1.样条曲线简介
样条曲线(Spline)本质是分段多项式实函数,在实数范围内有: S:[a,b]→R ,在区间 [a,b] 上包含 k 个子区间[ti−1,ti],且有:
a=t0<t1<⋯<tk−1<tk=b(1)
对应每一段区间 i 的存在多项式: Pi:[ti−1,ti]→R,且满足于:
S(t)=P1(t) , t0≤t<t1,S(t)=P2(t) , t1≤t<t2,⋮S(t)=Pk(t) , tk−1≤t≤tk.(2)
其中, Pi(t) 多项式中最高次项的幂,视为样条的阶数或次数(Order of spline),根据子区间 [ti−1,ti] 的区间长度是否一致分为均匀(Uniform)样条和非均匀(Non-uniform)样条。
满足了公式 (2) 的多项式有很多,为了保证曲线在 S 区间内具有据够的平滑度,一条n次样条,同时应具备处处连续且可微的性质:
P(j)i(ti)=P(j)i+1(ti);(3)
其中 i=1,…,k−1;j=0,…,n−1 。
2.三次样条曲线
2.1曲线条件
按照上述的定义,给定节点:
t:z:a=t0z0<t1z1<⋯⋯<tk−1zk−1<tkzk=b(4)
三次样条曲线满足三个条件:
- 在每段分段区间 [ti,ti+1],i=0,1,…,k−1 上, S(t)=Si(t) 都是一个三次多项式;
- 满足 S(ti)=zi,i=1,…,k−1 ;
- S(t) 的一阶导函数 S′(t) 和二阶导函数 S′′(t) 在区间 [a,b] 上都是连续的,从而曲线具有光滑性。
则三次样条的方程可以写为:
Si(t)=ai+bi(t−ti)+ci(t−ti)2+di(t−ti)3,(5)
其中, ai,bi,ci,di 分别代表 n 个未知系数。
- 曲线的连续性表示为:
Si(ti)=zi,(6)
Si(ti+1)=zi+1,(7)
其中 i=0,1,…,k−1 。
- 曲线微分连续性:
S′i(ti+1)=S′i+1(ti+1),(8)
S′′i(ti+1)=S′′i+1(ti+1),(9)
其中 i=0,1,…,k−2 。
- 曲线的导函数表达式:
S′i=bi+2ci(t−ti)+3di(t−ti)2,(10)
S′′i(x)=2ci+6di(t−ti),(11)
令区间长度 hi=ti+1−ti ,则有:
-
由公式 (6) ,可得: ai=zi ;
-
由公式 (7) ,可得: ai+bihi+cih2i+dih3i=zi+1 ;
-
由公式 (8) ,可得:
S′i(ti+1)=bi+2cihi+3dih2i ;
S′i+1(ti+1)=bi+1 ;
⇒bi+2cihi+3dih2i−bi+1=0 ; -
由公式 (9) ,可得:
S′′i(ti+1)=2ci+6dihi ;
S′′i+1(ti+1)=2ci+1 ;
⇒2ci+6dihi=2ci+1 ;设 mi=S′′i(xi)=2ci ,则:
A. mi+6dihi−mi+1=0⇒
di=mi+1−mi6hi ;B.将 ci,di 代入 zi+bihi+cih2i+dih3i=zi+1⇒
bi=zi+1−zihi−hi2mi−hi6(mi+1−mi) ;C.将 bi,ci,di 代入 bi+2cihi+3dih2i=bi+1⇒
himi+2(hi+hi+1)mi+1+hi+1mi+2=6[zi+2−zi+1hi+1−zi+1−zihi].(12)文章来源:https://www.toymoban.com/news/detail-738385.html
2.2端点条件
在上述分析中,曲线段的两个端点 t0 和 tk 是不适用的,有一些常用的端点限制条件,这里只讲解自然边界。
在自然边界下,首尾两端的二阶导函数满足 S′′=0 ,即 m0=0 和 mk=0 。文章来源地址https://www.toymoban.com/news/detail-738385.html
3.三次样条插值类的实现
头文件
/*
*Cubic spline interpolation class.
