![]() ![]() Image converted to 16 bits with scaling can result in different threshold values. the Triangle method applied to an 8 bit image and to the same when multiplying all pixels by a fixed value) returns a similar threshold result (within 2 greyscale levels of the original unscaled image) for all methods except Huang, Li and Triangle due to the way these algorithms work. The same image scaled by a fixed value (e.g. The current implementation avoids this offset-dependent problem.ĥ. when adding a fixed value to all pixels). The same image in 8 and 16 bits (without scaling) returns the same threshold value, however Li’s method originally would return different values when the image data was offset (e.g. Images and stacks that impossible to threshold remain unchanged.Ĥ. The “Try all” option retains the 16 bit format to show methods that might fail to obtain a threshold. This is to keep the data untouched in the remaining slices. However, for stacks where only 1 slice is thresholded, the result is still a 16 bit container with the thresholded phase shown as white. The result of 16 bit images and stacks (when processing all slices) is an 8 bit container showing the result in white to comply with the concept of “binary image” (i.e. Note that for speeding up, the histogram is bracketed to include only the range of bins that contain data (and avoid processing empty histogram bins at both extremes).ģ. Therefore, there might be differences in the results obtained on 16-bit images when using the applet and the true 16-bit results obtained with this plugin. Note that the ImageJ thresholder applet also processes 16-bit images, but in reality ImageJ first computes a histogram with 256 bins. Since the Auto Threshold plugin processes the full greyscale space, it can be slow when dealing with 16-bit images. From version 1.12 the plugin supports thresholding of 16-bit images. In essence, the Auto Threshold plugin, with the correct settings, can reproduce the results of the applet, but not the way round.Ģ. This means that applying the two commands to the same image can produce apparently different results. While the Auto Threshold plugin can use or ignore the extremes of the image histogram (Ignore black, Ignore white) the applet cannot: the ‘default’ method ignores the histogram extremes but the others methods do not. This plugin is accessed through the Image>Auto Threshold menu entry, however the thresholding methods were also partially implemented in ImageJ’s thresholder applet accessible through the Image>Adjust>Threshold… menu entry. not shown in red), so the particle analyzer should be able to pick the white pixels for the analysis.ġ. ![]() Since versions 1.8 and 1.1 of the two plugins respectively, the threshold of the binarised image is also silently set to 255 (i.e. Note that the thresholded phase is always shown as white. Selecting this option also selects the Stack option above automatically. Use stack histogram first computes the histogram of the whole stack, then computes the threshold based on that histogram and finally binarises all the slices with that single value. If this option is left unchecked, only the current slice will be processed. ![]() When processing a stack, two additional options are available: Stack can be used to process all the slices (the threshold of each slice will be computed separately). Set Threshold instead of Threshold (single images) sets the thresholding LUT, without changing the pixel data. White object on black background sets to white the pixels with values above the threshold value (otherwise, it sets to white the values less or equal to the threshold). This may be useful if the digitised image has under- or over- exposed pixels. The Ignore black and Ignore white options set the image histogram bins for and greylevels to 0 Method selects the algorithm to be applied (detailed below). Threshold and Image>Adjust>Auto Local Threshold.įiji: this plugin is part of the Fiji distribution, there is no need to download (it might show a different version number). After this, two new commands should appear in Image>Adjust>Auto ImageJ: Copy the ( Auto_Threshold.jar file) into the ImageJ/Plugins folder and either restart ImageJ or run the Help>Update Menus command. These two plugins binarise 8-bit images (and 16bit images in the case of Auto_Threshold) using various global (histogram-derived) and local (adaptive) thresholding methods.Īuto_Local_Threshold v1.11, date: 8/Mar/2021 Installation ![]()
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