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, IEEE
   (last updated on 2025/02/22)

   Abstract:
   Estimating an image M* +m1×m2 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.