Manifold regularization nonnegative triple decomposition of tensor sets for image compression and representation

DOI10.1007/s10957-022-02001-6zbMath1484.65032OpenAlexW4206951073MaRDI QIDQ2116615

Chaoqian Li, Fengsheng Wu, Yao-Tang Li

Publication date: 18 March 2022

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-022-02001-6

zbMATH Keywords

image compressionlow-rank approximationmanifold regularizationnonnegative triple decomposition

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Iterative numerical methods for linear systems (65F10) Algorithms for approximation of functions (65D15) Multilinear algebra, tensor calculus (15A69) Numerical methods for low-rank matrix approximation; matrix compression (65F55)

Cites Work

• Tensor Decompositions and Applications
• Tensor-Train Decomposition
• On the Best Rank-1 and Rank-(R₁ ,R₂ ,. . .,R_N) Approximation of Higher-Order Tensors
• Third-Order Tensors as Operators on Matrices: A Theoretical and Computational Framework with Applications in Imaging
• Triple Decomposition and Tensor Recovery of Third Order Tensors

This page was built for publication: Manifold regularization nonnegative triple decomposition of tensor sets for image compression and representation