Color-to-grayscale conversion with color clustering and significance criteria

Peter Majewicz

doi:10.1117/12.839095

8 February 2010 Color-to-grayscale conversion with color clustering and significance criteria

Peter Majewicz

Proceedings Volume 7532, Image Processing: Algorithms and Systems VIII; 75320A (2010) https://doi.org/10.1117/12.839095
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States

Abstract

An image processing algorithm is presented that adaptively converts color images to grayscale. The intent of the conversion is to preserve color information that is traditionally lost by the conversion process. The conversion produces high-contrast grayscale representations with enhanced color discriminability. A web-based psychometric study confirms that the algorithm is mostly preferred over traditional algorithms. The algorithm employs a multi-stepped approach that includes color clustering, 3-dimensional partitioning, and simulated annealing.

Citation Download Citation

Peter Majewicz "Color-to-grayscale conversion with color clustering and significance criteria", Proc. SPIE 7532, Image Processing: Algorithms and Systems VIII, 75320A (8 February 2010); https://doi.org/10.1117/12.839095

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