Nonlinear diffusion filtering of images obtained by planar laser-induced fluorescence spectroscopy

The application of nonlinear anisotropic diffusion filtering to reduce noise and enhance contours in images obtained by two-dimensional planar laser-induced fluorescence (PLIF) spectroscopy is presented. In this process the diffusion coefficient is locally adapted, becoming negligible as object boundaries are approached. Noise is efficiently removed, and object contours are strongly enhanced. The technique is demonstrated with PLIF images obtained from the OH radical recorded in turbulent flames. We show that nonlinear diffusion is suitable as a preprocessing step, before image segmentation becomes possible, and we demonstrate how the technique is applied for the quantitative extraction of flame reaction boundaries from PLIF data.