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Reseach Article

Performance Evaluation of Distortion Measures for Retinal Images

by Nirmala S. R, Dandapat S., Bora P. K.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 17 - Number 6
Year of Publication: 2011
Authors: Nirmala S. R, Dandapat S., Bora P. K.

Nirmala S. R, Dandapat S., Bora P. K. . Performance Evaluation of Distortion Measures for Retinal Images. International Journal of Computer Applications. 17, 6 ( March 2011), 17-23. DOI=10.5120/2225-2835

@article{ 10.5120/2225-2835,
author = { Nirmala S. R, Dandapat S., Bora P. K. },
title = { Performance Evaluation of Distortion Measures for Retinal Images },
journal = { International Journal of Computer Applications },
issue_date = { March 2011 },
volume = { 17 },
number = { 6 },
month = { March },
year = { 2011 },
issn = { 0975-8887 },
pages = { 17-23 },
numpages = {9},
url = { },
doi = { 10.5120/2225-2835 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T20:04:53.259674+05:30
%A Nirmala S. R
%A Dandapat S.
%A Bora P. K.
%T Performance Evaluation of Distortion Measures for Retinal Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 17
%N 6
%P 17-23
%D 2011
%I Foundation of Computer Science (FCS), NY, USA

Evaluating the quality of processed retinal images is an important issue in applications such as telemedicine. The traditional image quality measures are having limitation in emphasizing the loss of clinically significant information. We previously proposed a wavelet weighted blood vessel distortion measure (WBVDM) for retinal images. The WBVDM gives more importance to the distortion in clinical features (blood vessels) and less importance to the clinically nonsignificant distortion. This paper presents a statistical evaluation of the performance of a number of image quality measures in quantifying the distortion in retinal images. The measures are then investigated in terms of their correlation with subjective evaluation using the Pearson linear correlation coefficient (PLCC) and Spearman rank order correlation coefficient (SROCC). Their statistical behavior is also evaluated in terms of how discriminating they are to distortion artifacts when tested on a variety of images using the analysis of variance (ANOVA) method. The experimental results indicate that WBVDM performs better by showing higher values of PLCC, SROCC and ANOVA analysis.

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Index Terms

Computer Science
Information Sciences


Image quality DWT subband coefficients objective measures WBVDM MSSIM