FeatureStack3D (Fiji Javadocs 0-SNAPSHOT API)

java.lang.Object
- trainableSegmentation.FeatureStack3D

```
public class FeatureStack3D
extends Object
```
This class defines 3D images features to be used for classification/segmentation.

Author:

iarganda

Field Summary

Fields
Modifier and Type	Field and Description
`static String[]`	`availableFeatures` names of available filters
`static int`	`DERIVATIVES` Derivatives filter flag index
`static int`	`DOG` difference of Gaussian filter flag index
`static int`	`EDGES` edge filter flag index
`static int`	`GAUSSIAN` Gaussian filter flag index
`static int`	`HESSIAN` Hessian filter flag index
`static boolean[]`	`IMAGESCIENCE_FEATURES` Features only available if the ImageScience library is present.
`static int`	`LAPLACIAN` Laplacian filter flag index
`static int`	`MAXIMUM` Maximum flag index
`static int`	`MEAN` Mean flag index
`static int`	`MEDIAN` Median flag index
`static int`	`MINIMUM` Minimum flag index
`static int`	`STRUCTURE` structure tensor filter flag index
`static int`	`VARIANCE` Variance flag index

Constructor Summary

Constructors
Constructor and Description

FeatureStack3D(ij.ImagePlus image)
Construct object to store stack of image features

Constructors
Constructor and Description
`FeatureStack3D(ij.ImagePlus image)` Construct object to store stack of image features

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`static boolean[]`	`getDefaultEnabledFeatures()` Get the list of flags for the default features
`Callable<ArrayList<ij.ImagePlus>>`	`getDerivatives(ij.ImagePlus originalImage, double sigma, int xOrder, int yOrder, int zOrder)` Get derivatives features (to be submitted in an ExecutorService)
`Callable<ArrayList<ij.ImagePlus>>`	`getDoG(ij.ImagePlus originalImage, double sigma1, double sigma2)` Get difference of Gaussian features (to be submitted in an ExecutorService).
`Callable<ArrayList<ij.ImagePlus>>`	`getEdges(ij.ImagePlus originalImage, double sigma)` Get Edges features (to be submitted in an ExecutorService)
`boolean[]`	`getEnabledFeatures()` Get the boolean flags of enabled features
`FeatureStackArray`	`getFeatureStackArray()` Convert FeatureStack3D into a feature stack array (for 2D stacks).
`Callable<ArrayList<ij.ImagePlus>>`	`getGaussian(ij.ImagePlus originalImage, double sigma)` Get Gaussian features (to be submitted to an ExecutorService).
`Callable<ArrayList<ij.ImagePlus>>`	`getHessian(ij.ImagePlus originalImage, double sigma, boolean absolute)` Get Hessian features (to be submitted in an ExecutorService)
`Callable<ArrayList<ij.ImagePlus>>`	`getLaplacian(ij.ImagePlus originalImage, double sigma)` Get Laplacian features (to be submitted in an ExecutorService)
`Callable<ArrayList<ij.ImagePlus>>`	`getMaximum(ij.ImagePlus originalImage, double sigma)` Get Maximum features (to be submitted to an ExecutorService).
`Callable<ArrayList<ij.ImagePlus>>`	`getMean(ij.ImagePlus originalImage, double sigma)` Get Mean features (to be submitted to an ExecutorService).
`Callable<ArrayList<ij.ImagePlus>>`	`getMedian(ij.ImagePlus originalImage, double sigma)` Get Median features (to be submitted to an ExecutorService).
`Callable<ArrayList<ij.ImagePlus>>`	`getMinimum(ij.ImagePlus originalImage, double sigma)` Get Minimum features (to be submitted to an ExecutorService).
`Callable<ArrayList<ij.ImagePlus>>`	`getStructure(ij.ImagePlus originalImage, double sigma, double integrationScale)` Get structure tensor features (to be submitted in an ExecutorService).
`Callable<ArrayList<ij.ImagePlus>>`	`getVariance(ij.ImagePlus originalImage, double sigma)` Get Variance features (to be submitted to an ExecutorService).
`void`	`setEnableFeatures(boolean[] enableFeatures)` Set the boolean flags to enable/disable features
`void`	`setMaximumSigma(float maximumSigma)` Set the maximum sigma (or filter radius) of the features
`void`	`setMinimumSigma(float minimumSigma)` Set the minimum sigma (or filter radius) of the features
`boolean`	`updateFeaturesMT()` Update features with current list in a multi-thread fashion

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - GAUSSIAN
```
public static final int GAUSSIAN
```
    Gaussian filter flag index
    
    See Also:
    
    Constant Field Values
  - HESSIAN
```
public static final int HESSIAN
```
    Hessian filter flag index
    
