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Reseach Article

Color Image Compression using PCA

by Mohammad Mofarreh-bonab, Mostafa Mofarreh-bonab
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 111 - Number 5
Year of Publication: 2015
Authors: Mohammad Mofarreh-bonab, Mostafa Mofarreh-bonab
10.5120/19534-1186

Mohammad Mofarreh-bonab, Mostafa Mofarreh-bonab . Color Image Compression using PCA. International Journal of Computer Applications. 111, 5 ( February 2015), 16-19. DOI=10.5120/19534-1186

@article{ 10.5120/19534-1186,
author = { Mohammad Mofarreh-bonab, Mostafa Mofarreh-bonab },
title = { Color Image Compression using PCA },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 111 },
number = { 5 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 16-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume111/number5/19534-1186/ },
doi = { 10.5120/19534-1186 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:47:03.789393+05:30
%A Mohammad Mofarreh-bonab
%A Mostafa Mofarreh-bonab
%T Color Image Compression using PCA
%J International Journal of Computer Applications
%@ 0975-8887
%V 111
%N 5
%P 16-19
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Principal Component Analysis (PCA) is an efficient method for compressing high dimensional databases [1]. For image compression, it is called Hotelling or KL transform. The central idea of PCA is to reduce the dimensionality of a data set in which there are a large number of interrelated variables. [2] This reduction is achieved by transforming to a new set of variables, the principal components, which are uncorrelated, and which are ordered so that the first few retain most of the variation present in all of the original variables. Computation of the principal components reduces to the solution of an Eigen value – Eigen vector problem for a positive-semi definite symmetric matrix [2]. In spite of ordinary applications which utilize the PCA method for dataset compression, in this paper, a new method is introduced to compress a single image in RGB color space using the correlations between three Red, Green and Blue color domains.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Hotelling compression ratio Eigen value Eigen vector Principal Component Analysis color image compression