3 citations · 7 across the 7 of their papers we have counts for
7 papers
Hyperspectral Image Spectral-Spatial Feature Extraction via Tensor Principal Component Analysis
Yuemei Ren, Liang Liao, Stephen John Maybank +2
This paper addresses the challenge of spectral-spatial feature extraction for hyperspectral image classification by introducing a novel tensor-based framework. The proposed approac…
Color Image Recovery Using Generalized Matrix Completion over Higher-Order Finite Dimensional Algebra
Liang Liao, Zhuang Guo, Qi Gao +4
To improve the accuracy of color image completion with missing entries, we present a recovery method based on generalized higher-order scalars. We extend the traditional second-ord…
Approximation of Images via Generalized Higher Order Singular Value Decomposition over Finite-dimensional Commutative Semisimple Algebra
Liang Liao, Sen Lin, Lun Li +6
Low-rank approximation of images via singular value decomposition is well-received in the era of big data. However, singular value decomposition (SVD) is only for order-two data, i…
Generalized Image Reconstruction over T-Algebra
Liang Liao, Xuechun Zhang, Xinqiang Wang +2
Principal Component Analysis (PCA) is well known for its capability of dimension reduction and data compression. However, when using PCA for compressing/reconstructing images, imag…
General Data Analytics with Applications to Visual Information Analysis: A Provable Backward-Compatible Semisimple Paradigm over T-Algebra
Liang Liao, Stephen John Maybank
We consider a novel backward-compatible paradigm of general data analytics over a recently-reported semisimple algebra (called t-algebra). We study the abstract algebraic framework…
Intrinsic Dimension Estimation via Nearest Constrained Subspace Classifier
Liang Liao, Stephen John Maybank
We consider the problems of classification and intrinsic dimension estimation on image data. A new subspace based classifier is proposed for supervised classification or intrinsic…
Generalized Visual Information Analysis via Tensorial Algebra
Liang Liao, Stephen John Maybank
Higher order data is modeled using matrices whose entries are numerical arrays of a fixed size. These arrays, called t-scalars, form a commutative ring under the convolution produc…