Shearlet-based edge detection: Flame fronts and tidal flats
- Author(s)
- E.J. King, R. Reisenhofer, J. Kiefer, W.-Q. Lim, Z. Li, G. Heygster
- Abstract
Shearlets are wavelet-like systems which are better suited for handling geometric features in multi-dimensional data than traditional wavelets. A novel method for edge and line detection which is in the spirit of phase congruency but is based on a complex shearlet transform will be presented. This approach to detection yields an approximate tangent direction of detected discontinuities as a byproduct of the computation, which then yields local curvature estimates.
Two applications of the edge detection method will be discussed. First, the tracking and classification of flame fronts is a critical component of research in technical thermodynamics. Quite often, the flame fronts are transient or weak and the images are noisy. The standard methods used in the field for the detection of flame fronts do not handle such data well. Fortunately, using the shearlet-based edge measure yields good results as well as an accurate approximation of local curvature. Furthermore, a modification of the method will yield line detection, which is important for certain imaging modalities.
Second, the Wadden tidal flats are a biodiverse region along the North Sea coast. One approach to surveying the delicate region and tracking the topographical changes is to use pre-existing Synthetic Aperture Radar (SAR) images. Unfortunately, SAR data suffers from multiplicative noise as well as sensitivity to environmental factors. The first large-scale mapping project of that type showed good results but only with a tremendous amount of manual interaction because there are many edges in the data which are not boundaries of the tidal flats but are edges of features like fields or islands. Preliminary results will be presented.- Organisation(s)
- External organisation(s)
- Universität Bremen, Fraunhofer-Institut für Nachrichtentechnik
- No. of pages
- 11
- DOI
- https://doi.org/10.1117/12.2188652
- Publication date
- 2015
- Austrian Fields of Science 2012
- 102003 Image processing, 203024 Thermodynamics
- Keywords
- ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials, Condensed Matter Physics, Applied Mathematics, Electrical and Electronic Engineering, Computer Science Applications
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/shearletbased-edge-detection-flame-fronts-and-tidal-flats(cb8994a4-2a51-421a-bdb5-8ddafad6e952).html