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Structural Similarity Measure for Color Images

by Mohammed Hassan, Chakravarthy Bhagvati
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 14
Year of Publication: 2012
Authors: Mohammed Hassan, Chakravarthy Bhagvati
10.5120/6169-8590

Mohammed Hassan, Chakravarthy Bhagvati . Structural Similarity Measure for Color Images. International Journal of Computer Applications. 43, 14 ( April 2012), 7-12. DOI=10.5120/6169-8590

@article{ 10.5120/6169-8590,
author = { Mohammed Hassan, Chakravarthy Bhagvati },
title = { Structural Similarity Measure for Color Images },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 14 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 7-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number14/6169-8590/ },
doi = { 10.5120/6169-8590 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:33:22.969091+05:30
%A Mohammed Hassan
%A Chakravarthy Bhagvati
%T Structural Similarity Measure for Color Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 14
%P 7-12
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Color images reveal more meaningful information to the human observers rather than grayscale ones. Regardless of the advantages of the existing well-known objective image quality measures, one of the common and major limitations of these measures is that they evaluate the quality of grayscale images only and don't make use of color information. In this paper we propose an improved method for image quality assessment that adds a color comparison to the criteria of the well-known Multiscale Structural Similarity index (MSSIM). We evaluated the new color image quality measure through human subjective experiments. Our human subjective evaluation data contains 25 reference images and 875 test images produced by five popular color quantization algorithms. Each of the quantized images was evaluated by twenty two subjects and more than 19200 individual human quality judgments were carried out to obtain the final mean opinion scores. We also tested the proposed method on TID2008 image database to further verify our results. These results indicate that adding color comparison improves MSSIM for many distortions in TID2008 and for assessing quantized images in our database.

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Index Terms

Computer Science
Information Sciences

Keywords

Image Quality Assessment Structural Similarity Index Color Quantization

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