A contrast sensitivity model of the human visual system in modern conditions for presenting video content
Dr Anastasia Mozhaeva, Eastern Institute of Technology
Dr Igor Vlasuyk, Moscow Technical University of Communications and Informatics
Dr Lee Streeter, The University Waikato
Associate Professor Michael Cree, The University Waikato
Aleksei Potashnikov, Moscow Technical University of Communications and Informatics
Vladimir Mazin, Moscow Technical University of Communications and Informatics
Primary contact: Anastasia Mozhaeva amozhaeva@eit.ac.nz
Abstract:
In this work, the 40000 thresholds of the visibility of spatio-temporal sinusoidal variations necessary to determine the artefacts that a human perceives were measured by a new method using different spatial sizes and temporal modulation rates. A multidimensional model of human contrast sensitivity in modern conditions of video content presentation is proposed based on new large-scale data obtained during the experiment.
Central Vision:
The 27840 thresholds of the visibility of spatio-temporal sinusoidal variations that a human perceives were measured by a new method using different spatial sizes and temporal modulation rates.
The coefficients of the defined approximation polynomials of sl(k, f, 120) derivatives.
Article:
Mozhaeva A, Cree MJ, Durrant RJ, Vlasuyk I, Potashnikov A, Mazin V, Streeter L (2024). A contrast sensitivity model of the human visual system in modern conditions for presenting video content. PLoS One, 19(5). https://doi.org/10.1371/journal.pone.0303987
Peripheral Characteristics of Human Vision:
1760 values of contrast thresholds for the peripheral region of the human visual system were obtained.
Paper:
Mozhaeva A, Vlasuyk I, Potashnikov A, Mazin V and Streeter L (2024). Video Quality Metric Compatible with PSNR Considering Recent Knowledge of Peripheral Characteristics of Human Vision, 39th International Conference on Image and Vision Computing New Zealand (IVCNZ), Christchurch, New Zealand, pp. 1-6, doi: 10.1109/IVCNZ64857.2024.10794472.
Code and data [Github]