Vision transformers for single image dehazing
Image dehazing is a representative low-level vision task that estimates latent haze-free
images from hazy images. In recent years, convolutional neural network-based methods …
images from hazy images. In recent years, convolutional neural network-based methods …
A review of remote sensing image dehazing
J Liu, S Wang, X Wang, M Ju, D Zhang - Sensors, 2021 - mdpi.com
Remote sensing (RS) is one of the data collection technologies that help explore more earth
surface information. However, RS data captured by satellite are susceptible to particles …
surface information. However, RS data captured by satellite are susceptible to particles …
[HTML][HTML] Nationwide urban tree canopy mapping and coverage assessment in Brazil from high-resolution remote sensing images using deep learning
Urban tree canopy maps are essential for providing urban ecosystem services. The
relationship between urban trees and urban climate change, air pollution, urban noise …
relationship between urban trees and urban climate change, air pollution, urban noise …
Aerial image dehazing with attentive deformable transformers
A Kulkarni, S Murala - Proceedings of the IEEE/CVF Winter …, 2023 - openaccess.thecvf.com
Aerial imagery is widely utilized in visual data dependent applications such as military
surveillance, earthquake assessment, etc. For these applications, minute texture in the aerial …
surveillance, earthquake assessment, etc. For these applications, minute texture in the aerial …
Dehaze-AGGAN: Unpaired remote sensing image dehazing using enhanced attention-guide generative adversarial networks
Remote sensing image dehazing is of great scientific interest and application value in both
military and civil fields. In this article, we propose an enhanced attention-guide generative …
military and civil fields. In this article, we propose an enhanced attention-guide generative …
GIFM: An image restoration method with generalized image formation model for poor visible conditions
Recently, image restoration has attracted considerable attention from researchers, and
these methods generally restore degraded images based on the atmospheric scattering …
these methods generally restore degraded images based on the atmospheric scattering …
Encoder-free multi-axis physics-aware fusion network for remote sensing image dehazing
Y Wen, T Gao, J Zhang, Z Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Current methods for remote sensing image dehazing confront noteworthy computational
intricacies and yield suboptimal dehazed outputs, thereby circumscribing their pragmatic …
intricacies and yield suboptimal dehazed outputs, thereby circumscribing their pragmatic …
TMS-GAN: A twofold multi-scale generative adversarial network for single image dehazing
P Wang, H Zhu, H Huang, H Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In recent years, learning-based single image dehazing networks have been
comprehensively developed. However, performance improvement is limited due to domain …
comprehensively developed. However, performance improvement is limited due to domain …
[HTML][HTML] Remote sensing image gap filling based on spatial-spectral random forests
Remote sensing images play a significant role in global land cover monitoring. However,
due to the influence of cloud contamination, optical remote sensing images inevitably …
due to the influence of cloud contamination, optical remote sensing images inevitably …
Remote sensing image dehazing using adaptive region-based diffusion models
Y Huang, S Xiong - IEEE Geoscience and Remote Sensing …, 2023 - ieeexplore.ieee.org
Remote sensing (RS) dehazing is a long-standing topic, as the contrast and clarity of images
are seriously reduced in the severe environment. Recent learning-based ways achieve …
are seriously reduced in the severe environment. Recent learning-based ways achieve …