Recursive implementation of the Gaussian filter
Signal Processing
A multi-threaded streaming pipeline architecture for large structured data sets
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Processing of volumetric data by slice- and process-based streaming
AFRIGRAPH '07 Proceedings of the 5th international conference on Computer graphics, virtual reality, visualisation and interaction in Africa
Parallel Volume Image Segmentation with Watershed Transformation
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Advances on watershed processing on GPU architecture
ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
The Watershed Transform: Definitions, Algorithms and Parallelization Strategies
Fundamenta Informaticae
| Hi-index | 0.00 |
Since its introduction the watershed transform became a popular method for volume data segmentation. A range of various algorithms for its computation were developed, including parallel algorithms for computation on different architectures. Recently also algorithms for consumer graphical accelerators were developed. Neither of these, however, are able to process data larger than the available memory as the whole data has to be present in the memory of the device. In this paper we present two versions of a streamed multi-pass algorithm for watershed computation on a GPU. As the slice-based streaming approach is used both variants are capable of processing data exceeding the size of the available graphics accelerator memory.