Department of Mathematics
 Search | Help | Login | pdf version | printable version

Math @ Duke



Publications [#235764] of Robert Calderbank

Papers Published

  1. Xie, Y; Chi, Y; Calderbank, R, Low-rank matrix recovery with poison noise, 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings (December, 2013), pp. 622 [doi]
    (last updated on 2017/12/16)

    Estimating an image M* + m 1 ×m 2 from its linear measurements under Poisson noise is an important problem arises from applications such as optical imaging, nuclear medicine and x-ray imaging [1]. When the image M* has a low-rank structure, we can use a small number of linear measurements to recover M*, also known as low-rank matrix recovery. This is related to compressed sensing, where the goal is to develop efficient data acquisition systems by exploiting sparsity of underlying signals. © 2013 IEEE.
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320