Validation of no-reference image quality index for the assessment of digital mammographic images

2016 ◽  
Author(s):  
Helder C. R. de Oliveira ◽  
Bruno Barufaldi ◽  
Lucas R. Borges ◽  
Salvador Gabarda ◽  
Predrag R. Bakic ◽  
...  
Keyword(s):  
Image Quality ◽  
Quality Index ◽  
Reference Image ◽  
Mammographic Images ◽  
Image Quality Index

No-training, no-reference image quality index using perceptual features

2013 ◽  
Vol 52 (5) ◽  
pp. 057003 ◽  
Author(s):  
Chaofeng Li ◽  
Yiwen Ju ◽  
Alan C. Bovik ◽  
Xiaojun Wu ◽  
Qingbing Sang
Keyword(s):  
Image Quality ◽  
Quality Index ◽  
Reference Image ◽  
Perceptual Features ◽  
Image Quality Index

Adaptive DCT coding using the new universal image quality index

2005 ◽  
Author(s):  
Aldo Morales ◽  
Sedig Agili ◽  
Lakshmi P. Baskaran
Keyword(s):  
Image Quality ◽  
Quality Index ◽  
Image Quality Index ◽  
Dct Coding

A NOVEL COMPRESSED IMAGES QUALITY METRIC

2011 ◽  
Vol 11 (02) ◽  
pp. 281-292
Author(s):  
WEN LU ◽  
LIHUO HE ◽  
WENJIAN TANG ◽  
FEI GAO ◽  
WEILONG HOU
Keyword(s):  
Image Quality ◽  
Quality Index ◽  
Image Quality Assessment ◽  
Performance Indicator ◽  
Directional Information ◽  
Quality Metric ◽  
Compressed Images ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Image Quality Index

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.

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