Segmentation based coding of motion compensated prediction error images

  • Authors:

  • Wei Li;François-Xavier Mateo

  • Affiliations:

  • Signal Processing Laboratory, Swiss Federal Institute of Technology, Lausanne, Switzerland;Signal Processing Laboratory, Swiss Federal Institute of Technology, Lausanne, Switzerland

  • Venue:
  • ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
  • Year:
  • 1993

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper describes a novel segmentation-based method for coding the motion compensated prediction error images (PEI). The PEIs result from various motion compensation techniques, e.g., block matching and pel-recursive techniques. A detailed study is carried out on the statistics of this kind of images. The study shows that the correlation in the PEIs is very low compared to typical natural images. Therefore, the conventional transform coding or subband coding is not appropriate for the PEIs. The proposed method segments a PEI using dynamic thresholding and morphological operations. Various morphological op erators are applied resulting in a final clean image and a relatively small number of segments. The contour and the interior region are coded separately using entropy coding techniques. Comparisons with DCT show that the proposed algorithm outperforms the DCT based algorithm in terms of both PSNR and subjective visual quality.