Weighted Nuclear Norm Minimization with Application to Image Denoising
Hong Kong Polytechnic University · Harbin Institute of Technology · +1 more institution
Abstract
As a convex relaxation of the low rank matrix factorization problem, the nuclear norm minimization has been attracting significant research interest in recent years. The standard nuclear norm minimization regularizes each singular value equally to pursue the convexity of the objective function. However, this greatly restricts its capability and flexibility in dealing with many practical problems (e.g., denoising), where the singular values have clear physical meanings and should be treated differently. In this paper we study the weighted nuclear norm minimization (WNNM) problem, where the singular values are assigned different weights. The solutions of the WNNM problem are analyzed under different weighting…
Citation impact
- FWCI
- 82.41
- Percentile
- 100%
- References
- 44
Authors
4Topics & keywords
- Matrix norm
- Singular value
- Weighting
- Singular value decomposition
- Minification
- Norm (philosophy)
- Noise reduction
- Mathematics