A motion compression/reconstruction method based on max t-norm composite fuzzy relational equations

  • Authors:

  • Hajime Nobuhara;Witold Pedrycz;Salvatore Sessa;Kaoru Hirota

  • Affiliations:

  • Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, 4259 Nagatsuta, Midiri-ku, Yokohama 226-8502, Japan;Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada T6R 2G7;DICOMMA, University of Napoli "Federico II", Via Monteoliveto 3, 80134 Napoli, Italy;Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, 4259 Nagatsuta, Midiri-ku, Yokohama 226-8502, Japan

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2006

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Abstract

A motion compression/reconstruction method based on max t-norm composite fuzzy relational equations (MCF) is proposed, where into intra-pictures (I-pictures) and predictive-pictures (P-pictures) of the original motion are compressed by uniform and non-uniform coders, respectively. The non-uniform coders of the proposed method can preserve edge information of P-pictures on the compressed image. To perform an effective compression/reconstruction of the P-pictures, a design method of non-uniform coders is proposed based on an overlap level of fuzzy sets and a fuzzy equalization. An experiment using 10 P-pictures confirms that the root mean square error of the reconstructed images obtained by the proposed non-uniform coders is decreased to 89.4% of that one of the uniform coders under the condition that compression rate (the ratio between the file size of compressed image and original one) is 0.0057. Two test motions ('Tennis' and 'Woman', 100 frames) are compressed and reconstructed by the proposed MCF.