Efficient Fractal Image Coding using Fast Fourier Transform

Abstract

The fractal coding is a novel technique for
image compression. Though the technique has many
attractive features, the large encoding time makes it
unsuitable for real time applications. In this paper, an
efficient algorithm for fractal encoding which operates
on entire domain image instead of overlapping domain
blocks is presented.The algorithm drastically reduces
the encoding time as compared to classical full search
method. The reduction in encoding time is mainly due
to use of modified crosscorrelation based similarity
measure. The implemented algorithm employs exhaustive
search of domain blocks and their isometry transformations
to investigate their similarity with every
range block. The application of Fast Fourier Transform
in similarity measure calculation speeds up the
encoding process. The proposed eight isometry transformations
of a domain block exploit the properties of
Discrete Fourier Transform to minimize the number of
Fast Fourier Transform calculations. The experimental
studies on the proposed algorithm demonstrate that the
encoding time is reduced drastically with average speedup
factor of 538 with respect to the classical full
search method with comparable values of Peak Signal
To Noise Ratio.