Histogram evaluation and applications. More...

Detailed Description

Histogram evaluation and applications.

This module contains functions to evaluate image histograms and some applications such as contrast enhancement, histogram manipulation and thresholding

Collaboration diagram for Histogram:

Functions
template<class T >
	histogram (const Image< T > &imIn, size_t *h)
	Image histogram.

template<class T >
RES_T	histogram (const Image< T > &imIn, const Image< T > &imMask, size_t *h)
	Image histogram.

template<class T >
std::map< T, UINT >	histogram (const Image< T > &imIn, bool fullRange=false)
	histogram() - Image histogram

template<class T >
std::map< T, UINT >	histogram (const Image< T > &imIn, const Image< T > &imMask, bool fullRange=false)
	histogram() - Image histogram with a mask image.

template<class T , class T_out >
RES_T	threshold (const Image< T > &imIn, T minVal, T maxVal, T_out trueVal, T_out falseVal, Image< T_out > &imOut)
	threshold() - Image threshold

template<class T , class T_out >
RES_T	threshold (const Image< T > &imIn, T minVal, T maxVal, Image< T_out > &imOut)
	threshold() - Image threshold

template<class T , class T_out >
RES_T	threshold (const Image< T > &imIn, T minVal, Image< T_out > &imOut)
	threshold() - Image threshold

template<class T , class T_out >
RES_T	threshold (const Image< T > &imIn, Image< T_out > &imOut)
	threshold() - Otsu Image threshold

template<class T1 , class T2 >
RES_T	stretchHistogram (const Image< T1 > &imIn, T1 inMinVal, T1 inMaxVal, Image< T2 > &imOut, T2 outMinVal=numeric_limits< T2 >::min(), T2 outMaxVal=numeric_limits< T2 >::max())
	stretchHistogram() - Stretch histogram

template<class T1 , class T2 >
RES_T	stretchHistogram (const Image< T1 > &imIn, Image< T2 > &imOut, T2 outMinVal, T2 outMaxVal)
	stretchHistogram() - Stretch histogram

template<class T1 , class T2 >
RES_T	stretchHistogram (const Image< T1 > &imIn, Image< T2 > &imOut)
	stretchHistogram() - Stretch histogram

template<class T >
vector< T >	histogramRange (const Image< T > &imIn, double ignorePercent, bool cumulative=true)
	histogramRange() - Min and Max values of an histogram ignoring left/right low values (lower than a given height/cumulative height).

template<class T >
RES_T	enhanceContrast (const Image< T > &imIn, Image< T > &imOut, double saturation=0.25)
	enhanceContrast() - Enhance contrast

template<class T >
vector< T >	otsuThresholdValues (map< T, UINT > &hist, UINT threshLevels=1)
	otsuThresholdValues() - Return threshold values and the value of the resulting variance between classes

template<class T >
vector< T >	otsuThresholdValues (const Image< T > &im, UINT threshLevels=1)
	otsuThresholdValues() - Return threshold values and the value of the resulting variance between classes

template<class T >
vector< T >	otsuThresholdValues (const Image< T > &im, const Image< T > &imMask, UINT threshLevels=1)
	otsuThresholdValues() - Return threshold values and the value of the resulting variance between classes

template<class T , class T_out >
vector< T >	otsuThreshold (const Image< T > &imIn, Image< T_out > &imOut, UINT nbrThresholds)
	otsuThreshold() - Otsu Threshold

template<class T , class T_out >
T	otsuThreshold (const Image< T > &imIn, Image< T_out > &imOut)
	otsuThreshold() - Otsu Threshold

template<class T , class T_out >
vector< T >	otsuThreshold (const Image< T > &imIn, const Image< T > &imMask, Image< T_out > &imOut, UINT nbrThresholds=1)
	otsuThreshold() - Otsu Threshold

Function Documentation

◆ histogram() [1/4]

template<class T >

histogram	(	const Image< T > &	imIn,
		size_t *	h
	)

Image histogram.

Calculate the histogram of the image

Parameters

[in]	imIn	: input image
[out]	h	: vector with histogram

Note: Available only in C++

◆ histogram() [2/4]

template<class T >

RES_T histogram	(	const Image< T > &	imIn,
		const Image< T > &	imMask,
		size_t *	h
	)

Image histogram.

Returns the histogram of the image in the region defined by the image mask.

Parameters

[in]	imIn	: input image
[in]	imMask	: image mask
[out]	h	: vector with histogram

Note: Available only in C++

◆ histogram() [3/4]

template<class T >

std::map< T, UINT > histogram	(	const Image< T > &	imIn,
		bool	fullRange = `false`
	)

histogram() - Image histogram

Parameters

[in]	imIn	: input image
[in]	fullRange	: result contains all possible values in the image type range

Returns: the histogram as a map with the pairs <value, count>.

◆ histogram() [4/4]

template<class T >

std::map< T, UINT > histogram	(	const Image< T > &	imIn,
		const Image< T > &	imMask,
		bool	fullRange = `false`
	)

histogram() - Image histogram with a mask image.

Returns the histogram of the image in the region defined by the image mask.

