imagej软件使用教程合辑
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imagej软件使用教程合辑
强大的自动阈值选择插件
Robust Automatic Threshold Selection (RATS) computes a
threshold map for a 2d image based upon the value of pixels and
their gradients. The algorithm is applied across regions of the
image making it suitable for thresholding noisy images with
variable background.
Load an single channel image (8-bit, 16-bit or 32-bit). Note
that the plugin expects bright objects on dark background, so
you might want to callEdit ? Invert if your input image has dark
objects. Select the RATS plugin from the Plugins menu. The
following dialog will appear:
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
reference, defaults to 25).
2. LAMBDA FACTOR: A scaling factor. Higher values yield
larger particles. (see reference, defaults to 3)
3. MIN LEAF SIZE (pixels): The smallest allowed leaflet
(defaults to attempts to create up to 5 levels of quadtrees that fit
in the input image dimensions)
4. VERBOSE If set then output informational messages in the
log window (default is false).
That's it! A bilevel image is produced with the name "-mask"
appended to the original image name.