/
median.h
1372 lines (1180 loc) · 36.9 KB
/
median.h
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//
// Copyright (c) 2003-2010, MIST Project, Nagoya University
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// 1. Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// 3. Neither the name of the Nagoya University nor the names of its contributors
// may be used to endorse or promote products derived from this software
// without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
// IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
// FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
// DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
// IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF
// THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
/// @file mist/filter/median.h
//!
//! @brief 各次元の画像に対応したメディアン（中央値）を計算するためのライブラリ
//!
#ifndef __INCLUDE_MIST_MEDIAN_FILTER__
#define __INCLUDE_MIST_MEDIAN_FILTER__
#ifndef __INCLUDE_MIST_H__
#include "../mist.h"
#endif
#ifndef __INCLUDE_MIST_TYPE_TRAIT_H__
#include "../config/type_trait.h"
#endif
// カラー画像の設定を読み込む
#ifndef __INCLUDE_MIST_COLOR_H__
#include "../config/color.h"
#endif
#ifndef __INCLUDE_MIST_THREAD__
#include "../thread.h"
#endif
#include <algorithm>
// mist名前空間の始まり
_MIST_BEGIN
// メディアンフィルタ
namespace __median_filter_with_histogram__
{
// in : 入力画像. 入力画像の画素値は min と max の間とする
// out : 出力画像. 出力画像のメモリはあらかじめ割り当てられているものとする
// fw, fh, fd : フィルタサイズ
// min, max : 濃淡範囲
template < class Array1, class Array2, class Functor >
void median_filter( const Array1 &in, Array2 &out,
typename Array1::size_type fw, typename Array1::size_type fh, typename Array1::size_type fd,
typename Array1::value_type min, typename Array1::value_type max,
typename Array1::size_type thread_idy, typename Array1::size_type thread_numy,
typename Array1::size_type thread_idz, typename Array1::size_type thread_numz, Functor f )
{
typedef typename Array1::size_type size_type;
typedef typename Array1::difference_type difference_type;
typedef typename Array1::value_type value_type;
typedef typename Array2::value_type out_value_type;
typedef difference_type hist_value;
size_type range = static_cast< size_type >( max - min + 1 );
size_type a = 0, i, j, k, x, y, z, ri, leftnum;
difference_type pth, th, lt_med;
difference_type med;
size_type w = in.width( );
size_type h = in.height( );
size_type d = in.depth( );
const bool bprogress1 = thread_idy == 0 && d == 1;
const bool bprogress2 = thread_idz == 0 && d > 1;
size_type bw = fw / 2;
size_type bh = fh / 2;
size_type bd = fd / 2;
difference_type *leftmost = new difference_type[ fh * fd ];
difference_type *sort = new difference_type[ fw * fh * fd + 1 ];
hist_value *hist = new hist_value[ range ];
for( k = thread_idz ; k < d ; k += thread_numz )
{
for( j = thread_idy ; j < h ; j += thread_numy )
