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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Belarusian National Technical University
2020-08-01
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| Series: | Sistemnyj Analiz i Prikladnaâ Informatika |
| Subjects: | |
| Online Access: | https://sapi.bntu.by/jour/article/view/470 |
| Summary: | 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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| ISSN: | 2309-4923 2414-0481 |