Heuristic segmentations in Electron Tomography using the DOMP

Abstract

Today, Scanning Transmission Electron Microscopy plays an important role in designing nanomaterials to be used in the development of differentfields, such as green energy sources, catalysis and environmental protection. The Electron Tomography procedure involves a three-stage process:recording the original sample using an electron microscope; reconstructing the object under study from the information provided by the first stage;and segmenting the images before or after they are reconstructed. The discrete ordered median problem presents an application in electrontomography image segmentations. The adaptability of this problem to the different instances achieves high-quality image segmentations. However, the solutions provided by the discrete ordered median problem for large scale instances are obtained in high computing times. Image size is of great importance in electron tomography experiments, since the larger the image size, the higher the quality of the image. Therefore, applying this problem to images constituted by a large number of intensities could be impractical for electron tomography experiments due to the large number of images to be segmented. With the goal of reducing the computation times, this work introduces different heuristic procedures to obtain feasible solutions for the ordered median problem that provide high-quality images in low computing times. Moreover, some noticeable improvements of the heuristic techniques are developed taking advantage of the particular versions of the ordered median function that have been proven to be especially suitable in the electron tomography image segmentation.