• DocumentCode
    1856006
  • Title

    A fast layer-based multiview image coding algorithm

  • Author

    Gelman, Andriy ; Oñativia, Jon ; Dragotti, Pier Luigi

  • Author_Institution
    Commun. & Signal Process. Group, Imperial Coll., London, UK
  • fYear
    2012
  • fDate
    27-31 Aug. 2012
  • Firstpage
    1224
  • Lastpage
    1228
  • Abstract
    In [1,2] we presented a multiview image coding scheme. The approach is based on extracting depth layers from multiview images. Each layer is related to an object in the scene and is highly redundant. We exploit this redundancy by using a properly disparity compensated Wavelet Transform, followed by quantisation and entropy coding of the transform coefficients. In addition, to reconstruct the data we encode a 2D contour associated with each layer. In this paper we describe extensions to this coding scheme aimed at reducing the complexity of the algorithm, while retaining its rate-distortion (RD) performance. In particular, we propose a novel low-complexity scheme to encode the layer contours. Simulation results show that the approach remains competitive with the original method. In addition we show that the reduced complexity algorithm still outperforms H.264/AVC.
  • Keywords
    computational complexity; entropy codes; image coding; quantisation (signal); wavelet transforms; 2D contour; depth layers; entropy coding; fast layer-based multiview image coding; layer contours; low-complexity scheme; multiview images; quantisation; rate-distortion performance; transform coefficients; wavelet transform; Approximation methods; Cameras; Complexity theory; Encoding; Image coding; Image segmentation; Transforms; Multiview image coding; contour encoding; image-based rendering; wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European
  • Conference_Location
    Bucharest
  • ISSN
    2219-5491
  • Print_ISBN
    978-1-4673-1068-0
  • Type

    conf

  • Filename
    6334235