Sparse Diffraction Signature Modeling of Progressively Loaded Aluminum AlloyCP8

High energy X-ray diffraction data collected in-situ during loading experiments permits probing crystal structure of a plastically deforming material sample. The proposed image representation assumes the intensity signal to be a sparse nonnegative superposition of Gaussian basis functions drawn from an over-complete dictionary and facilitates analysis of data from material with arbitrary crystal granularity. The representation is shown to capture data morphology and reveal information about the sample’s processing history in experimental data.

This presentation is part of Contributed Presentation “CP8 - Contributed session 8

Authors:
Daniel Banco (Tufts University)
Eric Miller (Tufts University)
Matthew Miller (Cornell University)
Armand Beaudoin (University of Illinois Urbana-Champaign)
Keywords:
image representation