oln::convol::fast Namespace Reference

Implementation of algorithms for large structuring elements. More...

Functions
template<class C, class B, class I, class BE> mute< I, typename convoutput< C, B, typename mlc::exact< I >::ret::value_type >::ret >::ret	gaussian (const convert::abstract::conversion< C, B > &input_conv, const abstract::image< I > &in, ntg::float_s sigma, const abstract::behavior< BE > &behavior)
	Gaussian filter.
template<class C, class B, class I, class BE> mute< I, typename convoutput< C, B, typename mlc::exact< I >::ret::value_type >::ret >::ret	gaussian_derivative (const convert::abstract::conversion< C, B > &input_conv, const abstract::image< I > &in, ntg::float_s sigma, const abstract::behavior< BE > &behavior)
	Derivative gaussian filter.
template<class C, class B, class I, class BE> mute< I, typename convoutput< C, B, typename mlc::exact< I >::ret::value_type >::ret >::ret	gaussian_second_derivative (const convert::abstract::conversion< C, B > &input_conv, const abstract::image< I > &in, ntg::float_s sigma, const abstract::behavior< BE > &behavior)
	Second derivative gaussian filter.
template<class I, class BE> oln::mute< I >::ret	gaussian (const abstract::image< I > &in, ntg::float_s sigma, const abstract::behavior< BE > &behavior)
	Gaussian filter with a default conversion.
template<class I, class BE> oln::mute< I >::ret	gaussian_derivative (const abstract::image< I > &in, ntg::float_s sigma, const abstract::behavior< BE > &behavior)
	Derivative gaussian filter with a default conversion.
template<class I, class BE> oln::mute< I >::ret	gaussian_second_derivative (const abstract::image< I > &in, ntg::float_s sigma, const abstract::behavior< BE > &behavior=mirror_behavior<>())
	Second derivative gaussian filter with a default conversion.
template<class I> oln::mute< I >::ret	gaussian (const abstract::image< I > &in, ntg::float_s sigma)
	Gaussian filter with a default conversion and a default behavior.
template<class I> oln::mute< I >::ret	gaussian_derivative (const abstract::image< I > &in, ntg::float_s sigma)
	Derivative gaussian filter with a default conversion and a default behavior.
template<class I> oln::mute< I >::ret	gaussian_second_derivative (const abstract::image< I > &in, ntg::float_s sigma)
	Second derivative gaussian filter with a default conversion and a default behavior.
Variables
mute< I, typename convoutput< C, B, oln_value_type(I)>::ret >::re	gaussian )(const convert::abstract::conversion< C, B > &c, const abstract::image< I > &in, ntg::float_s sigma, const abstract::behavior< BE > &behavior)
mute< I, typename convoutput< C, B, oln_value_type(I)>::ret >::re	gaussian_derivative )(const convert::abstract::conversion< C, B > &c, const abstract::image< I > &in, ntg::float_s sigma, const abstract::behavior< BE > &behavior)
mute< I, typename convoutput< C, B, oln_value_type(I)>::ret >::re	gaussian_second_derivative )(const convert::abstract::conversion< C, B > &c, const abstract::image< I > &in, ntg::float_s sigma, const abstract::behavior< BE > &behavior)

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Detailed Description

Implementation of algorithms for large structuring elements.

The algorithms you can find here are fast. This mean these ones are evolved versions for large structuring elements.

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Function Documentation

template<class I> oln::mute< I >::ret gaussian (  const abstract::image< I > &  in, ntg::float_s  sigma )  [inline]

Gaussian filter with a default conversion and a default behavior. Gaussian filter implementation from "Recursively implementing the gaussian and its derivatives" Deriche 93 INRIA REPORT (num RR-1893). Warning: The content of the border is the mirror of the image. Parameters: I  Exact type of the image. in Input image. sigma Value of sigma when computing the gaussian. #include <oln/basics2d.hh> #include <oln/convol/fast_gaussian.hh> #include <oln/core/behavior.hh> #include <ntg/all.hh> int main() { typedef oln::image2d<ntg::int_u8> im_type; im_type im1(oln::load(IMG_IN "lena256.pgm")); oln::save(oln::convol::fast::gaussian(im1, 2), IMG_OUT "oln_convol_fast_gaussian_default.pbm"); return 0; } => Warning: If sigma is big enough, the result may differ a little bit with the -O3 flag of g++. Definition at line 326 of file fast_gaussian.hh. References gaussian(), and oln::mirror_bhv(). { return gaussian(convert::force<oln_value_type(I)>(), in, sigma, mirror_bhv()); }

template<class I, class BE> oln::mute< I >::ret gaussian (  const abstract::image< I > &  in, ntg::float_s  sigma, const abstract::behavior< BE > &  behavior )  [inline]

