Fractal Image Compression by YIQ Color Space

Author

Al-Hilo, Eman A. ; Zehwar, Rusul

Author_Institution

Phys. Dept., Kufa Univ., Najaf, Iraq

Volume

1

fYear

2014

fDate

10-13 March 2014

Firstpage

221

Lastpage

225

Abstract

In fractal compression the image to be encoded is partitioned into blocks called (ranges). Each range is coded by reference to some other part of the image called (domain) and by some affine transformation parameters. The number of ranges plays an important role in the compression ratio, encoding time and reconstructed image quality. In this paper, the fractal compression technique proposed by Jacquin is investigated for 24 bits/pixel color image. The data of the color component (R,G,B) are transformed to (YIQ) color space, to take the advantage of the existing spectral correlation to gain more compression. Also the low spatial resolution of the human vision systems to the chromatic components (I,Q) was utilized to increase the compression ratio without making significant subjective distortion. The test results show that PSNR (31.05) dB with CR (8.73) and encoding time (57.55) sec for Lena image (256x256) pixel.

Keywords

data compression; image coding; image colour analysis; Lena image; PSNR; RGB color component; YIQ color space; affine transformation parameters; chromatic components; compression ratio; domain image; encoding time; fractal image compression; image partitioning; peak signal-to-noise ratio; pixel color image; range image; reconstructed image quality; red-green-blue; subjective distortion; time 57.55 s; Equations; Fractals; Image coding; Image color analysis; Image reconstruction; Mathematical model; PSNR; Compression image; Fractal image compression; Iterated function system;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Science and Computational Intelligence (CSCI), 2014 International Conference on

Conference_Location

Las Vegas, NV

Type

conf

DOI

10.1109/CSCI.2014.45

Filename

6822112