Title :
Fractal Image Decoding Based on Extended Fixed-Point Theorem
Author :
He, Yan-min ; Wang, Hou-jun
Author_Institution :
Sch. of Photoelectric Inf., Univ. of Electron. & Sci. Technol. of China, Chengdu
Abstract :
A controllable decoding or progressive decoding is an elegant feature for some multimedia applications. In this paper, we present a new fractal image decoding method for fractal image compression based on an extended fixed-point iteration theorem. The experimental results show that controlling the fractal decoding process with different non-decreasing sequences is more effective and flexible than the existing conventional decoding methods
Keywords :
data compression; fractals; functional analysis; image coding; image sequences; iterative decoding; controllable decoding; extended fixed-point theorem; fractal image compression; fractal image decoding method; iterated function system; multimedia application; progressive decoding; Application software; Cybernetics; Data compression; Electronic mail; Fractals; Helium; Image coding; Image reconstruction; Information technology; Iterative decoding; Machine learning; Root mean square; Fractal image decoding; extended; fixed-point theorem;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258935
