PIQI: perceptual image quality index based on ensemble of Gaussian process regression

Author(s):  
Nisar Ahmed ◽  
Hafiz Muhammad Shahzad Asif ◽  
Hassan Khalid
2017 ◽  
Vol 60 ◽  
pp. 277-286 ◽  
Author(s):  
Zaifeng Shi ◽  
Kexin Chen ◽  
Ke Pang ◽  
Jiaping Zhang ◽  
Qingjie Cao

2005 ◽  
Author(s):  
Aldo Morales ◽  
Sedig Agili ◽  
Lakshmi P. Baskaran

2011 ◽  
Vol 11 (02) ◽  
pp. 281-292
Author(s):  
WEN LU ◽  
LIHUO HE ◽  
WENJIAN TANG ◽  
FEI GAO ◽  
WEILONG HOU

As the performance indicator of the image processing algorithms or systems, image quality assessment (IQA) has attracted the attention of many researchers. Aiming to the widely used compression standards, JPEG and JPEG2000, we propose a new no reference (NR) metric for compressed images to do IQA. This metric exploits the causes of distortion by JPEG and JPEG2000, employs the directional discrete cosine transform (DDCT) to obtain the detail and directional information of the images and incorporates with the visual perception to obtain the image quality index. Experimental results show that the proposed metric not only has outstanding performance on JPEG and JPEG2000 images, but also applicable to other types of artifacts.


2013 ◽  
Vol 52 (5) ◽  
pp. 057003 ◽  
Author(s):  
Chaofeng Li ◽  
Yiwen Ju ◽  
Alan C. Bovik ◽  
Xiaojun Wu ◽  
Qingbing Sang

2016 ◽  
Author(s):  
Helder C. R. de Oliveira ◽  
Bruno Barufaldi ◽  
Lucas R. Borges ◽  
Salvador Gabarda ◽  
Predrag R. Bakic ◽  
...  

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