Utilizing the wavelet transform's structure in compressed sensing

  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},
  volume={15 7},
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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Error Resilient Techniques for Wavelet Based Compressed Sensing

  • Yen-Chieh HuangS. Chang
  • Computer Science
    2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech)
  • 2020
This paper uses multiple description coding (MDC) to protect CS signals beforehand, transmit the protected signals, and recover the reconstruction with the calculations from the compensations of MDC, and applies compressed sensing to original image to obtain CS signals.

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