The anisotripic diffusion method contains a free parameter `K' which sets the size of a jump in the magnitude of the gradient of the image which is to be considered important (i.e. characteristic of the change in contrast between objects in the image). This case allows the user to investigate the effect of a list of different possible choices of `K' by diffusing the images and presenting the resultant diffused images alongside the original on a single page for visual comparison.
Input Data Options special purpose data requiring pre-processing (0) tomographic data (1) segmented data (2) burn data (3) medial axis data (4) throat data (5) Enter choice: 1
Data Processing Options plot image (1) plot slice histograms (2) resize tomographic data (3) generate circular fiducial polygon (4) segment data (5) porosity/cut_off dependence (6) investigate dfn K values (7) investigate dfn threshold values (8) |grad image| histogram (9) compress data in z direction (10) Enter choice: 7
The tomographic data file is raw data file (raw) partially diffused data file (dfn) Enter choice: raw
Tomographic data slices are contained in separate files (slc) a single file (vol) Enter file type (slc,vol): slc
Recognized tomographic data file types are ascii integer array ( ai) binary integer array ( bi) swapped binary integer array ( sbi) binary short integer array ( bs) swapped binary short array ( sbs) binary unsigned char array ( ubc) netcdf files ( nc) netcdf ascii files ( na) Kimberly Clark data ( kc) punch ascii files ( pa) sun rasterfile ( 8-bit color) ( sr8) sun rasterfile (24-bit color) (sr24) Enter data type (ai,bi,sbi,bs,sbs,ubc,nc,na,kc,pa,sr8,sr24): bi
Files assumed to be labelled basename.ext, basename is limited to 255 characters maximum, ext is a numerical designator lying between 000 and 999 It is assumed that the files have consecutively numbered extensions ie. 000 -> 056, or 021 -> 049
Enter basename for tomographic files: ../../Examples/data/berea/berea Are files compressed? [y,n]: y
Enter first and last slice of data to use: 1 1
Slice size of data, (nx,ny): 541 541
Fiducial polygon generation NONE (N) MANUALLY set (M) Enter method: M
MANUAL fiducial boundary calculation
The bounding curve for each fiducial polygon should be convex in the sense that at most 2 points on the bounding curve have the same y coordinate. Enter number of polygons: 1
Are the coordinates of the fiducial polygon(s) stored in a file: y Filename of fiducial polygon 1: ../../Examples/data/polygon.541
Enter range [min_val,max_val] to search for valley location: 10.000000 90000.000000
For each value K[i] of iteration parameter chosen, I[i] iterations will be performed, starting from the tomographic data in each case.
Enter 'n', number diffusion values, to be used: 2
Enter 2 K[i], I[i] pair values, 1 pair per line : 3.000000 5 : 10.000000 5
Enter basename for diffused files: berea Select method for determining MIN and MAX values for scaling data volume (v) slice (s) slice adjusted (sa) Enter choice: sa
Enter minimum counts to determine adjusted values low: 100 high: 100
Segmentation methods require binning data Default histogram contains 128 bins. Change number of bins? (y,n(dflt)): n
Merge histogram files of diffused image (y,n(dflt)): y Number of histogram files to be merged per page: 2 histogram files arranged nrows by ncols on a page Enter nrows and ncols: 1 2
Enter the title for histogram: berea
Enter the data label for histogram: \0
Specify layout of 3 merged tomographic+diffused raster files Regular matrix arrangment (r) user specified arrangment (u) Enter choice (r(dflt),u): r tomographic+diffused raster files arranged nrows by ncols on a page Enter nrows and ncols: 2 2
Rasterfile colormap choices rainbow (r) greyscale with void white (gv) greyscale with material white (gm) pinkscale with void pale (pv) pinkscale with material pale (pm) Enter choice (r,gv(dflt),gm,pv,pm): gv