Geometrical Aspects of Correlation-Extreme Methods for Object Recognition and HSI Compression
| Autor: | L. R. Lebedev |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry Cognitive neuroscience of visual object recognition Hyperspectral imaging 020206 networking & telecommunications Pattern recognition 02 engineering and technology Correlation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence Invariant (mathematics) business Signature recognition |
| Zdroj: | 2020 International Conference on Information Technology and Nanotechnology (ITNT). |
| Popis: | This paper presents the results of the studies of the correlation-extreme methods for signature recognition and methods for compression of hyperspectral images (HSI) with controlled losses depending on the templates selection technique, on the threshold value, on the type of threshold used and on the selected type of invariant transformation. Recommendations are formulated for the selection of the said parameters in order to more effectively form a set of templates. Experiments have been carried out on real HSI fragments. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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