In this space, you will find descriptions of all the descriptors in Breeze.
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Area of subsamples Calculate the area of the given class in a sub-sample.
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Axis percentage (descriptor) Center position percentage from the heaviest end along its main axis
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Band math Arithmetic expressions with spectral bands
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Classification of categories Classifies object into categories
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Classification using expression Use expressions to calculate properties of individual classes in a category.
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Clustering Unsupervised cluster classification
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Combine properties Combine properties, categories, or descriptors using expression to calculate new properties and display them in the table view.
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Combined RGB image Combine descriptor values to three channel RGB image
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Data slicing Classify data based on descriptor value ranges
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Distribution of subsamples Calculates the distribution of the subsamples in the measurement.
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Distribution statistics Calculate distribution statistics of quantification models.
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Dominant mineral Show dominant mineral class category for pixel majority classification
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Metadata from measurement Displays metadata in the table view.
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Model data (descriptor) Show calculated model data in table for each training sample
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MWL mapping Minimum wavelength mapping
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Number of subsamples Counts the number of samples in the measurement at different depths of the analyze tree
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PCA model Unsupervised PCA model
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Pixels by given class Calculate the number of pixels from a selected class in the objects.
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Python script (descriptor) Add descriptor value from external python script
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Quantification of properties Quantification of properties in a sample
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Registration depth Show the registration depth
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Row / column index Create an index for row-major or column-major order when objects are arranged in a grid
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Saturated pixels Show the saturation for each pixel
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Segmentation label Label object according to text file
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Shape and size Calculate the spatial value from samples in mm or by pixels for some predetermine spatial output.
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Spectral angle mapper (descriptor) Use spectral angle maps for object classification
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Statistics (properties) Outputs average sample quantitative error per cent.
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Statistics of pixels (properties) Summaries the pixel statistics of the objects.
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Subsamples by given class Counts the number of objects in a given class from a specified subsample.
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Summary of subsamples Subsample are summarized and displayed in the table view
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Train / Test Add column with information if data is in training set or test set
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Ternary RGB Combine three classifications to single rgb image.
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Unique ID (descriptor) Displays the Id of the selected output in the table view.
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Update classification (descriptor) Update or add custom-created classes. The update or new class will be assigned if the expression is satisfied.
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Unmixing (descriptor) Use the spectral information to gain information about the objects and display them in the table view
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USGS PRISM MICA Material Identification and Classification Algorithm Expert System
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Vegetation index Calculate the vegetation index using one of several predefined equations.
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White / dark values Choose a reference (dark or white) and display the selected output in the table view.