[IPOL announce] new article: A Parallel, O(n) Algorithm for an Unbiased, Thin Watershed
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Sat Apr 9 00:02:02 CEST 2022
A new article is available in IPOL: https://www.ipol.im/pub/art/2022/215/
Théodore Chabardès, Petr Dokládal, Matthieu Faessel, and Michel Bilodeau,
A Parallel, O(n) Algorithm for an Unbiased, Thin Watershed,
Image Processing On Line, 12 (2022), pp. 50–71.
https://doi.org/10.5201/ipol.2022.215
Abstract
The watershed transform is a powerful tool for morphological
segmentation. Most common implementations of this method involve a
strict hierarchy on gray tones in processing the pixels composing an
image. This hierarchical dependency complexifies the efficient use of
modern computational architectures. This paper introduces a new way of
computing the watershed transform that alleviates the sequential nature
of hierarchical queue propagation. It is shown that this method can
directly relate to the hierarchical flooding. Simultaneous and
disorderly growth can now be used to maximize performances on modern
architectures. Higher speed is reached, bigger data volume can be
processed. Experimental results show increased performances regarding
execution speed and memory consumption.
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