2d/nfg.hh File Reference
#include <mia/2d/image.hh>
Include dependency graph for 2d/nfg.hh:

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Functions

EXPORT_2D float get_jump_level (const C2DImage &image)
 
EXPORT_2D float get_jump_level (const C2DImage &image, float noise_level)
 
EXPORT_2D C2DFVectorfield get_nfg (const C2DImage &image)
 
EXPORT_2D C2DFVectorfield get_nfg_j (const C2DImage &image, float jump_level2)
 
EXPORT_2D C2DFVectorfield get_nfg_n (const C2DImage &image, float noise_level)
 
EXPORT_2D float get_noise_level (const C2DImage &image)
 

Function Documentation

◆ get_jump_level() [1/2]

EXPORT_2D float get_jump_level ( const C2DImage image)

Evaluate the gradient jump level as described in the paper.

Parameters
image
Returns
jump level

◆ get_jump_level() [2/2]

EXPORT_2D float get_jump_level ( const C2DImage image,
float  noise_level 
)

Evaluate the gradient jump level as described in the paper by using a specific noise level

Parameters
image
noise_level
Returns
jump level

◆ get_nfg()

EXPORT_2D C2DFVectorfield get_nfg ( const C2DImage image)

Evaluate the normalized gradient field of an image by estimating the noise using get_noise_level

Parameters
image
Returns
NGF

◆ get_nfg_j()

EXPORT_2D C2DFVectorfield get_nfg_j ( const C2DImage image,
float  jump_level2 
)

Evaluate the normalized gradient field of an image by using a specific jump level

Parameters
image
jump_level2square of the jump level
Returns
NGF

◆ get_nfg_n()

EXPORT_2D C2DFVectorfield get_nfg_n ( const C2DImage image,
float  noise_level 
)

Evaluate the normalized gradient field of an image by using a specific noise level

Parameters
image
noise_level
Returns
NGF

◆ get_noise_level()

EXPORT_2D float get_noise_level ( const C2DImage image)

Evaluate an approximate of the noise level - specifically this uses the deviation \(\sigma\) of the intensities

Parameters
image
Returns
noise level