{
i = 0;
memset( hist, 0, sizeof( hist_value ) * range );
pth = 0;
leftnum = 0;
for( z = k < bd ? 0 : k - bd ; z <= k + bd && z < d ; z++ )
{
for( y = j < bh ? 0 : j - bh ; y <= j + bh && y < h ; y++ )
{
leftmost[ leftnum++ ] = in( 0, y, z ) - min;
for( x = 0 ; x <= bw ; x++ )
{
sort[ pth++ ] = in( x, y, z ) - min;
hist[ in( x, y, z ) - min ]++;
}
}
}
// 昇順に並べ替える
std::sort( sort, sort + pth );
pth--;
th = pth / 2;
med = sort[ th ];
if( sort[ 0 ] == sort[ th ] )
{
lt_med = 0;
}
else
{
a = th;
while( med <= sort[ --a ] ){}
lt_med = static_cast< signed int >( a + 1 );
}
out( i, j, k ) = static_cast< out_value_type >( med + min );
for( i = 1 ; i < w ; i++ )
{
ri = i + bw;
if( bw < i )
{
for( a = 0 ; a < leftnum ; a++ )
{
hist[ leftmost[ a ] ]--;
pth--;
if( leftmost[ a ] < med )
{
lt_med--;
}
}
}
leftnum = 0;
for( z = k < bd ? 0 : k - bd ; z <= k + bd && z < d ; z++ )
{
for( y = j < bh ? 0 : j - bh ; y <= j + bh && y < h ; y++ )
{
if( ri < w )
{
hist[ in( ri, y, z ) - min ]++;
pth++;
if( in( ri, y, z ) - min < med )
{
lt_med++;
}
}
if( bw <= i )
{
leftmost[ leftnum++ ] = in( i - bw, y, z ) - min;
}
}
}
th = pth / 2;
if( lt_med <= th )
{
while( lt_med + hist[ med ] <= th )
{
lt_med += hist[ med ];
med++;
}
}
else
{
while( th < lt_med )
{
med--;
lt_med -= hist[ med ];
}
}
out( i, j, k ) = static_cast< out_value_type >( med + min );
}
if( bprogress1 )
{
f( static_cast< double >( j + 1 ) / static_cast< double >( h ) * 100.0 );
}
}
if( bprogress2 )
{
f( static_cast< double >( k + 1 ) / static_cast< double >( d ) * 100.0 );
}
}
delete [] hist;
delete [] sort;
delete [] leftmost;
}
}
namespace __median_filter_divide_conquer__
{
// T型の配列の中央値を高速に計算するアルゴリズム
// 配列の要素 数はnum個である。
// 配列内で第c番目に小さい値を検索する
// 入力されるDATA型の配列は中身を入れ替えない代わりに，ワーク配列を利用する
template < class T >
inline T nth_value( const T *a, size_t num, size_t c, T *work1, T *work2, T *work3 )
{
typedef T value_type;
size_t i;
size_t wi1, wi2, wi3;
value_type s;
value_type *w1 = work1;
value_type *w2 = work2;
value_type *src, *www;
wi1 = wi2 = wi3 = 0;
s = a[ c ];
for( i = 0 ; i < num ; i++ )
{
if( a[ i ] < s )
{
w1[ wi1++ ] = a[ i ];
}
else if( a[ i ] > s )
{
w2[ wi2++ ] = a[ i ];
}
else
{
wi3++;
}
}
if( wi1 > c )
{
src = w1;
w1 = work3;
num = wi1;
}
else if( wi1 + wi3 <= c )
{
src = w2;
w2 = work3;
c -= wi1 + wi3;
num = wi2;
}
else
{
return ( s );
}
while( true )
{
wi1 = wi2 = wi3 = 0;
s = src[ c ];
for( i = 0 ; i < num ; i++ )
{
if( src[ i ] < s )
{
w1[ wi1++ ] = src[ i ];
}
else if( src[ i ] > s )
{
w2[ wi2++ ] = src[ i ];
}
else
{
wi3++;
}
}
if( wi1 > c )
{
www = src;
src = w1;
w1 = www;
num = wi1;
}
else if( wi1 + wi3 <= c )
{
www = src;
src = w2;
w2 = www;
c -= wi1 + wi3;
num = wi2;
}
else
{
break;
}
}
return ( s );
}
// in : 入力画像. 入力画像の画素値は min と max の間とする
// out : 出力画像. 出力画像のメモリはあらかじめ割り当てられているものとする
// fw, fh, fd : フィルタサイズ
