Name
Abstract | ||
|---|---|---|
Multivariate mathematical morphology (MMM) aims to extend the mathematical morphology from gray scale images to images whose pixels are high-dimensional vectors, such as remote sensing hyperspectral images and functional magnetic resonance images (fMRIs). Defining an ordering over the multidimensional image data space is a fundamental issue MMM, to ensure that ensuing morphological operators and f... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TNNLS.2015.2461451 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | Field | DocType |
Lattices,Hyperspectral imaging,Support vector machines,Image segmentation,Training,Morphology | Chebyshev distance,Computer science,Image segmentation,Artificial intelligence,Data classification,Grayscale,Computer vision,Pattern recognition,Segmentation,Mathematical morphology,Support vector machine,Hyperspectral imaging,Machine learning | Journal |
Volume | Issue | ISSN |
27 | 9 | 2162-237X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manuel Graña Romay | 1 | 411 | 157.98 |
| Darya Chyzhyk | 2 | 137 | 10.82 |