Abstract
This paper presents new models for segmentation of 2D and 3D Scanning-Transmission Electron Microscope images based on the ordered median function. The main advantage of using this function is its good adaptability to the different types of images to be studied due to the wide range of weight vectors that can be cast. Classical segmentation models stand out for their ability to provide a segmentation of the original image very quickly and with low computational burden. However, they do not usually achieve high quality segmentations with a small number of clusters in order to classify the different elements which compose the structure represented in the image. The quality of the segmentation provided by our approach is analysed using different choices of the weight vector in some real instances. Moreover, improvements are proposed for the formulations to reduce the computational time needed to solve these problems by taking advantage of the weight vector structure.
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