DifferenceOfGaussian (Fiji Javadocs 0-SNAPSHOT API)

java.lang.Object
- mpicbg.imglib.algorithm.scalespace.DifferenceOfGaussian<A,B>

All Implemented Interfaces:: Algorithm, Benchmark, MultiThreaded

Direct Known Subclasses:: DifferenceOfGaussianReal

public class DifferenceOfGaussian<A extends Type<A>,B extends NumericType<B> & Comparable<B>>
extends Object
implements Algorithm, MultiThreaded, Benchmark

TODO

Author:: Stephan Preibisch

Nested Class Summary

Nested Classes
Modifier and Type Class and Description

static class DifferenceOfGaussian.SpecialPoint

Nested Classes
Modifier and Type	Class and Description
`static class`	`DifferenceOfGaussian.SpecialPoint`

Field Summary

Fields
Modifier and Type	Field and Description
`protected Converter<A,B>`	`converter`
`protected Image<B>`	`dogImage`
`protected ImageFactory<B>`	`factory`
`protected Image<A>`	`image`
`protected OutOfBoundsStrategyFactory<B>`	`outOfBoundsFactory`
`protected ArrayList<DifferenceOfGaussianPeak<B>>`	`peaks`

Constructor Summary

Constructors
Constructor and Description
`DifferenceOfGaussian(Image<A> img, ImageFactory<B> factory, Converter<A,B> converter, OutOfBoundsStrategyFactory<B> outOfBoundsFactory, double[] sigma1, double[] sigma2, B minPeakValue, B normalizationFactor)` Extracts local minima and maxima of a certain size.
`DifferenceOfGaussian(Image<A> img, ImageFactory<B> factory, Converter<A,B> converter, OutOfBoundsStrategyFactory<B> outOfBoundsFactory, double sigma1, double sigma2, B minPeakValue, B normalizationFactor)` Calls the DifferenceOfGaussian constructor with the given sigmas copied into double[] arrays, one entry per dimension.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`boolean`	`checkInput()`
`ArrayList<DifferenceOfGaussianPeak<B>>`	`findPeaks(Image<B> laPlace)`
`boolean`	`getComputeConvolutionsParalell()`
`Image<B>`	`getDoGImage()`
`String`	`getErrorMessage()`
`protected OutputAlgorithm<B>`	`getGaussianConvolution(double[] sigma, int nThreads)` This method returns the `OutputAlgorithm` that will compute the Gaussian Convolutions, more efficient versions can override this method
`boolean`	`getKeepDoGImage()`
`B`	`getMinPeakValue()`
`protected Function<B,B,B>`	`getNormalizedSubtraction()` Returns the function that does the normalized subtraction of the gauss images, more efficient versions can override this method
`int`	`getNumThreads()` The number of threads used by the algorithm
`ArrayList<DifferenceOfGaussianPeak<B>>`	`getPeaks()`
`long`	`getProcessingTime()`
`protected boolean`	`isPeakHighEnough(B value)` Checks if the absolute value of the current peak is high enough, more efficient versions can override this method
`protected DifferenceOfGaussian.SpecialPoint`	`isSpecialPoint(LocalNeighborhoodCursor<B> neighborhoodCursor, B centerValue)` Checks if the current position is a minima or maxima in a 3^n neighborhood, more efficient versions can override this method
`boolean`	`process()`
`void`	`setComputeConvolutionsParalell(boolean paralell)`
`void`	`setKeepDoGImage(boolean keepDoGImage)`
`void`	`setMinPeakValue(B value)`
`void`	`setNumThreads()` Sets the number of threads to the amount of processors available
`void`	`setNumThreads(int numThreads)` Sets the number of threads

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

- Field Detail
 - image
```
protected final Image<A extends Type<A>> image
```
 - dogImage
```
protected Image & Comparable> dogImage
```
 - factory
```
protected final ImageFactory & Comparable> factory
```
 - outOfBoundsFactory
```
protected final OutOfBoundsStrategyFactory & Comparable> outOfBoundsFactory
```
 - peaks
```
protected final ArrayList<DifferenceOfGaussianPeak & Comparable>> peaks
```
 - converter
```
protected final Converter<A extends Type<A>,B extends NumericType & Comparable> converter
```
- Constructor Detail
 - DifferenceOfGaussian
```
public DifferenceOfGaussian(Image<A> img,
 ImageFactory factory,
 Converter<A,B> converter,
 OutOfBoundsStrategyFactory outOfBoundsFactory,
 double sigma1,
 double sigma2,
 B minPeakValue,
 B normalizationFactor)
```
 Calls the DifferenceOfGaussian constructor with the given sigmas copied into double[] arrays, one entry per dimension.
 - DifferenceOfGaussian
```
public DifferenceOfGaussian(Image<A> img,
 ImageFactory factory,
 Converter<A,B> converter,
 OutOfBoundsStrategyFactory outOfBoundsFactory,
 double[] sigma1,
 double[] sigma2,
 B minPeakValue,
 B normalizationFactor)
```
 Extracts local minima and maxima of a certain size. It therefore computes the difference of gaussian for an Image and detects all local minima and maxima in 3x3x3x....3 environment, which is returned as an ArrayList of DifferenceOfGaussianPeaks. The two sigmas define the scale on which extrema are identified, it correlates with the size of the object. Note that not only extrema of this size are found, but they will have the higher absolute values. Note as well that the values of the difference of gaussian image is also defined by the distance between the two sigmas. A normalization if necessary can be found in the ScaleSpace class. Also note a technical detail, the method findPeaks(Image img) can be called on any image if the image from where the extrema should be computed already exists.
 
