Mb-taylorformer: Multi-branch efficient transformer expanded by taylor formula for image dehazing
In recent years, Transformer networks are beginning to replace pure convolutional neural
networks (CNNs) in the field of computer vision due to their global receptive field and …
networks (CNNs) in the field of computer vision due to their global receptive field and …
Learning an effective transformer for remote sensing satellite image dehazing
The existing remote sensing (RS) image dehazing methods based on deep learning have
sought help from the convolutional frameworks. Nevertheless, the inherent limitations of …
sought help from the convolutional frameworks. Nevertheless, the inherent limitations of …
AACNet: Asymmetric attention convolution network for hyperspectral image dehazing
Haze in hyperspectral images (HSIs) can lead to crosstalk between multiple bands, resulting
in errors that can be amplified and transmitted during data processing. As a consequence …
in errors that can be amplified and transmitted during data processing. As a consequence …
Depth Information Assisted Collaborative Mutual Promotion Network for Single Image Dehazing
Recovering a clear image from a single hazy image is an open inverse problem. Although
significant research progress has been made most existing methods ignore the effect that …
significant research progress has been made most existing methods ignore the effect that …
PhDnet: A novel physic-aware dehazing network for remote sensing images
Remote sensing haze removal is a popular computational imaging technique that directly
obtains clear remote sensing data from hazy remote sensing images. Apart from prior-based …
obtains clear remote sensing data from hazy remote sensing images. Apart from prior-based …
Hierarchical slice interaction and multi-layer cooperative decoding networks for remote sensing image dehazing
M Yu, SY Xu, H Sun, YL Zheng, W Yang - Image and Vision Computing, 2024 - Elsevier
Recently, U-shaped neural networks have gained widespread application in remote sensing
image dehazing and achieved promising performance. However, most of the existing U …
image dehazing and achieved promising performance. However, most of the existing U …
Visual Attention and ODE-inspired Fusion Network for image dehazing
S Yin, X Yang, R Lu, Z Deng, YH Yang - Engineering Applications of …, 2024 - Elsevier
Image dehazing is an improtant image pre-processing step for many computer vision tasks
with many proposed methods using convolutional neural networks. Ordinary Differential …
with many proposed methods using convolutional neural networks. Ordinary Differential …
Illumination controllable dehazing network based on unsupervised retinex embedding
On the one hand, the dehazing task is an ill-posedness problem, which means that no
unique solution exists. On the other hand, the dehazing task should take into account the …
unique solution exists. On the other hand, the dehazing task should take into account the …
MACGAN: an all-in-one image restoration under adverse conditions using multidomain attention-based conditional GAN
Various vision-based tasks suffer from inaccurate navigation and poor performance due to
inevitable problems, such as adverse weather conditions like haze, fog, rain, snow, and …
inevitable problems, such as adverse weather conditions like haze, fog, rain, snow, and …
RSDehamba: Lightweight Vision Mamba for Remote Sensing Satellite Image Dehazing
Remote sensing image dehazing (RSID) aims to remove nonuniform and physically
irregular haze factors for high-quality image restoration. The emergence of CNNs and …
irregular haze factors for high-quality image restoration. The emergence of CNNs and …