Prediction of perceived image quality by mobile device users

This paper provides an overview of the PhD research of perceived image quality (PIQ) assessment, which has a great potential for image processing in many applications. The outcome of this research can be used by smartphone vendors in order to shorten “time to market,” or by any image quality experts...

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Autores principales:	Zorea, Pinchas, Paladi, Florentin, Bragaru, Tudor
Formato:	article
Lenguaje:	EN
Publicado:	D.Ghitu Institute of Electronic Engineering and Nanotechnologies 2018
Materias:	Physics QC1-999 Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/855ad9245096475f831b6cb4d59a60ea
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id	oai:doaj.org-article:855ad9245096475f831b6cb4d59a60ea
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spelling	oai:doaj.org-article:855ad9245096475f831b6cb4d59a60ea2021-11-21T11:56:19ZPrediction of perceived image quality by mobile device users531.82537-63651810-648Xhttps://doaj.org/article/855ad9245096475f831b6cb4d59a60ea2018-12-01T00:00:00Zhttps://mjps.nanotech.md/archive/2018/article/71416https://doaj.org/toc/1810-648Xhttps://doaj.org/toc/2537-6365This paper provides an overview of the PhD research of perceived image quality (PIQ) assessment, which has a great potential for image processing in many applications. The outcome of this research can be used by smartphone vendors in order to shorten “time to market,” or by any image quality experts, particularly in the academia, to reduce the time and cost of PIQ assessment of smartphones with a small high-definition display. The method can be implemented in a software if it is embedded in the social network websites to predict and improve the image quality as perceived by the users in real time. The research was based on no reference (NR) PIQ evaluation experiments combined with the VIQET software application. The experiments include human visual tests (HVTs) for subjective image quality assessment. The results of HVTs analysis identify the most effective image quality attributes for perceived image quality. The VIQET software tool was calibrated according to the HVTs scores.Zorea, PinchasPaladi, FlorentinBragaru, TudorD.Ghitu Institute of Electronic Engineering and NanotechnologiesarticlePhysicsQC1-999ElectronicsTK7800-8360ENMoldavian Journal of the Physical Sciences, Vol 17, Iss 3-4, Pp 217-227 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Physics QC1-999 Electronics TK7800-8360
spellingShingle	Physics QC1-999 Electronics TK7800-8360 Zorea, Pinchas Paladi, Florentin Bragaru, Tudor Prediction of perceived image quality by mobile device users
description	This paper provides an overview of the PhD research of perceived image quality (PIQ) assessment, which has a great potential for image processing in many applications. The outcome of this research can be used by smartphone vendors in order to shorten “time to market,” or by any image quality experts, particularly in the academia, to reduce the time and cost of PIQ assessment of smartphones with a small high-definition display. The method can be implemented in a software if it is embedded in the social network websites to predict and improve the image quality as perceived by the users in real time. The research was based on no reference (NR) PIQ evaluation experiments combined with the VIQET software application. The experiments include human visual tests (HVTs) for subjective image quality assessment. The results of HVTs analysis identify the most effective image quality attributes for perceived image quality. The VIQET software tool was calibrated according to the HVTs scores.
format	article
author	Zorea, Pinchas Paladi, Florentin Bragaru, Tudor
author_facet	Zorea, Pinchas Paladi, Florentin Bragaru, Tudor
author_sort	Zorea, Pinchas
title	Prediction of perceived image quality by mobile device users
title_short	Prediction of perceived image quality by mobile device users
title_full	Prediction of perceived image quality by mobile device users
title_fullStr	Prediction of perceived image quality by mobile device users
title_full_unstemmed	Prediction of perceived image quality by mobile device users
title_sort	prediction of perceived image quality by mobile device users
publisher	D.Ghitu Institute of Electronic Engineering and Nanotechnologies
publishDate	2018
url	https://doaj.org/article/855ad9245096475f831b6cb4d59a60ea
work_keys_str_mv	AT zoreapinchas predictionofperceivedimagequalitybymobiledeviceusers AT paladiflorentin predictionofperceivedimagequalitybymobiledeviceusers AT bragarutudor predictionofperceivedimagequalitybymobiledeviceusers
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Prediction of perceived image quality by mobile device users

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