Package gov.nih.mipav.model.algorithms

Class SIFTImageSimilarity

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.SIFTImageSimilarity

All Implemented Interfaces:

ActionListener, WindowListener, Runnable, EventListener

public class SIFTImageSimilarity
extends AlgorithmBase

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
(package private) class	SIFTImageSimilarity.DMatch
private class	SIFTImageSimilarity.DMatchComparator
private class	SIFTImageSimilarity.KeyPoint
private class	SIFTImageSimilarity.KeypointComparator

Nested classes/interfaces inherited from class java.lang.Thread

Thread.Builder, Thread.State, Thread.UncaughtExceptionHandler

Field Summary

Fields

Modifier and Type	Field	Description
private double	assumed_blur
private final double	DBL_EPSILON
private Vector<Vector<Double>>	descriptors1
private Vector<Vector<Double>>	descriptors2
private int	image_border_width
private ModelImage	image1
private ModelImage	image2
private Vector<SIFTImageSimilarity.KeyPoint>	keypoints1
private Vector<SIFTImageSimilarity.KeyPoint>	keypoints2
private String	logFile
(package private) Logger	logger
private final int	NORM_L2
private int	num_intervals
private double	sigma
private double	tolerance

Fields inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

destFlag, destImage, image25D, mask, maxProgressValue, minProgressValue, multiThreadingEnabled, nthreads, progress, progressModulus, progressStep, runningInSeparateThread, separable, srcImage, threadStopped

Fields inherited from class java.lang.Thread

MAX_PRIORITY, MIN_PRIORITY, NORM_PRIORITY

Constructor Summary

Constructors

Constructor	Description
SIFTImageSimilarity()
SIFTImageSimilarity(ModelImage image1, ModelImage image2, double sigma, int num_intervals, double assumed_blur, int image_border_width, String logFile)

Method Summary

Modifier and Type	Method	Description
private void	batchDistance(Vector<Vector<Double>> src1, Vector<Vector<Double>> src2, double[][] dist, int[][] nidx, int normType, int K, Vector<Double> mask, int update, boolean crosscheck)
private void	BatchDistInvoker(Vector<Vector<Double>> src1, Vector<Vector<Double>> src2, double[][] dist, int[][] nidx, int K, Vector<Double> mask, int update)
private double[]	computeGradientAtCenterPixel(double[][][] pixel_array)
private double[][]	computeHessianAtCenterPixel(double[][][] pixel_array)
void	computeKeypointsAndDescriptors(ModelImage image, boolean doimage1)
private Vector<SIFTImageSimilarity.KeyPoint>	computeKeypointsWithOrientations(SIFTImageSimilarity.KeyPoint keypoint, int octave_index, ModelImage gaussian_image, double radius_factor, int num_bins, double peak_ratio, double scale_factor)
private int	computeNumberOfOctaves(int[] image_shape)
private Vector<SIFTImageSimilarity.KeyPoint>	convertKeypointsToInputImageSize(Vector<SIFTImageSimilarity.KeyPoint> keypoints)
private Vector<SIFTImageSimilarity.KeyPoint>	findScaleSpaceExtrema(ModelImage[][] gaussian_images, ModelImage[][] dog_images, int num_intervals, double sigma, int image_border_width, double contrast_threshold)
private ModelImage	generateBaseImage(ModelImage image, double sigma, double assumed_blur)
private Vector<Vector<Double>>	generateDescriptors(Vector<SIFTImageSimilarity.KeyPoint> keypoints, ModelImage[][] gaussian_images, int window_width, int num_bins, double scale_multiplier, double descriptor_max_value)
private ModelImage[][]	generateDoGImages(ModelImage[][] gaussian_images)
private ModelImage[][]	generateGaussianImages(ModelImage image, int num_octaves, double[] gaussian_kernels)
private double[]	generateGaussianKernels(double sigma, int num_intervals)
private boolean	isPixelAnExtremum(double[][][] subimages, double threshold)
private SIFTImageSimilarity.KeyPoint	localizeExtremumViaQuadraticFit(int[] localized_image_index, int i, int j, int image_index, int octave_index, int num_intervals, ModelImage[] dog_images_in_octave, double sigma, double contrast_threshold, int image_border_width, double eigenvalue_ratio, int num_attempts_until_convergence)
private Vector<SIFTImageSimilarity.KeyPoint>	removeDuplicateKeypoints(Vector<SIFTImageSimilarity.KeyPoint> keypoints)
void	runAlgorithm()	Actually runs the algorithm.
private void	unpackOctave(int[] octave, int[] layer, double[] scale, SIFTImageSimilarity.KeyPoint keypoint)

Methods inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

actionPerformed, addListener, addProgressChangeListener, calculateImageSize, calculatePrincipleAxis, computeElapsedTime, computeElapsedTime, convertIntoFloat, delinkProgressToAlgorithm, delinkProgressToAlgorithmMulti, displayError, errorCleanUp, finalize, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, generateProgressValues, getDestImage, getElapsedTime, getMask, getMaxProgressValue, getMinProgressValue, getNumberOfThreads, getProgress, getProgressChangeListener, getProgressChangeListeners, getProgressModulus, getProgressStep, getProgressValues, getSrcImage, isCompleted, isImage25D, isMultiThreadingEnabled, isRunningInSeparateThread, isThreadStopped, linkProgressToAlgorithm, linkProgressToAlgorithm, makeProgress, notifyListeners, removeListener, removeProgressChangeListener, run, setCompleted, setImage25D, setMask, setMaxProgressValue, setMinProgressValue, setMultiThreadingEnabled, setNumberOfThreads, setProgress, setProgressModulus, setProgressStep, setProgressValues, setProgressValues, setRunningInSeparateThread, setSrcImage, setStartTime, setThreadStopped, startMethod, windowActivated, windowClosed, windowClosing, windowDeactivated, windowDeiconified, windowIconified, windowOpened

