New explicit thresholding/shrinkage formulas for one class of regularization problems with overlapping group sparsity and their applications

@inproceedings{Liu2013NewET,
  title={New explicit thresholding/shrinkage formulas for one class of regularization problems with overlapping group sparsity and their applications},
  author={Gang Liu and Ting-Zhu Huang and Xiao-Guang Lv and Jun Liu},
  year={2013}
}
The least-square regression problems or inverse problems h ave been widely studied in many fields such as compressive sensing, signal processing, and image processing. To solve this kind of ill-posed problems, a regularization term (i.e ., r gularizer) should be introduced, under the assumption that the solutions have some specific pr operties, such as sparsity and group sparsity. Widely used regularizers include the l1 norm, total variation (TV) semi-norm, and so on. Recently, a new… CONTINUE READING
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Total variation wi th overlapping group sparsity gor image deblurring under impulse noise

  • G. Liu, T.-Z Huang, J. Liu, X. G. Lv
  • arXiv preprint arXiv:1312 .6208,
  • 2013
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