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Object-Based Subband/Wavelet Video Compression

  • Soo-Chul Han
  • John W. Woods
Chapter
  • 344 Downloads
Part of the The International Series in Engineering and Computer Science book series (SECS, volume 450)

Abstract

This chapter presents a subband/wavelet video coder using an object-based spatiotemporal segmentation. The moving objects in a video are extracted by means of a joint motion estimation and segmentation algorithm based on a compound Markov random field (MRF) model. The two important features of our technique are the temporal linking of the objects, and the guidance of the motion segmentation with spatial color information. This results in spatiotemporal (3-D) objects that are stable in time, and leads to a new motion-compensated temporal updating and contour coding scheme that greatly reduces the bit-rate to transmit the object boundaries. The object interiors can be encoded by either 2-D or 3-D subband/wavelet coding. Simulations at very low bit-rates yield comparable performance in terms of reconstructed PSNR to the H.263 coder. The object-based coder produces visually more pleasing video with less blurriness and is devoid of block artifacts.

Keywords

Motion Vector Motion Estimation Object Boundary Markov Random Field Video Compression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Soo-Chul Han
  • John W. Woods

There are no affiliations available

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