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首页> 外文期刊>Signal, Image and Video Processing >Switching-based clustering algorithms for segmentation of low-level salt-and-pepper noise–corrupted images - Springer
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Switching-based clustering algorithms for segmentation of low-level salt-and-pepper noise–corrupted images - Springer

机译：基于开关的聚类算法，用于对低级椒盐噪声损坏的图像进行分割-Springer

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摘要

This paper presents new clustering-based segmentation algorithms. The proposed switching-based clustering algorithms can minimize salt-and-pepper noise during segmentation without degrading the images’ fine details. The proposed algorithms incorporate the salt-and-pepper noise detection stage into the clustering algorithm, producing an adaptive technique specifically for segmentation of noisy images. Experimental results show that the proposed switching-based clustering algorithms produce better segmentation with fewer noise effects than conventional clustering algorithms. Quantitative and qualitative analyses show positive results for the proposed switching-based clustering algorithms, which consistently outperform conventional clustering algorithms in segmenting up to 50 % of salt-and-pepper noise density. Thus, these switching-based clustering algorithms can be used as pre- or post-processing task (i.e., segmenting images into regions of interest) in electronic products such as televisions and monitors.
机译：本文提出了新的基于聚类的分割算法。提出的基于开关的聚类算法可以将分割过程中的椒盐噪声降至最低，而不会降低图像的精细细节。所提出的算法将椒盐噪声检测阶段纳入了聚类算法中，从而产生了一种专门用于噪声图像分割的自适应技术。实验结果表明，与传统的聚类算法相比，基于交换的聚类算法能够产生更好的分割效果，并且具有较少的噪声影响。定量和定性分析显示了所提出的基于开关的聚类算法的积极结果，该算法在分割高达50％的盐和胡椒噪声密度方面始终优于常规聚类算法。因此，这些基于切换的聚类算法可以用作诸如电视机和监视器之类的电子产品中的预处理或后处理任务（即，将图像分割成感兴趣的区域）。

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  • 来源
    《Signal, Image and Video Processing》 |2015年第2期|387-398|共12页
  • 作者

    Siti Noraini Sulaiman; Nor Ashidi Mat Isa; Intan Aidha Yusoff; Fadzil Ahmad;

  • 作者单位

    1.Imaging and Intelligent System Research Team (ISRT) School of Electrical and Electronics Engineering Universiti Sains Malaysia Engineering Campus 14300 Nibong Tebal Penang Malaysia 2.Faculty of Electrical Engineering Universiti Teknologi MARA (UiTM) 13500 Permatang Pauh Penang Malaysia;

    1.Imaging and Intelligent System Research Team (ISRT) School of Electrical and Electronics Engineering Universiti Sains Malaysia Engineering Campus 14300 Nibong Tebal Penang Malaysia;

    1.Imaging and Intelligent System Research Team (ISRT) School of Electrical and Electronics Engineering Universiti Sains Malaysia Engineering Campus 14300 Nibong Tebal Penang Malaysia;

    2.Faculty of Electrical Engineering Universiti Teknologi MARA (UiTM) 13500 Permatang Pauh Penang Malaysia;

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

    Clustering; Image segmentation; Salt-and-pepper noise; Image processing;

    机译：聚类;图像分割;椒盐噪声;图像处理;

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