A motion compression method by fuzzy relational equations

Author

Nobuhara, Hajime ; Hirota, Kaoru

Author_Institution

Dept. of Comput. Intelligence & Syst. Sci., Tokyo Inst. of Technol., Japan

Volume

3

fYear

2003

fDate

16-20 July 2003

Firstpage

1463

Abstract

A motion compression method by max t-norm composite fuzzy relational equations (MCF) is proposed. In the case of MCF, a motion sequence is divided into intra-pictures (I-pictures) and predictive-pictures (P-pictures). The I-pictures and the P-pictures are compressed by using uniform coders and non-uniform coders, respectively. In order to perform an effective compression and reconstruction of the P-pictures, a design method of non-uniform coders is proposed. The proposed design method is based on an overlap level of fuzzy sets and a fuzzy equalization. Through a experiment using 10 P-pictures, it is confirmed that the root means square errors of the proposed method is decreased to 89.4% of the uniform coders, under the condition that the compression rate is 0.0057. A result of motion compression and reconstruction of motion (standard motion imagery) by MCF is also presented.

Keywords

fuzzy set theory; image coding; image reconstruction; image sequences; fuzzy equalization; fuzzy relation equation; fuzzy sets; intra-pictures; max t-norm composite fuzzy; motion compression method; motion reconstruction; nonuniform coders; overlap level; predictive-pictures; root means square errors; standard motion imagery; uniform coders; Calculus; Computational intelligence; Design methodology; Equations; Fuzzy sets; Image coding; Image decomposition; Image reconstruction; Root mean square; Watermarking;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence in Robotics and Automation, 2003. Proceedings. 2003 IEEE International Symposium on

Print_ISBN

0-7803-7866-0

Type

conf

DOI

10.1109/CIRA.2003.1222213

Filename

1222213