Download RATS_.jar to the plugins folder or a subfolder and restart ImageJ or use the menu selection Help > Update Menus.
RATS_ (Robust Automatic Threshold Selection) is based upon work of M.H.F. Wilkinson and others,
RATS establishes regionalized thresholds for a greyscale image
where the regions are established using recursive quadtree architecture. Within each
of the lowest quadtree regions the threshold is calculated as the sum of
the orginal pixels weighted by the gradient pixels.
for pixels within each region.
The threshold calculated in each region is required to
meet minimum criteria – these criteria are determined by the user as
a noise estimate (sigma) and a scaling factor (lambda). The user may also
select the minimum region size. The thresholds for all
region are then interpolated (bilinear) across the entire image.
In general, the best values for each of three parameters are determined
by trial and error for a given suite of images. See references in source code and below.
REFERENCE: M.H.F. Wilkinson (1998) Optimizing edge detectors for robust automatic threshold selection.
Graph. Models Image Proc. 60: M.H.F. Wilkinson (1996) Rapid automatic segmentation of fluorescent
and phase-contrast images of bacteria. In: Fluorescence Microscopy and Fluorescent Probes,(J.
Slavik, ed), pp 261-266, Plenum Press, New York.
REFERENCE: M.H.F. Wilkinson “Segmentation Techniques in Image Analysis of Microbes”
which is chapter 3 in Digital Image Analysis of Microbes: Imaging,
Morphometry, Fluorometry and Motility Techniques and Applications.
Edited by M.H.F. Wilkinson and F. Schut, Wiley Modern Microbiology Methods
The left image shows the dialog in which the user is prompted for…
1. NOISE THRESHOLD: An estimate of the noise. Estimate the noise by selecting a “background” portion of the image and using ImageJ to determine the standard deviation of gray values. Oddly, lower values yield smaller particles in general. (see refs, defaults to 25).
2. LAMBDA FACTOR: A scaling factor. Higher values yield larger particles. (see refs, defaults to 3)
3. MIN LEAF SIZE (pixels): The smallest allowed leaflet (defaults to 5 levels of quadtrees so the default value is computed on the fly based upon the input image width and height.
4. VERBOSE If set then output informational messages in the log window (default is false).
The center and right images show an example image its edge enhancement with the nested quadtrees for just one quadrant superimposed.
Author: Jerek Sacha (jarek at ieee.org) History: 2004/02/13: First version Source: Entropy_Threshold.java Installation: Download Entropy_Threshold.java to the plugins folder, or subfolder, and compile and run
Author: Yasunari Tosa (ytosa at att.net) History: 2006/04/14: First version Source: Multi_OtsuThreshold.java Installation: Download Multi_OtsuThreshold.java to the plugins folder, or subfolder, then compile and run
Author: Francois Richard (richard@SCIENCE.UOTTAWA.CA) Date: 2000/9/29 Source: Comment_Writer.java Installation: Copy Comment_Writer.class to the plugins folder and restart ImageJ. Description: This is a simple plugin that
Authors: Jeffrey Kuhn (email@example.com) The University of Texas at Austin Anthony Padua (firstname.lastname@example.org) Duke University Medical Center, Department of Radiology History: 2000/08/22: First version 2002/10/31: