%0 Journal Article
%T A MULTISCALE APPROACH TO THE REPRESENTATION OF 3D IMAGES, WITH APPLICATION TO POLYMER SOLAR CELLS
%A Ralf Thiedmann
%A Henrik Hassfeld
%A Ole Stenzel
%A L. Jan Anton Koster
%J Image Analysis and Stereology
%D 2011
%I Slovenian Society for Stereology and Quantitative Image Analysis
%R 10.5566/ias.v30.p19-30
%X A multiscale approach to the description of geometrically complex 3D image data is proposed which distinguishes between morphological features on a ¡®macro-scale¡¯ and a ¡®micro-scale¡¯. Since our method is mainly tailored to nanostructures observed in composite materials consisting of two different phases, an appropriate binarization of grayscale images is required first. Then, a morphological smoothing is applied to extract the structural information from binarized image data on the ¡®macro-scale¡¯. A stochastic algorithm is developed for the morphologically smoothed images whose goal is to find a suitable representation of the macro-scale structure by unions of overlapping spheres. Such representations can be interpreted as marked point patterns. They lead to an enormous reduction of data and allow the application of well-known tools from point-process theory for their analysis and structural modeling. All those voxels which have been ¡®misspecified¡¯ by the morphological smoothing and subsequent representation by unions of overlapping spheres are interpreted as ¡®micro-scale¡¯ structure. The exemplary data sets considered in this paper are 3D grayscale images of photoactive layers in hybrid solar cells gained by electron tomography. These composite materials consist of two phases: a polymer phase and a zinc oxide phase. The macro-scale structure of the latter is represented by unions of overlapping spheres.
%K adaptive thresholding
%K discrete skeleton
%K morphological smoothing
%K multiscale approach
%K representation by overlapping spheres
%U http://www.ias-iss.org/ojs/IAS/article/view/20