Mathematical Modeling
Vol. 6 (2022), Issue 4, pg(s) 100-102

THEORETICAL FOUNDATIONS AND SPECIFICITY OF MATHEMATICAL MODELLING

Procedure for analyzing the quality, structure and subjective rating of distorted images by the Full- Reference technique

  • 1 Institute for Informatics and Automation Problems of NAS, Yerevan, Armenia; Russian-Armenian University
  • 2 Institute for Informatics and Automation Problems of NAS, Yerevan, Armenia

Abstract

In the present work, we study the regularities of the influence of the type of distorting algorithm on the result of evaluating the image quality by the Full-Reference method in the presence of subjective quality assessments. As an example, we used the TID2013 database with 3000 images distorted by 24 types of algorithms and subjective mean square scores (MOS) quality ratings. An image quality score based on the Weibull distribution model and the usual PSNR similarity measure is applied. It is shown that the applied distorting algorithms are classified into two types – normal, leading to results consistent with the Human Visual System, and “anomalous”, the corresponding quality estimates of which are disordered or chaotic.

Keywords

References

  1. Joy K.R., Gopalakrishna Sarma E.. J. Theor. and Appl. Inform. Techn., 65 (1), pp.192-201, (2014).
  2. Chandler D. M., ISRN Signal Process, pp. 1–53, (2013).
  3. Alphy George, John Livingston S.. Int. J. Research in Engin. and Techn. 2 (12), pp. 303-307, (2013).
  4. Wang Z., Bovik A.C., Sheikh H.R., and. Simoncelli E.P, IEEE Trans. Image Process., 13(4), pp. 600– 612, (2004).
  5. Vipin Kamble, Bhurchandi K. M., Optik – Int. J. Light and Electron Optics, 126(11-12), pp.1090-1097, (2015).
  6. Аsatryan D. Int. Conf. on Computer Science and Inform. Techn., pp. 201–203, (2019).
  7. Tsung-Jung Liu, Yu-chieh Lin, Weisi Lin, and Jay Kuo C.- C. SIP, 2(4), (2013).
  8. Guangtao Zhai, Xiongkuo Min., 63, 211301:1–211301:52, (2020). https://doi.org/10.1007/s11432-019-2757-1
  9. Ponomarenko N., Jin L., Ieremeiev O., Lukin V., Egiazarian K., Astola J., Vozel B., Chehdi K., Carli M., Battisti F., et al. Image database tid2013: Signal Processing: Image Communication, 30, pp. 57–77, (2015).
  10. Asatryan D. G. Computer Optics, 43(2), pp. 245-250, (2019).
  11. Asatryan D. G. Computer Optics, 41(6), pp. 957-962, (2017).
  12. Asatryan D., Haroutunian M., Sazhumyan G., V Int. Sc. Conf. Math. Model., 5(3), pp. 5 – 7, (2021). http://www.mathmodel.eu/sbornik/2021.pdf

Article full text

Download PDF