Parallel Processing Implementations of a Contextual Classifier for Multispectral Remote Sensing Data
LARS Tech Report Number
060380
Abstract
Contextual classifiers are being developed as a method to exploit the spatial/spectral context of a pixel to achieve accurate classification. Classification algorithms such as the contextual classifier typically require large amounts of computation time. One way to reduce the execution time of these tasks is through the use of parallelism. The applicability of the CDC Flexible Processor system and of a proposed multimicroprocessor system (PASM) for implementing contextual classifiers is examined.
Date of this Version
January 1980
COinS