Impact of image size reducing for image quality assesment

The article describes studies of the effect of image reduction on the quantitative assessment of their quality. Image reduction refers to the proportional reduction of horizontal and vertical image resolutions in pixels. Within the framework of these studies, correlation analysis between quantitativ...

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Main Authors: Yu. I. Golub, F. V. Starovoitov, V. V. Starovoitov
Format: Article
Language:English
Published: Belarusian National Technical University 2020-08-01
Series:Системный анализ и прикладная информатика
Subjects:
Online Access:https://sapi.bntu.by/jour/article/view/470
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author Yu. I. Golub
F. V. Starovoitov
V. V. Starovoitov
author_facet Yu. I. Golub
F. V. Starovoitov
V. V. Starovoitov
author_sort Yu. I. Golub
collection DOAJ
description The article describes studies of the effect of image reduction on the quantitative assessment of their quality. Image reduction refers to the proportional reduction of horizontal and vertical image resolutions in pixels. Within the framework of these studies, correlation analysis between quantitative assessments of image quality and subjective assessments of experts was performed. For the experiments, we used images from the public TID2013 database with a resolution of 512 × 384 pixels and expert estimates of their quality, as well as photographs taken with a Nikon D5000 digital camera with a resolution of 4288 × 2848 pixels. All images were reduced in 2, 4 and 8 times. For this two methods were used: bilinear interpolation and interpolation by the nearest neighbor.22 measures were selected to evaluate image quality. Quantitative assessment of image quality was calculated in two stages. At the first stage, an array of local estimates was obtained in the vicinity of each pixel using the selected measures. At the second stage, a global quality assessment was calculated from the obtained local ones. To summarize local quality estimates, the parameters of 16 distributions of random variables were considered.According to the results of the experiments, it was concluded that the accuracy of the quality assessment for some measures decreases with image reduction (for example, FISH, GORD, HELM, LOEN measures). BREN and SHAR measures are recommended as the best. To reduce images, it is better to use the nearest neighbor interpolation method. At the same time, the computation time of estimates is reduced on average by 4 times while reducing images by 2 times. When images are reduced by 8 times, the calculation time decreases on average by 80 times. The amount of memory required to store the reduced images is 25 times less.
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2414-0481
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spelling doaj-art-5b73178c9f114a229908c01f537401472025-02-03T11:37:42ZengBelarusian National Technical UniversityСистемный анализ и прикладная информатика2309-49232414-04812020-08-0102354510.21122/2309-4923-2020-2-35-45354Impact of image size reducing for image quality assesmentYu. I. Golub0F. V. Starovoitov1V. V. Starovoitov2United Institute of Informatics Problems, National Academy of Sciences of BelarusBelarusian National Technical UniversityUnited Institute of Informatics Problems, National Academy of Sciences of BelarusThe article describes studies of the effect of image reduction on the quantitative assessment of their quality. Image reduction refers to the proportional reduction of horizontal and vertical image resolutions in pixels. Within the framework of these studies, correlation analysis between quantitative assessments of image quality and subjective assessments of experts was performed. For the experiments, we used images from the public TID2013 database with a resolution of 512 × 384 pixels and expert estimates of their quality, as well as photographs taken with a Nikon D5000 digital camera with a resolution of 4288 × 2848 pixels. All images were reduced in 2, 4 and 8 times. For this two methods were used: bilinear interpolation and interpolation by the nearest neighbor.22 measures were selected to evaluate image quality. Quantitative assessment of image quality was calculated in two stages. At the first stage, an array of local estimates was obtained in the vicinity of each pixel using the selected measures. At the second stage, a global quality assessment was calculated from the obtained local ones. To summarize local quality estimates, the parameters of 16 distributions of random variables were considered.According to the results of the experiments, it was concluded that the accuracy of the quality assessment for some measures decreases with image reduction (for example, FISH, GORD, HELM, LOEN measures). BREN and SHAR measures are recommended as the best. To reduce images, it is better to use the nearest neighbor interpolation method. At the same time, the computation time of estimates is reduced on average by 4 times while reducing images by 2 times. When images are reduced by 8 times, the calculation time decreases on average by 80 times. The amount of memory required to store the reduced images is 25 times less.https://sapi.bntu.by/jour/article/view/470digital imageimage quality assessmentimage reductionimage resolutionspearman correlationdistribution of random variables
spellingShingle Yu. I. Golub
F. V. Starovoitov
V. V. Starovoitov
Impact of image size reducing for image quality assesment
Системный анализ и прикладная информатика
digital image
image quality assessment
image reduction
image resolution
spearman correlation
distribution of random variables
title Impact of image size reducing for image quality assesment
title_full Impact of image size reducing for image quality assesment
title_fullStr Impact of image size reducing for image quality assesment
title_full_unstemmed Impact of image size reducing for image quality assesment
title_short Impact of image size reducing for image quality assesment
title_sort impact of image size reducing for image quality assesment
topic digital image
image quality assessment
image reduction
image resolution
spearman correlation
distribution of random variables
url https://sapi.bntu.by/jour/article/view/470
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