// min, max : 濃淡範囲
template < class Array1, class Array2, class Functor >
void median_filter( const Array1 &in, Array2 &out,
typename Array1::size_type fw, typename Array1::size_type fh, typename Array1::size_type fd,
typename Array1::size_type thread_idy, typename Array1::size_type thread_numy,
typename Array1::size_type thread_idz, typename Array1::size_type thread_numz, Functor f )
{
typedef typename Array1::size_type size_type;
typedef typename Array1::value_type value_type;
typedef typename Array2::value_type out_value_type;
size_type i, j, k, x, y, z, ri;
size_type pth, c, th, windex;
size_type w = in.width( );
size_type h = in.height( );
size_type d = in.depth( );
const bool bprogress1 = thread_idy == 0 && d == 1;
const bool bprogress2 = thread_idz == 0 && d > 1;
size_type bw = fw / 2;
size_type bh = fh / 2;
size_type bd = fd / 2;
size_type bbh, bbd;
size_type size = fw * fh * fd;
value_type *work = new value_type[ size + 1 ];
value_type *work1 = new value_type[ size + 1 ];
value_type *work2 = new value_type[ size + 1 ];
value_type *work3 = new value_type[ size + 1 ];
value_type **sort = new value_type*[ fw ];
for( k = thread_idz ; k < d ; k += thread_numz )
{
if( k < bd )
{
bbd = k + bd + 1;
}
else if( k + bd >= d )
{
bbd = d - k + bd + 1;
}
else
{
bbd = fd;
}
for( j = thread_idy ; j < h ; j += thread_numy )
{
if( j < bh )
{
bbh = j + bh + 1;
}
else if( j + bh >= h )
{
bbh = h - j + bh + 1;
}
else
{
bbh = fh;
}
for( i = 0 ; i < fw ; i++ )
{
sort[ i ] = work + i * bbh * bbd;
}
i = 0;
windex = 0;
for( x = 0 ; x <= bw ; x++ )
{
windex = windex % fw;
c = 0;
for( z = k < bd ? 0 : k - bd ; z <= k + bd && z < d ; z++ )
{
for( y = j < bh ? 0 : j - bh ; y <= j + bh && y < h ; y++ )
{
sort[ windex ][ c++ ] = in( x, y, z );
}
}
windex++;
}
pth = ( bw + 1 ) * bbh * bbd;
th = ( pth - 1 ) / 2;
out( i, j, k ) = static_cast< out_value_type >( nth_value( work, pth, th, work1, work2, work3 ) );
for( i = 1 ; i < bw ; i++ )
{
ri = i + bw;
pth = ( i + bw + 1 ) * bbh * bbd;
windex = windex % fw;
c = 0;
for( z = k < bd ? 0 : k - bd ; z <= k + bd && z < d ; z++ )
{
for( y = j < bh ? 0 : j - bh ; y <= j + bh && y < h ; y++ )
{
sort[ windex ][ c++ ] = in( i, y, z );
}
}
th = ( pth - 1 ) / 2;
out( i, j, k ) = static_cast< out_value_type >( nth_value( work, pth, th, work1, work2, work3 ) );
windex++;
}
pth = fw * bbh * bbd;
th = ( pth - 1 ) / 2;
for( ; i + bw < w ; i++ )
{
ri = i + bw;
windex = windex % fw;
c = 0;
for( z = k < bd ? 0 : k - bd ; z <= k + bd && z < d ; z++ )
{
for( y = j < bh ? 0 : j - bh ; y <= j + bh && y < h ; y++ )
{
sort[ windex ][ c++ ] = in( ri, y, z );
}
}
out( i, j, k ) = static_cast< out_value_type >( nth_value( work, pth, th, work1, work2, work3 ) );
windex++;
}
for( ; i < w ; i++ )
{
windex = windex % fw;
c = 0;
for( z = k < bd ? 0 : k - bd ; z <= k + bd && z < d ; z++ )
