Math with F0-transform support

Functions
void	cv::ft::FT02D_components (InputArray matrix, InputArray kernel, OutputArray components, InputArray mask=noArray())
	Computes components of the array using direct \(F^0\)-transform. More...
void	cv::ft::FT02D_FL_process (InputArray matrix, const int radius, OutputArray output)
	Sligtly less accurate version of \(F^0\)-transfrom computation optimized for higher speed. The methods counts with linear basic function. More...
void	cv::ft::FT02D_FL_process_float (InputArray matrix, const int radius, OutputArray output)
	Sligtly less accurate version of \(F^0\)-transfrom computation optimized for higher speed. The methods counts with linear basic function. More...
void	cv::ft::FT02D_inverseFT (InputArray components, InputArray kernel, OutputArray output, int width, int height)
	Computes inverse \(F^0\)-transfrom. More...
int	cv::ft::FT02D_iteration (InputArray matrix, InputArray kernel, OutputArray output, InputArray mask, OutputArray maskOutput, bool firstStop)
	Computes \(F^0\)-transfrom and inverse \(F^0\)-transfrom at once and return state. More...
void	cv::ft::FT02D_process (InputArray matrix, InputArray kernel, OutputArray output, InputArray mask=noArray())
	Computes \(F^0\)-transfrom and inverse \(F^0\)-transfrom at once. More...

Detailed Description

Fuzzy transform ( \(F^0\)-transform) of the 0th degree transforms whole image to a matrix of its components. These components are used in latter computation where each of them represents average color of certain subarea.

Function Documentation

FT02D_components()

void cv::ft::FT02D_components	(	InputArray	matrix,
		InputArray	kernel,
		OutputArray	components,
		InputArray	mask = noArray()
	)

Python:
	components	=	cv.ft.FT02D_components(	matrix, kernel[, components[, mask]]	)

#include <opencv2/fuzzy/fuzzy_F0_math.hpp>

Computes components of the array using direct \(F^0\)-transform.

Parameters

matrix	Input array.
kernel	Kernel used for processing. Function ft::createKernel can be used.
components	Output 32-bit float array for the components.
mask	Mask can be used for unwanted area marking.

The function computes components using predefined kernel and mask.

FT02D_FL_process()

void cv::ft::FT02D_FL_process	(	InputArray	matrix,
		const int	radius,
		OutputArray	output
	)

Python:
	output	=	cv.ft.FT02D_FL_process(	matrix, radius[, output]	)

#include <opencv2/fuzzy/fuzzy_F0_math.hpp>

Sligtly less accurate version of \(F^0\)-transfrom computation optimized for higher speed. The methods counts with linear basic function.

Parameters

matrix	Input 3 channels matrix.
radius	Radius of the ft::LINEAR basic function.
output	Output array.

This function computes F-transfrom and inverse F-transfotm using linear basic function in one step. It is ~10 times faster than ft::FT02D_process method.

FT02D_FL_process_float()

void cv::ft::FT02D_FL_process_float	(	InputArray	matrix,
		const int	radius,
		OutputArray	output
	)

Python:
	output	=	cv.ft.FT02D_FL_process_float(	matrix, radius[, output]	)

#include <opencv2/fuzzy/fuzzy_F0_math.hpp>

Sligtly less accurate version of \(F^0\)-transfrom computation optimized for higher speed. The methods counts with linear basic function.

Parameters

matrix	Input 3 channels matrix.
radius	Radius of the ft::LINEAR basic function.
output	Output array.

This function computes F-transfrom and inverse F-transfotm using linear basic function in one step. It is ~9 times faster then ft::FT02D_process method and more accurate than ft::FT02D_FL_process method.

FT02D_inverseFT()

void cv::ft::FT02D_inverseFT	(	InputArray	components,
		InputArray	kernel,
		OutputArray	output,
		int	width,
		int	height
	)

Python:
	output	=	cv.ft.FT02D_inverseFT(	components, kernel, width, height[, output]	)

#include <opencv2/fuzzy/fuzzy_F0_math.hpp>

Computes inverse \(F^0\)-transfrom.

Parameters

components	Input 32-bit float single channel array for the components.
kernel	Kernel used for processing. Function ft::createKernel can be used.
output	Output 32-bit float array.
width	Width of the output array.
height	Height of the output array.

Computation of inverse F-transform.

FT02D_iteration()

int cv::ft::FT02D_iteration	(	InputArray	matrix,
		InputArray	kernel,
		OutputArray	output,
		InputArray	mask,
		OutputArray	maskOutput,
		bool	firstStop
	)

Python:
	retval, output, maskOutput	=	cv.ft.FT02D_iteration(	matrix, kernel, mask, firstStop[, output[, maskOutput]]	)

#include <opencv2/fuzzy/fuzzy_F0_math.hpp>

Computes \(F^0\)-transfrom and inverse \(F^0\)-transfrom at once and return state.

Parameters

matrix	Input matrix.
kernel	Kernel used for processing. Function ft::createKernel can be used.
output	Output 32-bit float array.
mask	Mask used for unwanted area marking.
maskOutput	Mask after one iteration.
firstStop	If true function returns -1 when first problem appears. In case of false the process is completed and summation of all problems returned.

This function computes iteration of F-transfrom and inverse F-transfotm and handle image and mask change. The function is used in ft::inpaint function.

FT02D_process()

void cv::ft::FT02D_process	(	InputArray	matrix,
		InputArray	kernel,
		OutputArray	output,
		InputArray	mask = noArray()
	)

Python:
	output	=	cv.ft.FT02D_process(	matrix, kernel[, output[, mask]]	)

#include <opencv2/fuzzy/fuzzy_F0_math.hpp>

Computes \(F^0\)-transfrom and inverse \(F^0\)-transfrom at once.

Parameters

matrix	Input matrix.
kernel	Kernel used for processing. Function ft::createKernel can be used.
output	Output 32-bit float array.
mask	Mask used for unwanted area marking.

This function computes F-transfrom and inverse F-transfotm in one step. It is fully sufficient and optimized for cv::Mat.