• DocumentCode
    247686
  • Title

    Luminance coding in graph-based representation of multiview images

  • Author

    Maugey, Thomas ; Yung-Hsuan Chao ; Gadde, Akshay ; Ortega, Antonio ; Frossard, Pascal

  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    130
  • Lastpage
    134
  • Abstract
    Multi-view video transmission poses great challenges because of its data size and dimension. Therefore, how to design efficient 3D scene representations and coding (of luminance and geometry) has become a critical research topic. Recently, the graph-based representation (GBR) is introduced, which provides a lossless compression of multi-view geometry by connecting informative pixels among views. This representation has been shown as a promising alternative to the classical depth-based representation, where the view synthesis accuracy is hard to control. In this work, we study the luminance compression under GBR, which is not well considered in existing literature. With a proper structural reformulation, we show that the graph-based transform can be applied on the GBR paradigm, hence better extracting the correlation among pixels along graph connections. Moreover, we extend the popular SPIHT coding scheme to further improve coding efficiency. The experimental results show that our method leads to better RD coding performance as compared the classical luminance coding algorithms.
  • Keywords
    brightness; computational geometry; data compression; feature extraction; graph theory; image representation; transforms; video coding; 3D scene coding; 3D scene representations; GBR paradigm; RD coding; SPIHT coding scheme; coding efficiency improvement; data dimension; data size; graph connections; graph-based multiview image representation; graph-based transform; informative pixels; lossless compression; luminance coding; luminance compression; multiview geometry; multiview video transmission; Bipartite graph; Encoding; Geometry; Image coding; Image color analysis; Three-dimensional displays; Transforms; 3D representation; Multiview image coding; graph-based representation; graph-based transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025025
  • Filename
    7025025