Group Sparse Reconstruction of
Vector-Valued Images
Joshua Trzasko1, Armando Manduca1
1Mayo Clinic, Rochester, MN, United
States
In this work we investigate a generalization of
sparsity-driven undersampled image reconstruction strategies for image series
which do not have a readily identifiable temporal or parametric sparse
transformation but for which strong yet unknown spatiotemporal correlations
are anticipated.
