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geodma_2:features [2021/08/27 22:14] – [Segmentation-based spatial features] tkortinggeodma_2:features [2026/01/22 12:33] (atual) – [Segmentation-based spatial features] thales
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 | CONTSE_BAND | Contrast SE returns a measure of the intensity contrast between a pixel and its southeast neighbor over the object. Contrast is 0 for a constant object. It is also known as //Sum of Squares Variance// | $Contrast = \sum_{i=0}^{D-1}\sum_{j=0}^{D-1}p_{i,j} . |i - j|^2$         | $[0, (size(GLCM, 1)-1)^2]$ | - | | CONTSE_BAND | Contrast SE returns a measure of the intensity contrast between a pixel and its southeast neighbor over the object. Contrast is 0 for a constant object. It is also known as //Sum of Squares Variance// | $Contrast = \sum_{i=0}^{D-1}\sum_{j=0}^{D-1}p_{i,j} . |i - j|^2$         | $[0, (size(GLCM, 1)-1)^2]$ | - |
 | DISSE_BAND | Dissimilarity SE measures how different the elements of the GLCM are from each other and it is high when the local region has a high contrast. | $dissimilarity = \sum_{i=0}^{D-1}\sum_{j=0}^{D-1}p_{i,j}|i-j|$ | $\geq 0$ | - | | DISSE_BAND | Dissimilarity SE measures how different the elements of the GLCM are from each other and it is high when the local region has a high contrast. | $dissimilarity = \sum_{i=0}^{D-1}\sum_{j=0}^{D-1}p_{i,j}|i-j|$ | $\geq 0$ | - |
-| ENERGSE_BAND    | Energy SE returns the squared root of Angular Second Moment, computed by the sum of the squared elements in GLCM. Energy is 1 for a constant image.  | $energy = \sum_{i=0}^{D-1} \sum{j=0}^{D-1} p_{i,j}^2}$ | $[0,1]$ | - |+| ENERGSE_BAND    | Energy SE returns the squared root of Angular Second Moment, computed by the sum of the squared elements in GLCM. Energy is 1 for a constant image.  | $energy = \sum_{i=0}^{D-1}\sum_{j=0}^{D-1} p_{i,j}^2$ | $[0,1]$ | - |
 | ENTRSE_BAND   | Entropy SE measures the disorder in an image. When the image is not uniform, many GLCM elements have small values, resulting in large entropy. | $entropy = -\sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} p_{ij} . \log{p_{ij}}$ | $\geq 0$ | - | | ENTRSE_BAND   | Entropy SE measures the disorder in an image. When the image is not uniform, many GLCM elements have small values, resulting in large entropy. | $entropy = -\sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} p_{ij} . \log{p_{ij}}$ | $\geq 0$ | - |
 | HOMOGSE_BAND | Homogeneity SE assumes higher values for smaller differences in the GLCM. Also called //Inverse Difference Moment//. Homogeneity is 1 for a diagonal GLCM. | $homog = \sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} \frac{p_{ij}}{1 + (i - j)^2}$ | $\geq 0$ | - | | HOMOGSE_BAND | Homogeneity SE assumes higher values for smaller differences in the GLCM. Also called //Inverse Difference Moment//. Homogeneity is 1 for a diagonal GLCM. | $homog = \sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} \frac{p_{ij}}{1 + (i - j)^2}$ | $\geq 0$ | - |
-| KURT_BAND     | Kurtosis returns the kurtosis value for all the valid pixels (not dummy) inside the object.                                                | $K = \frac{n(n+1)(n-1)}{(n-2)(n-3)} . \frac{\sum_{i=1}^{N}(px_i-\mu)^4}{(\sum_{i=1}^N (px_i - \mu)^2)^2$ | $\geq 1$ | -  |+| KURT_BAND     | Kurtosis returns the kurtosis value for all the valid pixels (not dummy) inside the object.  | $K = \frac{n(n+1)(n-1)}{(n-2)(n-3)}.\frac{\sum_{i=1}^{N}(px_i-\mu)^4}{(\sum_{i=1}^N (px_i - \mu)^2)^2}$ | $\geq 1$ | -  |
