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Proceedings Paper

Multidimensional image quality measure using singular value decomposition
Author(s): Aleksandr Shnayderman; Alexander Gusev; Ahmet M. Eskicioglu
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Paper Abstract

The important criteria used in subjective evaluation of distorted images include the amount of distortion, the type of distortion, and the distribution of error. An ideal image quality measure should therefore be able to mimic the human observer. We present a new image quality measure that can be used as a multidimensional or a scalar measure to predict the distortion introduced by a wide range of noise sources. Based on the Singular Value Decomposition, it reliably measures the distortion not only within a distortion type at different distortion levels but also across different distortion types. The measure was applied to Lena using six types of distortion (JPEG, JPEG 2000, Gaussian blur, Gaussian noise, sharpening and DC-shifting), each with five distortion levels.

Paper Details

Date Published: 18 December 2003
PDF: 11 pages
Proc. SPIE 5294, Image Quality and System Performance, (18 December 2003); doi: 10.1117/12.530554
Show Author Affiliations
Aleksandr Shnayderman, Brooklyn College (United States)
Alexander Gusev, Brooklyn College (United States)
Ahmet M. Eskicioglu, Brooklyn College (United States)

Published in SPIE Proceedings Vol. 5294:
Image Quality and System Performance
Yoichi Miyake; D. Rene Rasmussen, Editor(s)

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