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Proceedings Paper

Local contrast enhancement
Author(s): Marco Bressan; Christopher R. Dance; Hervé Poirier; Damián Arregui
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Paper Abstract

We introduce a novel algorithm for local contrast enhancement. The algorithm exploits a background image which is estimated with an edge-preserving filter. The background image controls a gain which enhances important details hidden in underexposed regions of the input image. Our designs for the gain, edge-preserving filter and chrominance recovery avoid artifacts and ensure the superior image quality of our results, as extensively validated by user evaluations. Unlike previous local contrast methods, ours is fully automatic in the sense that it can be directly applied to any input image with no parameter adjustment. This is because we exploit a trainable decision mechanism which classifies images as benefiting from enhancement or otherwise. Finally, a novel windowed TRC mechanism based on monotonic regression ensures that the algorithm takes only 0.3 s to process a 10 MPix image on a 3 GHz Pentium.

Paper Details

Date Published: 29 January 2007
PDF: 12 pages
Proc. SPIE 6493, Color Imaging XII: Processing, Hardcopy, and Applications, 64930Y (29 January 2007); doi: 10.1117/12.724721
Show Author Affiliations
Marco Bressan, Xerox Research Ctr. Europe (France)
Christopher R. Dance, Xerox Research Ctr. Europe (France)
Hervé Poirier, Xerox Research Ctr. Europe (France)
Damián Arregui, Xerox Research Ctr. Europe (France)

Published in SPIE Proceedings Vol. 6493:
Color Imaging XII: Processing, Hardcopy, and Applications
Reiner Eschbach; Gabriel G. Marcu, Editor(s)

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