This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
Recently, there has been growing interest in using compressed sensing to perform imaging. Most of these algorithms capture the image of a scene by taking projections of the imaged ...
Fourier Transform Infrared (FT-IR) spectroscopic imaging is a potentially valuable tool for diagnosing breast and prostate cancer, but its clinical deployment is limited due to lo...
The theory of compressed sensing tells a dramatic story that sparse signals can be reconstructed near-perfectly from a small number of random measurements. However, recent work ha...
This paper addresses the problem of Through-the-Wall Radar Imaging (TWRI) using the Multiple-Measurement Vector (MMV) compressive sensing model. TWR image formation is reformulate...
Jie Yang, Abdesselam Bouzerdoum, Fok Hing Chi Tivi...