Abstract
This paper presents an overview on the advances of watershed processing algorithms executed on GPU architecture. The programming model, memory hierarchy and restrictions are discussed, and its influence on image processing algorithms detailed. The recently proposed algorithms of watershed transform for GPU computation are examined and briefly described. Its implementations are analyzed in depth and evaluations are made to compare them both on the GPU, against a CPU version and on two different GPU cards. © 2011 Springer-Verlag.
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CITATION STYLE
Körbes, A., Vitor, G. B., De Alencar Lotufo, R., & Ferreira, J. V. (2011). Advances on watershed processing on GPU architecture. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6671 LNCS, pp. 260–271). https://doi.org/10.1007/978-3-642-21569-8_23
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