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A tutorial on applications of power watershed optimization to image processing

Danda, S and Challa, A and Sagar, BSD and Najman, L (2021) A tutorial on applications of power watershed optimization to image processing. In: European Physical Journal: Special Topics .

eur_phy_jou_230-10_2337-2361_2021.pdf - Published Version

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Official URL: https://doi.org/10.1140/epjs/s11734-021-00264-0


This tutorial review paper consolidates the existing applications of the power watershed (PW) optimization framework in the context of image processing. In the literature, it is known that PW framework when applied to some well-known graph-based image segmentation and filtering algorithms such as random walker, isoperimetric partitioning, ratio-cut clustering, multi-cut and shortest path filters yield faster yet consistent solutions. In this paper, the intuition behind the working of PW framework, i.e. exploitation of contrast invariance on image data is explained. The intuitions are illustrated with toy images and experiments on simulated astronomical images. This article is primarily aimed at researchers working on image segmentation and filtering problems in application areas such as astronomy where images typically have huge number of pixels. Classic graph-based cost minimization methods provide good results on images with small number of pixels but do not scale well for images with large number of pixels. The ideas from the article can be adapted to a large class of graph-based cost minimization methods to obtain scalable segmentation and filtering algorithms. © 2021, The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature.

Item Type: Journal Article
Publication: European Physical Journal: Special Topics
Publisher: Springer Science and Business Media Deutschland GmbH
Additional Information: The copyright for this article belongs to Authors
Department/Centre: Division of Electrical Sciences > Computer Science & Automation
Date Deposited: 03 Dec 2021 06:48
Last Modified: 03 Dec 2021 06:48
URI: http://eprints.iisc.ac.in/id/eprint/70099

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