Image Quality Assessment Based on Mutual Information in Pixel Domain

2015 ◽  
pp. 503-512
Author(s):  
Hongqiang Xu ◽  
Wen Lu ◽  
Yuling Ren ◽  
Xinbo Gao
Keyword(s):  
Image Quality ◽  
Mutual Information ◽  
Quality Assessment ◽  
Image Quality Assessment

Perceptual image quality assessment metric using mutual information of Gabor features

2014 ◽  
Vol 57 (3) ◽  
pp. 1-9 ◽  
Author(s):  
Yong Ding ◽  
Yuan Zhang ◽  
Xiang Wang ◽  
XiaoLang Yan ◽  
Andrey S. Krylov
Keyword(s):  
Image Quality ◽  
Mutual Information ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Gabor Features ◽  
Perceptual Image Quality

Image quality assessment based on multi-channel regional mutual information

2012 ◽  
Vol 66 (9) ◽  
pp. 784-787 ◽  
Author(s):  
Jing Li ◽  
Kaizhi Wu ◽  
Xuming Zhang ◽  
Mingyue Ding
Keyword(s):  
Image Quality ◽  
Mutual Information ◽  
Quality Assessment ◽  
Image Quality Assessment

scholarly journals A Full-Reference Image Quality Assessment for Multiply Distorted Image based on Visual Mutual Information

2019 ◽  
Vol 63 (6) ◽  
pp. 60504-1-60504-11
Author(s):  
Yin Zhang ◽  
Xuehan Bai ◽  
Junhua Yan ◽  
Yongqi Xiao ◽  
Wanyi Zhang ◽  
...  
Keyword(s):  
Image Quality ◽  
Mutual Information ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Reference Image ◽  
Assessment Index ◽  
Distorted Image ◽  
Gaussian Scale Mixture ◽  
Full Reference ◽  
Reference Images

Abstract A full-reference image quality assessment (FR-IQA) method for multi-distortion based on visual mutual information (MD-IQA) is proposed to solve the problem that the existing FR-IQA methods are mostly applicable to single-distorted images, but the assessment result for multiply distorted images is not ideal. First, the reference image and the distorted image are preprocessed by steerable pyramid decomposition and contrast sensitivity function (CSF). Next, a Gaussian scale mixture (GSM) model and an image distorted model are respectively constructed for the reference images and the distorted images. Then, visual distorted models are constructed both for the reference images and the distorted images. Finally, the mutual information between the processed reference image and the distorted image is calculated to obtain the full-reference quality assessment index for multiply distorted images. The experimental results show that the proposed method has higher accuracy and better performance for multiply distorted images.

Remore Sensing Image Quality Assessment based on the Ratio of Spatial Feature Weighted Mutual Information

2018 ◽  
Vol 62 (2) ◽  
pp. 205051-2050512
Author(s):  
Junhua Yan ◽  
Jingcheng Wang ◽  
Yin Zhang ◽  
Xuehan Bai ◽  
Yongqi Xiao
Keyword(s):  
Image Quality ◽  
Mutual Information ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Spatial Feature

A Novel Hybrid Image Quality Assessment Algorithm

2011 ◽  
Vol 4 (4) ◽  
pp. 107-108
Author(s):  
Deepa Maria Thomas ◽  
◽  
S. John Livingston
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment
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