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Study on medical image enhancement based on IFOA improved grayscale image adaptive enhancement

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Abstract

In allusion to deficiencies of traditional medical image enhancement algorithms such as poor applicability, large calculated amount and manual parameter setting and local optimum problem of FOA algorithm, this paper introduces chaos theory into FOA algorithm for improvement based on good global optimum searching performance of fruit fly optimization algorithm and optimizes normalized incomplete Beta function with IFOA for medical image enhancement. The experimental result shows that the improved FOA algorithm can highlight image features effectively, improve visual effect of images and efficiency, avoid invariability of manual parameter adjustment, configure best parameters of normalized incomplete Beta function automatically while guaranteeing best image quality and achieve adaptive enhancement of medical images.

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Authors and Affiliations

  1. Affiliated Hospital of North China University of Science and Technology, Tangshan, 063000, People’s Republic of China

    Yuxi Xie, Yonggui He, Aibin Cheng & Junwei Zhang

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  1. Yuxi Xie
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  2. Yonggui He
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  3. Aibin Cheng
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  4. Junwei Zhang
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Correspondence to Yuxi Xie.

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Xie, Y., He, Y., Cheng, A. et al. Study on medical image enhancement based on IFOA improved grayscale image adaptive enhancement. Multimed Tools Appl 75, 14367–14379 (2016). https://doi.org/10.1007/s11042-016-3358-6

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  • DOI: https://doi.org/10.1007/s11042-016-3358-6

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