Image Compression based on Iteration-Free Fractal and
using Fuzzy Clustering on DCT Coefficients
Sobia Mahalingam1,
Valarmathi Lakshapalam1, and Saranya Ekabaram2
1Department of Computer Science and
Engineering, Government College of Technology, India
2Department of Computer Science and Engineering, VSB College
of Engineering Technical Campus, India
Abstract: In the proposed method, the encoding time
is reduced by combining iteration-free fractal compression technique with fuzzy
c-means clustering approach to classify the domain blocks. In iteration-free
fractal image compression, the mean image is considered as domain pool for
range-domain mapping that reduces the number of fractal matching. Discrete
cosine transform (DCT) coefficient is used as a new metric for range and domain
blocks comparison. Also fuzzy clustering approach reduces the search space to
only a subset of domain pool. Based on Fuzzy clustering on DCT space, the
domain pool is grouped into three clusters and the search is made in any one of
the three clusters. The proposed method has been tested for various standard
images and found that the encoding time is reduced about 42 times than the
iteration-free fractal coding method with only a slight degradation in the
quality of images.
Keywords: Fractal image compression, fuzzy clustering, DCT
coefficients, contractive affine transformation.