Blind image quality assessment for color images with additive Gaussian white noise using standard deviation

Chern Loon Lim, Raveendran Paramesran

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

7 Citations (Scopus)

Abstract

This paper presents a no-reference (NR) quality assessment method for color images contaminated with additive Gaussian white noise (AGWN). The proposed metric operates on the test image and the scaled down version of the test image. Standard deviations for each of the RGB components for the test image and its scaled down version are computed. The standard deviation ratios of the scaled down version image to the original test image are weighted summed to obtain the quality score for noise. The performance of the proposed metric is compared with existing full-reference (FR) and NR metrics on LIVE database. Pearson correlation coefficient (CC), mean absolute error (MAE) and root mean square error (RMSE) are used to evaluate the performance of the proposed metric. A CC score of 0.9785 shows that the proposed metric has high correlation with the subjective scores for the LIVE database.

Original languageEnglish
Title of host publication2014 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2014
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages39-41
Number of pages3
ISBN (Electronic)9781479961207
DOIs
Publication statusPublished - 27 Jan 2014
Externally publishedYes
EventIEEE International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS) 2014 - Kuching, Sarawak, Malaysia
Duration: 1 Dec 20144 Dec 2014
https://ieeexplore.ieee.org/xpl/conhome/7006982/proceeding (Proceedings)

Conference

ConferenceIEEE International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS) 2014
Abbreviated titleISPACS 2014
Country/TerritoryMalaysia
CityKuching, Sarawak
Period1/12/144/12/14
Internet address

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