Spectral (CVSpectral.dll) 15.0
Preprocessing

Preprocessing exports. More...

Functions

cvbres_t CVSCubeAddition (CVCOMPOSITE ImageCube1, CVCOMPOSITE ImageCube2, cvbbool_t ClipResults, CVCOMPOSITE &ImageCubeOut)
 Element-wise addition of two Cubes. More...
 
cvbres_t CVSCubeDivision (CVCOMPOSITE Dividend, CVCOMPOSITE Divisor, CVCOMPOSITE &ImageCubeOut)
 Element-wise division of two Cubes. More...
 
cvbres_t CVSCubeMultiplication (CVCOMPOSITE ImageCube1, CVCOMPOSITE ImageCube2, cvbbool_t ClipResults, CVCOMPOSITE &ImageCubeOut)
 Element-wise multiplication of two Cubes. More...
 
cvbres_t CVSCubeNormalize (CVCOMPOSITE ImageCubeIn, CVCOMPOSITE WhiteReference, CVCOMPOSITE BlackReference, CVSNormalizationMethod NormalizationMethod, CVCOMPOSITE &ImageCubeOut)
 Normalizes the Spectral cube. More...
 
cvbres_t CVSCubeSubtraction (CVCOMPOSITE Minuend, CVCOMPOSITE Subtrahend, cvbbool_t ClipResults, CVCOMPOSITE &ImageCubeOut)
 Element-wise subtraction of two Cubes. More...
 

Detailed Description

Preprocessing exports.

Version
0.0.1.0


For details see function documentation.

Function Documentation

◆ CVSCubeAddition()

cvbres_t CVSCubeAddition ( CVCOMPOSITE  ImageCube1,
CVCOMPOSITE  ImageCube2,
cvbbool_t  ClipResults,
CVCOMPOSITE &  ImageCubeOut 
)

Element-wise addition of two Cubes.

Creates a new Cube after adding all values of ImageCube1 and ImageCube2 for each element (ImageCube1 + ImageCube2).

Parameters
[in]ImageCube1Any kind of cube is supported as long as the dimensions match with ImageCube2
[in]ImageCube2Any kind of cube is supported as long as the dimensions match with ImageCube1
[in]ClipResultsIn case of TRUE: Clips the resulting pixel values to the maximum possible value of the resulting data type. In case of false the result might lead to overflow
[out]ImageCubeOutLinear cube of the same dimensions and data type. The metadata is a copy from ImageCube1
Returns
See also
CVSCubeMultiplication CVSCubeDivision CVSCubeSubtraction CVSCubeNormalize

◆ CVSCubeDivision()

cvbres_t CVSCubeDivision ( CVCOMPOSITE  Dividend,
CVCOMPOSITE  Divisor,
CVCOMPOSITE &  ImageCubeOut 
)

Element-wise division of two Cubes.

Creates a new Cube after dividing all values of Dividend and Divisor for each element (Dividend / Divisor).

Parameters
[in]DividendAny kind of cube is supported as long as the dimensions match with Divisor
[in]DivisorAny kind of cube is supported as long as the dimensions match with Dividend
[out]ImageCubeOutLinear cube of the same dimensions of data type float. The metadata is a copy from Dividend
Returns
See also
CVSCubeMultiplication CVSCubeAddition CVSCubeSubtraction CVSCubeNormalize

◆ CVSCubeMultiplication()

cvbres_t CVSCubeMultiplication ( CVCOMPOSITE  ImageCube1,
CVCOMPOSITE  ImageCube2,
cvbbool_t  ClipResults,
CVCOMPOSITE &  ImageCubeOut 
)

Element-wise multiplication of two Cubes.

Creates a new Cube after multiplying all values of ImageCube1 and ImageCube2 for each element.

Parameters
[in]ImageCube1Any kind of cube is supported as long as the dimensions match with ImageCube2
[in]ImageCube2Any kind of cube is supported as long as the dimensions match with ImageCube1
[in]ClipResultsIn case of TRUE: Clips the resulting pixel values to the maximum or minimum possible value of the resulting data type. In case of false the result might lead to overflow
[out]ImageCubeOutLinear cube of the same dimensions and data type. The metadata is a copy from ImageCube1
Returns
See also
CVSCubeDivision CVSCubeAddition CVSCubeSubtraction CVSCubeNormalize

◆ CVSCubeNormalize()

cvbres_t CVSCubeNormalize ( CVCOMPOSITE  ImageCubeIn,
CVCOMPOSITE  WhiteReference,
CVCOMPOSITE  BlackReference,
CVSNormalizationMethod  NormalizationMethod,
CVCOMPOSITE &  ImageCubeOut 
)

Normalizes the Spectral cube.

This function creates a normalized cube using the white- and black reference and the object cube. More details in CVSNormalizationMethod

Note
This function does not support stacked cubes (CVSCubeType = CVSCT_StackedCube). If you want to use this function anyhow, duplicate your cube with CVSCreateDuplicatedContinuousCube to get a continous cube.
Parameters
[in]ImageCubeInSpectral Cube to work on
[in]WhiteReferenceThe white reference contains a linear Cube with matching dimensions for samples and bands to ImageCubeIn
[in]BlackReferenceThe black reference contains a linear Cube with matching dimensions for samples and bands to ImageCubeIn
[in]NormalizationMethodDefines the normalization method. More detailed information in CVSNormalizationMethod
[out]ImageCubeOutNormalized image of data type float32
Returns
See also
CVSCreateDuplicatedContinuousCube CVSCubeGetType CVSCubeMultiplication CVSCubeDivision CVSCubeAddition CVSCubeSubtraction

◆ CVSCubeSubtraction()

cvbres_t CVSCubeSubtraction ( CVCOMPOSITE  Minuend,
CVCOMPOSITE  Subtrahend,
cvbbool_t  ClipResults,
CVCOMPOSITE &  ImageCubeOut 
)

Element-wise subtraction of two Cubes.

Creates a new Cube after subtracting all values of Minuend and Subtrahend for each element (Minuend - Subtrahend).

Parameters
[in]MinuendAny kind of cube is supported as long as the dimensions match with Subtrahend
[in]SubtrahendAny kind of cube is supported as long as the dimensions match with Minuend
[in]ClipResultsIn case of TRUE: Clips the resulting pixel values to the minimum possible value of the resulting data type. In case of false the result might lead to overflow
[out]ImageCubeOutLinear cube of the same dimensions and data type. The metadata is a copy from Minuend
Returns
See also
CVSCubeAddition CVSCubeMultiplication CVSCubeDivision CVSCubeNormalize