scholarly journals Quality Assessment of Digital Picture. Approaches to Objective Assessment Method of Digital Image; Categories and Characters of Objective Assessment Method.

1999 ◽  
Vol 53 (9) ◽  
pp. 1199-1205 ◽  
Author(s):  
Shuichi Matsumoto ◽  
Ryoichi Kawada
Keyword(s):  
Quality Assessment ◽  
Digital Image ◽  
Objective Assessment ◽  
Assessment Method ◽  
Digital Picture

No-Reference Image Quality Assessment Based on Multi-Order Gradients Statistics

2020 ◽  
Vol 64 (1) ◽  
pp. 10505-1-10505-16
Author(s):  
Yin Zhang ◽  
Xuehan Bai ◽  
Junhua Yan ◽  
Yongqi Xiao ◽  
C. R. Chatwin ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Assessment Method ◽  
Image Distortion ◽  
Image Feature ◽  
Reference Image ◽  
Gradient Magnitude ◽  
Distortion Type

Abstract A new blind image quality assessment method called No-Reference Image Quality Assessment Based on Multi-Order Gradients Statistics is proposed, which is aimed at solving the problem that the existing no-reference image quality assessment methods cannot determine the type of image distortion and that the quality evaluation has poor robustness for different types of distortion. In this article, an 18-dimensional image feature vector is constructed from gradient magnitude features, relative gradient orientation features, and relative gradient magnitude features over two scales and three orders on the basis of the relationship between multi-order gradient statistics and the type and degree of image distortion. The feature matrix and distortion types of known distorted images are used to train an AdaBoost_BP neural network to determine the image distortion type; the feature matrix and subjective scores of known distorted images are used to train an AdaBoost_BP neural network to determine the image distortion degree. A series of comparative experiments were carried out using Laboratory of Image and Video Engineering (LIVE), LIVE Multiply Distorted Image Quality, Tampere Image, and Optics Remote Sensing Image databases. Experimental results show that the proposed method has high distortion type judgment accuracy and that the quality score shows good subjective consistency and robustness for all types of distortion. The performance of the proposed method is not constricted to a particular database, and the proposed method has high operational efficiency.

A Video Quality Assessment Method for VoIP Applications Based on User Experience

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Zedong Wang ◽  
Jing Wang ◽  
Fei Wang ◽  
Chengcai Li ◽  
Zesong Fei ◽  
...  
Keyword(s):  
Quality Assessment ◽  
User Experience ◽  
Video Quality ◽  
Assessment Method ◽  
Video Quality Assessment ◽  
Quality Assessment Method

scholarly journals Coloring Pictures for Electron Microscopists or Elements of Digital Image Manipulation for Students

2008 ◽  
Vol 16 (4) ◽  
pp. 62-63
Author(s):  
V.M. Dusevich ◽  
J.H. Purk ◽  
J.D. Eick
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Digital Image ◽  
Secondary Electron ◽  
Image Manipulation ◽  
Sem Micrographs ◽  
Backscattered Electrons ◽  
Digital Picture ◽  
Scanning Electron

Coloring pictures is an educational exercise, which is fun, and helps develop important skills. Coloring SEM micrographs is especially suitable for electron microscopists. Color micrographs are not just great looking on a lab wall; they inspire both microscopists and students to exercise digital picture manipulation. Many microscopists enjoyed looking at the beautiful color micrographs by D. Scharf, but were frustrated to learn they needed a very particular scanning electron microscope equipped with multiple secondary electron detectors in order to color their own pictures. Fortunately, there are other ways to color SEM micrographs. Most SEMs are equipped with at least two detectors, for secondary and backscattered electrons.

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