Cargando…
Deep Unsupervised Fusion Learning for Hyperspectral Image Super Resolution
Hyperspectral image (HSI) super-resolution (SR) is a challenging task due to its ill-posed nature, and has attracted extensive attention by the research community. Previous methods concentrated on leveraging various hand-crafted image priors of a latent high-resolution hyperspectral (HR-HS) image to...
Autores principales: | Liu, Zhe, Zheng, Yinqiang, Han, Xian-Hua |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8036288/ https://www.ncbi.nlm.nih.gov/pubmed/33800532 http://dx.doi.org/10.3390/s21072348 |
Ejemplares similares
-
Spectral Representation via Data-Guided Sparsity for Hyperspectral Image Super-Resolution †
por: Han, Xian-Hua, et al.
Publicado: (2019) -
Unsupervised super-resolution reconstruction of hyperspectral histology images for whole-slide imaging
por: Ma, Ling, et al.
Publicado: (2022) -
Unsupervised super-resolution reconstruction of hyperspectral histology images for whole-slide imaging (Errata)
por: Ma, Ling, et al.
Publicado: (2022) -
An Unsupervised Deep Hyperspectral Anomaly Detector
por: Ma, Ning, et al.
Publicado: (2018) -
Restoration and Calibration of Tilting Hyperspectral Super-Resolution Image
por: Zhang, Xizhen, et al.
Publicado: (2020)