Parameters

[in]	imIn	: input image
[in]	imMask	: image mask
[in]	fullRange	: result contains all possible values in the image type range

Returns: the histogram as a map with the pairs <value, count>.

◆ threshold() [1/4]

template<class T , class T_out >

RES_T threshold	(	const Image< T > &	imIn,
		T	minVal,
		T	maxVal,
		T_out	trueVal,
		T_out	falseVal,
		Image< T_out > &	imOut
	)

threshold() - Image threshold

Image threshold based on a range of values defined by [minVal, maxVal].

The result is a image where :

imOut(x) = (imIn(x) >= minVal && imIn(x) < maxVal ? trueVal : falseVal)

Parameters

[in]	imIn	: input image
[in]	minVal,maxVal	: interest range of pixel values
[in]	trueVal	: value to assign to pixels in the interest range
[in]	falseVal	: value to assign to pixels outside the interest range
[out]	imOut	: output image

◆ threshold() [2/4]

template<class T , class T_out >

RES_T threshold	(	const Image< T > &	imIn,
		T	minVal,
		T	maxVal,
		Image< T_out > &	imOut
	)

threshold() - Image threshold

Image threshold based on a range of values defined by [minVal, maxVal].

The result is a image where :

imOut(x) = (imIn(x) >= minVal && imIn(x) < maxVal ? max(T) : min(T))

Parameters

[in]	imIn	: input image
[in]	minVal,maxVal	: interest range of pixel values
[out]	imOut	: output image

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ threshold() [3/4]

template<class T , class T_out >

RES_T threshold	(	const Image< T > &	imIn,
		T	minVal,
		Image< T_out > &	imOut
	)

threshold() - Image threshold

Image threshold based on some threshold.

The result is a image where :

imOut(x) = (imIn(x) >= minVal ? max(T) : men(T))

Parameters

[in]	imIn	: input image
[in]	minVal	: threshold
[out]	imOut	: output image

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ threshold() [4/4]

template<class T , class T_out >

RES_T threshold	(	const Image< T > &	imIn,
		Image< T_out > &	imOut
	)

threshold() - Otsu Image threshold

Parameters

[in]	imIn	: input image
[out]	imOut	: output image

See also

Otsu's method

◆ stretchHistogram() [1/3]

template<class T1 , class T2 >

RES_T stretchHistogram	(	const Image< T1 > &	imIn,
		T1	inMinVal,
		T1	inMaxVal,
		Image< T2 > &	imOut,
		T2	outMinVal = `numeric_limits<T2>::min()`,
		T2	outMaxVal = `numeric_limits<T2>::max()`
	)

stretchHistogram() - Stretch histogram

Create a new image based on a linear transformation of the histogram of the input image.

The output image is created by the following rules :

coef = (outMaxVal - outMinVal) / (inMaxVal - inMinVal)
imOut(x) = coeff * (imIn(x) - inMinVal) + outMinVal
output values are upper and lower bounded by the valid range [min(T2), max(T2)]

Parameters

[in]	imIn	: input image
[in]	inMinVal,inMaxVal	: input range coefficient
[out]	imOut	: output image
[out]	outMinVal,outMaxVal	: output range

◆ stretchHistogram() [2/3]

template<class T1 , class T2 >

RES_T stretchHistogram	(	const Image< T1 > &	imIn,
		Image< T2 > &	imOut,
		T2	outMinVal,
		T2	outMaxVal
	)

stretchHistogram() - Stretch histogram

Create a new image based on a linear transformation of the histogram of the input image.

As before but the range values in the input image are taken from the range of its histogram.

The output image is created by the following rules :

(inMinVal, inMaxVal) = range(imIn). See rangeVal()
coef = (outMaxVal - outMinVal) / (inMaxVal - inMinVal)
imOut(x) = coeff * (imIn(x) - inMinVal) + outMinVal
output values are upper and lower bounded by the valid range [min(T2), max(T2)]

Parameters

[in]	imIn	: input image
[out]	imOut	: output image
[out]	outMinVal,outMaxVal	: output range

◆ stretchHistogram() [3/3]

template<class T1 , class T2 >

RES_T stretchHistogram	(	const Image< T1 > &	imIn,
		Image< T2 > &	imOut
	)

stretchHistogram() - Stretch histogram

Create a new image based on a linear transformation of the histogram of the input image.

As before but the range values in the input image are taken from the range of its histogram and the range values in the output image are the range defined by the data type.

The output image is created by the following rules :

(inMinVal, inMaxVal) = range(imIn). See rangeVal()
coef = (max(T2) - min(T2)) / (inMaxVal - inMinVal)
imOut(x) = coeff * (imIn(x) - inMinVal) + min(T2)

Parameters

[in]	imIn	: input image
[out]	imOut	: output image

◆ histogramRange()

template<class T >

vector< T > histogramRange	(	const Image< T > &	imIn,
		double	ignorePercent,
		bool	cumulative = `true`
	)

histogramRange() - Min and Max values of an histogram ignoring left/right low values (lower than a given height/cumulative height).

