• DocumentCode
    1960428
  • Title

    Embedded denoising for the H.264/AVC extension-spatial SVC

  • Author

    Luo, Enming ; Au, Oscar C L ; Guo, Liwei ; Wu, Yannan ; Tu, Shing Fat

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Hong Kong Univ. of Sci. & Technol., Hong Kong, China
  • fYear
    2009
  • fDate
    23-26 Aug. 2009
  • Firstpage
    280
  • Lastpage
    283
  • Abstract
    Recently, many schemes that embed the denoising process into the video encoding have been proposed. They are mainly implemented into the single-layer encoder, like the H.264 reference encoder joint model (JM). In this paper, we propose to embed the denoising process into the multi-layer spatial SVC encoder. Since either for the base layer or the enhancement layer our proposed filter could achieve linear minimum mean square error (LMMSE) and meanwhile the additional inter-layer prediction tools could be utilized, the encoder performance can be largely improved. The experimental results show that the multi-layer embedded approach can remove most of the noise while achieving spatial scalability. And the R-D curve shows the optional use of inter-layer prediction tools can help yield better denoising performance and coding efficiency.
  • Keywords
    least mean squares methods; signal denoising; video coding; H.264 reference encoder; H.264/AVC extension; embedded denoising; linear minimum mean square error; scalable video coding; single layer encoder; spatial SVC; video encoding; Automatic voltage control; Brain modeling; Discrete cosine transforms; Encoding; Gold; Noise reduction; Nonlinear filters; Predictive models; Static VAr compensators; Tin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Computers and Signal Processing, 2009. PacRim 2009. IEEE Pacific Rim Conference on
  • Conference_Location
    Victoria, BC
  • Print_ISBN
    978-1-4244-4560-8
  • Electronic_ISBN
    978-1-4244-4561-5
  • Type

    conf

  • DOI
    10.1109/PACRIM.2009.5291358
  • Filename
    5291358