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Image enhancement based on intuitionistic fuzzy sets theory

机译:基于直觉模糊集理论的图像增强

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摘要

Enhancement of images with weak edges faces great challenges in imaging applications. In this study, the authors propose a novel image enhancement approach based on intuitionistic fuzzy sets. The proposed method first divides an image into sub-object and sub-background areas, and then successively implements new fuzzification, hyperbolisation, and defuzzification operations on each area. In this way, an enhanced image is obtained, where the visual quality of region of interest (ROI) is significantly improved. Several types of images are utilised to validate the proposed method with respect to the enhancement performance. Experimental results demonstrate that the proposed algorithm not only works more stably for different types of images, but also has better enhancement performance, in comparison to conventional methods. This is a great merit of such design for discerning specific ROIs.
机译:具有弱边缘的图像的增强在成像应用中面临巨大挑战。在这项研究中,作者提出了一种基于直觉模糊集的新颖图像增强方法。所提出的方法首先将图像划分为子对象和子背景区域,然后在每个区域上依次执行新的模糊化,超bolgingization和去模糊化操作。以此方式,获得了增强的图像,其中感兴趣区域(ROI)的视觉质量得到了显着改善。关于增强性能,利用几种类型的图像来验证所提出的方法。实验结果表明,与传统方法相比,该算法不仅对于不同类型的图像更稳定,而且具有更好的增强性能。这种设计可以很好地识别特定的ROI。

著录项

  • 来源
    《Image Processing, IET》 |2016年第10期|701-709|共9页
  • 作者单位

    Wuhan Institute of Physics and Mathematics, People's Republic of China;

    Wuhan Institute of Physics and Mathematics, People's Republic of China;

    Wuhan Institute of Physics and Mathematics, People's Republic of China;

    Wuhan Institute of Physics and Mathematics, People's Republic of China;

    Wuhan Institute of Physics and Mathematics, People's Republic of China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    image enhancement; edge detection; fuzzy set theory;

    机译:图像增强;边缘检测;模糊集理论;

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