Selection of compression test images using variance-based statistical method

In this research paper, we used a variance-based statistical method to select 20 test images, according to these latter types (natural, satellite and medical) among a sample of 300 images (100 natural, 100 satellite and 100 medical). The images selection has been done using parameters of image quali...

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Main Authors: Allaoui, Chems El Houda (Author), Bassou, Abdesselam (Author), Benyahia, Ismahane (Author), Khelifi, Mustapha (Author)
Format: EJournal Article
Published: Institute of Advanced Engineering and Science, 2019-10-01.
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042 |a dc 
100 1 0 |a Allaoui, Chems El Houda  |e author 
100 1 0 |e contributor 
700 1 0 |a Bassou, Abdesselam  |e author 
700 1 0 |a Benyahia, Ismahane  |e author 
700 1 0 |a Khelifi, Mustapha  |e author 
245 0 0 |a Selection of compression test images using variance-based statistical method 
260 |b Institute of Advanced Engineering and Science,   |c 2019-10-01. 
500 |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/17699 
520 |a In this research paper, we used a variance-based statistical method to select 20 test images, according to these latter types (natural, satellite and medical) among a sample of 300 images (100 natural, 100 satellite and 100 medical). The images selection has been done using parameters of image quality, namely PSNR, MSSIM and VIF, which were applied on three compression algorithms (DWT+SPIHT, JPEG, and JPEG2000). 
540 |a Copyright (c) 2019 Institute of Advanced Engineering and Science 
540 |a http://creativecommons.org/licenses/by-nc/4.0 
546 |a eng 
690 |a Image compression 
690 |a Image compression; Discrete Wavelet Transform; JPEG; JPEG2000; selection algorithm; SPHIT; evaluation parameters 
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 16, No 1: October 2019; 243-258 
786 0 |n 2502-4760 
786 0 |n 2502-4752 
786 0 |n 10.11591/ijeecs.v16.i1 
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