 | MAX_VAL_BAND  | Maximum Value computes the maximum gray level value (not dummy) inside the object.                                                | $maxVal = max(X)$ | $X$ | $px$  | | MAX_VAL_BAND  | Maximum Value computes the maximum gray level value (not dummy) inside the object.                                                | $maxVal = max(X)$ | $X$ | $px$  |
 | MEAN_BAND         | Mean computes the average value for all $N$ pixels inside the object. | $\mu = \frac{\sum_{i=1}^N px_i}{N}$ | $\geq 0$ | $px$ | | MEAN_BAND         | Mean computes the average value for all $N$ pixels inside the object. | $\mu = \frac{\sum_{i=1}^N px_i}{N}$ | $\geq 0$ | $px$ |
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 | MODE_BAND         | Mode returns the most occurring gray level value (mode) for all $N$ (not dummy) pixels inside the object. When the object is multimodal, the first value is assumed. | | $X$ | $px$ | | MODE_BAND         | Mode returns the most occurring gray level value (mode) for all $N$ (not dummy) pixels inside the object. When the object is multimodal, the first value is assumed. | | $X$ | $px$ |
 | N_MOD_BAND    | Num Modes returns the number of modes for the object.         | | $\geq 1$ | $px$ | | N_MOD_BAND    | Num Modes returns the number of modes for the object.         | | $\geq 1$ | $px$ |
-| SKEW_BAND     | Returns the Skewness value for all the valid pixels (not dummy) inside the object.                                                | $S = \frac{n\sqrt{n-1}}{n-2} . \frac{\sum_{i=1}^{N}(px_i-\mu)^3}{(\sum_{i=1}^N (px_i - \mu)^2)^\frac{3}{2}$ | - | -  |+| SKEW_BAND     | Returns the Skewness value for all the valid pixels (not dummy) inside the object.                                                | $S = \frac{n\sqrt{n-1}}{n-2}.\frac{\sum_{i=1}^{N}(px_i-\mu)^3}{(\sum_{i=1}^N (px_i - \mu)^2)^\frac{3}{2}}$ | - | -  |
 | STDDEV_BAND | Returns the Standard Deviation of all $N$ (not dummy) pixels ($\mu$ is the mean value) inside the object. | $\sigma = \sqrt{\frac{1}{N-1}\sum_{i=1}^N \left(px_i - \mu \right)^2}$ | $\geq 0$ | $px$ | | STDDEV_BAND | Returns the Standard Deviation of all $N$ (not dummy) pixels ($\mu$ is the mean value) inside the object. | $\sigma = \sqrt{\frac{1}{N-1}\sum_{i=1}^N \left(px_i - \mu \right)^2}$ | $\geq 0$ | $px$ |
 | SUM_BAND | Returns the Sum of all $N$ (not dummy) pixels inside the object.                                           | $sum = \sum_{i = 1}^{N}px_i$ | $\geq 0$ | $px$ | | SUM_BAND | Returns the Sum of all $N$ (not dummy) pixels inside the object.                                           | $sum = \sum_{i = 1}^{N}px_i$ | $\geq 0$ | $px$ |
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 | Name | Description | Formula | Range | Units | | Name | Description | Formula | Range | Units |
-| POL_ANGLE | Represents the main angle of an object. It is obtained by computing the minimum circumscribing ellipse, and the angle of the biggest radius of the ellipse suits to the object's angle. | | $\left[-\pi, \pi]$ | $rad$ |+| POL_ANGLE | Represents the main angle of an object. It is obtained by computing the minimum circumscribing ellipse, and the angle of the biggest radius of the ellipse suits to the object's angle. | | $\left[-\pi, \pi\right]$ | $rad$ |
