New Robust PCA for Outliers and Heavy Sparse Noises’ Detection via Affine Transformation, the L∗,w and L2,1 Norms, and Spatial Weight Matrix in High-Dimensional Images: From the Perspective of Signal Processing
In this paper, we propose a novel robust algorithm for image recovery via affine transformations, the weighted nuclear, L∗,w, and the L2,1 norms. The new method considers the spatial weight matrix to account the correlated samples in the data, the L2,1 norm to tackle the dilemma of extreme values in...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | International Journal of Mathematics and Mathematical Sciences |
| Online Access: | http://dx.doi.org/10.1155/2021/3047712 |
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