An approximate message passing approach for compressive hyperspectral imaging using a simultaneous low-rank and joint-sparsity prior.
Yangqing LiSaurabh PrasadWei ChenChangchuan YinZhu HanPublished in: CoRR (2016)
Keyphrases
- message passing
- low rank
- hyperspectral imaging
- target detection
- convex optimization
- matrix factorization
- belief propagation
- linear combination
- missing data
- sparse representation
- high dimensional data
- singular value decomposition
- distributed systems
- semi supervised
- high order
- approximate inference
- markov random field
- compressive sensing
- computer vision
- dimensionality reduction
- graphical models
- graph cuts
- stereo matching
- high dimensional
- multiscale
- face recognition
- data sets
- clustering algorithm
- low dimensional