Paper
2 June 2000 Percentage scaling: a new method for evaluating multiply impaired images
Huib de Ridder, Martijn C. Willemsen
Author Affiliations +
Proceedings Volume 3959, Human Vision and Electronic Imaging V; (2000) https://doi.org/10.1117/12.387201
Event: Electronic Imaging, 2000, San Jose, CA, United States
Abstract
Data compression of digitized images usually leads to pictures with two or more perceptually distinguishable coding artifacts. In this paper, percentage scaling is presented as a new method for analyzing the perceived quality of multiply impaired images. By this method, subjects assess, per coding level, the proportion each artifact contributes to the overall impairment of the perceived quality of the coded image. These proportions are expressed in percentages such that the total sum is always 100%. As an illustration, percentage scaling has been employed to evaluate the perceived quality of JPEG-coded images comprising three types of coding artifacts: blockiness, ringing and blur. In one experiment, eight subjects expressed in percentages how much they believed these artifacts contributed to the overall impairment. In addition, overall impairment as well as the perceived strengths of blockiness, ringing and blur was assessed on 11-point numerical category scales. The percentages were found to vary with the coding level. Blockiness appeared to be the most dominant artifact at high compression levels, whereas ringing turned out to be the most annoying artifact at low compression levels. The results support the claim that perceptually distinguishable coding artifacts can be represented by a set of orthogonal vectors in a multidimensional Euclidean space.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Huib de Ridder and Martijn C. Willemsen "Percentage scaling: a new method for evaluating multiply impaired images", Proc. SPIE 3959, Human Vision and Electronic Imaging V, (2 June 2000); https://doi.org/10.1117/12.387201
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Cited by 13 scholarly publications.
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KEYWORDS
Image quality

Image compression

Data compression

Information technology

Chlorine

Data modeling

Visualization

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