glcm_features {ForestTools} | R Documentation |
GLCM Features
Description
GLCM Features
Usage
glcm_mean(glcm)
glcm_variance(glcm)
glcm_autoCorrelation(glcm)
glcm_cProminence(glcm)
glcm_cShade(glcm)
glcm_cTendency(glcm)
glcm_contrast(glcm)
glcm_correlation(glcm)
glcm_differenceEntropy(glcm, base = 2)
glcm_dissimilarity(glcm)
glcm_energy(glcm)
glcm_entropy(glcm, base = 2)
glcm_homogeneity1(glcm)
glcm_homogeneity2(glcm)
glcm_IDMN(glcm)
glcm_IDN(glcm)
glcm_inverseVariance(glcm)
glcm_maxProb(glcm)
glcm_sumAverage(glcm)
glcm_sumEntropy(glcm, base = 2)
glcm_sumVariance(glcm)
Arguments
glcm |
A matrix of class "glcm" produced by |
base |
Base of the logarithm in differenceEntropy. |
Functions
-
glcm_mean()
: Mean -
glcm_variance()
: Variance -
glcm_autoCorrelation()
: Autocorrelation -
glcm_cProminence()
: Cluster Prominence -
glcm_cShade()
: Cluster Shade -
glcm_cTendency()
: Cluster Tendency -
glcm_contrast()
: Contrast -
glcm_correlation()
: Correlation -
glcm_differenceEntropy()
: Difference Entropy -
glcm_dissimilarity()
: Dissimilarity -
glcm_energy()
: Energy -
glcm_entropy()
: Entropy -
glcm_homogeneity1()
: Homogeneity -
glcm_homogeneity2()
: Homogeneity 2 -
glcm_IDMN()
: Inverse Difference Moment (Normalized) -
glcm_IDN()
: Inverse Difference (Normalized) -
glcm_inverseVariance()
: Inverse Variance -
glcm_maxProb()
: Maximum Probability -
glcm_sumAverage()
: Sum Average -
glcm_sumEntropy()
: Sum Entropy -
glcm_sumVariance()
: Sum Variance
References
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0102107