 | POL_AREA | Returns the area of the object, measured in the unit of measure of the current Spatial Reference System.                                   | | $\geq 0$ | $[m,degrees,...]^2$ | | POL_AREA | Returns the area of the object, measured in the unit of measure of the current Spatial Reference System.                                   | | $\geq 0$ | $[m,degrees,...]^2$ |
 | PBOX_AREA | Returns the bounding box area of an object, measured in the unit of measure of the current Spatial Reference System. | | $\geq 0$ | $[m,degrees,...]^2$ |  | PBOX_AREA | Returns the bounding box area of an object, measured in the unit of measure of the current Spatial Reference System. | | $\geq 0$ | $[m,degrees,...]^2$ | 
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 | PBOX_LEN | It is the height of the object's bounding box, measured in the unit of measure of the current Spatial Reference System. | | $\geq 0$ | $[m, degrees, ...]$ | | PBOX_LEN | It is the height of the object's bounding box, measured in the unit of measure of the current Spatial Reference System. | | $\geq 0$ | $[m, degrees, ...]$ |
 | P_PERIM | Returns the perimeter of the object, measured in the unit of measure of the current Spatial Reference System. | | $\geq 0$ | $[m,degrees,...]$ | | P_PERIM | Returns the perimeter of the object, measured in the unit of measure of the current Spatial Reference System. | | $\geq 0$ | $[m,degrees,...]$ |
-| P_PERARAT | Calculates the ratio between the perimeter and the area of an object. | $\frac{\textit{perimeter}}{\textit{area}}$ | $\geq 0$ | $px^{-1}$ |+| P_PERARAT | Calculates the ratio between the perimeter and the area of an object. | $\frac{perimeter}{area}$ | $\geq 0$ | $px^{-1}$ |
 | PRECTFIT | This feature fits a minimum rectangle outside the object and calculates the ratio between its area and the area of this rectangle. The closer to $1$ is this feature, the most similar to a rectangle. | $\frac{\textit{area}}{\textit{minBoxArea}}$ | $\left[0, 1\right]$ | - | | PRECTFIT | This feature fits a minimum rectangle outside the object and calculates the ratio between its area and the area of this rectangle. The closer to $1$ is this feature, the most similar to a rectangle. | $\frac{\textit{area}}{\textit{minBoxArea}}$ | $\left[0, 1\right]$ | - |
 | PBOX_WIDTH | Returns the width of the object's bounding box, measured in the unit of measure of the current Spatial Reference System. | | $\geq 0$ | $[m, degrees, ...]$ | | PBOX_WIDTH | Returns the width of the object's bounding box, measured in the unit of measure of the current Spatial Reference System. | | $\geq 0$ | $[m, degrees, ...]$ |
-| P_COMPAC | Returns the compacity of the object. | $\frac{\textit{perimAreaRatio}}{\sqrt{\textit{area}}}}$ | $\geq 0$ | - |+| P_COMPAC | Returns the compacity of the object. | $\frac{perimAreaRatio}{\sqrt{area}}$ | $\geq 0$ | - |
 | PDENSITY | This feature corresponds to the ratio between the polygon area and the polygon radius. | $\frac{\textit{area}}{\textit{radius}}$ | $\geq 0$ | - | | PDENSITY | This feature corresponds to the ratio between the polygon area and the polygon radius. | $\frac{\textit{area}}{\textit{radius}}$ | $\geq 0$ | - |
-| PSHAPEIDX | This feature corresponds to the ratio between the polygon perimeter and the squared root of the polygon area. | $\frac{\textit{perimeter}}{4 * \sqrt{\textit{area}}}$ | $\geq 0$ | - |+| PSHAPEIDX | This feature corresponds to the ratio between the polygon perimeter and the squared root of the polygon area. | $\frac{\textit{perimeter}}{4\sqrt{\textit{area}}}$ | $\geq 0$ | - |
  
  
geodma_2/features.1630102487.txt.gz · Última modificação: 2021/08/27 22:14 por tkorting