Package qupath.opencv.tools

Class LocalNormalization.LocalNormalizationType

java.lang.Object

qupath.opencv.tools.LocalNormalization.LocalNormalizationType

Enclosing class:

LocalNormalization

public static class LocalNormalization.LocalNormalizationType
extends Object

Helper class to store local normalization parameters.

Field Summary

Fields

Modifier and Type	Field	Description
final LocalNormalization.SmoothingScale	scale	Smoothing scale for Gaussian subtraction.
final LocalNormalization.SmoothingScale	scaleVariance	Smoothing scale for Gaussian-weighted standard deviation estimate.

Method Summary

Modifier and Type	Method	Description
static LocalNormalization.LocalNormalizationType	getInstance(LocalNormalization.SmoothingScale scale, double varianceScaleRatio)	Get an object containing the parameters necessary for normalization.
static LocalNormalization.LocalNormalizationType	getInstance(LocalNormalization.SmoothingScale scale, LocalNormalization.SmoothingScale scaleVariance)	Get an object containing the parameters necessary for normalization.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details

scale

public final LocalNormalization.SmoothingScale scale

Smoothing scale for Gaussian subtraction.

scaleVariance

public final LocalNormalization.SmoothingScale scaleVariance

Smoothing scale for Gaussian-weighted standard deviation estimate.

Method Details

getInstance

public static LocalNormalization.LocalNormalizationType getInstance(LocalNormalization.SmoothingScale scale,
 LocalNormalization.SmoothingScale scaleVariance)

Get an object containing the parameters necessary for normalization.

Parameters:

scale - Gaussian sigma value used for initial filters (mean subtraction)

scaleVariance - sigma value used for variance estimation (may be null to apply subtraction only)

Returns:

getInstance

public static LocalNormalization.LocalNormalizationType getInstance(LocalNormalization.SmoothingScale scale,
 double varianceScaleRatio)

Get an object containing the parameters necessary for normalization.

Parameters:

scale - Gaussian sigma value used for initial filters (mean subtraction)

varianceScaleRatio - multiplicative factor applied to scale to determine the variance estimation scale

Returns: