"An Optimally Sparse Representation of Cylindrical 3-D Data using Shearlets"
Sep 29, 2021 Schedule:
- Tea Time - F2F ( 417 DSL) / Virtual ( Zoom)
- 03:00 to 03:30 PM Eastern Time (US and Canada)
- Colloquium - F2F ( 499 DSL) / Virtual ( Zoom)
- 03:30 to 04:30 PM Eastern Time (US and Canada)
Meeting # 942 7359 5552
Abstract:
Fourier Transform has a long history and has applications in many fields such as signal representation, frequency analysis, and image processing. Since sine and cosine functions form the basis for the transform, the represen- tation provided by the transform is impressive for sufficiently smooth signals. However, the global nature of the Fourier bases causes an unintended problem while attempting to represent signals containing discontinuities or sharp edges in many cases resulting in the Gibbs phenomenon. Consequently, researchers introduced localized basis systems termed wavelets to deal with this issue and the problem arising from the manifestation of the un- certainty principle in simultaneous localization in time and frequency domains. This time-frequency localization property is critical for constructing sparse representations. It allows building function expansions where only a relatively small number of expansion coefficients are affected by local function perturbations...
