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Analysis of global spatial statistics features in existing contrast image quality assessment algorithm

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dc.citedby2
dc.contributor.authorAhmed I.T.en_US
dc.contributor.authorDer C.S.en_US
dc.contributor.authorJamil N.en_US
dc.contributor.authorHammad B.T.en_US
dc.contributor.authorid57193324906en_US
dc.contributor.authorid7410253413en_US
dc.contributor.authorid36682671900en_US
dc.contributor.authorid57193327622en_US
dc.date.accessioned2023-05-29T07:24:52Z
dc.date.available2023-05-29T07:24:52Z
dc.date.issued2019
dc.descriptionHigher order statistics; Distorted images; Image quality assessment; Kurtosis and skewness; Lighting conditions; Linear correlation coefficient; No-reference image quality assessments; Spatial statistics; Uneven Contrast; Image qualityen_US
dc.description.abstractMost of existing image quality assessment algorithms (IQAs) have been developed during the past decade. However, most of them are designed for images distorted by compression, noise and blurring. There are very few IQAs designed specifically for CDI, e.g. Contrast distortion may be caused by poor lighting condition and poor-quality image acquisition device. No Reference-Image Quality Assessment (NR-IQA) for Contrast-Distorted Images (NR-IQA-CDI) is one of these few IQAs. The five features used in NR-IQA-CDI are the global spatial statistics of an image including the mean, standard deviation, entropy, kurtosis and skewness. Unfortunately, the performance of NR-IQA-CDI are not encouraging in two of the three test image databases, TID2013 and CSIQ, where the Pearson Linear Correlation Coefficients are only around 0.57 and 0.76, respectively. Therefore, this paper presents the reason which led to poor results in existing NR-IQA-CDI. This paper also can address the problem of existing NR-IQA-CDI which the weakness of the global features in assessing images with uneven contrast. � 2019 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo8835319
dc.identifier.doi10.1109/ICoICT.2019.8835319
dc.identifier.scopus2-s2.0-85073192228
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85073192228&doi=10.1109%2fICoICT.2019.8835319&partnerID=40&md5=04e0510d29bd9532e9906673b0d323ca
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24594
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2019 7th International Conference on Information and Communication Technology, ICoICT 2019
dc.titleAnalysis of global spatial statistics features in existing contrast image quality assessment algorithmen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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