Image segmentation - Watershed More...

Detailed Description

Image segmentation - Watershed

In the study of image processing, a watershed is a transformation defined on a grayscale image. The name refers metaphorically to a geological watershed, or drainage divide, which separates adjacent drainage basins. The watershed transformation treats the image it operates upon like a topographic map, with the brightness of each point representing its height, and finds the lines that run along the tops of ridges.

See also: Watershed - Image segmentation

Collaboration diagram for Watershed Segmentation:

Functions
template<class T , class labelT >
RES_T	basins (const Image< T > &imIn, const Image< labelT > &imMarkers, Image< labelT > &imBasinsOut, const StrElt &se=DEFAULT_SE)
	Constrained basins.

template<class T , class labelT >
RES_T	watershed (const Image< T > &imIn, const Image< labelT > &imMarkers, Image< T > &imOut, Image< labelT > &imBasinsOut, const StrElt &se=DEFAULT_SE)
	Constrained watershed.

template<class T >
RES_T	lblSkiz (Image< T > &labelIm1, Image< T > &labelIm2, const Image< T > &maskIm, const StrElt &se=DEFAULT_SE)
	Skiz on label image.

template<class T1 , class T2 >
RES_T	inflBasins (const Image< T1 > &imIn, Image< T2 > &basinsOut, const StrElt &se=DEFAULT_SE)
	Influences basins.

template<class T >
RES_T	inflZones (const Image< T > &imIn, Image< T > &imOut, const StrElt &se=DEFAULT_SE)
	Influences zones.

template<class T >
RES_T	waterfall (const Image< T > &gradIn, const Image< T > &wsIn, Image< T > &imGradOut, Image< T > &imWsOut, const StrElt &se=DEFAULT_SE)
	Waterfall.

template<class T >
RES_T	waterfall (const Image< T > &gradIn, UINT nLevel, Image< T > &imWsOut, const StrElt &se=DEFAULT_SE)
	Waterfall.

Function Documentation

◆ basins()

template<class T , class labelT >

RES_T basins	(	const Image< T > &	imIn,
		const Image< labelT > &	imMarkers,
		Image< labelT > &	imBasinsOut,
		const StrElt &	se = `DEFAULT_SE`
	)

Constrained basins.

Hierachical queue based algorithm as described by S. Beucher (2011) [1]

Parameters

[in]	imIn	Input image.
[in]	imMarkers	Label image containing the markers.
[out]	imBasinsOut	(optional) Output image containing the basins.
[in]	se	Structuring element After processing, this image will contain the basins with the same label values as the initial markers.

Example

from smilPython import *
 
# Load an image
imIn = Image("https://smil.cmm.minesparis.psl.eu/images/DNA_small.png")
imIn.show()
 
# Create a gradient image
imGrad = Image(imIn)
gradient(imIn, imGrad)
 
# Manually impose markers on image
imMark = Image(imIn, "UINT16")
imMark << 0
# One for the background...
imMark.setPixel(75, 40, 1)
# and one on two connected particules
imMark.setPixel(78, 86, 2)
imMark.setPixel(88, 76, 3)
 
# Dilate the markers to avoid to be blocked in a minimum
dilate(imMark, imMark, 2)
#imMark.showLabel()
 
# Create the watershed
imWS = Image(imIn)
watershed(imGrad, imMark, imWS)
 
# Display output
imWS.show()
 
# Display the output as overlay on the original image
imIn.getViewer().drawOverlay(imWS & 1)
 

◆ watershed()

template<class T , class labelT >

RES_T watershed	(	const Image< T > &	imIn,
		const Image< labelT > &	imMarkers,
		Image< T > &	imOut,
		Image< labelT > &	imBasinsOut,
		const StrElt &	se = `DEFAULT_SE`
	)

Constrained watershed.

Hierachical queue based algorithm as described by S. Beucher (2011) [1]

Parameters

[in]	imIn	Input image.
[in]	imMarkers	Label image containing the markers.
[in]	se	Structuring element
[out]	imOut	Output image containing the watershed lines.
[out]	imBasinsOut	(optional) Output image containing the basins. After processing, this image will contain the basins with the same label values as the initial markers.

Example

from smilPython import *
 
# Load an image
imIn = Image("https://smil.cmm.minesparis.psl.eu/images/DNA_small.png")
imIn.show()
 
# Create a gradient image
imGrad = Image(imIn)
gradient(imIn, imGrad)
 
# Manually impose markers on image
imMark = Image(imIn, "UINT16")
imMark << 0
# One for the background...
imMark.setPixel(75, 40, 1)
# and one on two connected particules
imMark.setPixel(78, 86, 2)
imMark.setPixel(88, 76, 3)
 
# Dilate the markers to avoid to be blocked in a minimum
dilate(imMark, imMark, 2)
#imMark.showLabel()
 
# Create the watershed
imWS = Image(imIn)
watershed(imGrad, imMark, imWS)
 
# Display output
imWS.show()
 
# Display the output as overlay on the original image
imIn.getViewer().drawOverlay(imWS & 1)
 

◆ lblSkiz()

template<class T >

RES_T lblSkiz	(	Image< T > &	labelIm1,
		Image< T > &	labelIm2,
		const Image< T > &	maskIm,
		const StrElt &	se = `DEFAULT_SE`
	)

Skiz on label image.

Performs the influence zones on a label image as described by S. Beucher (2011) [3] If a maskIm is provided, the skiz is geodesic.

◆ inflBasins()

template<class T1 , class T2 >

RES_T inflBasins	(	const Image< T1 > &	imIn,
		Image< T2 > &	basinsOut,
		const StrElt &	se = `DEFAULT_SE`
	)

Influences basins.

Performs the influence basins using the lblSkiz function. Input image is supposed to be binary.

◆ inflZones()