A novel approach to the selection of spatially invariant features for classification of hyperspectral images
2009
Conference Paper
ei
This paper presents a novel approach to feature selection for the classification of hyperspectral images. The proposed approach aims at selecting a subset of the original set of features that exhibits two main properties: i) high capability to discriminate among the considered classes, ii) high invariance in the spatial domain of the investigated scene. This approach results in a more robust classification system with improved generalization properties with respect to standard feature-selection methods. The feature selection is accomplished by defining a multi-objective criterion function made up of two terms: i) a term that measures the class separability, ii) a term that evaluates the spatial invariance of the selected features. In order to assess the spatial invariance of the feature subset we propose both a supervised method and a semisupervised method (which choice depends on the available reference data). The multi-objective problem is solved by an evolutionary algorithm that estimates the set of Pareto-optimal solutions. Experiments carried out on a hyperspectral image acquired by the Hyperion sensor on a complex area confirmed the effectiveness of the proposed approach.
Author(s): | Persello, C. and Bruzzone, L. |
Pages: | II-61-II-64 |
Year: | 2009 |
Month: | July |
Day: | 0 |
Publisher: | IEEE |
Department(s): | Empirical Inference |
Bibtex Type: | Conference Paper (inproceedings) |
DOI: | 10.1109/IGARSS.2009.5418001 |
Event Name: | IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2009) |
Event Place: | Cape Town, South Africa |
Address: | Piscataway, NJ, USA |
Digital: | 0 |
ISBN: | 978-1-4244-3394-0 |
Links: |
Web
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BibTex @inproceedings{PerselloB2009, title = {A novel approach to the selection of spatially invariant features for classification of hyperspectral images }, author = {Persello, C. and Bruzzone, L.}, pages = {II-61-II-64 }, publisher = {IEEE}, address = {Piscataway, NJ, USA}, month = jul, year = {2009}, doi = {10.1109/IGARSS.2009.5418001}, month_numeric = {7} } |