A novel RPCA method using log-weighted nuclear and L2,1 norms combined with contrast-limited adaptive histogram equalization (CLAHE) for high dimensional natural and medical image data
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Date
Authors
Likassa, Habte Tadesse
Chen, Ding-Geng (Din)
Sun, Dayu
Journal Title
Journal ISSN
Volume Title
Publisher
Lifescience Global
Abstract
Please read abstract in the article.
Description
Keywords
Low-rank, Computational statistics, Medical data, Robust principal component analysis (RPCA), Singular value decomposition (SVD), Log weighted nuclear norm (LWNN), Alternating direction method of multipliers (ADMM), State-of-the-art method (SOTA), Contrast limited AHE (CLAHE), Adaptive histogram equalization (AHE), SDG-09: Industry, innovation and infrastructure
Sustainable Development Goals
SDG-09: Industry, innovation and infrastructure
Citation
Likassa, H.T., Chen, D.G., Sun, D. 2024, 'A novel RPCA method using log-weighted nuclear and L2,1 norms combined with contrast-limited adaptive histogram equalization (CLAHE) for high dimensional natural and medical image data', International Journal of Statistics in Medical Research, vol. 13, pp. 275-290.
https://DOI.org/10.6000/1929-6029.2024.13.25.