A harder-than-usual inverse problem
What is it about?
The novel methodology presented herre using image synthesis ideas and newly developed priors on sparsity, within a very high-dimensional MCMC-based inferential scheme.
Why is it important?
We present a new Bayesian methodology to learn the unknown material density of a given sample by inverting its two-dimensional images that are taken with a Scanning Electron Microscope. The method is applied to learn the material density of a 3-D sample of a nano-structure, using real image data. Illustrations on simulated image data of alloy samples are also included.
The following have contributed to this page: Dr Dalia Chakrabarty and Professor Shashi Paul