| Paper title: |
Segmentation Method for Hyperspectral Images using Tensor Decomposition |
| DOI: | https://doi.org/10.4316/JACSM.202002001 |
| Published in: | Issue 2, (Vol. 14) / 2020 |
| Publishing date: | 2020-07-14 |
| Pages: | 9-14 |
| Author(s): | BILIUS Laura-Bianca, PENTIUC Stefan-Gheorghe |
| Abstract. | Hyperspectral Images are a challenging area because of big dimensions, spatial and spectral low resolution. This paper aims to propose a method to provide an accurate and quick classification based on tensor decomposition and map segmentation. For reducing the dimensions of hyperspectral data and obtain the abundances map we used Parafac decomposition. For determining the segmentation abundances map representing the segmentation abundances matrix, an algorithm based on the Dynamic Clustering Algorithm [1] principle was used having as input the estimated abundances matrix. The segmentation abundances map was visually labeled using the true color image. |
| Keywords: | Tensor Decomposition, Parafac, Segmentation, Hyperspectral Images |
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