Abstract
We present an automated algorithm for global contrast enhancement of images with multimodal histograms. To locate modes and valleys, histogram analysis is performed by kernel density estimation, a robust nonparametric statistical method. Histogram warping by monotonic splines pushes the modes apart, spreading them out more evenly across the dynamic range. This technique can assist in the contrast correction of images taken facing the light source.
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Grundland, M., A. Dodgson, N. (2006). AUTOMATIC CONTRAST ENHANCEMENT BY HISTOGRAM WARPING. In: Wojciechowski, K., Smolka, B., Palus, H., Kozera, R., Skarbek, W., Noakes, L. (eds) Computer Vision and Graphics. Computational Imaging and Vision, vol 32. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4179-9_42
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DOI: https://doi.org/10.1007/1-4020-4179-9_42
Publisher Name: Springer, Dordrecht
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