We combine confocal microscopy and imaging spectroscopy to determine spatial morphology and chemical composition of a target in three spatial dimensions from backscattered light. We assume the target comprises few chemical species with known spectra and develop conditions on the spectra and number of measurements for unique image recovery. Images are formed by solving a regularized least squares problem using an iterative algorithm. Simulations illustrate imaging of cellular phantoms and sub-wavelength targets from noisy measurements.

This presentation is part of Minisymposium “MS42 - Low dimensional structures in imaging science (3 parts)”
organized by: Wenjing Liao (Georgia Institute of Technology) , Haizhao Yang (Duke University) , Zhizhen Zhao (University of Illinois Urbana-Champaign) .

Authors:

Yoram Bresler (University of Illinois at Urbana-Champaign)

Luke Pfister (Dept. of ECE, University of Illinois at Urbana-Champaign)

Rohit Bhargava (University of Illinois at Urbana-Champaign)

P. Scott Carney (Dept. of ECE, University of Illinois at Urbana-Champaign)

Keywords:

computed tomography, confocal microscopy, image reconstruction, imaging spectroscopy, inverse problems, unique recovery conditions