Adaptive denoising for magnetic resonance image based on nonlocal structural similarity and low-rank sparse representation.
Hongyu WangYing LiSongtao DingXiaoying PanZhanyi GaoShaohua WanJun FengPublished in: Clust. Comput. (2023)
Keyphrases
- magnetic resonance
- low rank
- structural similarity
- denoising
- sparse representation
- low rank matrix recovery
- high dimensional data
- mr images
- image denoising
- convex optimization
- total variation
- medical images
- dictionary learning
- linear combination
- low rank matrix
- sparse coding
- image data
- matrix factorization
- natural images
- missing data
- image processing
- image registration
- matrix completion
- norm minimization
- dimensionality reduction
- face recognition
- semi supervised
- singular value decomposition
- image classification
- compressive sensing
- data points
- high order
- low rank and sparse
- image patches
- low dimensional
- image representation
- data analysis
- signal processing
- data sets
- singular values
- compressed sensing
- computer vision
- test images
- multiscale
- high dimensional
- image compression