Hierarchical clustering algorithms for segmentation of multispectral images
| Autor: | I. A. Pestunov, S. A. Rylov, V. B. Berikov |
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| Rok vydání: | 2015 |
| Předmět: |
business.industry
Computer science Multispectral image Pattern recognition Condensed Matter Physics Grid Hierarchical clustering ComputingMethodologies_PATTERNRECOGNITION Computer Science::Computer Vision and Pattern Recognition Metric (mathematics) Segmentation Computer vision Artificial intelligence Electrical and Electronic Engineering Photonics business Instrumentation Algorithm |
| Zdroj: | Optoelectronics, Instrumentation and Data Processing. 51:329-338 |
| ISSN: | 1934-7944 8756-6990 |
| DOI: | 10.3103/s8756699015040020 |
| Popis: | Computationally efficient HCA and HECA hierarchical clustering algorithms for segmentation of multispectral images have been developed using the grid and ensemble approaches. A special metric is proposed to identify embedded clusters even in the presence of overlapping. The efficiency of the algorithms has been confirmed by the results of experimental studies using model and real data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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