    See Also:
    
    Constant Field Values
  - DERIVATIVES
```
public static final int DERIVATIVES
```
    Derivatives filter flag index
    
    See Also:
    
    Constant Field Values
  - LAPLACIAN
```
public static final int LAPLACIAN
```
    Laplacian filter flag index
    
    See Also:
    
    Constant Field Values
  - STRUCTURE
```
public static final int STRUCTURE
```
    structure tensor filter flag index
    
    See Also:
    
    Constant Field Values
  - EDGES
```
public static final int EDGES
```
    edge filter flag index
    
    See Also:
    
    Constant Field Values
  - DOG
```
public static final int DOG
```
    difference of Gaussian filter flag index
    
    See Also:
    
    Constant Field Values
  - MINIMUM
```
public static final int MINIMUM
```
    Minimum flag index
    
    See Also:
    
    Constant Field Values
  - MAXIMUM
```
public static final int MAXIMUM
```
    Maximum flag index
    
    See Also:
    
    Constant Field Values
  - MEAN
```
public static final int MEAN
```
    Mean flag index
    
    See Also:
    
    Constant Field Values
  - MEDIAN
```
public static final int MEDIAN
```
    Median flag index
    
    See Also:
    
    Constant Field Values
  - VARIANCE
```
public static final int VARIANCE
```
    Variance flag index
    
    See Also:
    
    Constant Field Values
  - availableFeatures
```
public static final String[] availableFeatures
```
    names of available filters
  - IMAGESCIENCE_FEATURES
```
public static final boolean[] IMAGESCIENCE_FEATURES
```
    Features only available if the ImageScience library is present.
- Constructor Detail
  - FeatureStack3D
```
public FeatureStack3D(ij.ImagePlus image)
```
    Construct object to store stack of image features
    
    Parameters:
    
    image - original image
- Method Detail
  - getDefaultEnabledFeatures
```
public static boolean[] getDefaultEnabledFeatures()
```
    Get the list of flags for the default features
    
    Returns:
    
    list of boolean flags for the default features
  - getDerivatives
```
public Callable<ArrayList<ij.ImagePlus>> getDerivatives(ij.ImagePlus originalImage,
                                                        double sigma,
                                                        int xOrder,
                                                        int yOrder,
                                                        int zOrder)
```
    Get derivatives features (to be submitted in an ExecutorService)
    
    Parameters:
    
    originalImage - input image
    
    sigma - isotropic smoothing scale
    
    xOrder - x-order of differentiation
    
    yOrder - y-order of differentiation
    
    zOrder - z-order of differentiation
    
    Returns:
    
    filter image after specific order derivatives
  - getDoG
```
public Callable<ArrayList<ij.ImagePlus>> getDoG(ij.ImagePlus originalImage,
                                                double sigma1,
                                                double sigma2)
```
    Get difference of Gaussian features (to be submitted in an ExecutorService). Sigma values will be adjusted based on original image calibration.
    
    Parameters:
    
    originalImage - input image
    
    sigma1 - sigma of the smaller Gaussian
    
    sigma2 - sigma of the larger Gaussian
    
    Returns:
    
    filter image after specific order derivatives
  - getHessian
```
public Callable<ArrayList<ij.ImagePlus>> getHessian(ij.ImagePlus originalImage,
                                                    double sigma,
                                                    boolean absolute)
```
    Get Hessian features (to be submitted in an ExecutorService)
    
    Parameters:
    
    originalImage - input image
    
    sigma - isotropic smoothing scale
    
    absolute - determines whether eigenvalues are compared in absolute sense
    
    Returns:
    
    filter Hessian filter images
  - getLaplacian
```
public Callable<ArrayList<ij.ImagePlus>> getLaplacian(ij.ImagePlus originalImage,
                                                      double sigma)
```
    Get Laplacian features (to be submitted in an ExecutorService)
    
    Parameters:
    
    originalImage - input image
    
    sigma - isotropic smoothing scale
    
    Returns:
    
    filter Laplacian filter image
  - getEdges
```
public Callable<ArrayList<ij.ImagePlus>> getEdges(ij.ImagePlus originalImage,
                                                  double sigma)
```
    Get Edges features (to be submitted in an ExecutorService)
    
    Parameters:
    
    originalImage - input image
    
    sigma - isotropic smoothing scale
    
    Returns:
    
    filter Edges filter image
  - getMinimum
```
public Callable<ArrayList<ij.ImagePlus>> getMinimum(ij.ImagePlus originalImage,
                                                    double sigma)
```
    Get Minimum features (to be submitted to an ExecutorService). Sigma values will be adjusted based on original image calibration.
    
