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An Overview of SaT Segmentation Methodology and Its Applications in Image Processing

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Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging

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Abstract

As a fundamental and challenging task in many subjects such as image processing and computer vision, image segmentation is of great importance but is constantly challenging to deliver, particularly, when the given images or data are corrupted by different types of degradations like noise, information loss, and/or blur. In this article, we introduce a segmentation methodology – smoothing and thresholding (SaT) – which can provide a flexible way of producing superior segmentation results with fast and reliable numerical implementations. A bunch of methods based on this methodology are to be presented, including many applications with different types of degraded images in image processing.

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Acknowledgements

Supported in part by HKRGC Grants No. CUHK14306316, CUHK14301718, CityU11301120, CityU Grant 9380101, CRF Grant C1007-15G, AoE/M-05/12.

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Authors and Affiliations

  1. School of Electronics and Computer Science, University of Southampton, Southampton, UK

    Xiaohao Cai

  2. Department of Mathematics, College of Science, City University of Hong Kong, Kowloon Tong, Hong Kong, China

    Raymond Chan

  3. Department of Mathematics, The Chinese University of Hong Kong, Shatin, Hong Kong, China

    Tieyong Zeng

Authors
  1. Xiaohao Cai
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  2. Raymond Chan
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  3. Tieyong Zeng
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Corresponding authors

Correspondence to Xiaohao Cai , Raymond Chan or Tieyong Zeng .

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Editors and Affiliations

  1. Department of Mathematical Sciences, The University of Liverpool, Liverpool, UK

    Ke Chen

  2. Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK

    Carola-Bibiane Schönlieb

  3. Hong Kong Center for Cerebrocardiovascular Health Engineering (COCHE), Shatin, Hong Kong

    Xue-Cheng Tai

  4. Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA

    Laurent Younes

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Cai, X., Chan, R., Zeng, T. (2023). An Overview of SaT Segmentation Methodology and Its Applications in Image Processing. In: Chen, K., Schönlieb, CB., Tai, XC., Younes, L. (eds) Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging. Springer, Cham. https://doi.org/10.1007/978-3-030-98661-2_75

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