Share Email Print

Proceedings Paper

A color image quality assessment using a reduced-reference image machine learning expert
Author(s): Christophe Charrier; Gilles Lebrun; Olivier Lezoray
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

A quality metric based on a classification process is introduced. The main idea of the proposed method is to avoid the error pooling step of many factors (in frequential and spatial domain) commonly applied to obtain a final quality score. A classification process based on final quality class with respect to the standard quality scale provided by the UIT. Thus, for each degraded color image, a feature vector is computed including several Human Visual System characteristics, such as, contrast masking effect, color correlation, and so on. Selected features are of two kinds: 1) full-reference features and 2) no-reference characteristics. That way, a machine learning expert, providing a final class number is designed.

Paper Details

Date Published: 28 January 2008
PDF: 12 pages
Proc. SPIE 6808, Image Quality and System Performance V, 68080U (28 January 2008); doi: 10.1117/12.766473
Show Author Affiliations
Christophe Charrier, Univ. de Caen-Basse Normandie (France)
Gilles Lebrun, Univ. de Caen-Basse Normandie (France)
Olivier Lezoray, Univ. de Caen-Basse Normandie (France)

Published in SPIE Proceedings Vol. 6808:
Image Quality and System Performance V
Susan P. Farnand; Frans Gaykema, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?