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Haralick Textural Features: Difference between revisions
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# Sum Average: <math>f_6 = \sum_{i=2}^{2N_g} ip_{x+y}(i)</math> | # Sum Average: <math>f_6 = \sum_{i=2}^{2N_g} ip_{x+y}(i)</math> | ||
# Sum Entropy: <math>f_7 = \sum_{i=2}^{2N_g} (i-f_6)^2 p_{x+y}(i)</math> | # Sum Entropy: <math>f_7 = \sum_{i=2}^{2N_g} (i-f_6)^2 p_{x+y}(i)</math> | ||
# Entropy: | #* Note that the original paper has a typo. | ||
# Difference Variance: | # Entropy: <math>f_9 = - \sum_i \sum_j p(i,j) \log(p(i,j))</math> | ||
# Difference Entropy: | # Difference Variance: <math>f_10= var(p_{x-y})</math> | ||
# Difference Entropy: <math>f_{11} = -\sum_{i=0}^{N_{g}-1} p_{x-y}(i) \log p_{x-y}(i)</math> | |||
# Information Measures of Correlation 1: | # Information Measures of Correlation 1: | ||
# Information Measures of Correlation 2: | # Information Measures of Correlation 2: | ||
# Maximal Correlation Coefficient: | # Maximal Correlation Coefficient: <math>f_{14} = (second largest eigenvalue of Q)^{1/2}</math> where <math>Q(i,j) = \sum_k \frac{p(i,k)p(j,k)}{p_x(i)p_y(k)}</math> | ||
Notation: | |||
* <math>p(i,j)</math> = i,j value in the noramlized co-occurance matrix | |||
* <math>p_x(i)</math> = marginal probability (<math>\sum_j p(i,j)</math>) | |||
* <math>N_g</math> number of gray tones | |||
==Resources== | ==Resources== | ||