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

Hajime Nobuhara*, Witold Pedrycz, Salvatore Sessa, Kaoru Hirota

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

53 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)2526-2552
Number of pages27
JournalInformation Sciences
Volume176
Issue number17
DOIs
Publication statusPublished - 3 Sept 2006
Externally publishedYes

Keywords

  • Fuzzy equalization
  • Fuzzy relational equations
  • Motion compression

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