Gaussian filter with a default conversion. Gaussian filter implementation from "Recursively implementing the gaussian and its derivatives" Deriche 93 INRIA REPORT (num RR-1893). Parameters: I  Exact type of the image. BE  Exact type of the behavior. in Input image. sigma Value of sigma when computing the gaussian. behavior Object to know how to work on borders. #include <oln/basics2d.hh> #include <oln/convol/fast_gaussian.hh> #include <oln/core/behavior.hh> #include <ntg/all.hh> int main() { typedef oln::image2d<ntg::int_u8> im_type; im_type im1(oln::load(IMG_IN "lena256.pgm")); oln::save(oln::convol::fast::gaussian(im1, 2, oln::value_behavior<oln_value_type_(im_type)>(0)), IMG_OUT "oln_convol_fast_gaussian.pbm"); return 0; } => Warning: If sigma is big enough, the result may differ a little bit with the -O3 flag of g++. Definition at line 180 of file fast_gaussian.hh. References gaussian(). { return gaussian(convert::force<oln_value_type(I)>(), in, sigma, behavior); }

template<class C, class B, class I, class BE> mute<I, typename convoutput<C, B, typename mlc::exact< I >::ret::value_type>::ret>::ret gaussian (  const convert::abstract::conversion< C, B > &  input_conv, const abstract::image< I > &  in, ntg::float_s  sigma, const abstract::behavior< BE > &  behavior )

Gaussian filter. Gaussian filter implementation from "Recursively implementing the gaussian and its derivatives" Deriche 93 INRIA REPORT (num RR-1893). Parameters: C  Exact type of the conversion object. B  Base type of the conversion object. I  Exact type of the image. BE  Exact type of the behavior. input_conv Converter object. in Input image. sigma Value of sigma when computing the gaussian. behavior Object to know how to work on borders. Warning: If sigma is big enough, the result may differ a little bit with the -O3 flag of g++. Referenced by gaussian().

template<class I> oln::mute< I >::ret gaussian_derivative (  const abstract::image< I > &  in, ntg::float_s  sigma )  [inline]

Derivative gaussian filter with a default conversion and a default behavior. Gaussian filter implementation from "Recursively implementing the gaussian and its derivatives" Deriche 93 INRIA REPORT (num RR-1893). Warning: The content of the border is the mirror of the image. Parameters: I  Exact type of the image. BE  Exact type of the behavior. in Input image. sigma Value of sigma when computing the gaussian. behavior Object to know how to work on borders. #include <oln/basics2d.hh> #include <oln/convol/fast_gaussian.hh> #include <oln/core/behavior.hh> #include <ntg/all.hh> int main() { typedef oln::image2d<ntg::int_u8> im_type; im_type im1(oln::load(IMG_IN "lena256.pgm")); oln::save(oln::convol::fast::gaussian_derivative(im1, 2), IMG_OUT "oln_convol_fast_gaussian_derivative_default.pbm"); return 0; } => Warning: If sigma is big enough, the result may differ a little bit with the -O3 flag of g++. Definition at line 376 of file fast_gaussian.hh. References gaussian_derivative(), and oln::mirror_bhv(). { return gaussian_derivative(convert::force<oln_value_type(I)>(), in, sigma, mirror_bhv()); }

template<class I, class BE> oln::mute< I >::ret gaussian_derivative (  const abstract::image< I > &  in, ntg::float_s  sigma, const abstract::behavior< BE > &  behavior )  [inline]

Derivative gaussian filter with a default conversion. Gaussian filter implementation from "Recursively implementing the gaussian and its derivatives" Deriche 93 INRIA REPORT (num RR-1893). Parameters: I  Exact type of the image. BE  Exact type of the behavior. in Input image. sigma Value of sigma when computing the gaussian. behavior Object to know how to work on borders. #include <oln/basics2d.hh> #include <oln/convol/fast_gaussian.hh> #include <oln/core/behavior.hh> #include <ntg/all.hh> int main() { typedef oln::image2d<ntg::int_u8> im_type; im_type im1(oln::load(IMG_IN "lena256.pgm")); oln::save(oln::convol::fast::gaussian_derivative(im1, 2, oln::value_behavior<oln_value_type_(im_type)>(0)), IMG_OUT "oln_convol_fast_gaussian_derivative.pbm"); return 0; } => Warning: If sigma is big enough, the result may differ a little bit with the -O3 flag of g++. Definition at line 228 of file fast_gaussian.hh. References gaussian_derivative(). { return gaussian_derivative(convert::force<oln_value_type(I)>(), in, sigma, behavior); }

template<class C, class B, class I, class BE> mute<I, typename convoutput<C, B, typename mlc::exact< I >::ret::value_type>::ret>::ret gaussian_derivative (  const convert::abstract::conversion< C, B > &  input_conv, const abstract::image< I > &  in, ntg::float_s  sigma, const abstract::behavior< BE > &  behavior )