{
for( y = j < bh ? 0 : j - bh ; y <= j + bh && y < h ; y++ )
{
sort[ windex ][ c++ ] = 0;
}
}
out( i, j, k ) = static_cast< out_value_type >( nth_value( work, pth, th, work1, work2, work3 ) );
windex++;
}
if( bprogress1 )
{
f( static_cast< double >( j + 1 ) / static_cast< double >( h ) * 100.0 );
}
}
if( bprogress2 )
{
f( static_cast< double >( k + 1 ) / static_cast< double >( d ) * 100.0 );
}
}
delete [] work;
delete [] work1;
delete [] work2;
delete [] work3;
delete [] sort;
}
}
namespace __median_filter_specialized_version__
{
template < class T >
inline void sort3x3( const T &v0, const T &v1, const T &v2, T v[ 3 ] )
{
if( v0 > v1 )
{
if( v1 > v2 )
{
v[ 0 ] = v0;
v[ 1 ] = v1;
v[ 2 ] = v2;
}
else
{
if( v0 > v2 )
{
v[ 0 ] = v0;
v[ 1 ] = v2;
v[ 2 ] = v1;
}
else
{
v[ 0 ] = v2;
v[ 1 ] = v0;
v[ 2 ] = v1;
}
}
}
else
{
if( v0 > v2 )
{
v[ 0 ] = v1;
v[ 1 ] = v0;
v[ 2 ] = v2;
}
else
{
if( v1 > v2 )
{
v[ 0 ] = v1;
v[ 1 ] = v2;
v[ 2 ] = v0;
}
else
{
v[ 0 ] = v2;
v[ 1 ] = v1;
v[ 2 ] = v0;
}
}
}
}
template < class T >
inline void sort2x2( const T &v0, const T &v1, T v[ 3 ] )
{
if( v0 > v1 )
{
v[ 0 ] = v0;
v[ 1 ] = v1;
}
else
{
v[ 0 ] = v1;
v[ 1 ] = v0;
}
}
template < class T >
inline void sort3x3( const T &v0, const T &v1, const T &v2, T w0[ 3 ], T w1[ 3 ], T w2[ 3 ], T *v[ 3 ] )
{
if( v0 > v1 )
{
if( v1 > v2 )
{
v[ 0 ] = w0;
v[ 1 ] = w1;
v[ 2 ] = w2;
}
else
{
if( v0 > v2 )
{
v[ 0 ] = w0;
v[ 1 ] = w2;
v[ 2 ] = w1;
}
else
{
v[ 0 ] = w2;
v[ 1 ] = w0;
v[ 2 ] = w1;
}
}
}
else
{
if( v0 > v2 )
{
v[ 0 ] = w1;
v[ 1 ] = w0;
v[ 2 ] = w2;
}
else
{
if( v1 > v2 )
{
v[ 0 ] = w1;
v[ 1 ] = w2;
v[ 2 ] = w0;
}
else
{
v[ 0 ] = w2;
v[ 1 ] = w1;
v[ 2 ] = w0;
}
}
}
}
template < class T >
inline void sort2x2( const T &v0, const T &v1, T w0[ 3 ], T w1[ 3 ], T *v[ 3 ] )
{
if( v0 > v1 )
{
v[ 0 ] = w0;
v[ 1 ] = w1;
}
else
{
v[ 0 ] = w1;
v[ 1 ] = w0;
}
}
template < class T >
inline const T &minimum( const T &v0, const T &v1 )
{
return( v0 < v1 ? v0 : v1 );
}
template < class T >
inline const T &minimum( const T &v0, const T &v1, const T &v2 )
{
return( v0 < v1 ? ( v0 < v2 ? v0 : v2 ) : ( v1 < v2 ? v1 : v2 ) );
}
template < class T >
inline const T &maximum( const T &v0, const T &v1, const T &v2 )
{
return( v0 > v1 ? ( v0 > v2 ? v0 : v2 ) : ( v1 > v2 ? v1 : v2 ) );
}
template < class T >
inline const T &maximum( const T &v0, const T &v1 )
{
return( v0 > v1 ? v0 : v1 );
}
template < class T >
inline const T &median( const T &v0, const T &v1, const T &v2 )
{
if( v0 > v1 )
{
if( v1 > v2 )
{
return( v1 );
}
else
{
if( v0 > v2 )
{
return( v2 );
}
else
{
return( v0 );
}
}
}
else
{
if( v0 > v2 )
{
return( v0 );
}
else
{
if( v1 > v2 )
{
return( v2 );
}
else
{
return( v1 );
}
}
}
}
/****************************************************************************************************************************************
