• DOI:10.1109/ICIP.2008.4711899
Corpus ID: 9282476

Kalman filtered Compressed Sensing

@article{Vaswani2008KalmanFC,
  title={Kalman filtered Compressed Sensing},
  author={N. Vaswani},
  journal={2008 15th IEEE International Conference on Image Processing},
  year={2008},
  pages={893-896}
}

N. Vaswani

Published 2008

Computer Science, Mathematics

2008 15th IEEE International Conference on Image Processing

We consider the problem of reconstructing time sequences of spatially sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear "incoherent" measurements, in real-time. The signals are sparse in some transform domain referred to as the sparsity basis. For a single spatial signal, the solution is provided by Compressed Sensing (CS). The question that we address is, for a sequence of sparse signals, can we do better than CS, if (a) the sparsity pattern of… CONTINUE READING

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