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Specific root length and median root radius were the best predictors for hydraulic conductivity changes.
OSEM ordered subset expected maximum, MAP maximum a posteriori, MRP median root prior.
The Median Root Prior (MRP) used a 3x3x3 neighbourhood and a Bayes parameter of 0.1 for all frames.
As a result of the incorporated smoothing or median root priors, the images from MAP reconstructions were smoother and more homogeneous within the compartments than the OSEM3D images.
In Hybrid Recon also, a maximum a posteriori (MAP) algorithm with a smoothing prior (MAPsmoothing) and with a median root prior (MAPMRP) was available.
At the last iteration, the regularization is based on the median root prior method that was first introduced for positron emission tomography (PET) [18] and whose extension to SPECT was shown to be straightforward [19].
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Using previously calibrated ("default") values of a free parameter γ, all models predict the observations reasonably well (median root-mean-square wave height errors are between 10%and20%0%) at all field sites.
Six features were considered in this study: normalised spectral index (NSM5), median frequency, root mean square, waveform length, normalised root mean square (NRMS), and increase in synchronization (IIS) index.
Note that this sequence is a median filter root sequence.
Step-and-ramp sequence (median filter root) for k=1,2,…,420; Fig. 1 A simulated 420-point signal.
The median of Root Mean Square Error was about 0.026 cm d−1 and the median of maximum cross correlation was 0.96 when the method was calibrated adequately.
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