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_level2	square 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