DMelt:Image/2 Image Manipulation IJ

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Image manipulation using ImageJ

The example below shows how to load an image and apply a filter. It also show how to access its internals. Look at the complete API of the IJ package.

from ij import *
from ij.process import *
from ij.measure import *

# we open the file manually. Generate  ImagePlus object
imp = IJ.openImage(file)
print dir(imp) # check image manipulation methods

# display it
print imp.getWidth()

# do manipulations with the clone
imp.getProcessor().setThreshold(174, 174, ImageProcessor.NO_LUT_UPDATE),"Convert to Mask",""),"Watershed", "")

# get all the pixels
pix = imp.getProcessor().getPixels()

Next we can perform a detailed analysis of images. For example, one can create a histogram:

from ij import *
imp = IJ.openImage(""), "Histogram", "")
stats = imp.getStatistics()
print stats.histogram

One can extract data from image and perform manipulation. Then a new modified array can be used to build a new image. Look at the example:

Edge detection of images

In this example, let's detect edges of the image of DMelt logo. Below we show 2 examples: one reads this logo using the URL, and the second example reads this logo from local file.

The output of these scripts is below:

DMelt example: Detect edges using imput image

Note that it makes sense to convert the image into back-white. Also, one can swap the colors.

Below we will consider other topics, such as

  • Creating an image from a text file
  • Obtain/View histogram and measurements from an image
  • Removing bleeding from one channel to another
  • Subtract the minimal value to an image
  • Extract a specific color channel for a given time frame
  • Visualize any number of TIFF stacks in a single composite multi-color image stack
  • Sort all points into a chain by distance to each other
  • Correct illumination in a stack: apply the illumination of one slice to all others
  • Add a mouse listener to the canvas of every open image
  • Add a key listener to the canvas of every open image
  • Create a virtual stack from the TIF files present in a folder
  • Open the slices of a very large multi-image stack file one by one, and save each as a new image file
  • Apply a binary mask to every slice in an image stack
More information on this topic is in DMelt books