Weighted Nonnegative Matrix Factorization for Image Inpainting and Clustering
Conventional nonnegative matrix factorization and its variants cannot separate the noise data space into a clean space and learn an effective low-dimensional subspace from Salt and Pepper noise or Contiguous Occlusion. This paper proposes a weighted nonnegative matrix factorization (WNMF) to improve...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Atlantis Press
2020-06-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/125941271/view |