An overview of SaT segmentation methodology and its applications in image processing

Cai, Xiaohao, Chan, Raymond and Zeng, Tieyong (2023) An overview of SaT segmentation methodology and its applications in image processing. In, Chen, Ke, Schönlieb, Carola-Bibiane, Tai, Xue-Cheng and Younes, Laurent (eds.) Handbook of mathematical models and algorithms in computer vision and imaging: mathematical imaging and vision. (Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging: Mathematical Imaging and Vision) Springer Cham, pp. 1385-1411. (doi:10.1007/978-3-030-98661-2_75).

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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Contributors

Author: Xiaohao Cai

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