**
** 参考文献:
**
** 浜村倫行, 入江文平, ``３×３メディアンフィルタの高速アルゴリズム,'' FIT（情報科学技術フォーラム）, LI-9, 2002
** ``A Fast Algorithm for 3x3 Median Filtering''
**
** ※ヒストグラムを利用するもの等と比較し，中央値を求めるのに必要な比較回数が非常に少なく，高速な動作が可能
**
** Coded by ddeguchi.
**
****************************************************************************************************************************************/
template < class T1, class T2, class Allocator1, class Allocator2, class Functor >
void median_filter3x3( const array2< T1, Allocator1 > &in, array2< T2, Allocator2 > &out,
typename array2< T1, Allocator1 >::size_type thread_id, typename array2< T1, Allocator1 >::size_type thread_num, Functor f )
{
typedef typename array2< T1, Allocator1 >::size_type size_type;
typedef typename array2< T1, Allocator1 >::value_type value_type;
typedef typename array2< T1, Allocator1 >::difference_type difference_type;
typedef typename array2< T2, Allocator2 >::value_type out_value_type;
size_type i, j, wi;
size_type w = in.width( );
size_type h = in.height( );
value_type work0[ 3 ];
value_type work1[ 3 ];
value_type work2[ 3 ];
value_type *work[ 3 ] = { work0, work1, work2 };
value_type *sort[ 3 ];
// 一番上の部分
for( j = thread_id ; j < 1 ; j += thread_num )
{
sort2x2( in( 0, 0 ), in( 0, 1 ), work0 );
sort2x2( in( 1, 0 ), in( 1, 1 ), work1 );
sort2x2( work0[ 1 ], work1[ 1 ], work0, work1, sort );
out( 0, 0 ) = static_cast< out_value_type >( minimum( sort[ 0 ][ 1 ], sort[ 1 ][ 0 ] ) );
for( i = 1 ; i < w - 1 ; i++ )
{
wi = ( i + 1 ) % 3;
sort2x2( in( i + 1, 0 ), in( i + 1, 0 + 1 ), work[ wi ] );
sort3x3( work0[ 1 ], work1[ 1 ], work2[ 1 ], work0, work1, work2, sort );
value_type &x = sort[ 1 ][ 1 ];
value_type &y = sort[ 0 ][ 1 ];
value_type &z = sort[ 2 ][ 0 ];
if( x < z )
{
value_type &w = sort[ 1 ][ 0 ];
out( i, 0 ) = static_cast< out_value_type >( minimum( y, z, w ) );
}
else
{
out( i, 0 ) = static_cast< out_value_type >( x );
}
}
sort2x2( work[ ( w - 2 ) % 3 ][ 1 ], work[ ( w - 1 ) % 3 ][ 1 ], work[ ( w - 2 ) % 3 ], work[ ( w - 1 ) % 3 ], sort );
out( w - 1, 0 ) = static_cast< out_value_type >( minimum( sort[ 0 ][ 1 ], sort[ 1 ][ 0 ] ) );
if( thread_id == 0 )
{
f( static_cast< double >( j + 1 ) / static_cast< double >( h ) * 100.0 );
}
}
// 真ん中部分
for( ; j < h - 1 ; j += thread_num )
{
sort3x3( in( 0, j - 1 ), in( 0, j ), in( 0, j + 1 ), work0 );
sort3x3( in( 1, j - 1 ), in( 1, j ), in( 1, j + 1 ), work1 );
sort2x2( work0[ 1 ], work1[ 1 ], work0, work1, sort );
out( 0, j ) = static_cast< out_value_type >( median( sort[ 0 ][ 2 ], sort[ 1 ][ 0 ], sort[ 1 ][ 1 ] ) );
for( i = 1 ; i < w - 1 ; i++ )
{
wi = ( i + 1 ) % 3;
sort3x3( in( i + 1, j - 1 ), in( i + 1, j ), in( i + 1, j + 1 ), work[ wi ] );
sort3x3( work0[ 1 ], work1[ 1 ], work2[ 1 ], work0, work1, work2, sort );
value_type &x = sort[ 1 ][ 1 ];
value_type &y = sort[ 0 ][ 2 ];
value_type &z = sort[ 2 ][ 0 ];
if( x < y && x < z )
{
value_type &w = sort[ 1 ][ 0 ];
out( i, j ) = static_cast< out_value_type >( minimum( y, z, w ) );
}
else if( x > y && x > z )
{
value_type &w = sort[ 1 ][ 2 ];
out( i, j ) = static_cast< out_value_type >( maximum( y, z, w ) );
}
else
{
out( i, j ) = static_cast< out_value_type >( x );
}
}
sort2x2( work[ ( w - 2 ) % 3 ][ 1 ], work[ ( w - 1 ) % 3 ][ 1 ], work[ ( w - 2 ) % 3 ], work[ ( w - 1 ) % 3 ], sort );
