In this work, we investigate howilluminant estimation techniques can be improved, taking into account automatically extracted information about the content of the images.We considered indoor/outdoor classification because the images of these classes present different content and are usually taken under different illumination conditions. We have designed different strategies for the selection and the tuning of the most appropriate algorithm (or combination of algorithms) for each class. We also considered the adoption of an uncertainty class which corresponds to the images where the indoor/outdoor classifier is not confident enough. The illuminant estimation algorithms considered here are derived from the framework recently proposed byVan deWeijer and Gevers. We present a procedure to automatically tune the algorithms' parameters. We have tested the proposed strategies on a suitable subset of the widely used Funt and Ciurea dataset. Experimental results clearly demonstrate that classification based strategies outperform general purpose algorithms. © 2008 IEEE.

Schettini, R., Cusano, C., Ciocca, G., Bianco, S. (2008). Improving Color Constancy Using Indoor-Outdoor Image Classification. IEEE TRANSACTIONS ON IMAGE PROCESSING, 17(12), 2381-2392 [10.1109/TIP.2008.2006661].

Improving Color Constancy Using Indoor-Outdoor Image Classification

SCHETTINI, RAIMONDO;CUSANO, CLAUDIO;CIOCCA, GIANLUIGI;BIANCO, SIMONE
2008

Abstract

In this work, we investigate howilluminant estimation techniques can be improved, taking into account automatically extracted information about the content of the images.We considered indoor/outdoor classification because the images of these classes present different content and are usually taken under different illumination conditions. We have designed different strategies for the selection and the tuning of the most appropriate algorithm (or combination of algorithms) for each class. We also considered the adoption of an uncertainty class which corresponds to the images where the indoor/outdoor classifier is not confident enough. The illuminant estimation algorithms considered here are derived from the framework recently proposed byVan deWeijer and Gevers. We present a procedure to automatically tune the algorithms' parameters. We have tested the proposed strategies on a suitable subset of the widely used Funt and Ciurea dataset. Experimental results clearly demonstrate that classification based strategies outperform general purpose algorithms. © 2008 IEEE.
Articolo in rivista - Articolo scientifico
color constancy, indoor outdoor classification, adaptive algorithm
English
2381
2392
12
Schettini, R., Cusano, C., Ciocca, G., Bianco, S. (2008). Improving Color Constancy Using Indoor-Outdoor Image Classification. IEEE TRANSACTIONS ON IMAGE PROCESSING, 17(12), 2381-2392 [10.1109/TIP.2008.2006661].
Schettini, R; Cusano, C; Ciocca, G; Bianco, S
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/12984
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