Abstract
Many grayscale image processing techniques such as edge and feature detection, template matching, require the computations of image gradients and intensity difference. These computations in grayscale are very much like measuring color difference between two colors. The goal of this work is to determine an efficient method to represent color difference so that many existing grayscale image processing techniques that require the computations of intensity difference and image gradients can be adapted for color without significantly increasing the amount of data to process and without significantly altering the grayscale-based algorithms. In this paper, several perceptual color contrast measurement formulas are evaluated to determine the most applicable metric for color difference representation. Well-known edge and feature detection algorithms using color contrast are implemented to prove its feasibility.
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Xiong, G., Lee, DJ., Fowers, S.G., Gong, J., Chen, H. (2010). Using Perceptual Color Contrast for Color Image Processing. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17277-9_42
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DOI: https://doi.org/10.1007/978-3-642-17277-9_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17276-2
Online ISBN: 978-3-642-17277-9
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