We consider two imaging applications of compressed sensing where the acquired data corresponds to samples
in the Fourier domain (aka k- space). The rst one is magnetic resonance imaging (MRI), which has been
one of the standard examples in the compressed sensing literature. The second one is synthetic aperture radar
(SAR). We consider the practical issues of applying compressed sensing ideas in these two applications noting
that the physical prossesses involved in these two sensing modalities are very different. We consider the issues
of: appropriate image models and sampling strategies, dealing with noise, and the need for calibration.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.