Dictionary learning based reconstruction for distributed compressed video sensing
Leveraging more realistic video signal models that go beyond simple sparsity. A novel undersampling correlation noise model for subsampled video signals. To learn a dictionary that efficiently describes the video contents and structures. A maximum-likelihood (ML) dictionary learning based reconstruction for DCVS. Signal recovery is performed within ML learning, not as an independent task.
dictionary learning distributed compressed video sensing undersampled correlation noise model compressed sensing distributed video coding sparse recovery maximum likelihood energy minimization