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Robust and Efficient ‘RGB’ based Fractal Image Compression: Flower Pollination based Optimization

by Gaganpreet Kaur, Dheerendra Singh, Manjinder Kaur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 78 - Number 10
Year of Publication: 2013
Authors: Gaganpreet Kaur, Dheerendra Singh, Manjinder Kaur
10.5120/13524-1215

Gaganpreet Kaur, Dheerendra Singh, Manjinder Kaur . Robust and Efficient ‘RGB’ based Fractal Image Compression: Flower Pollination based Optimization. International Journal of Computer Applications. 78, 10 ( September 2013), 11-15. DOI=10.5120/13524-1215

@article{ 10.5120/13524-1215,
author = { Gaganpreet Kaur, Dheerendra Singh, Manjinder Kaur },
title = { Robust and Efficient ‘RGB’ based Fractal Image Compression: Flower Pollination based Optimization },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 78 },
number = { 10 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 11-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume78/number10/13524-1215/ },
doi = { 10.5120/13524-1215 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:51:12.621168+05:30
%A Gaganpreet Kaur
%A Dheerendra Singh
%A Manjinder Kaur
%T Robust and Efficient ‘RGB’ based Fractal Image Compression: Flower Pollination based Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 78
%N 10
%P 11-15
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Fractal image compression uses the property of self-similarity in an image and utilizes the partitioned iterated function system to encode it. Fractal image compression is attractive because of high compression ratio, fast decompression and multi-resolution properties. The main drawback of Fractal Image Compression is the high computational cost and is the poor retrieved image qualities. To overcome this drawback, we design a new algorithm which is based on Pollination Based Optimization which is used to classify the phantom, satellite and rural image dataset. Flower Pollination Based Optimization is nature inspired algorithm which decreases the search complexity of matching between range block and domain block. Also, the optimization technique has effectively reduced the encoding time while retaining the quality of the image. Peak signal to noise ratio, entropy, compression ratio and mean square error is found for phantom, rural and satellite images data set. This new method showed improved highly accurate results.

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Index Terms

Computer Science
Information Sciences

Keywords

Pollination Based Optimization (PBO) Fractal Image Compression (FIC) Satellite Image Phantom Images Partitioned Iterated Function System Range Block Domain Block Peak Signal Noise Ratio (PSNR) Mean Square Error (MSE) Compression Ratio Entropy.

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