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A Block Fixed Point Continuation Algorithm for Block-Sparse Reconstruction
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DOI：10.1109/LSP.2012.2195488.png)
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Abstract
En 中文
Block-sparse reconstruction, which arises from the reconstruction of block-sparse signals in structured compressed sensing, is generally considered difficult to solve due to the mixed-norm structure. In this letter, we propose an algorithm for reconstructing block-sparse signals, that is an extension of fixed point continuation in block-wise case by incorporating block coordinate descent technique. We also apply our algorithm to multiple measurement vector reconstruction, that is a special case of block-sparse reconstruction and can be used in magnetic resonance imaging reconstruction. Numerical results show the validity of our algorithm for both synthetic and real-world data.
Keywords:
Block coordinate descent
block-sparse reconstruction
fixed point continuation
structured compressed sensing
Journal
IF:
9.6
Papers:
1.1W
Citations:
1.7W