An introduction to digital image processing
An introduction to digital image processing
A methodology for the development and the support of massively parallel programs
Future Generation Computer Systems - Special triple issue: parallel and distributed workstation systems
Introduction to parallel computing: design and analysis of algorithms
Introduction to parallel computing: design and analysis of algorithms
Environments and tools for parallel scientific computing
Environments and tools for parallel scientific computing
Digital image processing algorithms
Digital image processing algorithms
PIKS foundation C programmer's guide
PIKS foundation C programmer's guide
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
Digital image processing
Practical parallel programming
Practical parallel programming
Pattern classification: a unified view of statistical and neural approaches
Pattern classification: a unified view of statistical and neural approaches
Digital Image Warping
Evaluating the DIPORSI Framework: Distributed Processing of Remotely Sensed Imagery
Proceedings of the 8th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
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This paper presents the parallel image processing package MMIPPS (multitemporal and multispectral image processing on parallel systems) developed in a project of the partly EC funded Parallel Computing Initiative II. Image classification and rectification are computational intensive image processing routines, capable to benefit from parallelization. This paper reports the development approach and the performance results achieved on standard networks of PC's and workstations. It is shown, that the MMIPPS package provides the expected results and speed-ups for the selected image processing tasks, leading to shorter completion times and a more efficient service.