Olena: oln::utils Namespace Reference

oln::utils Namespace Reference

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Classes
class	buffer
	Buffer used for MD5 data type abstraction. More...
struct	hist_traits
	Traits for oln::utils::abstract::histogram hierarchy. More...
struct	hist_traits< histogram< T, CPT, V2P, Exact > >
	Traits for oln::utils::abstract::histogram hierarchy. More...
class	histogram
struct	hist_traits< histogram_minmax< T, CPT, V2P, Exact > >
class	histogram_minmax
struct	hist_traits< histogram_min< T, CPT, V2P, Exact > >
class	histogram_min
struct	hist_traits< histogram_max< T, CPT, V2P, Exact > >
class	histogram_max
struct	select_distrib_sort
struct	select_distrib_sort< true >
class	key
	16 bytes key More...
class	MD5
	Class used to compute a MD5 digest. More...
class	se_stat
	Compute the variance and the mean within a window. More...
struct	f_minmax
	Unary function that stores the min and the max. More...
struct	f_moments
	Computes the mean, the variance and store the min, the max. More...
class	timer
Functions
template<class T> mlc::exact< T >::ret::value_type	min (const abstract::histogram< T > &hist)
template<class T> mlc::exact< T >::ret::value_type	max (const abstract::histogram< T > &hist)
template<typename T, typename CPT, class V2P, class Exact> T	min (histogram_minmax< T, CPT, V2P, Exact > &hist)
	Minimum non-zero value of an histogram.
template<typename T, typename CPT, class V2P, class Exact> T	min (histogram_min< T, CPT, V2P, Exact > &hist)
	Minimum non-zero value of an histogram.
template<typename T, typename CPT, class V2P, class Exact> T	max (histogram_minmax< T, CPT, V2P, Exact > &hist)
	Maximum non-zero value of an histogram.
template<typename T, typename CPT, class V2P, class Exact> T	max (histogram_max< T, CPT, V2P, Exact > &hist)
	Maximum non-zero value of an histogram.
template<class I> void	distrib_sort (const oln::abstract::image< I > &im, std::vector< typename mlc::exact< I >::ret::point_type > &v)
template<class I> void	distrib_sort_inv (const oln::abstract::image< I > &im, std::vector< typename mlc::exact< I >::ret::point_type > &v)
template<class I> key	md5 (const oln::abstract::non_vectorial_image< I > &im)
	Compute The Md5 value of an image.
template<class I> key	md5 (const oln::abstract::vectorial_image< I > &im)
	Compute The Md5 value of an image.

Function Documentation

template<class I>
void distrib_sort	(	const oln::abstract::image< I > &	im,
		std::vector< typename mlc::exact< I >::ret::point_type > &	v
	)

Sort the values of an image, and store the result in a vector

This sort is efficient.

im Image non_vectorial.
v sorted vector at the end of the function.
Precondition:
precondition(v.size() == im.npoints());
A histogram of the image has to be possible.

Definition at line 676 of file histogram.hh.

References oln::abstract::image< Exact >::npoints().

00678     {
00679       typedef oln_value_type(I) val;
00680 
00681       typedef typename ntg_is_a(val, ntg::non_vectorial)::ensure_type
00682                                                          ensure_type;
00683 
00684       // check the size
00685       precondition(v.size() == im.npoints());
00686 
00687       // calculate the histogram of the image
00688       utils::histogram<val> histo(im);
00689 
00690       // Initialize the array of pointer to the point in the result.
00691       // With the histogram the number of each color can be deduced and
00692       // then it calculates an array of pointer for quick access to each
00693       // value of the image.
00694       const ntg_cumul_type(val) card = ntg_max_val(val)
00695                                         - ntg_min_val(val) + 1;
00696       std::vector<oln_point_type(I)* > ptr(card);
00697       ptr[0] = &(v[0]);
00698       for (ntg_cumul_type(val) i = 1; i < card; ++i)
00699         ptr[i] = ptr[i - 1] + histo[i - 1 + ntg_min_val(val)];
00700 
00701       // Now iterate on the image to sort point in the order of their
00702       // level
00703       oln_iter_type(I) p(im);
00704       for_all(p)
00705         *(ptr[unsigned(im[p] - ntg_min_val(val))]++) = p;
00706     }

template<class I>
void distrib_sort_inv	(	const oln::abstract::image< I > &	im,
		std::vector< typename mlc::exact< I >::ret::point_type > &	v
	)

Inverted sort of the values of an image, and store the result in a vector

This sort is efficient.

im Image non_vectorial.
v sorted vector at the end of the function.
Precondition:
precondition(v.size() == im.npoints());
A histogram of the image has to be possible.

