3dedge3


Usage: 3dedge3 [options] dset dset ...
Does 3D Edge detection using the library 3DEdge by;
by Gregoire Malandain (gregoire.malandain@sophia.inria.fr)

Options :

  -input iii  = Input dataset

  -verbose    = Print out some information along the way.

  -prefix ppp = Sets the prefix of the output dataset.

  -datum ddd  = Sets the datum of the output dataset.

  -fscale     = Force scaling of the output to the maximum integer range.
  -gscale     = Same as '-fscale', but also forces each output sub-brick to
                  to get the same scaling factor.
  -nscale     = Don't do any scaling on output to byte or short datasets.
  -scale_floats VAL = Multiply input by VAL, but only if the input datum is
                      float. This is needed when the input dataset
                      has a small range, like 0 to 2.0 for instance.
                      With such a range, very few edges are detected due to
                      what I suspect to be truncation problems.
                      Multiplying such a dataset by 10000 fixes the problem
                      and the scaling is undone at the output.

  -automask   = For automatic, internal calculation of a mask in the usual
                AFNI way. Again, this mask is only applied after all calcs
                (so using this does not speed up the calc or affect
                distance values).
                ** Special note: you can also write '-automask+X', where
                X is some integer; this will dilate the initial automask
                number of times (as in 3dAllineate); must have X>0.


References for the algorithms:
 -  Optimal edge detection using recursive filtering
    R. Deriche, International Journal of Computer Vision,
    pp 167-187, 1987.
 -  Recursive filtering and edge tracking: two primary tools
    for 3-D edge detection, O. Monga, R. Deriche, G. Malandain
    and J.-P. Cocquerez, Image and Vision Computing 4:9,
    pp 203-214, August 1991.


++ Compile date = Aug  5 2022 {AFNI_22.2.05:linux_ubuntu_16_64}