Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation

@article{Rubinstein2010DoubleSL,
  title={Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation},
  author={Ron Rubinstein and Michael Zibulevsky and Michael Elad},
  journal={IEEE Transactions on Signal Processing},
  year={2010},
  volume={58},
  pages={1553-1564}
}
An efficient and flexible dictionary structure is proposed for sparse and redundant signal representation. The proposed sparse dictionary is based on a sparsity model of the dictionary atoms over a base dictionary, and takes the form D = ¿ A, where ¿ is a fixed base dictionary and A is sparse. The sparse dictionary provides efficient forward and adjoint operators, has a compact representation, and can be effectively trained from given example data. In this, the sparse structure bridges the gap… CONTINUE READING
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