Image & Video Quality Assessment and Human Visual Perception

International Journal of Computer & Organization Trends  (IJCOT)          
© 2016 by IJCOT Journal
Volume - 6 Issue - 3
Year of Publication : 2016
AuthorsRavi Kumar Saini, Mrs. Mamta Yadav


Ravi Kumar Saini, Mrs. Mamta Yadav"Image & Video Quality Assessment and Human Visual Perception", International Journal of Computer & organization Trends (IJCOT), V6(3):1-4 May - Jun 2016, ISSN:2249-2593, Published by Seventh Sense Research Group.

Abstract Images and videos have become an essential part of day to day life, we observe the images and videos and draw the conclusion that a particular image or video is of good quality or bad quality as lots of time we say that the particular video is a high definition video so some questions arise how we assess the quality of an image and video? What are the factors and parameters that make the image of good or bad quality? How the images and videos are perceived by the human eyes? So this paper is concentrated around all the issues related to the quality assessment of the images and the videos. This letter describes the state of art related to the image and video quality by utilizing the some pre-existing quality metrics like PSNR, SSIM and VQM etc. And it also give emphasize on the human visual perception that describes the sensitivities of human eyes towards the images and videos.


[1] T. D. Kite, B. L. Evans, A. C. Bovik, and T. L. Sculley, “Digital halftoning as 2-D delta-sigma modulation,” in Proc. IEEE Int. Conf. Image Proc., vol. 1, Oct. 1997.
[2] Q. Lin, “Halftone image quality analysis based on a human vision model,” in Proc. SPIE, vol. 1913, Feb. 1993.
[3] T. Mitsa, K. L.Varkur, and J. R. Alford, “Frequency channel based visual models as quantitative quality measures in halftoning,” in Proc. SPIE, vol. 1913, Feb. 1993.
[4] T. Mitsa and K. L. Varkur, “Evaluation of contrast sensitivity functions for the formulation of quality measures incorporated in halftoning algorithms,” in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing, vol. 3, Mar. 1992.
[5] S. Daly, “The visible differences predictor: An algorithm for the assessment for image fidelity,” in Proc. SPIE Conf. on Human Vision, Visual Processing, Digital Display, vol. 1666, San Jose, CA, Feb. 1992.
[6] J. Lubin, “A visual discrimination model for imaging system design and evaluation,” in Vision Models for Target Detection and Recognition, Singapore: World Scientific, 1995.
[7] P. Teo and D. Heeger, “A model of perceptual image fidelity,” in Proc. IEEE Conf. Image Processing, vol. 2, Oct. 1995.
[8] “Perceptual image distortion,” in Proc. IEEE Conf. Image Processing, vol. 2, Nov. 1994.
[9] E. Peli, “Contrast in complex images,” J. Opt. Soc. Amer. Oct. 1990.
[10] T. Mitsa, “Image quality metrics for halftone images,” in Proc. SPIE, vol. 1778, Mar. 1992.
[11] R. Ulichney, Digital Halftoning. Cambridge, MA: MIT Press, 1987.
[12] B. A.Wandell, Foundations of Vision. Sunderland, MA: Sinauer, 1995.
[13] P. Barten, “Evaluation of subjective image quality with the square-rootintegral method,” J. Opt. Soc. Amer. A, vol. 7 Oct. 1990.
[14] SSIM BASED RANGE IMAGE QUALITY ASSESSMENT by W.S. Malpica and A.C. Bovik Vision Res, June 1986.
[15] Overview of scalable H.264 / MPEG4-AVC extension by Thomas Wiegand.
[16 ] Evaluation of MPEG4-SVC for QoE protection in context of transmission errors by Yohann Pitery, Marcus Barkowsky, Patrick Le Callet, Romuald Pépion IRRCyN Lab , Image & Video Communication Group Ecole Polytechnique Nantes, France.

Error sensitivity, human visual system (HVS), image coding, image quality assessment, JPEG, JPEG2000, perceptual quality, structural information, structural similarity(SSIM ), Video Quality Assessment (VQA), Peak Signal Noise Ratio(PSNR).