Image Processing by the Human Visual System

1991 ◽  
pp. 309-341 ◽  
Author(s):  
Simon J. Thorpe
Keyword(s):  
Image Processing ◽  
Visual System ◽  
Human Visual System

Technical Vision Model of the Visual Systems for Industry Application

2021 ◽  
pp. 288-310
Author(s):  
Oleg Sytnik ◽  
Vladimir Kartashov
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Visual System ◽  
Mathematical Models ◽  
Human Visual System ◽  
Vision System ◽  
Vision Systems ◽  
Industrial Systems ◽  
Visual Systems ◽  
Technical Vision

The problems of highlighting the main informational aspects of images and creating their adequate models are discussed in the chapter. Vision systems can receive information about an object in different frequency ranges and in a form that is not accessible to the human visual system. Vision systems distort the information contained in the image. Therefore, to create effective image processing and transmission systems, it is necessary to formulate mathematical models of signals and interference. The chapter discusses the features of perception by the human visual system and the issues of harmonizing the technical characteristics of industrial systems for receiving and transmitting images. Methods and algorithms of pattern recognition are discussed. The problem of conjugation of the characteristics of the technical vision system with the consumer of information is considered.

A Novel Method of Image Quality Assessment

2014 ◽  
Vol 556-562 ◽  
pp. 5064-5067 ◽  
Author(s):  
Ming Wei Guo ◽  
Chen Bin Zhang ◽  
Zong Hai Chen
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Selective Attention ◽  
Visual System ◽  
Quality Assessment ◽  
Human Visual System ◽  
Image Quality Assessment ◽  
Visual Selective Attention ◽  
Research Areas ◽  
Novel Method

Image quality assessment (IQA) is one of the hot research areas in the field of image processing. For the reason that human being is the final receiver of the image, the image quality assessment should match the characteristics of human visual system. In this paper, we propose a novel method of image quality assessment which uses the visual selective attention of human visual system. For an image of a certain category, our method firstly detects the object in it and then calculate the saliency of the object. Lastly we use the combination of the detector’s score and the saliency as the image quality assessment. Experiments on some images of Pascal VOC dataset and INRIA dataset show that our method does well in image quality assessment.

Using Human Visual System modeling for bio-inspired low level image processing

2010 ◽  
Vol 114 (7) ◽  
pp. 758-773 ◽  
Author(s):  
A. Benoit ◽  
A. Caplier ◽  
B. Durette ◽  
J. Herault
Keyword(s):  
Image Processing ◽  
Visual System ◽  
Human Visual System ◽  
System Modeling ◽  
Low Level
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