Abstract
Many conventional and well-known image enhancement methods suffer from a tendency to increase the visibility of noise when they enhance the underlying details. In this paper, a new kind of image analysis tool — ridgelet frame is introduced into the arena of image enhancement. We design an enhancement operator with the advantages that it not only enhance image details but also avoid the amplification of noise within source image. Different from those published previously, our operator has more parameters, which results in more flexibility for different category images. Based on an objective criterion, we search the optimal parameters for each special image using Immune Clone Algorithm (ICA). Experimental results show the superiority of our method in terms of both subjective and objective evaluation.
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Shan, T., Wang, S., Zhang, X., Jiao, L. (2005). Automatic Image Enhancement Driven by Evolution Based on Ridgelet Frame in the Presence of Noise. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2005. Lecture Notes in Computer Science, vol 3449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32003-6_31
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DOI: https://doi.org/10.1007/978-3-540-32003-6_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25396-9
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