A GENERIC GLARE SENSATION MODEL BASED ON THE HUMAN VISUAL SYSTEM

2021 ◽  
Author(s):  
M.C.J.M. Vissenberg ◽  
M. Perz ◽  
M.A.H. Donners ◽  
D. Sekulovski
Keyword(s):  
Receptive Field ◽  
Visual System ◽  
Human Visual System ◽  
Spatial Summation ◽  
Light Sources ◽  
Model Based ◽  
Lighting Conditions ◽  
Discomfort Glare ◽  
Pupil Constriction ◽  
Indoor Lighting

Conventional discomfort glare measures are based on glare source properties like luminous intensity or luminance and typically are valid only to specific situations and to specific types of light sources. For instance, the Unified Glare Rating (UGR) is intended for indoor lighting conditions with medium-sized glare sources, whereas another class of discomfort glare measures is specifically devoted to car headlamps. Recently, CIE TC 3-57 started with the aim to develop a more generic glare sensation model based on the human visual system. We present an example of such a model, including a detailed description of aspects like pupil constriction, retinal image formation, photoreceptor response and adaptation, receptive field-type filtering in the retina, and neural spatial summation. The linear correlation of the model to UGR in an indoor setting, and to subjective glare responses in an outdoor-like setting indicate that the human-visual-system-based model may indeed be considered generic.

scholarly journals Structured Computational Modeling of Human Visual System for No-reference Image Quality Assessment

2021 ◽  
Author(s):  
Wen-Han Zhu ◽  
Wei Sun ◽  
Xiong-Kuo Min ◽  
Guang-Tao Zhai ◽  
Xiao-Kang Yang
Keyword(s):  
Information Processing ◽  
Image Quality ◽  
Visual System ◽  
Computational Modeling ◽  
Quality Assessment ◽  
Human Visual System ◽  
Visual Communication ◽  
Visual Experience ◽  
Image Quality Assessment ◽  
Model Based

AbstractObjective image quality assessment (IQA) plays an important role in various visual communication systems, which can automatically and efficiently predict the perceived quality of images. The human eye is the ultimate evaluator for visual experience, thus the modeling of human visual system (HVS) is a core issue for objective IQA and visual experience optimization. The traditional model based on black box fitting has low interpretability and it is difficult to guide the experience optimization effectively, while the model based on physiological simulation is hard to integrate into practical visual communication services due to its high computational complexity. For bridging the gap between signal distortion and visual experience, in this paper, we propose a novel perceptual no-reference (NR) IQA algorithm based on structural computational modeling of HVS. According to the mechanism of the human brain, we divide the visual signal processing into a low-level visual layer, a middle-level visual layer and a high-level visual layer, which conduct pixel information processing, primitive information processing and global image information processing, respectively. The natural scene statistics (NSS) based features, deep features and free-energy based features are extracted from these three layers. The support vector regression (SVR) is employed to aggregate features to the final quality prediction. Extensive experimental comparisons on three widely used benchmark IQA databases (LIVE, CSIQ and TID2013) demonstrate that our proposed metric is highly competitive with or outperforms the state-of-the-art NR IQA measures.

The Study of Spatial Frequency Channels for Human Visual System

2019 ◽  
Vol 33 (06) ◽  
pp. 1955007
Author(s):  
Xiangyang Xu ◽  
Qiao Chen ◽  
Ruixin Xu
Keyword(s):  
Receptive Field ◽  
Spatial Frequency ◽  
Visual System ◽  
Human Visual System ◽  
Frequency Tuning ◽  
Tuning Curve ◽  
Vision System ◽  
Human Vision ◽  
Psychophysical Experiment ◽  
Human Vision System

Similar to auditory perception of sound system, color perception of the human visual system also presents a multi-frequency channel property. In order to study the multi-frequency channel mechanism of how the human visual system processes color information, the paper proposed a psychophysical experiment to measure the contrast sensitivities based on 17 color samples of 16 spatial frequencies on CIELAB opponent color space. Correlation analysis was carried out on the psychophysical experiment data, and the results show obvious linear correlations of observations for different spatial frequencies of different observers, which indicates that a linear model can be used to model how human visual system processes spatial frequency information. The results of solving the model based on the experiment data of color samples show that 9 spatial frequency tuning curves can exist in human visual system with each lightness, R–G and Y–B color channel and each channel can be represented by 3 tuning curves, which reflect the “center-around” form of the human visual receptive field. It is concluded that there are 9 spatial frequency channels in human vision system. The low frequency tuning curve of a narrow-frequency bandwidth shows the characteristics of lower level receptive field for human vision system, the medium frequency tuning curve shows a low pass property of the change of medium frequent colors and the high frequency tuning curve of a width-frequency bandwidth, which has a feedback effect on the low and medium frequency channels and shows the characteristics of higher level receptive field for human vision system, which represents the discrimination of details.

Infrared target detection method based on the receptive field and lateral inhibition of human visual system

2017 ◽  
Vol 56 (30) ◽  
pp. 8555 ◽  
Author(s):  
Shangnan Zhao ◽  
Yong Song ◽  
Yufei Zhao ◽  
Yun Li ◽  
Lin Li ◽  
...  
Keyword(s):  
Receptive Field ◽  
Visual System ◽  
Target Detection ◽  
Lateral Inhibition ◽  
Human Visual System ◽  
Detection Method

Two-Stroke Apparent Motion

2017 ◽  
Author(s):  
George Mather
Keyword(s):  
Receptive Field ◽  
Visual System ◽  
Apparent Motion ◽  
Motion Detection ◽  
Human Visual System ◽  
Motion Aftereffect ◽  
Temporal Response ◽  
Motion Sensing ◽  
Receptive Field Properties ◽  
Directional Motion

“Two-stroke” apparent motion is a powerful illusion of directional motion generated by alternating just two animation frames, which occurs when a brief blank interframe interval is inserted at alternate frame transitions. This chapter discusses this illusion, which can be explained in terms of the receptive field properties of motion-sensing neurons in the human visual system. The temporal response of these neurons contains both an excitatory phase and an inhibitory phase; when the timing of the interframe interval just matches the switch in response sign, the illusion occurs. Concepts covered in this chapter include four-stroke as well as two-stroke apparent motion, motion aftereffect, and motion detection.

Clustering Model Based on the Human Visual System

2021 ◽  
pp. 169-192
Author(s):  
Erik Cuevas ◽  
Alma Rodríguez ◽  
Avelina Alejo-Reyes ◽  
Carolina Del-Valle-Soto
Keyword(s):  
Visual System ◽  
Human Visual System ◽  
Model Based ◽  
Clustering Model
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