def apply_filter3d(imp,
radiusx=5,
radiusy=5,
radiusz=5,
filtertype='MEDIAN'):
# initialize filter
f3d = Filters3D()
# create filter dictionary for 3d filters
filterdict = {}
filterdict['MEAN'] = f3d.MEAN
filterdict['MIN'] = f3d.MIN
filterdict['MAX'] = f3d.MAX
# filterdict['MAXLOCAL'] = f3d.MAXLOCAL # did not work
filterdict['MEDIAN'] = f3d.MEDIAN
filterdict['VAR'] = f3d.VAR
stack = imp.getStack() # get the stack within the ImagePlus
newstack = f3d.filter(stack,
filterdict[filtertype],
radiusx,
radiusy,
radiusz)
imp = ImagePlus('Filtered 3D', newstack)
return imp
def meanIJ(cs, xysigma):
# type: (CellStack, float) -> None
"""
Perform ImageJ mean filter 3D with same sigma along x and y axes on a CellStack (locally)
"""
stack = cs.getImageStack()
new_stack = Filters3D.filter(stack, Filters3D.MEAN, xysigma, xysigma, xysigma * cs.scaleZ)
cs.setStack(new_stack)
# 6. Further examples
####################################################
# This snippet performs a filtering operation on the active image and
# exemplifies how to create a generic, reusable script based on the
# IJ1 API[1]. Input parameters are retrieved using @Parameters[2]
#
# [1] http://javadoc.imagej.net
# [2] https://imagej.net/Script_Parameters
from ij.plugin import Filters3D
from ij import ImagePlus
# Get the image stack within the ImagePlus of img
stack = img.getStack()
# Instantiate ij.plugin.Filters3D
f3d = Filters3D()
# Retrieve filtered stack
newStack = f3d.filter(stack, f3d.MEDIAN, xradius, yradius, zradius)
# Construct a new ImagePlus from the stack
fImg = ImagePlus("Filtered_" + img.getTitle(), newStack)
# Other processing could go here (...)
#IJ.run(fImg, "Shen-Castan Edge Detector", "coefficient=0.50");
# Display result
fImg.show()
def filter_stack_max_3d(imp, dx ,dy, dz):
stack_filtered = Filters3D.filter(imp.getStack(), Filters3D.MAX, dx, dy, dz)
return ImagePlus("max filtered", stack_filtered)