Shearlet-Based Detection of Flame Fronts

Identifying and characterizing flame fronts is the most common task in the computer-assisted analysis of data obtained from imaging techniques such as planar laser-induced fluorescence (PLIF), laser Rayleigh scattering (LRS), or particle imaging velocimetry (PIV). We present Complex Shearlet-Based Ridge and Edge Measure (CoShREM), a novel edge and ridge (line) detection algorithm based on complexvalued wavelet-like analyzing functions – so-called complex shearlets – displaying several traits useful for the extraction of flame fronts. In addition to providing a unified approach to the detection of edges and ridges, our method inherently yields estimates of local tangent orientations and local curvatures. To examine the applicability for high-frequency recordings of combustion processes, the algorithm is applied to mock images distorted with varying degrees of noise and real-world PLIF images of both OH and CH radicals. Furthermore, we compare the performance of the newly proposed complex shearlet-based measure to well-established edge and ridge detection techniques such as the Canny edge detector, another shearlet-based edge detector, and the phase congruency measure. Rafael Reisenhofer Computational Data Analysis, Fachbereich 3, Universität Bremen, Postfach 330440, 28334 Bremen Johannes Kiefer Technische Thermodynamik, Fachbereich 4, Universität Bremen, Badgasteiner Str. 1, 28359 Bremen Tel.: +49-421-218-64777 Fax: +49-421-218-64771 E-mail: [email protected] Emily J. King Computational Data Analysis, Fachbereich 3, Universität Bremen, Postfach 330440, 28334 Bremen