out( w - 1, j ) = static_cast< out_value_type >( median( sort[ 0 ][ 2 ], sort[ 1 ][ 0 ], sort[ 1 ][ 1 ] ) );
if( thread_id == 0 )
{
f( static_cast< double >( j + 1 ) / static_cast< double >( h ) * 100.0 );
}
}
// 一番下の部分
for( ; j < h ; j += thread_num )
{
sort2x2( in( 0, h - 2 ), in( 0, h - 1 ), work0 );
sort2x2( in( 1, h - 2 ), in( 1, h - 1 ), work1 );
sort2x2( work0[ 1 ], work1[ 1 ], work0, work1, sort );
out( 0, h - 1 ) = static_cast< out_value_type >( minimum( sort[ 0 ][ 1 ], sort[ 1 ][ 0 ] ) );
for( i = 1 ; i < w - 1 ; i++ )
{
wi = ( i + 1 ) % 3;
sort2x2( in( i + 1, h - 2 ), in( i + 1, h - 1 ), work[ wi ] );
sort3x3( work0[ 1 ], work1[ 1 ], work2[ 1 ], work0, work1, work2, sort );
value_type &x = sort[ 1 ][ 1 ];
value_type &y = sort[ 0 ][ 1 ];
value_type &z = sort[ 2 ][ 0 ];
if( x < z )
{
value_type &w = sort[ 1 ][ 0 ];
out( i, h - 1 ) = static_cast< out_value_type >( minimum( y, z, w ) );
}
else
{
out( i, h - 1 ) = static_cast< out_value_type >( x );
}
}
sort2x2( work[ ( w - 2 ) % 3 ][ 1 ], work[ ( w - 1 ) % 3 ][ 1 ], work[ ( w - 2 ) % 3 ], work[ ( w - 1 ) % 3 ], sort );
out( w - 1, h - 1 ) = static_cast< out_value_type >( minimum( sort[ 0 ][ 1 ], sort[ 1 ][ 0 ] ) );
if( thread_id == 0 )
{
f( static_cast< double >( j + 1 ) / static_cast< double >( h ) * 100.0 );
}
}
}
}
// メディアンフィルタのスレッド実装
namespace __median_filter_controller__
{
template < class T, class Allocator >
void get_min_max( const array< T, Allocator > &in, typename array< T, Allocator >::value_type &min, typename array< T, Allocator >::value_type &max )
{
min = max = in[ 0 ];
for( typename array< T, Allocator >::size_type i = 0 ; i < in.size( ) ; i++ )
{
if( min > in[ i ] )
{
min = in[ i ];
}
else if( max < in[ i ] )
{
max = in[ i ];
}
}
}
template < bool b >
struct __median_filter__
{
template < class T1, class Allocator1, class T2, class Allocator2, class Functor >
static void median_filter( const array< T1, Allocator1 > &in, array< T2, Allocator2 > &out,
typename array< T1, Allocator1 >::size_type fw, typename array< T1, Allocator1 >::size_type fh, typename array< T1, Allocator1 >::size_type fd,
typename array< T1, Allocator1 >::size_type thread_id, typename array< T1, Allocator1 >::size_type thread_num, Functor f )
{
typedef typename array< T1, Allocator1 >::value_type value_type;
value_type min = in[ 0 ];
value_type max = in[ 0 ];
get_min_max( in, min, max );
__median_filter_with_histogram__::median_filter( in, out, fw, fh, fd, min, max, 0, 1, thread_id, thread_num, f );
}
template < class T1, class Allocator1, class T2, class Allocator2, class Functor >
static void median_filter( const array2< T1, Allocator1 > &in, array2< T2, Allocator2 > &out,
typename array2< T1, Allocator1 >::size_type fw, typename array2< T1, Allocator1 >::size_type fh, typename array2< T1, Allocator1 >::size_type fd,
typename array2< T1, Allocator1 >::size_type thread_id, typename array2< T1, Allocator1 >::size_type thread_num, Functor f )
{
typedef typename array2< T1, Allocator1 >::value_type value_type;
if( fw == 3 && fh == 3 )
{
__median_filter_specialized_version__::median_filter3x3( in, out, thread_id, thread_num, f );
}
else
{
value_type min = in[ 0 ];
value_type max = in[ 0 ];
get_min_max( in, min, max );
__median_filter_with_histogram__::median_filter( in, out, fw, fh, fd, min, max, thread_id, thread_num, 0, 1, f );
}
