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geodma:features [2014/09/04 10:06] tkorting [Landscape-based features] |
geodma:features [2017/07/18 11:56] (current) tkorting |
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| - | ====== GeoDMA Features ====== | + | ====== GeoDMA 0.2 Features ====== |
| GeoDMA has metrics integrating Polygons, Cells, and Images. Through image segmentation, GeoDMA creates Polygons. | GeoDMA has metrics integrating Polygons, Cells, and Images. Through image segmentation, GeoDMA creates Polygons. | ||
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| | rX_entropy_B | Measures the disorder in an image. When the image is not uniform, many GLCM elements have small values, resulting in large entropy. | $-\sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} p_{ij} . \log{p_{ij}}$ | $\geq 0$ | - | | | rX_entropy_B | Measures the disorder in an image. When the image is not uniform, many GLCM elements have small values, resulting in large entropy. | $-\sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} p_{ij} . \log{p_{ij}}$ | $\geq 0$ | - | | ||
| | rX_homogeneity_B | Assumes higher values for smaller differences in the GLCM. | $\sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} \frac{p_{ij}}{1 + (i - j)^2}$ | $\geq 0$ | - | | | rX_homogeneity_B | Assumes higher values for smaller differences in the GLCM. | $\sum_{i=1}^{D - 1} \sum_{j=1}^{D - 1} \frac{p_{ij}}{1 + (i - j)^2}$ | $\geq 0$ | - | | ||
| - | | rX_mean_B | Returns the average value for all $N$ pixels inside the object. | $ \frac{\sum_{i=1}^N px_i} | {N}$ | $\geq 0$ | $px$ | | + | | rX_mean_B | Returns the average value for all $N$ pixels inside the object. | $ \frac{\sum_{i=1}^N px_i}{N}$ | $\geq 0$ | $px$ | |
| | rX_mode_B | Returns the most occurring value (mode) for all $N$ pixels inside the object. When the object is multimodal, the first value is assumed. | | $\geq 0$ | $px$ | | | rX_mode_B | Returns the most occurring value (mode) for all $N$ pixels inside the object. When the object is multimodal, the first value is assumed. | | $\geq 0$ | $px$ | | ||
| | rX_std_B | Returns the standard deviation of all $N$ pixels ($\mu$ is the mean value). | $\sqrt{\frac{1}{N-1}\sum_{i=1}^N \left(px_i - \mu \right)^2}$ | $\geq 0$ | $px$ | | | rX_std_B | Returns the standard deviation of all $N$ pixels ($\mu$ is the mean value). | $\sqrt{\frac{1}{N-1}\sum_{i=1}^N \left(px_i - \mu \right)^2}$ | $\geq 0$ | $px$ | | ||
