Incremental quaternion singular value decomposition and its application for low rank quaternion matrix completion
DOI10.1007/S40314-024-02874-5MaRDI QIDQ6590214
Publication date: 21 August 2024
Published in: Computational and Applied Mathematics (Search for Journal in Brave)
incremental quaternion singular value decompositionlow rank quaternion matrix completionproximal linearized minimization algorithm
Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Eigenvalues, singular values, and eigenvectors (15A18) Multilinear algebra, tensor calculus (15A69)
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Tensor-Train Decomposition
- A fast structure-preserving method for computing the singular value decomposition of quaternion matrices
- Proximal alternating linearized minimization for nonconvex and nonsmooth problems
- A quaternion framework for color image smoothing and segmentation
- Weighted nuclear norm minimization and its applications to low level vision
- Singular value decomposition of third order quaternion tensors
- Lanczos method for large-scale quaternion singular value decomposition
- Robust low-rank tensor recovery: models and algorithms
- A nonconvex approach to low-rank matrix completion using convex optimization
- A Singular Value Thresholding Algorithm for Matrix Completion
- Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
- First-Order Methods in Optimization
- Quaternion-Michelson Descriptor for Color Image Classification
- Low-Rank Quaternion Approximation for Color Image Processing
- Robust quaternion matrix completion with applications to image inpainting
- Restricted $p$-Isometry Properties of Nonconvex Matrix Recovery
- Quaternions and matrices of quaternions
- Low-rank matrix recovery problem minimizing a new ratio of two norms approximating the rank function then using an ADMM-type solver with applications
- Efficient low-rank quaternion matrix completion under the learnable transforms for color image recovery
- Approximation strategy based on the T-product for third-order quaternion tensors with application to color video compression
- Tensor Robust Principal Component Analysis via Tensor Fibered Rank and \({\boldsymbol{{l_p}}}\) Minimization
- An iterative algorithm for low-rank tensor completion problem with sparse noise and missing values.
This page was built for publication: Incremental quaternion singular value decomposition and its application for low rank quaternion matrix completion
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6590214)