Explains the ghost effect to ODF reconstruction and the MTEX option ghostcorrection.

A general problem in estimating an ODF from pole figure data is the fact that the odd order Fourier coefficients of the ODF
are not present anymore in the pole figure data and therefore it is difficult to estimate them. Artifacts in the estimated
ODF that are due to underestimated odd order Fourier coefficients are called **ghost effects**. It is known that for sharp textures the ghost effect is relatively small due to the strict non-negativity condition. For
weak textures, however, the ghost effect might be remarkable. For those cases, **MTEX** provides the option **ghost_correction** which tries to determine the uniform portion of the unknown ODF and to transform the unknown weak ODF into a sharp ODF by
substracting this uniform portion. This is almost the approach Matthies proposed in his book (He called the uniform portion
**phon**). In this section, we are going to demonstrate the power of ghost correction at a simple, synthetic example.

A unimodal ODF with a high uniform portion.

cs = crystalSymmetry('222'); mod1 = orientation('Euler',0,0,0,cs); odf = 0.9*uniformODF(cs) + ... 0.1*unimodalODF(mod1,'halfwidth',10*degree)

odf = ODF crystal symmetry : 222 specimen symmetry: 1 Uniform portion: weight: 0.9 Radially symmetric portion: kernel: de la Vallee Poussin, halfwidth 10° center: (0°,0°,0°) weight: 0.1

% specimen directions r = equispacedS2Grid('resolution',5*degree,'antipodal'); % crystal directions h = [Miller(1,0,0,cs),Miller(0,1,0,cs),Miller(0,0,1,cs)]; % compute pole figures pf = calcPoleFigure(odf,h,r); plot(pf)

without ghost correction:

rec = calcODF(pf,'noGhostCorrection','silent');

with ghost correction:

`rec_cor = calcODF(pf,'silent');`

without ghost correction:

`calcError(pf,rec,'RP')`

progress: 100% ans = 0.0087 0.0087 0.0106

with ghost correction:

`calcError(pf,rec_cor,'RP')`

progress: 100% ans = 0.0267 0.0258 0.0273

without ghost correction:

calcError(rec,odf)

progress: 100% ans = 0.1253

with ghost correction:

calcError(rec_cor,odf)

progress: 100% ans = 0.0053

without ghost correction:

plot(rec,'sections',9,'silent','sigma')

progress: 100%

with ghost correction:

plot(rec_cor,'sections',9,'silent','sigma')

progress: 100%

radial plot of the true ODF

close all f = fibre(Miller(0,1,0,cs),yvector); plot(odf,f,'linewidth',2); hold all

radial plot without ghost correction:

`plot(rec,f,'linewidth',2);`

radial plot with ghost correction:

plot(rec_cor,f,'linestyle','--','linewidth',2); hold off legend({'true ODF','without ghost correction','with ghost correction'})

Next, we want to analyze the fit of the Fourier coefficients of the reconstructed ODFs. To this end, we first compute Fourier representations for each ODF

odf = FourierODF(odf,25) rec = FourierODF(rec,25) rec_cor = FourierODF(rec_cor,25)

odf = ODF crystal symmetry : 222 specimen symmetry: 1 Harmonic portion: degree: 25 weight: 1 rec = ODF crystal symmetry : 222 specimen symmetry: 1 Harmonic portion: degree: 25 weight: 1 rec_cor = ODF crystal symmetry : 222 specimen symmetry: 1 Harmonic portion: degree: 25 weight: 1

without ghost correction:

`calcError(rec,odf,'L2')`

ans = 0.3602

with ghost correction:

`calcError(rec_cor,odf,'L2')`

ans = 0.0316

Plotting the Fourier coefficients of the recalculated ODFs shows that the Fourier coefficients without ghost correction oscillates much more than the Fourier coefficients with ghost correction

true ODF

close all; plotFourier(odf,'linewidth',2)

keep plotting windows and add next plots

`hold all`

Without ghost correction:

`plotFourier(rec,'linewidth',2)`

with ghost correction

plotFourier(rec_cor,'linewidth',2) legend({'true ODF','without ghost correction','with ghost correction'}) % next plot command overwrites plot window hold off

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