• DocumentCode
    3327617
  • Title

    Parametrizations of planar models for region-merging based lossy depth-map compression

  • Author

    Schiopu, Ionut ; Tabus, Ioan

  • Author_Institution
    Dept. of Signal Process., Tampere Univ. of Technol., Tampere, Finland
  • fYear
    2015
  • fDate
    8-10 July 2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    We present efficient methods for parametrizing planar models, to be used for depth value reconstruction inside selected regions in a depth image. The optimal plane for each region is represented using its quantized heights at three pixel locations. The decoder uses the decoded quantized heights to approximately represent the optimal plane. The three pixel locations are selected so that the distortion due to the approximation of the plane over the region is minimized. The planar reconstructions are used in competition with the piecewise constant reconstruction at the regions obtained through a merging process, where the two regions to be merged are those ensuring the optimal slope in the rate-distortion curve. The lossy depth compression algorithm including the planar modeling obtains a significantly better rate-distortion performance than the algorithm that uses only constant regions, with improvements up to 8 dB.
  • Keywords
    data compression; decoding; image coding; image reconstruction; image representation; piecewise constant techniques; rate distortion theory; decoder; depth image reconstruction; piecewise constant planar reconstruction; planar model parametrization; rate distortion curve; region representation; region-merging based lossy depth map compression; Computational modeling; Decoding; Distortion; Encoding; Image coding; Image reconstruction; Rate-distortion; Planar model; entropy coding; greedy slope optimization; plane parametrization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON), 2015
  • Conference_Location
    Lisbon
  • Type

    conf

  • DOI
    10.1109/3DTV.2015.7169377
  • Filename
    7169377