Derivative gaussian filter. Gaussian filter implementation from "Recursively implementing the gaussian and its derivatives" Deriche 93 INRIA REPORT (num RR-1893). Parameters: C  Exact type of the conversion object. B  Base type of the conversion object. I  Exact type of the image. BE  Exact type of the behavior. input_conv Converter object. in Input image. sigma Value of sigma when computing the gaussian. behavior Object to know how to work on borders. Warning: If sigma is big enough, the result may differ a little bit with the -O3 flag of g++. Referenced by gaussian_derivative().

template<class I> oln::mute< I >::ret gaussian_second_derivative (  const abstract::image< I > &  in, ntg::float_s  sigma )  [inline]

Second derivative gaussian filter with a default conversion and a default behavior. Gaussian filter implementation from "Recursively implementing the gaussian and its derivatives" Deriche 93 INRIA REPORT (num RR-1893). Warning: The content of the border is the mirror of the image. Parameters: I  Exact type of the image. BE  Exact type of the behavior. in Input image. sigma Value of sigma when computing the gaussian. behavior Object to know how to work on borders. #include <oln/basics2d.hh> #include <oln/convol/fast_gaussian.hh> #include <oln/core/behavior.hh> #include <ntg/all.hh> int main() { typedef oln::image2d<ntg::int_u8> im_type; im_type im1(oln::load(IMG_IN "lena256.pgm")); oln::save(oln::convol::fast::gaussian_second_derivative(im1, 2), IMG_OUT "oln_convol_fast_gaussian_second_derivative_default.pbm"); return 0; } => Warning: If sigma is big enough, the result may differ a little bit with the -O3 flag of g++. Definition at line 426 of file fast_gaussian.hh. References gaussian_second_derivative(), and oln::mirror_bhv(). { return gaussian_second_derivative(convert::force<oln_value_type(I)>(), in, sigma, mirror_bhv()); }

template<class I, class BE> oln::mute< I >::ret gaussian_second_derivative (  const abstract::image< I > &  in, ntg::float_s  sigma, const abstract::behavior< BE > &  behavior = mirror_behavior<>() )  [inline]

Second derivative gaussian filter with a default conversion. Gaussian filter implementation from "Recursively implementing the gaussian and its derivatives" Deriche 93 INRIA REPORT (num RR-1893). Parameters: I  Exact type of the image. BE  Exact type of the behavior. in Input image. sigma Value of sigma when computing the gaussian. behavior Object to know how to work on borders. #include <oln/basics2d.hh> #include <oln/convol/fast_gaussian.hh> #include <oln/core/behavior.hh> #include <ntg/all.hh> int main() { typedef oln::image2d<ntg::int_u8> im_type; im_type im1(oln::load(IMG_IN "lena256.pgm")); oln::save(oln::convol::fast::gaussian_second_derivative(im1, 2, oln::value_behavior<oln_value_type_(im_type)>(0)), IMG_OUT "oln_convol_fast_gaussian_second_derivative.pbm"); return 0; } => Warning: If sigma is big enough, the result may differ a little bit with the -O3 flag of g++. Definition at line 275 of file fast_gaussian.hh. References gaussian_second_derivative(). { return gaussian_second_derivative(convert::force<oln_value_type(I)>(), in, sigma, behavior); }

template<class C, class B, class I, class BE> mute<I, typename convoutput<C, B, typename mlc::exact< I >::ret::value_type>::ret>::ret gaussian_second_derivative (  const convert::abstract::conversion< C, B > &  input_conv, const abstract::image< I > &  in, ntg::float_s  sigma, const abstract::behavior< BE > &  behavior )

Second derivative gaussian filter. Gaussian filter implementation from "Recursively implementing the gaussian and its derivatives" Deriche 93 INRIA REPORT (num RR-1893). Parameters: C  Exact type of the conversion object. B  Base type of the conversion object. I  Exact type of the image. BE  Exact type of the behavior. input_conv Converter object. in Input image. sigma Value of sigma when computing the gaussian. behavior Object to know how to work on borders. Warning: If sigma is big enough, the result may differ a little bit with the -O3 flag of g++. Referenced by gaussian_second_derivative().

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