The watershed transformation is a common step in dif-
ferent image processing tasks. With the fast development
of general-purpose computing on GPUs, a number of paral-
lel watershed algorithms have been introduced for that setup.
We propose two novel parallel watershed algorithms: one in-
tended for relatively larger images and another for smaller
images. Our algorithms are based on the combination of the
parallel path reduction technique, introduced in our previous
paper on the topic, and the parallel version of the Union–Find
algorithm. We show through multiple experiments, both in
2D and 3D, that our algorithms achieve unmatched execution
times. On a typical gaming GPU, our algorithm processes an 800 megavoxel image in around 2.5 seconds.