Methods inherited from class java.lang.Thread

activeCount, checkAccess, clone, countStackFrames, currentThread, dumpStack, enumerate, getAllStackTraces, getContextClassLoader, getDefaultUncaughtExceptionHandler, getId, getName, getPriority, getStackTrace, getState, getThreadGroup, getUncaughtExceptionHandler, holdsLock, interrupt, interrupted, isAlive, isDaemon, isInterrupted, isVirtual, join, join, join, join, ofPlatform, ofVirtual, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, sleep, start, startVirtualThread, stop, suspend, threadId, toString, yield

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Details

image1

private ModelImage image1

image2

private ModelImage image2

sigma

private double sigma

num_intervals

private int num_intervals

assumed_blur

private double assumed_blur

image_border_width

private int image_border_width

tolerance

private double tolerance

logFile

private String logFile

logger

Logger logger

DBL_EPSILON

private final double DBL_EPSILON

See Also:

• Constant Field Values

keypoints1

private Vector<SIFTImageSimilarity.KeyPoint> keypoints1

descriptors1

private Vector<Vector<Double>> descriptors1

keypoints2

private Vector<SIFTImageSimilarity.KeyPoint> keypoints2

descriptors2

private Vector<Vector<Double>> descriptors2

NORM_L2

private final int NORM_L2

See Also:

• Constant Field Values

Constructor Details

SIFTImageSimilarity

public SIFTImageSimilarity()

SIFTImageSimilarity

public SIFTImageSimilarity(ModelImage image1,
 ModelImage image2,
 double sigma,
 int num_intervals,
 double assumed_blur,
 int image_border_width,
 String logFile)

Method Details

runAlgorithm

public void runAlgorithm()

Description copied from class: AlgorithmBase

Actually runs the algorithm. Implemented by inheriting algorithms.

Specified by:

runAlgorithm in class AlgorithmBase

batchDistance

private void batchDistance(Vector<Vector<Double>> src1,
 Vector<Vector<Double>> src2,
 double[][] dist,
 int[][] nidx,
 int normType,
 int K,
 Vector<Double> mask,
 int update,
 boolean crosscheck)

BatchDistInvoker

private void BatchDistInvoker(Vector<Vector<Double>> src1,
 Vector<Vector<Double>> src2,
 double[][] dist,
 int[][] nidx,
 int K,
 Vector<Double> mask,
 int update)

computeKeypointsAndDescriptors

public void computeKeypointsAndDescriptors(ModelImage image,
 boolean doimage1)

generateBaseImage

private ModelImage generateBaseImage(ModelImage image,
 double sigma,
 double assumed_blur)

computeNumberOfOctaves

private int computeNumberOfOctaves(int[] image_shape)

generateGaussianKernels

private double[] generateGaussianKernels(double sigma,
 int num_intervals)

generateGaussianImages

private ModelImage[][] generateGaussianImages(ModelImage image,
 int num_octaves,
 double[] gaussian_kernels)

generateDoGImages

private ModelImage[][] generateDoGImages(ModelImage[][] gaussian_images)

findScaleSpaceExtrema

private Vector<SIFTImageSimilarity.KeyPoint> findScaleSpaceExtrema(ModelImage[][] gaussian_images,
 ModelImage[][] dog_images,
 int num_intervals,
 double sigma,
 int image_border_width,
 double contrast_threshold)

isPixelAnExtremum

private boolean isPixelAnExtremum(double[][][] subimages,
 double threshold)

localizeExtremumViaQuadraticFit

private SIFTImageSimilarity.KeyPoint localizeExtremumViaQuadraticFit(int[] localized_image_index,
 int i,
 int j,
 int image_index,
 int octave_index,
 int num_intervals,
 ModelImage[] dog_images_in_octave,
 double sigma,
 double contrast_threshold,
 int image_border_width,
 double eigenvalue_ratio,
 int num_attempts_until_convergence)

computeGradientAtCenterPixel

private double[] computeGradientAtCenterPixel(double[][][] pixel_array)

computeHessianAtCenterPixel

private double[][] computeHessianAtCenterPixel(double[][][] pixel_array)

computeKeypointsWithOrientations

private Vector<SIFTImageSimilarity.KeyPoint> computeKeypointsWithOrientations(SIFTImageSimilarity.KeyPoint keypoint,
 int octave_index,
 ModelImage gaussian_image,
 double radius_factor,
 int num_bins,
 double peak_ratio,
 double scale_factor)

removeDuplicateKeypoints

private Vector<SIFTImageSimilarity.KeyPoint> removeDuplicateKeypoints(Vector<SIFTImageSimilarity.KeyPoint> keypoints)

convertKeypointsToInputImageSize

private Vector<SIFTImageSimilarity.KeyPoint> convertKeypointsToInputImageSize(Vector<SIFTImageSimilarity.KeyPoint> keypoints)

unpackOctave

private void unpackOctave(int[] octave,
 int[] layer,
 double[] scale,
 SIFTImageSimilarity.KeyPoint keypoint)

generateDescriptors

private Vector<Vector<Double>> generateDescriptors(Vector<SIFTImageSimilarity.KeyPoint> keypoints,
 ModelImage[][] gaussian_images,
 int window_width,
 int num_bins,
 double scale_multiplier,
 double descriptor_max_value)