Paper
27 August 1992 Minkowski-metrics as a combination rule for digital-image-coding impairments
Author Affiliations +
Proceedings Volume 1666, Human Vision, Visual Processing, and Digital Display III; (1992) https://doi.org/10.1117/12.135953
Event: SPIE/IS&T 1992 Symposium on Electronic Imaging: Science and Technology, 1992, San Jose, CA, United States
Abstract
The urge to compress the amount of information needed to represent digitized images while preserving perceptual image quality has led to a plethora of image-coding algorithms. At high data compression ratios, these algorithms usually introduce several coding artifacts, each impairing image quality to a greater or lesser extent. These impairments often occur simultaneously. For the evaluation of image-coding algorithms, it is important to find out how these impairments combine and how this can be described. The objective of the present study is to show that Minkowski-metrics can be used as a combination rule for small impairments like those usually encountered in digitally coded images. To this end, an experiment has been conducted in which subjects assessed the perceptual quality of scale-space-coded color images comprising three kinds of impairment, viz., 'unsharpness', 'phantoms' (dark/bright patches within bright/dark homogeneous regions) and 'color desaturation'. The results show an accumulation of these impairments that is efficiently described by a Minkowski-metric with an exponent of about two. The latter suggests that digital-image-coding impairments may be represented by a set of orthogonal vectors along the axes of a multidimensional Euclidean space. An extension of Minkowski-metrics is presented to generalize the proposed combination rule to large impairments.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Huib de Ridder "Minkowski-metrics as a combination rule for digital-image-coding impairments", Proc. SPIE 1666, Human Vision, Visual Processing, and Digital Display III, (27 August 1992); https://doi.org/10.1117/12.135953
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Cited by 79 scholarly publications.
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KEYWORDS
Image quality

Visualization

Ultraviolet radiation

Human vision and color perception

Image compression

Visual process modeling

Quantization

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