Paper
1 October 1990 Numerical category scaling: an efficient method for assessing digital image coding impairments
Huib de Ridder, Gijberta M.M. Majoor
Author Affiliations +
Proceedings Volume 1249, Human Vision and Electronic Imaging: Models, Methods, and Applications; (1990) https://doi.org/10.1117/12.19661
Event: Electronic Imaging: Advanced Devices and Systems, 1990, Santa Clara, CA, United States
Abstract
A current problem in perceptual image quality assessment is the evaluation of the visible effects of digital image coding on the perceptual quality of images displayed on video screens. These effects are anticipated to be too small to be assessed by the widely employed method of rating on a category scale consisting of adjectives. A possible solution to this problem is to enhance the flexibility of category scaling by using numbers instead of adjectives. In that case the category scale can, in principle, adapt to any given quality range. In this paper experiments are described in which numerical category scaling has been used to assess impairment of perceptual image quality due to quantization errors in scale-space coding. The results show that (1) direct numerical category scaling is an efficient method for assessing slight effects like the ones usually encountered in digitally coded images, (2) direct category scaling and a scaling procedure in accordance with functional measurement theory end in the same functional relationship between impairment and degree of quantization, and (3) unrelated impairments add up to form the overall impression of impairment.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Huib de Ridder and Gijberta M.M. Majoor "Numerical category scaling: an efficient method for assessing digital image coding impairments", Proc. SPIE 1249, Human Vision and Electronic Imaging: Models, Methods, and Applications, (1 October 1990); https://doi.org/10.1117/12.19661
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Cited by 33 scholarly publications.
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KEYWORDS
Image compression

Quantization

Image quality

Human vision and color perception

Visual process modeling

Electronic imaging

Digital imaging

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