Core-Loss Edge Detection and Background Subtraction Techniques for EELS
Published in 2014 Hyperspectral Imaging and Applications Conference, Coventry, UK, 2014
Recommended citation: V. C. Angadi and T. Walther (2014), "Core-Loss Edge Detection and Background Subtraction Techniques for EELS", In 2014 Hyperspectral Imaging and Applications Conferenc, Coventry, UK.
The paper proposes a novel approach for automated background subtraction of core-loss edges. In conventional back-ground subtraction methods, prior knowledge of the pre-edge region is inevitable. We exploit the fact that the core-loss edge is superimposed on an almost exponentially decaying background. Principle component analysis (PCA) is used to detect clustersof positive slope angle between the spectral points. A moving average filter is adopted to minimise the false detection of core-loss edges due to shot noise.
Recommended citation: V. C. Angadi and T. Walther (2014), "Core-Loss Edge Detection and Background Subtraction Techniques for EELS", In 2014 Hyperspectral Imaging and Applications Conferenc, Coventry, UK.