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interimage:operators_documentation [2010/06/23 14:41] – tkortinginterimage:operators_documentation [2011/01/28 19:05] – tkorting
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 [[interimage:|InterIMAGE wiki]]  [[interimage:|InterIMAGE wiki]] 
- 
  
 ====== TerraAIDA Operators Documentation ====== ====== TerraAIDA Operators Documentation ======
-Operators reference version: 1.0.5 +Operators reference version: 1.0.6 
-===== TerraAIDA Arithmetic =====+ 
 +InterIMAGE is a multi-platform framework, written in C++, currently with implementations for LINUX and Windows operational systems. Moreover, InterIMAGE provides support for the integration of image processing operators in the interpretation process and, as such operators are treated as external programs by its control mechanism, they can be coded in any computer language, and even in proprietary programs. The InterIMAGE framework offers, nonetheless, a repository of operators, called TerraAIDA ([[http://www.dpi.inpe.br/terraaida]]), assembled with software classes and functions supplied by the [[http://www.terralib.org/|TerraLib]] library. 
 + 
 +===== TA Arithmetic =====
  
 **Authors**  **Authors** 
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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 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. | |
  
-===== TerraAIDA Baatz Segmenter =====+===== TA Baatz Segmenter =====
  
 **Authors**  **Authors** 
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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 |
  
-===== TerraAIDA Bottom-Up Export =====+===== TA Bottom-Up Export =====
  
 **Author**  **Author** 
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 {{ interimage:buexport.png }} {{ interimage:buexport.png }}
  
-===== TerraAIDA C4.5 Classifier =====+===== TA C4.5 Classifier =====
  
 **Author**  **Author** 
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 ^ Parameter Name  ^ Type            ^ Description               ^   Valid Values      ^   Note   ^    ^ Parameter Name  ^ Type            ^ Description               ^   Valid Values      ^   Note   ^   
 | a) Training Set File | * .shp | Training shape file name.   | A valid shape file name.  | The shapefile must be composed by polygons, their respective attributes and particularly one attribute called "class".  | | a) Training Set File | * .shp | Training shape file name.   | A valid shape file name.  | The shapefile must be composed by polygons, their respective attributes and particularly one attribute called "class".  |
-| b) Input Shape File | *.shp | Shape file name of the file to be classified. | A valid shape file name. | The shapefile must be composed by polygons, and the *same set of attributes* in the training shape file. |+| b) Input Shape File | *.shp | Shape file name of the file to be classified. | A valid shape file name. | The shapefile must be composed by polygons, and the **same set of attributes** in the training shape file. |
  
 Note: The generated decision tree will be placed in a //.txt// file, located in the **same place as your input shape file**, with the same name as your input file. Note: The generated decision tree will be placed in a //.txt// file, located in the **same place as your input shape file**, with the same name as your input file.
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 One example of this operator can be found [[interimage:examples:supervised_c45|here]]. One example of this operator can be found [[interimage:examples:supervised_c45|here]].
  
-===== TerraAIDA Checkerboard Segmenter =====+ 
 + 
 + 
 +===== TA Checkerboard Segmenter =====
  
 **Author**  **Author** 
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 ^ Parameter Name  ^ Type            ^ Description               ^   Valid Values      ^   Note   ^    ^ Parameter Name  ^ Type            ^ Description               ^   Valid Values      ^   Note   ^   
-| 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] |  |+| Amount of points in X | Integer | Number of pixels per cell in X dimension.   | Greater than zero.  |          | 
 +| Amount of points in Y | Integer | Number of pixels per cell in Y dimension.     | Greater than zero.  |          | 
 +| 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 =====+ 
 +===== TA NDVI Segmenter =====
  
 **Authors**  **Authors** 
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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 =====+===== TA Region Growing Segmenter =====
  
 **Authors**  **Authors** 
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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] |  |
  
 ** Segmentation Example** ** Segmentation Example**
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-===== TerraAIDA ShapeFile Import =====+===== TA ShapeFile Import =====
  
 **Authors**  **Authors** 
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 Shape file attributes with the the following names will not be imported: REGION, CLASS, ID, GEOWEST, GEONORTH, GEOEAST, GEOSOUTH, FILE_GEOWEST, FILE_GEONORTH, FILE_GEOEAST, FILE_GEOSOUTH, P, FILE, LLX, LLY, URX, URY. Shape file attributes with the the following names will not be imported: REGION, CLASS, ID, GEOWEST, GEONORTH, GEOEAST, GEOSOUTH, FILE_GEOWEST, FILE_GEONORTH, FILE_GEOEAST, FILE_GEOSOUTH, P, FILE, LLX, LLY, URX, URY.
 +
 +**Processing sequence**
 +
 +  -Read user input shape file.
 +  -Generates the intersection between the loaded shape file polygons and the operator execution area.
 +  -Apply the user decision rule (using the supplied training set) over the intersection  polygons.
 +  -Generate the output hypothesis.
  
 **Input parameters** **Input parameters**
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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] |  |
  
 {{ :interimage:shape_file_import_example.png }} {{ :interimage:shape_file_import_example.png }}
  
-===== TerraAIDA ShapeFile Intersection =====+===== TA ShapeFile Intersection =====
  
 **Authors**  **Authors** 
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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.]]
 +
 +**Processing sequence**
 +
 +  -Read user input shape file.
 +  -Generates the intersection between the loaded shape file polygons and the operator execution area.
 +  -Using the intersection result generates a set of intermediate hypothesis of "MyClass" and the opposite class "n-MyClass", as describe above.
 +  -Apply the user decision rule (using the supplied training set) over the intermediate hypothesis set.
 +  -Generate the output hypothesis from the decision rule result.
  
 **Input parameters** **Input parameters**
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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. | |
  
 {{ :interimage:shape_file_intersection_example.png }} {{ :interimage:shape_file_intersection_example.png }}
interimage/operators_documentation.txt · Última modificação: 2016/08/05 14:44 por tkorting