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imagej中文教程

683 时间:2020-03-21 01:05:43 坐标: 339281

精选的imagej中文教程

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).


Thats it! A bilevel image is produced with the name "-mask" appended to the original image name.


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