest coding. In: Proceedings of ICIP, Vancouver, Canada, 2000, 2:923-926.
  • 7Hannuksela M. M. , Wang Ye-Kui, Gabbouj M.. Sub-picture:ROI coding and unequal error protection. In: Proceedings of ICIP, Vancouver, Canada, 2002, 2:537-540.
  • 8Christopoulos C. , Askelof J. , Larsson M,. Efficient methods for encoding regions of interest in the upcoming JPEG2000 still image coding standard. IEEE Signal Rocessing Letters, 2000,7(9): 247-249.
  • 9Said A. , Pearlman W. A.. A new, fast, and efficient image code based on set partitioning in hierarchical trees. IEEE Transactions on Circuits Systems, Video Technology, 1996, 6(3): 243-250.
  • 10Shapiro J. M.. Embedded image coding using zerotrees of wavelet coefficients. IEEE Transactions on Signal Processing,1993, 41(12): 3445-3462.

共引文献28

同被引文献11

  • 1C-oyal V K. Multiple description coding: compression meets the network[J]. IEEE Signal Processing Magazine, 2001, 18(5): 74-94.
  • 2Wang I.iangjun, Wu Transaction on Image Fomasier M, Rauhut New York: Springer, Xiaolin, Shi Guangming. Binned progressive quantization for compressive sensing[J], IEEE Processing, 2012, 21(6): 2 980-2 990.
  • 3H. Compressive Sensing[M]//Scherzer O. Handbook of Mathematical Methods in Imaging. 2011: 187-228.
  • 4Gandes E, Romberg J, Tao Terence. Robust uncertainty principles: Exact signal reconstruction from highly in- complete frequency information[Jl. IEEE Transaction on Information Theory, 2006, 52(2): 489-509.
  • 5Do T T, Gan L, Nguyen N H, et al. Fast and efficient compressive sensing using structurally random matrices[J].IEEE Transactions on Signal Processing, 2012, 60(1): 139-154.
  • 6Mcllhagga W. The canny edge detector revisited[J]. International Joumal of Computer Vision, 2011, 91(3):251- 261.
  • 7Portilla J, Strela V, Wainwright M J, et al. Image denoising using scale mixtures of gaussians in the wavelet domain[J]. IEEE Transaction on Image Process, 2003, 12(11): 1 338-1 351.
  • 8刘丹华,石光明,周佳社,高大化,吴家骥.基于Compressed Sensing框架的图像多描述编码方法[J].红外与毫米波学报,2009,28(4):298-302. 被引量:21
  • 9赵春晖,刘巍.基于交织抽取与分块压缩感知策略的图像多描述编码方法[J].电子与信息学报,2011,33(2):461-465. 被引量:7
  • 10王相海,方锦,宋传鸣.基于DCT分层结构的遥感图像分级多描述编码算法[J].遥感学报,2011,15(5):989-1007. 被引量:3

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部