Definition at line 719 of file histogram.hh.

References oln::abstract::image< Exact >::npoints().

00721     {
00722       typedef oln_value_type(I) val;
00723 
00724       typedef typename ntg_is_a(val, ntg::non_vectorial)::ensure_type
00725                                                         ensure_type;
00726 
00727       precondition(v.size() == im.npoints());
00728 
00729       utils::histogram<val> histo(im);
00730 
00731       const ntg_cumul_type(val) card = ntg_max_val(val)
00732                                         - ntg_min_val(val) + 1;
00733       std::vector<oln_point_type(I)* > ptr(card);
00734       ptr[card - 1] = &(v[0]);
00735 
00736       for (ntg_signed_cumul_type(val) i = card - 2; i >= 0; --i)
00737         ptr[i] = ptr[i + 1] + histo[i + 1 + ntg_min_val(val)];
00738 
00739       oln_iter_type(I) p(im);
00740       for_all(p)
00741         *(ptr[unsigned(im[p] - ntg_min_val(val))]++) = p;
00742     }

template<class T>
mlc::exact< T >::ret::value_type max	(	const abstract::histogram< T > &	hist	)	`[inline]`

Maximum value of an histogram.

Return the higher value within the image used to build the histogram.

Note:: It can be slow when the histogram is sparse because it iterates over a large range of 0. Use histogram_max or histogram_minmax instead.

See also:: histogram_max

Definition at line 330 of file histogram.hh.

00331     {
00332       typedef typename ntg_is_a(oln_value_type(T),
00333                                 ntg::non_vectorial)::ensure_type ensure_type;
00334 
00335       oln_value_type(T) i;
00336       for (i = ntg_max_val(oln_value_type(T));
00337            i != ntg_min_val(oln_value_type(T));
00338            i = ntg::pred(i))
00339         if (hist[i] > ntg_zero_val(oln_cpt_type(T)))
00340           break;
00341       return i;
00342     }

template<class I>
key oln::utils::md5	(	const oln::abstract::vectorial_image< I > &	im	)	`[inline]`

Compute The Md5 value of an image.

Parameters:

I	Exact type of the image.

im Image to process.

Vectorial image version.

Definition at line 507 of file md5.hh.

template<class I>
key oln::utils::md5	(	const oln::abstract::non_vectorial_image< I > &	im	)	`[inline]`

Compute The Md5 value of an image.

Parameters:

I	Exact type of the image.

im Image to process.

Non vectorial image version.

Definition at line 490 of file md5.hh.

template<class T>
mlc::exact< T >::ret::value_type min	(	const abstract::histogram< T > &	hist	)	`[inline]`

Minimum value of an histogram.

Return the smaller value within the image used to build the histogram.

Note:: It can be slow when the histogram is sparse because it iterates over a large range of 0. Use histogram_min or histogram_minmax instead.

See also:: histogram_min

Definition at line 305 of file histogram.hh.

00306     {
00307       typedef typename ntg_is_a(oln_value_type(T),
00308                                 ntg::non_vectorial)::ensure_type ensure_type;
00309 
00310       oln_value_type(T) i;
00311       for (i = ntg_min_val(oln_value_type(T));
00312            i != ntg_max_val(oln_value_type(T));
00313            i = ntg::succ(i))
00314         if (hist[i] > ntg_zero_val(oln_cpt_type(T)))
00315           break;
00316       return i;
00317     }

Generated on Thu Apr 15 20:17:21 2004 for Olena by

1.3.6-20040222

oln::utils Namespace Reference

Classes

Functions

Detailed Description

Function Documentation