Composite wavelet representations for reconstruction of missing data

Wojciech Czaja; Julia Dobrosotskaya; Benjamin Manning

doi:10.1117/12.2019219

Abstract

We shall introduce a novel methodology for data reconstruction and recovery, based on composite wavelet representations. These representations include shearlets and crystallographic wavelets, among others, and they allow for an increased directional sensitivity in comparison with the standard multiscale techniques. Our new approach allows us to recover missing data, due to sparsity of composite wavelet representations, especially when compared to inpainting algorithms induced by traditional wavelet representations, and also due to the flexibility of our variational approach.

Citation Download Citation

Wojciech Czaja, Wojciech Czaja, Julia Dobrosotskaya, Julia Dobrosotskaya, Benjamin Manning, Benjamin Manning, } "Composite wavelet representations for reconstruction of missing data", Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 875003 (29 May 2013); doi: 10.1117/12.2019219; https://doi.org/10.1117/12.2019219

ACCESS THE FULL ARTICLE

PERSONAL SIGN IN
Full access may be available with your subscription

Email or Username Forgot your username?

Password Forgot your password?

Show

Remember Email/Username on this computer

Remember Password

No SPIE account? Create an account
or Institutional Sign In via Shibboleth

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $14.40

Non-members: $18.00 ADD TO CART

Show All Keywords

Keywords/Phrases

Search In:

Publication Years