Documentation of 'Catalano.Imaging.Texture.HaralickDescriptors' Java class
HaralickDescriptors
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Catalano.Imaging.Texture

Class HaralickDescriptors


  • public final class HaralickDescriptors
extends java.lang.Object
    Haralick's texture classification metrics.

    • Constructor Summary

      Constructors 
      Constructor and Description
      HaralickDescriptors()
      Don't let anyone instantiate this class.

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method and Description
      static double ClusterProminence(double[][] coocurrenceMatrix)
      Compute cluster prominence.
      static double ClusterShade(double[][] coocurrenceMatrix)
      Compute cluster shade.
      static double ClusterTendency(double[][] coocurrenceMatrix)
      Probabilities are weighted by their deviation from the mean values.
      static double Contrast(double[][] coocurrenceMatrix)
      Weighs probabilities by their distance to the diagonal.
      static double Correlation(double[][] coocurrenceMatrix)
      Increases in the presence of large homogeneous regions.
      static double Energy(double[][] coocurrenceMatrix)
      Compute energy.
      static double Entropy(double[][] coocurrenceMatrix)
      Compute entropy.
      double[] getFeatures(double[][] coocurrenceMatrix) 
      static double Inertia(double[][] coocurrenceMatrix)
      An exaggeration of the contrast metric, as it weighs probabilities by the square of the distance to the diagonal.
      static double InverseDifference(double[][] coocurrenceMatrix)
      Valid only for nondiagonal elements i != j .
      static double InverseDifferenceMoment(double[][] coocurrenceMatrix)
      The metric complementary to inertia.
      static double TextureHomogeneity(double[][] coocurrenceMatrix)
      Weighs the probabilities by proximity to the diagonal and is therefore the complement of contrast.

      • Methods inherited from class java.lang.Object

        equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Constructor Detail

      • HaralickDescriptors

        public HaralickDescriptors()
        Don't let anyone instantiate this class.

    • Method Detail

      • getFeatures

        public double[] getFeatures(double[][] coocurrenceMatrix)

      • Energy

        public static double Energy(double[][] coocurrenceMatrix)
        Compute energy.
        Parameters:
        coocurrenceMatrix - Coocurrence matrix.
        Returns:
        Energy.

      • Entropy

        public static double Entropy(double[][] coocurrenceMatrix)
        Compute entropy.
        Parameters:
        coocurrenceMatrix - Coocurrence matrix.
        Returns:
        Entropy.

      • Contrast

        public static double Contrast(double[][] coocurrenceMatrix)
        Weighs probabilities by their distance to the diagonal.
        Parameters:
        coocurrenceMatrix - Coocurrence matrix.
        Returns:
        Contrast.

      • Inertia

        public static double Inertia(double[][] coocurrenceMatrix)
        An exaggeration of the contrast metric, as it weighs probabilities by the square of the distance to the diagonal.
        Parameters:
        coocurrenceMatrix - Coocurrence matrix.
        Returns:
        Inertia.

      • Correlation

        public static double Correlation(double[][] coocurrenceMatrix)
        Increases in the presence of large homogeneous regions.
        Parameters:
        coocurrenceMatrix - Coocurrence matrix.
        Returns:
        Correlation.

      • TextureHomogeneity

        public static double TextureHomogeneity(double[][] coocurrenceMatrix)
        Weighs the probabilities by proximity to the diagonal and is therefore the complement of contrast.
        Parameters:
        coocurrenceMatrix - Coocurrence matrix.
        Returns:
        Texture homogeneity.

      • InverseDifference

        public static double InverseDifference(double[][] coocurrenceMatrix)
        Valid only for nondiagonal elements i != j . Closely related to texture homogeneity.
        Parameters:
        coocurrenceMatrix - Coocurrence matrix.
        Returns:
        Inverse difference.

      • InverseDifferenceMoment

        public static double InverseDifferenceMoment(double[][] coocurrenceMatrix)
        The metric complementary to inertia. Probabilities are weighted by proximity to the diagonal.
        Parameters:
        coocurrenceMatrix - Coocurrence matrix.
        Returns:
        Invere difference moment.

      • ClusterTendency

        public static double ClusterTendency(double[][] coocurrenceMatrix)
        Probabilities are weighted by their deviation from the mean values.
        Parameters:
        coocurrenceMatrix - Coocurrence matrix.
        Returns:
        Cluster tendency.

      • ClusterShade

        public static double ClusterShade(double[][] coocurrenceMatrix)
        Compute cluster shade.
        Parameters:
        coocurrenceMatrix - Coocurrence matrix.
        Returns:
        Cluster shade.

      • ClusterProminence

        public static double ClusterProminence(double[][] coocurrenceMatrix)
        Compute cluster prominence.
        Parameters:
        coocurrenceMatrix - Coocurrence matrix.
        Returns:
        Cluster priminence.
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