Abstract: Methods of aligning specimen images of specimen sections situated on a substrate include obtaining an optical or SEM image of the substrate and locating and aligning optical or SEM images of each specimen section. The specimen sections are then imaged with an SEM to obtain preview images, and a region of interest (ROI) in at least one of the preview images is selected. The preview images are processed so that at least portions of the preview images proximate the ROI are aligned. Based on the alignment of the preview images, final SEM image of selected specimen sections are obtained so that a set of images aligned in three dimensions is available. Image alignment can use cross-correlation with a fixed or variable reference that can be updated as specimen section images are processed.

Abstract: Pixels of an image (200) are coded as color vectors specified by RGB values. The image (200) is filtered by calculating new color vectors for the pixels on a pixel by pixel basis. A new color vector for a subject pixel (201) is calculated from the average of neighbor pixels (203) in a window (202) around the subject pixel (201). A first threshold is calculated from the standard deviation of the color vectors of the neighbor pixels (203) in the window (202). A second threshold is calculated from the median maximum difference between the values defining the color vectors of the respective neighbor pixels (203) in the window (202) and the standard deviation of the values. Only neighbor pixels (203) having a color vector that differs from the color vector of the subject pixel (201) by less than or the same as the first and second thresholds are used in calculation of the new color vector for the subject pixel (201).

Abstract: Pixels of an image (200) are coded as colour vectors specified by RGB values. The image (200) is filtered by calculating new colour vectors for the pixels on a pixel by pixel basis. A new colour vector for a subject pixel (201) is calculated from the average of neighbour pixels (203) in a window (202) around the subject pixel (201). A first threshold is calculated from the standard deviation of the colour vectors of the neighbour pixels (203) in the window (202). A second threshold is calculated from the median maximum difference between the values defining the colour vectors of the respective neighbour pixels (203) in the window (202) and the standard deviation of the values. Only neighbour pixels (203) having a colour vector that differs from the colour vector of the subject pixel (201) by less than or the same as the first and second thresholds are used in calculation of the new colour vector for the subject pixel (201).