 Parameters:
 
 img - - The input Image
 
 factory - - The ImageFactory which defines the datatype in which the computation is performed
 
 converter - - The Converter which defines how to convert into
 outOfBoundsFactory - - The OutOfBoundsStrategyFactory necessary for the GaussianConvolution
 
 sigma1 - - The lower sigma
 
 sigma2 - - The higher sigma
 
 minPeakValue - -
 
 normalizationFactor -
Method Detail

setMinPeakValue

public void setMinPeakValue(B value)

getMinPeakValue

public B getMinPeakValue()

getDoGImage

public Image getDoGImage()

setKeepDoGImage

public void setKeepDoGImage(boolean keepDoGImage)

getKeepDoGImage

public boolean getKeepDoGImage()

getPeaks

public ArrayList<DifferenceOfGaussianPeak> getPeaks()

setComputeConvolutionsParalell

public void setComputeConvolutionsParalell(boolean paralell)

getComputeConvolutionsParalell

public boolean getComputeConvolutionsParalell()

getGaussianConvolution

protected OutputAlgorithm getGaussianConvolution(double[] sigma, int nThreads)

This method returns the OutputAlgorithm that will compute the Gaussian Convolutions, more efficient versions can override this method

Parameters:

sigma - - the sigma of the convolution

nThreads - - the number of threads for this convolution

Returns:

getNormalizedSubtraction

protected Function<B,B,B> getNormalizedSubtraction()

Returns the function that does the normalized subtraction of the gauss images, more efficient versions can override this method

Returns:

- the Subtraction Function

isPeakHighEnough

protected boolean isPeakHighEnough(B value)

Checks if the absolute value of the current peak is high enough, more efficient versions can override this method

Parameters:

value - - the current value

Returns:

true if the absoluted value is high enough, otherwise false

isSpecialPoint

protected DifferenceOfGaussian.SpecialPoint isSpecialPoint(LocalNeighborhoodCursor neighborhoodCursor, B centerValue)

Checks if the current position is a minima or maxima in a 3^n neighborhood, more efficient versions can override this method

Parameters:

neighborhoodCursor - - the LocalNeighborhoodCursor

centerValue - - the value in the center which is tested

Returns:

- if is a minimum, maximum or nothig

process

public boolean process()

Specified by:

process in interface Algorithm

findPeaks

public ArrayList<DifferenceOfGaussianPeak> findPeaks(Image laPlace)

checkInput

public boolean checkInput()

Specified by:

checkInput in interface Algorithm

getErrorMessage

public String getErrorMessage()

Specified by:

getErrorMessage in interface Algorithm

getProcessingTime

public long getProcessingTime()

Specified by:

getProcessingTime in interface Benchmark

setNumThreads

public void setNumThreads()

Description copied from interface: MultiThreaded

Sets the number of threads to the amount of processors available

Specified by:

setNumThreads in interface MultiThreaded

setNumThreads

public void setNumThreads(int numThreads)

Description copied from interface: MultiThreaded

Sets the number of threads

Specified by:

setNumThreads in interface MultiThreaded

Parameters:

numThreads - - number of threads to use

getNumThreads

public int getNumThreads()

Description copied from interface: MultiThreaded

The number of threads used by the algorithm

Specified by:

getNumThreads in interface MultiThreaded

Returns:

- the number of threads

Class DifferenceOfGaussian<A extends Type<A>,B extends NumericType<B> & Comparable<B>>

Nested Class Summary

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

image

dogImage

factory

outOfBoundsFactory

peaks

converter

Constructor Detail

DifferenceOfGaussian

DifferenceOfGaussian

Method Detail

setMinPeakValue

getMinPeakValue

getDoGImage

setKeepDoGImage

getKeepDoGImage

getPeaks

setComputeConvolutionsParalell

getComputeConvolutionsParalell

getGaussianConvolution

getNormalizedSubtraction

isPeakHighEnough

isSpecialPoint

process

findPeaks

checkInput

getErrorMessage

getProcessingTime

setNumThreads

setNumThreads

getNumThreads