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Adaptive Semi-blind Immune Algorithm for Image Enhancement

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Abstract

The principle and steps of semi-blind immune algorithm are studied, and an adaptive image enhancement method using semi-blind immune algorithm is proposed. The non-linear transform of gray level is an efficient way of image enhancement. In classical image enhancement methods, the specific transform function is determined according to the gray level distribution in the processed image. Tubbs proposed a normalized incomplete Beta function to represent the four kinds of non-linear transform functions most commonly used. But how to adaptively define the coefficients of the Beta function is still a problem. We adopt an adaptive semi-blind immune algorithm that explicitly searches the optimal or suboptimal coefficients more quickly. Compared with the common image adjustment approach, our method is more efficient and powerful.

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Authors and Affiliations

  1. Department of Radio Engineering, Southeast University, Nanjing, 210096, P. R. China

    Zhenya He, Qinzhen Xu, Chengjian Wei, Wenjiang Pei & Yunnong Zhang

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  1. Zhenya He
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  2. Qinzhen Xu
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  3. Chengjian Wei
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  4. Wenjiang Pei
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  5. Yunnong Zhang
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He, Z., Xu, Q., Wei, C. et al. Adaptive Semi-blind Immune Algorithm for Image Enhancement. Multidim Syst Sign Process 16, 107–118 (2005). https://doi.org/10.1007/s11045-004-4740-5

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  • DOI: https://doi.org/10.1007/s11045-004-4740-5

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