On The Spatial Frequency Response Of The Visual System In The Assessment Of Image Quality

1987 ◽  
Author(s):  
Y. Feng ◽  
K. Biedermann
Keyword(s):  
Image Quality ◽  
Spatial Frequency ◽  
Visual System ◽  
Frequency Response

Using the dead leaves pattern for more than spatial frequency response measurements

2020 ◽  
Vol 2020 (16) ◽  
pp. 148-1-148-6
Author(s):  
Uwe Artmann
Keyword(s):  
Image Quality ◽  
Light Intensity ◽  
Spatial Frequency ◽  
Noise Reduction ◽  
Frequency Response ◽  
Dynamic Range ◽  
Video Streams ◽  
Camera System ◽  
Camera Systems ◽  
The Dead

The dead leaves pattern is very useful to obtain an SFR from a stochastic pattern and can be used to measure texture loss due to noise reduction or compression in images and video streams. In this paper, we present results from experiments that use the pattern and different analysis approaches to measure the dynamic range of a camera system as well as to describe the dependency of the SFR on object contrast and light intensity. The results can be used to improve the understanding of the performance of modern camera systems. These systems work adaptively and are scene aware but are not well described by standard image quality metrics.

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.

Evidence on the local character of spatial frequency channels in the human visual system

1985 ◽  
Vol 25 (9) ◽  
pp. 1233-1240 ◽  
Author(s):  
Eckart Perizonius ◽  
Wolfgang Schill ◽  
Hans Geiger ◽  
Rainer Röhler
Keyword(s):  
Spatial Frequency ◽  
Visual System ◽  
Human Visual System ◽  
Local Character

Independent Processing across Spatial Frequency in Moving Broadband Patterns

Perception ◽  
1997 ◽  
Vol 26 (8) ◽  
pp. 961-976 ◽  
Author(s):  
Richard A Eagle
Keyword(s):  
Spatial Frequency ◽  
Visual System ◽  
High Frequency ◽  
Spatial Scales ◽  
Power Spectra ◽  
Frequency Noise ◽  
Low Contrast ◽  
Task Requirements ◽  
Noise Frequency ◽  
Frame Motion

The aim of the experiments was to discover whether the visual system has independent access to motion information at different spatial scales when presented with a broadband stimulus. Subjects were required to discriminate between a pair of two-frame motion sequences, one containing a coherently displacing pattern and the other containing a pattern with high-frequency noise. The stimuli were either narrowband (1 octave) or broadband (6 octaves spanning 0.23–15.0 cycles deg−1) and their power spectra were either flat or followed a 1 /f2 function. For the broadband stimuli, noise was introduced cumulatively into increasingly lower frequencies. For the narrowband stimuli, noise was introduced into the same frequency band as the signal. All stimuli could be defined by the lowest noise frequency ( n1) they contained. For each stimulus, the largest spatial displacement across the two frames at which the task could be performed was measured ( dmax). For the narrowband stimuli, dmax increased as n1 was lowered. This was true over the entire frequency range for the 1 /f2 stimuli, though the task became impossible for the flat-spectrum stimuli at the lowest frequencies. This is attributed to the very low contrast of these latter stimuli. The dmax values for the broadband stimuli tended to shadow those of the narrowband stimuli with the equivalent values of n1 being around 25% lower. The data were modelled by spatiotemporally filtering the stimuli and considering the amount of directional power in the signal and noise sequences. The results suggest that there must be multiple spatial-frequency channels in operation, and that for broadband patterns the visual system has perceptual access to these individual channel outputs, utilising different filters depending on the task requirements.

Comparison at a Distance

Perception ◽  
10.1068/p3393 ◽  
2003 ◽  
Vol 32 (4) ◽  
pp. 395-414 ◽  
Author(s):  
Marina V Danilova ◽  
John D Mollon
Keyword(s):  
Visual Field ◽  
Spatial Frequency ◽  
Visual System ◽  
Spatial Separation ◽  
Orientation Discrimination ◽  
Human Observer ◽  
Systematic Effect ◽  
Trained Subjects ◽  
Stimulus Attribute ◽  
The Subject

The visual system is known to contain hard-wired mechanisms that compare the values of a given stimulus attribute at adjacent positions in the visual field; but how are comparisons performed when the stimuli are not adjacent? We ask empirically how well a human observer can compare two stimuli that are separated in the visual field. For the stimulus attributes of spatial frequency, contrast, and orientation, we have measured discrimination thresholds as a function of the spatial separation of the discriminanda. The three attributes were studied in separate experiments, but in all cases the target stimuli were briefly presented Gabor patches. The Gabor patches lay on an imaginary circle, which was centred on the fixation point and had a radius of 5 deg of visual angle. Our psychophysical procedures were designed to ensure that the subject actively compared the two stimuli on each presentation, rather than referring just one stimulus to a stored template or criterion. For the cases of spatial frequency and contrast, there was no systematic effect of spatial separation up to 10 deg. We conclude that the subject's judgment does not depend on discontinuity detectors in the early visual system but on more central codes that represent the two stimuli individually. In the case of orientation discrimination, two naïve subjects performed as in the cases of spatial frequency and contrast; but two highly trained subjects showed a systematic increase of threshold with spatial separation, suggesting that they were exploiting a distal mechanism designed to detect the parallelism or non-parallelism of contours.

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