SoIntensityStatisticsQuantification Class Reference
[Statistics]

SoIntensityStatisticsQuantification engine advanced basic statistics of an image. More...

#include <ImageViz/Engines/ImageAnalysis/Statistics/SoIntensityStatisticsQuantification.h>

Inheritance diagram for SoIntensityStatisticsQuantification:

Classes
class	SbStatisticsDetail
	Results details of statistics global measure. More...
Public Types
enum	RangeMode { MIN_MAX = 0, OTHER = 1 }
Public Member Functions
	SoIntensityStatisticsQuantification ()
Public Attributes
SoSFEnum	computeMode
SoSFImageDataAdapter	inImage
SoSFEnum	rangeMode
SoSFVec2i32	intensityRangeInput
SoImageVizEngineAnalysisOutput < SbStatisticsDetail >	outResult

Detailed Description

SoIntensityStatisticsQuantification engine advanced basic statistics of an image.

For an introduction to global measurements, see section Image Analysis Operations.

The SoIntensityStatisticsQuantification engine gives some of the image characteristics such as: the total number of pixels/voxels, the minimum and maximum gray levels, the mean, the range, the standard deviation, the kurtosis and the skewness.

$range = Max ~-~ Min ~+~ 1$

$\mu_k = \sum{(I(i,j)-mean)}^{k}$

$stddev = \sigma=\sqrt{\mu_2}$

$skewness = \frac{\mu_3}{\sigma^3}$

$kurtosis = (\frac{\mu_4}{\sigma^4})-3$

The SKEWNESS is the degree of asymmetry of a distribution. If the distribution has a tail length smaller than the maximum, the function has negative skewness. Otherwise, it has positive skewness.

The KURTOSIS is the degree of peakedness of a distribution, also called the "excess" or "excess coefficient." Kurtosis is a normalized form of the fourth central moment of a distribution.