Hybrid noise removal in hyperspectral imagery with a spatial–spectral gradient network
The existence of hybrid noise in hyperspectral images (HSIs) severely degrades the data
quality, reduces the interpretation accuracy of HSIs, and restricts the subsequent HSI …
quality, reduces the interpretation accuracy of HSIs, and restricts the subsequent HSI …
[HTML][HTML] A directional global sparse model for single image rain removal
Rain removal from a single image is an important issue in the fields of outdoor vision. Rain,
a kind of bad weather that is often seen, usually causes complex local intensity changes in …
a kind of bad weather that is often seen, usually causes complex local intensity changes in …
Joint analysis and weighted synthesis sparsity priors for simultaneous denoising and destri** optical remote sensing images
Z Huang, Y Zhang, Q Li, X Li, T Zhang… - … on Geoscience and …, 2020 - ieeexplore.ieee.org
Stripe and random noise are two different degradation phenomena that commonly coexist in
optical remote sensing images, and they are often modeled as inverse problems. In model …
optical remote sensing images, and they are often modeled as inverse problems. In model …
[HTML][HTML] Remote sensing images destri** using unidirectional hybrid total variation and nonconvex low-rank regularization
In this paper, we propose a novel model for remote sensing images destri**, which
includes the Schatten 1∕ 2-norm and the unidirectional first-order and high-order total …
includes the Schatten 1∕ 2-norm and the unidirectional first-order and high-order total …
Tensor cascaded-rank minimization in subspace: A unified regime for hyperspectral image low-level vision
Low-rank tensor representation philosophy has enjoyed a reputation in many hyperspectral
image (HSI) low-level vision applications, but previous studies often failed to …
image (HSI) low-level vision applications, but previous studies often failed to …