Hyperspectral image denoising using constraint smooth rank approximation and weighted enhance 3DTV
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Hyperspectral image denoising using constraint smooth rank approximation and weighted enhance 3DTV
Authors
Keywords
-
Journal
DISPLAYS
Volume 74, Issue -, Pages 102197
Publisher
Elsevier BV
Online
2022-03-24
DOI
10.1016/j.displa.2022.102197
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Local low-rank matrix recovery for hyperspectral image denoising with ℓ0 gradient constraint
- (2020) Yanhong Yang et al. PATTERN RECOGNITION LETTERS
- Joint Analysis and Weighted Synthesis Sparsity Priors for Simultaneous Denoising and Destriping Optical Remote Sensing Images
- (2020) Zhenghua Huang et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Application of hyperspectral technology in detection of agricultural products and food: A Review
- (2020) Min Zhu et al. Food Science & Nutrition
- Double-Factor-Regularized Low-Rank Tensor Factorization for Mixed Noise Removal in Hyperspectral Image
- (2020) Yu-Bang Zheng et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Color image multiplicative noise and blur removal by saturation-value total variation
- (2020) Wei Wang et al. APPLIED MATHEMATICAL MODELLING
- A Novel Rank Approximation Method for Mixture Noise Removal of Hyperspectral Images
- (2019) Hailiang Ye et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Hyperspectral image restoration by subspace representation with low-rank constraint and spatial-spectral total variation
- (2019) Jun Ye et al. IET Image Processing
- Mixed Noise Removal in Hyperspectral Image via Low-Fibered-Rank Regularization
- (2019) Yu-Bang Zheng et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Hyperspectral Image Restoration Using Weighted Group Sparsity-Regularized Low-Rank Tensor Decomposition
- (2019) Yong Chen et al. IEEE Transactions on Cybernetics
- Hyperspectral Image Restoration Via Total Variation Regularized Low-Rank Tensor Decomposition
- (2018) Yao Wang et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Fast Superpixel Based Subspace Low Rank Learning Method for Hyperspectral Denoising
- (2018) Le Sun et al. IEEE Access
- Hyperspectral Image Restoration Using Low-Rank Tensor Recovery
- (2017) Haiyan Fan et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Denoising of Hyperspectral Images Using Nonconvex Low Rank Matrix Approximation
- (2017) Yongyong Chen et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Image compressed sensing based on non-convex low-rank approximation
- (2017) Yan Zhang et al. MULTIMEDIA TOOLS AND APPLICATIONS
- Total-Variation-Regularized Low-Rank Matrix Factorization for Hyperspectral Image Restoration
- (2016) Wei He et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Hyperspectral Image Restoration via Iteratively Regularized Weighted Schatten $p$ -Norm Minimization
- (2016) Yuan Xie et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Anisotropic Spectral-Spatial Total Variation Model for Multispectral Remote Sensing Image Destriping
- (2015) Yi Chang et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Application of hyperspectral remote sensing to cyanobacterial blooms in inland waters
- (2015) Raphael M. Kudela et al. REMOTE SENSING OF ENVIRONMENT
- Hyperspectral Image Restoration Using Low-Rank Matrix Recovery
- (2013) Hongyan Zhang et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Robust principal component analysis?
- (2011) Emmanuel J. Candès et al. JOURNAL OF THE ACM
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now