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| | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE region format. | | | | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE region format. | | | ||
| | Decision Rule | Decision Rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | | Decision Rule | Decision Rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | ||
| - | | Node Weight | Floating point | This node weight (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | | + | | Reliability | Floating point | The reliability (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | |
| | Non Class Name | String | If Multi-Class support is active, the discarded hypothesis will fall in the node named by this parameter. | One string with the name of some node in the tree, in the same level. | | | | Non Class Name | String | If Multi-Class support is active, the discarded hypothesis will fall in the node named by this parameter. | One string with the name of some node in the tree, in the same level. | | | ||
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| | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE regions format. | | | | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE regions format. | | | ||
| | Decision Rule | Decision Rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | | Decision Rule | Decision Rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | ||
| - | | Node Weight | Floating point | This node weight (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | | + | | Reliability | Floating point | The reliability (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | |
| | Euclidean Distance Threshold | Floating point | The minimum Euclidean Distance between each segment feature. | Greater than 0. | This parameter is required to merge adjacent block segments when the optimization option is enabled | | | Euclidean Distance Threshold | Floating point | The minimum Euclidean Distance between each segment feature. | Greater than 0. | This parameter is required to merge adjacent block segments when the optimization option is enabled | | ||
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| | Number of grid lines | Integer | Number of lines to divide the image. | Greater than zero. | | | | Number of grid lines | Integer | Number of lines to divide the image. | Greater than zero. | | | ||
| | Number of grid columns | Integer | Number of columns to divide the image. | Greater than zero. | | | | Number of grid columns | Integer | Number of columns to divide the image. | Greater than zero. | | | ||
| - | | Node Weight | Floating point | This node weight (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | | + | | Reliability | Floating point | The reliability (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | |
| ===== TerraAIDA NDVI Segmenter ===== | ===== TerraAIDA NDVI Segmenter ===== | ||
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| **Multi-Class support** | **Multi-Class support** | ||
| - | Yes. If you select //true// in the "Top Down Multi-Class" option, you must create another node in the same level with a corresponding opposite name, with prefix "n-". For example, if this class name is "MyClass" the opposite class name will be "n-MyClass". Hypothesis discarded by this operator will be classified as "n-MyClass". | + | Yes. If you select //true// in the "Top Down Multi-Class" option, you must create another node in the same level with a corresponding opposite name, with prefix "n-". For example, if this class name is "MyClass" the opposite class name will be "n-MyClass". Hypothesis discarded by this operator will be classified as "n-MyClass". Alternatively, you can define a new node name in the input parameter named **Non Class Name**. |
| [[interimage:example_supervised_c45|Example of using Multi-Class support.]] | [[interimage:example_supervised_c45|Example of using Multi-Class support.]] | ||
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| | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE regions format. | | | | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE regions format. | | | ||
| | Decision Rule | Decision Rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | | Decision Rule | Decision Rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | ||
| - | | Node Weight | Floating point | This node weight (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | | + | | Reliability | Floating point | The reliability (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | |
| + | | Non Class Name | String | If Multi-Class support is active, the discarded hypothesis will fall in the node named by this parameter. | One string with the name of some node in the tree, in the same level. | | | ||
| ===== TerraAIDA Region Growing Segmenter ===== | ===== TerraAIDA Region Growing Segmenter ===== | ||
| Line 298: | Line 299: | ||
| | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE regions format. | | | | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE regions format. | | | ||
| | Decision Rule | Decision Rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | | Decision Rule | Decision Rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | ||
| - | | Node Weight | Floating point | This node weight (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | | + | | Reliability | Floating point | The reliability (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | |
| ** Segmentation Example** | ** Segmentation Example** | ||
| Line 348: | Line 349: | ||
| | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE region format. | | | | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE region format. | | | ||
| | Decision Rule | Decision rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | | Decision Rule | Decision rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | ||
| - | | Node Weight | Floating point | This node weight (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | | + | | Reliability | Floating point | The reliability (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | |
| {{ :interimage:shape_file_import_example.png }} | {{ :interimage:shape_file_import_example.png }} | ||
| Line 373: | Line 374: | ||
| **Multi-Class support** | **Multi-Class support** | ||
| - | Yes. If you select //true// in the "Top Down Multi-Class" option, you must create another node in the same level with a corresponding opposite name, with prefix "n-". For example, if this class name is "MyClass" the opposite class name will be "n-MyClass". Hypothesis discarded by this operator will be classified as "n-MyClass". | + | Yes. If you select //true// in the "Top Down Multi-Class" option, you must create another node in the same level with a corresponding opposite name, with prefix "n-". For example, if this class name is "MyClass" the opposite class name will be "n-MyClass". Hypothesis discarded by this operator will be classified as "n-MyClass". Alternatively, you can define a new node name in the input parameter named **Non Class Name**. |
| [[interimage:example_supervised_c45|Example of using Multi-Class support.]] | [[interimage:example_supervised_c45|Example of using Multi-Class support.]] | ||
| Line 394: | Line 395: | ||
| | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE regions format. | | | | Training Set File | *.shp | A file with training samples for supervised classification. | The file must be in the InterIMAGE regions format. | | | ||
| | Decision Rule | Decision Rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | | Decision Rule | Decision Rule | Decision rule applied to the generated hypothesis. | | Leave blank to accept all generated hypothesis. | | ||
| - | | Node Weight | Floating point | This node weight (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | | + | | Reliability | Floating point | The reliability (higher priority will be given to nodes with higher weights in cases where there are geographic overlays). | [0.0, 1.0] | | |
| + | | Non Class Name | String | If Multi-Class support is active, the discarded hypothesis will fall in the node named by this parameter. | One string with the name of some node in the tree, in the same level. | | | ||
| {{ :interimage:shape_file_intersection_example.png }} | {{ :interimage:shape_file_intersection_example.png }} | ||
