Connected morphological attribute filters on distributed memory parallel machines

Abstract

We present a new algorithm for attribute filtering of extremely large images, using a forest of modified max-trees, suitable for distributed memory parallel machines. First, max-trees of tiles of the image are computed, after which messages are exchanged to modify the topology of the trees and update attribute data, such that filtering the modified trees on each tile gives exactly the same results as filtering a regular max-tree of the entire image. On a cluster, a speed-up of up to 53× is obtained on 64, and up to 100× on 128 single CPU nodes. On a shared memory machine a peak speed-up of 50× on 64 cores was obtained.