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.