Conference paper

Editor list: Grosky, WI; Plasil, F

Publication year: 2002

Pages: 208-217

Journal: Lecture notes in computer science

Volume number: 2540

ISSN: 0302-9743

ISBN: 3-540-00145-X

Conference: 29th Conference on Current Trends in Theory and Practice of Informatics

Publisher: Springer

Title of series: LECTURE NOTES IN COMPUTER SCIENCE

Abstract: 
Image compression and manipulation by weighted finite automata exploit similarities in the images in order to obtain notable compression ratios and manipulation tools. The investigations are often based on two-dimensional images. A natural extension is to consider three- or even n-dimensional images which axe decomposed in two-dimensional slices, e. g. data produced by tomography. By applying the two-dimensional methods to the slices the volume similarities may be disregarded. Building three-dimensional patterns by merging sequenced images of movie scenes may result in increased similarities. Here we consider transformations of the input strings for weighted finite automata in order to obtain dimension transformations which preserve multidimensional similarities. We focus our investigations on the state complexity and show that a noticeable reduction of the number of states can be achieved.

Harvard Citation style: Kutrib, M. and Löwe, J. (2002) String transformation for n-dimensional image compression, Lecture notes in computer science (Schriftenreihe), 2540, pp. 208-217

APA Citation style: Kutrib, M., & Löwe, J. (2002). String transformation for n-dimensional image compression. Lecture notes in computer science (Schriftenreihe). 2540, 208-217.