}
template < class T1, class Allocator1, class T2, class Allocator2, class Functor >
static void median_filter( const array3< T1, Allocator1 > &in, array3< T2, Allocator2 > &out,
typename array3< T1, Allocator1 >::size_type fw, typename array3< T1, Allocator1 >::size_type fh, typename array3< T1, Allocator1 >::size_type fd,
typename array3< T1, Allocator1 >::size_type thread_id, typename array3< T1, Allocator1 >::size_type thread_num, Functor f )
{
typedef typename array3< T1, Allocator1 >::value_type value_type;
value_type min = in[ 0 ];
value_type max = in[ 0 ];
get_min_max( in, min, max );
__median_filter_with_histogram__::median_filter( in, out, fw, fh, fd, min, max, 0, 1, thread_id, thread_num, f );
}
};
// ヒストグラムを作成できない場合のメディアンフィルタ
// 浮動小数点など
template < >
struct __median_filter__< false >
{
template < class T1, class Allocator1, class T2, class Allocator2, class Functor >
static void median_filter( const array< T1, Allocator1 > &in, array< T2, Allocator2 > &out,
typename array< T1, Allocator1 >::size_type fw, typename array< T1, Allocator1 >::size_type fh, typename array< T1, Allocator1 >::size_type fd,
typename array< T1, Allocator1 >::size_type thread_id, typename array< T1, Allocator1 >::size_type thread_num, Functor f )
{
__median_filter_divide_conquer__::median_filter( in, out, fw, fh, fd, 0, 1, thread_id, thread_num, f );
}
template < class T1, class Allocator1, class T2, class Allocator2, class Functor >
static void median_filter( const array2< T1, Allocator1 > &in, array2< T2, Allocator2 > &out,
typename array2< T1, Allocator1 >::size_type fw, typename array2< T1, Allocator1 >::size_type fh, typename array2< T1, Allocator1 >::size_type fd,
typename array2< T1, Allocator1 >::size_type thread_id, typename array2< T1, Allocator1 >::size_type thread_num, Functor f )
{
if( fw == 3 && fh == 3 )
{
__median_filter_specialized_version__::median_filter3x3( in, out, thread_id, thread_num, f );
}
else
{
__median_filter_divide_conquer__::median_filter( in, out, fw, fh, fd, thread_id, thread_num, 0, 1, f );
}
}
template < class T1, class Allocator1, class T2, class Allocator2, class Functor >
static void median_filter( const array3< T1, Allocator1 > &in, array3< T2, Allocator2 > &out,
typename array3< T1, Allocator1 >::size_type fw, typename array3< T1, Allocator1 >::size_type fh, typename array3< T1, Allocator1 >::size_type fd,
typename array3< T1, Allocator1 >::size_type thread_id, typename array3< T1, Allocator1 >::size_type thread_num, Functor f )
{
__median_filter_divide_conquer__::median_filter( in, out, fw, fh, fd, 0, 1, thread_id, thread_num, f );
}
};
template < class T1, class T2, class Functor >
class median_thread : public mist::thread< median_thread< T1, T2, Functor > >
{
public:
typedef mist::thread< median_thread< T1, T2, Functor > > base;
typedef typename base::thread_exit_type thread_exit_type;
typedef typename T1::size_type size_type;
typedef typename T1::value_type value_type;
private:
size_t thread_id_;
size_t thread_num_;
// 入出力用の画像へのポインタ
const T1 *in_;
T2 *out_;
size_type fw_;
size_type fh_;
size_type fd_;
Functor f_;
public:
void setup_parameters( const T1 &in, T2 &out, size_t fw, size_type fh, size_type fd, size_type thread_id, size_type thread_num, Functor f )
{
in_ = ∈
out_ = &out;
fw_ = fw;
fh_ = fh;