Density reconstruction from schlieren images through Bayesian nonparametric models

Code

• github.com/bnubald/pof-schlieren-density-reconstruction
  OfficialIn papernone★ 0
• github.com/bnubald/dce-schlieren-density-reconstruction
  OfficialIn papernone★ 0

Abstract

This study proposes a radically alternate approach for extracting quantitative information from schlieren images. The method uses a scaled, derivative enhanced Gaussian process model to obtain true density estimates from two corresponding schlieren images with the knife-edge at horizontal and vertical orientations. We illustrate our approach on schlieren images taken from a wind tunnel sting model, a supersonic aircraft in flight, and a high-order numerical shock tube simulation.

Tasks

Reproductions