https://doi.org/10.1140/epjs/s11734-021-00264-0
Review
A tutorial on applications of power watershed optimization to image processing
1
Computer Science and Information Systems, APPCAIR, BITS-Pilani K K Birla Goa Campus, Sancoale, Goa, India
2
Computer Science and Automation, Indian Institute of Science, Bengaluru, India
3
Systems Science and Informatics Unit, Indian Statistical Institute, Bengaluru, India
4
Université Gustave Eiffel, LIGM, Equipe A3SI, ESIEE, Paris, France
Received:
6
January
2021
Accepted:
3
August
2021
Published online:
2
September
2021
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.
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2021
