VSI: A Visual Saliency-Induced Index for Perceptual Image Quality Assessment

2014 ◽  
Vol 23 (10) ◽  
pp. 4270-4281 ◽  
Author(s):  
Lin Zhang ◽  
Ying Shen ◽  
Hongyu Li
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Visual Saliency ◽  
Perceptual Image Quality

Perceptual image quality assessment metric that handles arbitrary motion blur

2012 ◽  
Author(s):  
Fabien Gavant ◽  
Laurent Alacoque ◽  
Antoine Dupret ◽  
Tien Ho-Phuoc ◽  
Dominique David
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Motion Blur ◽  
Perceptual Image Quality

A weighted full-reference image quality assessment based on visual saliency

2017 ◽  
Vol 43 ◽  
pp. 119-126 ◽  
Author(s):  
Yang Wen ◽  
Ying Li ◽  
Xiaohua Zhang ◽  
Wuzhen Shi ◽  
Lin Wang ◽  
...  
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Visual Saliency ◽  
Reference Image ◽  
Full Reference

scholarly journals Total Variation Based Perceptual Image Quality Assessment Modeling

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Yadong Wu ◽  
Hongying Zhang ◽  
Ran Duan
Keyword(s):  
Image Quality ◽  
Visual System ◽  
Quality Assessment ◽  
Total Variation ◽  
Human Visual System ◽  
Image Quality Assessment ◽  
Reference Image ◽  
Distorted Image ◽  
Perceptual Image Quality ◽  
Tv Model

Visual quality measure is one of the fundamental and important issues to numerous applications of image and video processing. In this paper, based on the assumption that human visual system is sensitive to image structures (edges) and image local luminance (light stimulation), we propose a new perceptual image quality assessment (PIQA) measure based on total variation (TV) model (TVPIQA) in spatial domain. The proposed measure compares TVs between a distorted image and its reference image to represent the loss of image structural information. Because of the good performance of TV model in describing edges, the proposed TVPIQA measure can illustrate image structure information very well. In addition, the energy of enclosed regions in a difference image between the reference image and its distorted image is used to measure the missing luminance information which is sensitive to human visual system. Finally, we validate the performance of TVPIQA measure with Cornell-A57, IVC, TID2008, and CSIQ databases and show that TVPIQA measure outperforms recent state-of-the-art image quality assessment measures.

scholarly journals Perceptual Image Quality Assessment with Transformers

2021 ◽  
Author(s):  
Manri Cheon ◽  
Sung-Jun Yoon ◽  
Byungyeon Kang ◽  
Junwoo Lee
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Perceptual Image Quality
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