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Color image sharpening based on local color statistics

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Abstract

This paper presents an effective color image sharpening method, which is based on local color statistics. First, the variance of a set of color samples is measured by a scalar that is computed based on the sum of distances of color vectors, whereas other studies usually treat a color variance as a 3D vector. This is because what a variance expresses is the degree of the deviation of the image (vector) signal from its mean, indicating that describing this degree of deviation by a scalar is reasonable. Then, the local scalar variance and mean vector are combined together to measure the change of color image signal from a pixel to its neighboring ones, and the polarity of the change is determined by the change of luminance. Finally, based on the measure of the change, an effective sharpening operator is developed. Experimental results show that the proposed method excellently sharpens different kinds of color images and at the same time preserves image chromaticity well, and outperforms other typical sharpening techniques in both objective assessment and visual evaluation.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (61370181 and 61370179).

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Authors and Affiliations

  1. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China

    Lianghai Jin, Zhiliang Zhu & Enmin Song

  2. School of Software Engineering, Huazhong University of Science and Technology, Wuhan, China

    Min Jin

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  1. Lianghai Jin
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  2. Min Jin
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  3. Zhiliang Zhu
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  4. Enmin Song
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Correspondence to Min Jin.

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Jin, L., Jin, M., Zhu, Z. et al. Color image sharpening based on local color statistics. Multidim Syst Sign Process 29, 1819–1837 (2018). https://doi.org/10.1007/s11045-017-0532-6

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  • DOI: https://doi.org/10.1007/s11045-017-0532-6

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