- Tytuł:
- Large-scale hyperspectral image compression via sparse representations based on online learning
- Autorzy:
-
Ülkü, İ.
Kizgut, E. - Powiązania:
- https://bibliotekanauki.pl/articles/331241.pdf
- Data publikacji:
- 2018
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
hyperspectral imaging
compression algorithm
dictionary learning
sparse coding
obrazowanie wielospektralne
algorytm kompresji
nauczanie online
kodowanie rzadkie - Opis:
- In this study, proximity based optimization algorithms are used for lossy compression of hyperspectral images that are inherently large scale. This is the first time that such proximity based optimization algorithms are implemented with an online dictionary learning method. Compression performances are compared with the one obtained by various sparse representation algorithms. As a result, proximity based optimization algorithms are listed among the three best ones in terms of compression performance values for all hyperspectral images. Additionally, the applicability of anomaly detection is tested on the reconstructed images.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2018, 28, 1; 197-207
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł