Mixed Noise Removal for Hyperspectral Images Based on Global Tensor Low-Rankness and Nonlocal SVD-Aided Group Sparsity
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3257851
Abstract: In hyperspectral images (HSIs), mixed noise (e.g., Gaussian noise, impulse noise, stripe noise, and deadlines) contamination is a common phenomenon that greatly reduces the visual quality of the image. In recent years, methods combining global… read more here.
Keywords: group sparsity; noise; tensor; low rankness ... See more keywords
Cooperated Spectral Low-Rankness Prior and Deep Spatial Prior for HSI Unsupervised Denoising
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3211471
Abstract: Model-driven methods and data-driven methods have been widely developed for hyperspectral image (HSI) denoising. However, there are pros and cons in both model-driven and data-driven methods. To address this issue, we develop a self-supervised HSI… read more here.
Keywords: rankness prior; deep spatial; hsi; low rankness ... See more keywords
Tensor Completion Using Bilayer Multimode Low-Rank Prior and Total Variation.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2023.3266841
Abstract: In this article, we propose a novel bilayer low-rankness measure and two models based on it to recover a low-rank (LR) tensor. The global low rankness of underlying tensor is first encoded by LR matrix… read more here.
Keywords: low rankness; rankness; low rank; tensor completion ... See more keywords
Guaranteed Tensor Recovery Fused Low-rankness and Smoothness
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.48550/arxiv.2302.02155
Abstract: Vast visual data like multi-spectral images and multi-frame videos are essentially with the tensor format. However, due to the defects of signal acquisition equipments, the practically collected tensor data are always with evident degradations like… read more here.
Keywords: tensor; tensor recovery; low rankness; tensor data ... See more keywords