In this paper, we develop algorithms for robust linear regression by leveraging the connection between the problems of robust regression and sparse signal recovery. We explicitly ...
Sparse signal recovery algorithms utilizing multiple measurement vectors (MMVs) are known to have better performance compared to the single measurement vector case. However, curre...
A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
This paper presents a method for alignment of images acquired by sensors of di erent modalities (e.g., EO and IR). The paper has two main contributions: (i) It identi es an approp...
Recent advances in spatio-spectral sampling and panchromatic pixels have contributed to increased spatial resolution and enhanced noise performance. As such, it is necessary to co...