PFF-RVM: A new no reference image quality measure

2020 ◽  
Vol 167 ◽  
pp. 404-414
Author(s):  
Besma Sadou ◽  
Atidel Lahoulou ◽  
Toufik Bouden
2013 ◽  
Vol 13 (02) ◽  
pp. 1340005 ◽  
Author(s):  
KANJAR DE ◽  
V. MASILAMANI

In many modern image processing applications determining quality of the image is one of the most challenging tasks. Researchers working in the field of image quality assessment design algorithms for measuring and quantifying image quality. The human eye can identify the difference between a good quality image and a noisy image by simply looking at the image, but designing a computer algorithm to automatically determine the quality of an image is a very challenging task. In this paper, we propose an image quality measure using the concept of object separability. We define object separability using variance. Two objects are very well separated if variance of individual object is less and mean pixel values of neighboring objects are very different. Degradation in images can be due to a number of reasons like additive noises, quantization defects, sampling defects, etc. The proposed no-reference image quality measure will determine quality of degraded images and differentiate between good and degraded images.


2011 ◽  
Vol 6 (11) ◽  
pp. 216-224
Author(s):  
Abdelkaher Ait Abdelouahad ◽  
Mohammed El Hassouni ◽  
Hocine Cherifi ◽  
Driss Aboutajdine

2016 ◽  
Vol 19 (3) ◽  
pp. 34-38 ◽  
Author(s):  
Karen Panetta ◽  
Long Bao ◽  
Sos Agaian

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