Free planes script

C = INSERTROWS(A,B,IND) inserts the rows of matrix B into the matrix A at the positions IND. Row k of matrix B will be inserted after position IND(k)in the matrix A. If A is a N-by-X matrix and B is a M-by-X matrix, C will be a (N M)-by-X matrix. IND can contain non-integers.

If B is a 1-by-N matrix, B will be inserted for each insertion position specified by IND. If IND is a single value, the whole matrix B will be inserted at that position. If B is a single value, B is expanded to a row vector. In all other cases, the number of elements in IND should be equal to the number of rows in B, and the number of columns, planes etc should be the same for both matrices A and B. If any of the inputs are empty, C will return A.

Examples:
% the size of A,B, and IND all match
C = insertrows(rand(5,2),zeros(2,2),[1.5 3])
% the row vector B is inserted twice
C = insertrows(ones(4,3),1:3,[1 Inf])
% matrix B is expanded to a row vector and inserted twice (as in 2)
C = insertrows(ones(5,3),999,[2 4])
% the whole matrix B is inserted once
C = insertrows(ones(5,3),zeros(2,3),2)
[C, RA, RB] = INSERTROWS(...) will return the row indices RA and RB for which C
corresponds to the rows of either A and B.
[c,ra,rb] = insertrows([1:4].,99,[0 3]) ;
c. % -> [99 1 2 3 99 4] ;
c(ra). % -> [1 2 3 4] ;
c(rb). % -> [99 99] ;
To insert columns, planes, etc., you can permute the inputs and ipermute the result.
A = ones(4,3) ; B = zeros(4,1) ;
C = insertrows(permute(A,[2 1]), permute(B,[2 1]),1) ;
C = ipermute(C,[2 1]) ;
See also PERMUTE, IPERMUTE, RESHAPE, CAT

Requirements:

• MATLAB Release: R13

Major Features:

1. Visualization: false color representation with different types of mapping
2. Shaded, logarithmical, gradient- and edge-detected, local contrast representation, Canny lines
3. OpenGL 3D data display: false color or material representation
4. Easily editable color maps and OpenGL materials
5. Basic operations: rotation, flipping, inversion, data arithmetic, crop, resampling
6. Leveling: plane leveling, profiles leveling, three-point leveling, facet leveling, polynomial background removal
7. Value reading, distance and angle measurement
8. Profiles: profile extraction, measuring distances in profile graph, profile export
9. Filtering: mean, median, conservative denoise, Kuwahara, minimum, maximum, checker pattern removal
10. General convolution filter with user-defined kernel
11. Statistical functions: Ra, RMS, projected and surface area, inclination, histograms, correlation functions, PSDF, 1D and 2D angular distributions, Minkowski functionals, facet orientation analysis
12. Statistical quantities calculated from area under arbitrary mask
13. Row/column statistical quantities plots
14. Grains: threshold marking and unmarking, watershed marking
15. Grain statistics: overall and distributions of size, height, area, volume, boundary length, bounding dimensions
16. Intergral transforms: 2D FFT, 2D continuous wavelet transform (CWT), 2D discrete wavelet transform (DWT), wavelet anisotropy detection
17. Fractal dimension analysis
18. Data correction: spot remove, outlier marking, scar marking, several line correction methods (median, modus)
19. Removal of data under arbitrary mask using Laplace or fractal interpolation
20. Automatic xy plane rotation correction
21. Arbitrary polynomial deformation on xy plane
22. 1D and 2D FFT filtering
23. Fast scan axis drift correction
24. Task editting: adding, removing or intersecting with rectangles and ellipses, inversion, extraction, expansion, shrinking
25. Simple graph function fitting, critical dimension determination
26. Axes scale callibration
27. Merging and immersion of images
28. Tip modelling, blind estimation, dilation and erosion