    Parameters:
    
    originalImage - input image
    
    sigma - filter radius
    
    Returns:
    
    filter Minimum filter image
  - getGaussian
```
public Callable<ArrayList<ij.ImagePlus>> getGaussian(ij.ImagePlus originalImage,
                                                     double sigma)
```
    Get Gaussian features (to be submitted to an ExecutorService). Sigma values will be adjusted based on original image calibration.
    
    Parameters:
    
    originalImage - input image
    
    sigma - filter radius
    
    Returns:
    
    filter Gaussian filtered image
  - getMaximum
```
public Callable<ArrayList<ij.ImagePlus>> getMaximum(ij.ImagePlus originalImage,
                                                    double sigma)
```
    Get Maximum features (to be submitted to an ExecutorService). Sigma values will be adjusted based on original image calibration.
    
    Parameters:
    
    originalImage - input image
    
    sigma - filter radius
    
    Returns:
    
    filter Maximum filter image
  - getMean
```
public Callable<ArrayList<ij.ImagePlus>> getMean(ij.ImagePlus originalImage,
                                                 double sigma)
```
    Get Mean features (to be submitted to an ExecutorService). Sigma values will be adjusted based on original image calibration.
    
    Parameters:
    
    originalImage - input image
    
    sigma - filter radius
    
    Returns:
    
    filter Mean filter image
  - getMedian
```
public Callable<ArrayList<ij.ImagePlus>> getMedian(ij.ImagePlus originalImage,
                                                   double sigma)
```
    Get Median features (to be submitted to an ExecutorService). Sigma values will be adjusted based on original image calibration.
    
    Parameters:
    
    originalImage - input image
    
    sigma - filter radius
    
    Returns:
    
    filter Median filter image
  - getVariance
```
public Callable<ArrayList<ij.ImagePlus>> getVariance(ij.ImagePlus originalImage,
                                                     double sigma)
```
    Get Variance features (to be submitted to an ExecutorService). Sigma values will be adjusted based on original image calibration.
    
    Parameters:
    
    originalImage - input image
    
    sigma - filter radius
    
    Returns:
    
    filter Variance filter image
  - getStructure
```
public Callable<ArrayList<ij.ImagePlus>> getStructure(ij.ImagePlus originalImage,
                                                      double sigma,
                                                      double integrationScale)
```
    Get structure tensor features (to be submitted in an ExecutorService). It computes, for all pixels in the input image, the eigenvalues of the so-called structure tensor.
    
    Parameters:
    
    originalImage - input image
    
    sigma - isotropic smoothing scale
    
    integrationScale - integration scale (standard deviation of the Gaussian kernel used for smoothing the elements of the structure tensor, must be larger than zero)
    
    Returns:
    
    filter structure tensor filter image
  - updateFeaturesMT
```
public boolean updateFeaturesMT()
```
    Update features with current list in a multi-thread fashion
    
    Returns:
    
    true if the features are correctly updated
  - getFeatureStackArray
```
public FeatureStackArray getFeatureStackArray()
```
    Convert FeatureStack3D into a feature stack array (for 2D stacks). Experimental.
    
    Returns:
    
    array of feature stacks
  - setMinimumSigma
```
public void setMinimumSigma(float minimumSigma)
```
    Set the minimum sigma (or filter radius) of the features
    
    Parameters:
    
    minimumSigma - minimum sigma to use
  - setMaximumSigma
```
public void setMaximumSigma(float maximumSigma)
```
    Set the maximum sigma (or filter radius) of the features
    
    Parameters:
    
    maximumSigma - maximum sigma to use
  - setEnableFeatures
```
public void setEnableFeatures(boolean[] enableFeatures)
```
    Set the boolean flags to enable/disable features
    
    Parameters:
    
    enableFeatures - array of flags
  - getEnabledFeatures
```
public boolean[] getEnabledFeatures()
```
    Get the boolean flags of enabled features
    
    Returns:
    
    array of flags with enabled/disabled features

Class FeatureStack3D

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

GAUSSIAN

HESSIAN

DERIVATIVES

LAPLACIAN

STRUCTURE

EDGES

DOG

MINIMUM

MAXIMUM

MEAN

MEDIAN

VARIANCE

availableFeatures

IMAGESCIENCE_FEATURES

Constructor Detail

FeatureStack3D

Method Detail

getDefaultEnabledFeatures

getDerivatives

getDoG

getHessian

getLaplacian

getEdges

getMinimum

getGaussian

getMaximum

getMean

getMedian

getVariance

getStructure

updateFeaturesMT

getFeatureStackArray

setMinimumSigma

setMaximumSigma

setEnableFeatures

getEnabledFeatures