Image compression quality rating using anchored scales

Niranjan Avadhanam; V. Ralph Algazi

doi:10.1117/12.302437

1 April 1998 Image compression quality rating using anchored scales

Niranjan Avadhanam, V. Ralph Algazi

Proceedings Volume 3308, Very High Resolution and Quality Imaging III; (1998) https://doi.org/10.1117/12.302437
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

Abstract

Traditional image quality rating schemes use descriptive scales applicable to wide ranges of quality. These scales, based on equal interval verbal descriptors, cannot be used for restricted ranges of quality now encountered in image compression studies. Although numerical category scales have been successfully used in some studies for quantifying small variations in quality arising from lossy image compression, problems arise in more general image coding applications. In this work, we propose a double anchored numerical category scale based on a 3-context visual assessment scheme for image coding applications. The goal is to devise a common subjective scale applicable to a set of images produced from multiple scenes compressed by multiple coding algorithms. Therefore, the contexts are in the use of distinct coders and distinct images. The first two contexts, using a specific image scene, are the visibility of specific coder induced artifacts and the visibility of artifacts arising from different coders. In the third context, the artifact visibility is in terms of the content of different image scenes. Separate scales are obtained for images differing in scene content and for each coding algorithm, using numerical category scaling with explicit high and low anchors. These scales are linked using pairwise matching techniques to obtain a robust image quality sale.

Citation Download Citation

Niranjan Avadhanam and V. Ralph Algazi "Image compression quality rating using anchored scales", Proc. SPIE 3308, Very High Resolution and Quality Imaging III, (1 April 1998); https://doi.org/10.1117/12.302437

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KEYWORDS

Image quality

Image compression

Visibility

Wavelets

Visualization

Psychophysics

Molybdenum

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