Utilizing the wavelet transform's structure in compressed sensing

@article{Dwork2021UtilizingTW,
  title={Utilizing the wavelet transform's structure in compressed sensing},
  author={Nicholas Dwork and Daniel O’Connor and Corey A. Baron and Ethan M. I. Johnson and Adam B. Kerr and John M. Pauly and Peder Eric Zufall Larson},
  journal={Signal, image and video processing},
  year={2021},
  volume={15 7},
  pages={
          1407-1414
        }
}
Compressed sensing has empowered quality image reconstruction with fewer data samples than previously thought possible. These techniques rely on a sparsifying linear transformation. The Daubechies wavelet transform is commonly used for this purpose. In this work, we take advantage of the structure of this wavelet transform and identify an affine transformation that increases the sparsity of the result. After inclusion of this affine transformation, we modify the resulting optimization problem… 

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