Cargando…
Recovering Depth from Still Images for Underwater Dehazing Using Deep Learning
Estimating depth from a single image is a challenging problem, but it is also interesting due to the large amount of applications, such as underwater image dehazing. In this paper, a new perspective is provided; by taking advantage of the underwater haze that may provide a strong cue to the depth of...
Autores principales: | Pérez, Javier, Bryson, Mitch, Williams, Stefan B., Sanz, Pedro J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472610/ https://www.ncbi.nlm.nih.gov/pubmed/32824156 http://dx.doi.org/10.3390/s20164580 |
Ejemplares similares
-
Impact of Dehazing on Underwater Marker Detection for Augmented Reality
por: Žuži, Marek, et al.
Publicado: (2018) -
Image Dehazing Using LiDAR Generated Grayscale Depth Prior
por: Chung, Won Young, et al.
Publicado: (2022) -
Dehazing in hyperspectral images: the GRANHHADA database
por: Carvelo, Sol Fernández, et al.
Publicado: (2023) -
Deep guided transformer dehazing network
por: Zhang, Shengdong, et al.
Publicado: (2023) -
Nighttime Image Dehazing by Render
por: Jin, Zheyan, et al.
Publicado: (2023)