If cumulative is true, it stops when the integral of the histogram values reaches ignorePercent * NbrPixels. Otherwise, it stops at the first value of the histogram higher than ignorePercent * max(histogram)

Parameters

[in]	imIn	: input image
[in]	ignorePercent	: explained above
[in]	cumulative	: explained above

Returns: a vector with the pair of extrema values of the histogram.

◆ enhanceContrast()

template<class T >

RES_T enhanceContrast	(	const Image< T > &	imIn,
		Image< T > &	imOut,
		double	saturation = `0.25`
	)

enhanceContrast() - Enhance contrast

Parameters

[in]	imIn	: input image
[out]	imOut	: output image
[in]	saturation	:

◆ otsuThresholdValues() [1/3]

template<class T >

vector< T > otsuThresholdValues	(	map< T, UINT > &	hist,
		UINT	threshLevels = `1`
	)

otsuThresholdValues() - Return threshold values and the value of the resulting variance between classes

Parameters

[in]	hist	: image histogram
[in]	threshLevels	: number of threshold levels (default : 1)

Returns: vector with the threshold levels

◆ otsuThresholdValues() [2/3]

template<class T >

vector< T > otsuThresholdValues	(	const Image< T > &	im,
		UINT	threshLevels = `1`
	)

otsuThresholdValues() - Return threshold values and the value of the resulting variance between classes

Parameters

[in]	im	: image
[in]	threshLevels	: number of threshold levels (default : 1)

Returns: vector with the threshold levels

◆ otsuThresholdValues() [3/3]

template<class T >

vector< T > otsuThresholdValues	(	const Image< T > &	im,
		const Image< T > &	imMask,
		UINT	threshLevels = `1`
	)

otsuThresholdValues() - Return threshold values and the value of the resulting variance between classes

Parameters

[in]	im	: image
[in]	imMask	: image mask
[in]	threshLevels	: number of threshold levels (default : 1)

Returns: vector with the threshold levels

◆ otsuThreshold() [1/3]

template<class T , class T_out >

vector< T > otsuThreshold	(	const Image< T > &	imIn,
		Image< T_out > &	imOut,
		UINT	nbrThresholds
	)

otsuThreshold() - Otsu Threshold

Image threshold based on the Otsu algorithm.

See also

Otsu's method

Parameters

[in]	imIn	: input image
[out]	imOut	: output image
[in]	nbrThresholds	: number of thresholds. The output image will have `nbrThresholds + 1` classes.

Example

from smilPython import *
 
# Load an image
im1 = Image("https://smil.cmm.minesparis.psl.eu/images/lena.png")
im1.show()
 
# Manual threshold (between 100 and 255)
im2 = Image(im1)
threshold(im1, 100, 255, im2)
im2.show()
 
# Otsu automatic threshold
im3 = Image(im1)
# Generate two threshold values (i.e. 3 classes)
otsuThreshold(im1, im3, 2)
# Display the resulting image with three labels values corresponding to the three classes
im3.showLabel()

◆ otsuThreshold() [2/3]

template<class T , class T_out >

T otsuThreshold	(	const Image< T > &	imIn,
		Image< T_out > &	imOut
	)

otsuThreshold() - Otsu Threshold

Image threshold based on the Otsu algorithm.

Output image will have only two classes.

See also

Otsu's method

Parameters

[in]	imIn	: input image
[out]	imOut	: output image

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ otsuThreshold() [3/3]

template<class T , class T_out >

vector< T > otsuThreshold	(	const Image< T > &	imIn,
		const Image< T > &	imMask,
		Image< T_out > &	imOut,
		UINT	nbrThresholds = `1`
	)

otsuThreshold() - Otsu Threshold

Image threshold based on the Otsu algorithm (a mask will be applied before threshold).

See also

Otsu's method

Parameters

[in]	imIn	: input image
[in]	imMask	: mask image
[out]	imOut	: output image
[in]	nbrThresholds	: number of thresholds. The output image will have `nbrThresholds + 1` classes.

Example

from smilPython import *
 
# Load an image
im1 = Image("https://smil.cmm.minesparis.psl.eu/images/lena.png")
im1.show()
 
# Manual threshold (between 100 and 255)
im2 = Image(im1)
threshold(im1, 100, 255, im2)
im2.show()
 
# Otsu automatic threshold
im3 = Image(im1)
# Generate two threshold values (i.e. 3 classes)
otsuThreshold(im1, im3, 2)
# Display the resulting image with three labels values corresponding to the three classes
im3.showLabel()

Detailed Description

Functions

Function Documentation

◆ histogram() [1/4]

◆ histogram() [2/4]

◆ histogram() [3/4]

◆ histogram() [4/4]

◆ threshold() [1/4]

◆ threshold() [2/4]

◆ threshold() [3/4]

◆ threshold() [4/4]

◆ stretchHistogram() [1/3]

◆ stretchHistogram() [2/3]

◆ stretchHistogram() [3/3]

◆ histogramRange()

◆ enhanceContrast()

◆ otsuThresholdValues() [1/3]

◆ otsuThresholdValues() [2/3]

◆ otsuThresholdValues() [3/3]

◆ otsuThreshold() [1/3]

◆ otsuThreshold() [2/3]

◆ otsuThreshold() [3/3]