Fractal image compression using upper bound on scaling parameter
Article Type
Research Article
Publication Title
Chaos, Solitons and Fractals
Abstract
This paper presents a novel approach to calculate the affine parameters of fractal encoding, in order to reduce its computational complexity. A simple but efficient approximation of the scaling parameter is derived which satisfies all properties necessary to achieve convergence. It allows us to substitute to the costly process of matrix multiplication with a simple division of two numbers. We have also proposed a modified horizontal-vertical (HV) block partitioning scheme, and some new ways to improve the encoding time and decoded quality, over their conventional counterparts. Experiments on standard images show that our approach yields performance similar to the state-of-the-art fractal based image compression methods, in much less time.
First Page
1339
Last Page
1351
DOI
10.1016/j.chaos.2017.11.013
Publication Date
1-1-2018
Recommended Citation
Roy, Swalpa Kumar; Kumar, Siddharth; Chanda, Bhabatosh; Chaudhuri, Bidyut B.; and Banerjee, Soumitro, "Fractal image compression using upper bound on scaling parameter" (2018). Journal Articles. 1609.
https://digitalcommons.isical.ac.in/journal-articles/1609