5 papers
Sensing Matrix Design via Capacity Maximization for Block Compressive Sensing Applications
Richard Obermeier, Jose Angel Martinez-Lorenzo
It is well established in the compressive sensing (CS) literature that sensing matrices whose elements are drawn from independent random distributions exhibit enhanced reconstructi…
Generalized Optimization of High Capacity Compressive Imaging Systems
Richard Obermeier, Jose Angel Martinez-Lorenzo
One of the greatest challenges in applying compressive sensing (CS) signal processing techniques to electromagnetic imaging applications is designing a sensing matrix that has good…
Detecting Breast Cancer using a Compressive Sensing Unmixing Algorithm
Richard Obermeier, Jose Angel Martinez-Lorenzo
Traditional breast cancer imaging methods using microwave Nearfield Radar Imaging (NRI) seek to recover the complex permittivity of the tissues at each voxel in the imaging region.…
A compressive sensing approach for enhancing breast cancer detection using a hybrid DBT / NRI configuration
Richard Obermeier, Jose Angel Martinez Lorenzo
This work presents a novel breast cancer imaging approach that uses compressive sensing in a hybrid Digital Breast Tomosynthesis (DBT) / Nearfield Radar Imaging (NRI) system config…
Model-based Optimization of Compressive Antennas for High-Sensing-Capacity Applications
Richard Obermeier, Jose Angel Martinez-Lorenzo
This paper presents a novel, model-based compressive antenna design method for high sensing capacity imaging applications. Given a set of design constraints, the method maximizes t…