English

Denosing Using Wavelets and Projections onto the L1-Ball

Optimization and Control 2014-06-11 v1 Computer Vision and Pattern Recognition

Abstract

Both wavelet denoising and denosing methods using the concept of sparsity are based on soft-thresholding. In sparsity based denoising methods, it is assumed that the original signal is sparse in some transform domains such as the wavelet domain and the wavelet subsignals of the noisy signal are projected onto L1-balls to reduce noise. In this lecture note, it is shown that the size of the L1-ball or equivalently the soft threshold value can be determined using linear algebra. The key step is an orthogonal projection onto the epigraph set of the L1-norm cost function.

Keywords

Cite

@article{arxiv.1406.2528,
  title  = {Denosing Using Wavelets and Projections onto the L1-Ball},
  author = {A. Enis Cetin and Mohammad Tofighi},
  journal= {arXiv preprint arXiv:1406.2528},
  year   = {2014}
}

Comments

Submitted to Signal Processing Magazine

R2 v1 2026-06-22T04:34:58.835Z