Statistics
[Image Analysis]

The Statistics category contains analysis engines applying an intensity- based measurement globally to the input image. More...

Classes
class	SoAutoThresholdingQuantification
	SoAutoThresholdingQuantification engine More...
class	SoCompareImageQuantification
	SoCompareImageQuantification engine applies a comparison test between two images More...
class	SoCompareValueQuantification
	SoCompareValueQuantification engine applies a comparison test between an image and a constant value. More...
class	SoCooccurrenceQuantification2d
	SoCooccurrenceQuantification2d engine provides texture indicators based on the co-occurrence matrix computation. More...
class	SoIntensityExtremaQuantification
	SoIntensityExtremaQuantification engine computes basic statistics of an image. More...
class	SoIntensityStatisticsQuantification
	SoIntensityStatisticsQuantification engine advanced basic statistics of an image. More...
class	SoLocalMaximaQuantification
	SoLocalMaximaQuantification engine More...
class	SoMaskedStatisticsQuantification
	SoMaskedStatisticsQuantification engine advanced basic statistics of an image within a mask. More...
class	SoMeasureGaussianNoiseQuantification
	SoMeasureGaussianNoiseQuantification engine computes an estimation of a gaussian noise standard deviation. More...

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Detailed Description

The Statistics category contains analysis engines applying an intensity- based measurement globally to the input image.

For an introduction, see section Image Analysis

These engines extend the set of global shape-based measures to the gray level based measurements. Features are no longer obtained from binary images, but from gray level images, potentially masked with the individualized cells.