Hierarchical Alternating Least Squares Methods for Quaternion Nonnegative Matrix Factorizations

Fuente: arXiv
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Autor principal: Pan, Junjun
Formato: Preprint
Publicado: 2024
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author Pan, Junjun
author_facet Pan, Junjun
contents In this report, we discuss a simple model for RGB color and polarization images under a unified framework of quaternion nonnegative matrix factorization (QNMF) and present a hierarchical nonnegative least squares method to solve the factor matrices. The convergence analysis of the algorithm is discussed as well. We test the proposed method in the polarization image and color facial image representation. Compared to the state-of-the-art methods, the experimental results demonstrate the effectiveness of the hierarchical nonnegative least squares method for the QNMF model.
format Preprint
id arxiv_https___arxiv_org_abs_2407_15557
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hierarchical Alternating Least Squares Methods for Quaternion Nonnegative Matrix Factorizations
Pan, Junjun
Numerical Analysis
In this report, we discuss a simple model for RGB color and polarization images under a unified framework of quaternion nonnegative matrix factorization (QNMF) and present a hierarchical nonnegative least squares method to solve the factor matrices. The convergence analysis of the algorithm is discussed as well. We test the proposed method in the polarization image and color facial image representation. Compared to the state-of-the-art methods, the experimental results demonstrate the effectiveness of the hierarchical nonnegative least squares method for the QNMF model.
title Hierarchical Alternating Least Squares Methods for Quaternion Nonnegative Matrix Factorizations
topic Numerical Analysis
url https://arxiv.org/abs/2407.15557