*
*/
#ifndef CUBICSPLINEINTERPOLATION_H
#pragma once
#define CUBICSPLINEINTERPOLATION_H
#include <iostream>
#include <vector>
#include <math.h>
#include <opencv2/opencv.hpp>
using namespace std;
using namespace cv;
/* Cubic spline interpolation coefficients */
class CubicSplineCoeffs
{
public:
CubicSplineCoeffs( const int &count )
{
a = std::vector<double>(count);
b = std::vector<double>(count);
c = std::vector<double>(count);
d = std::vector<double>(count);
}
~CubicSplineCoeffs()
{
std::vector<double>().swap(a);
std::vector<double>().swap(b);
std::vector<double>().swap(c);
std::vector<double>().swap(d);
}
public:
std::vector<double> a, b, c, d;
};
enum CubicSplineMode
{
CUBIC_NATURAL, // Natural
CUBIC_CLAMPED, // TODO: Clamped
CUBIC_NOT_A_KNOT // TODO: Not a knot
};
enum SplineFilterMode
{
CUBIC_WITHOUT_FILTER, // without filter
CUBIC_MEDIAN_FILTER // median filter
};
/* Cubic spline interpolation */
class CubicSplineInterpolation
{
public:
CubicSplineInterpolation() {}
~CubicSplineInterpolation() {}
public:
/*
Calculate cubic spline coefficients.
- node list x (input_x);
- node list y (input_y);
- output coefficients (cubicCoeffs);
- ends mode (splineMode).
*/
void calCubicSplineCoeffs( std::vector<double> &input_x,
std::vector<double> &input_y, CubicSplineCoeffs *&cubicCoeffs,
CubicSplineMode splineMode = CUBIC_NATURAL,
SplineFilterMode filterMode = CUBIC_MEDIAN_FILTER );
/*
Cubic spline interpolation for a list.
- input coefficients (cubicCoeffs);
- input node list x (input_x);
- output node list x (output_x);
- output node list y (output_y);
- interpolation step (interStep).
*/
void cubicSplineInterpolation( CubicSplineCoeffs *&cubicCoeffs,
std::vector<double> &input_x, std::vector<double> &output_x,
std::vector<double> &output_y, const double interStep = 0.5 );
/*
Cubic spline interpolation for a value.
- input coefficients (cubicCoeffs);
- input a value(x);
- output interpolation value(y);
*/
void cubicSplineInterpolation2( CubicSplineCoeffs *&cubicCoeffs,
std::vector<double> input_x, double x, double &y );
/*
calculate tridiagonal matrices with Thomas Algorithm(TDMA) :
example:
| b1 c1 0 0 0 0 | |x1 | |d1 |
| a2 b2 c2 0 0 0 | |x2 | |d2 |
| 0 a3 b3 c3 0 0 | |x3 | = |d3 |
| ... ... | |...| |...|
| 0 0 0 0 an bn | |xn | |dn |
Ci = ci/bi , i=1; ci / (bi - Ci-1 * ai) , i = 2, 3, ... n-1;
Di = di/bi , i=1; ( di - Di-1 * ai )/(bi - Ci-1 * ai) , i = 2, 3, ..., n-1
xi = Di - Ci*xi+1 , i = n-1, n-2, 1;
*/
bool caltridiagonalMatrices( cv::Mat_<double> &input_a,
cv::Mat_<double> &input_b, cv::Mat_<double> &input_c,
cv::Mat_<double> &input_d, cv::Mat_<double> &output_x );
/* Calculate the curve index interpolation belongs to */
int calInterpolationIndex( double &pt, std::vector<double> &input_x );
/* median filtering */
void cubicMedianFilter( std::vector<double> &input, const int filterSize = 5 );
double cubicSort( std::vector<double> &input );
// double cubicNearestValue( std::vector );
};
#endif // CUBICSPLINEINTERPOLATION_H
实现文件(cpp)
/*
* CubicSplineInterpolation.cpp
*/
#include "cubicsplineinterpolation.h"
void CubicSplineInterpolation::calCubicSplineCoeffs(
std::vector<double> &input_x,
std::vector<double> &input_y,
CubicSplineCoeffs *&cubicCoeffs,
CubicSplineMode splineMode /* = CUBIC_NATURAL */,
SplineFilterMode filterMode /*= CUBIC_MEDIAN_FILTER*/ )
{
int sizeOfx = input_x.size();
int sizeOfy = input_y.size();
if ( sizeOfx != sizeOfy )
{
std::cout << "Data input error!" << std::endl <<
"Location: CubicSplineInterpolation.cpp" <<
" -> calCubicSplineCoeffs()" << std::endl;
return;
}
/*
hi*mi + 2*(hi + hi+1)*mi+1 + hi+1*mi+2
= 6{ (yi+2 - yi+1)/hi+1 - (yi+1 - yi)/hi }
so, ignore the both ends:
| - - - 0 ... 0 | |m0 |
| h0 2(h0+h1) h1 0 ... 0 | |m1 |
| 0 h1 2(h1+h2) h2 0 ... | |m2 |
| ... ... 0 | |...|
| 0 ... 0 h(n-2) 2(h(n-2)+h(n-1)) h(n-1) | | |
| 0 ... ... - | |mn |
*/
std::vector<double> copy_y = input_y;
if ( filterMode == CUBIC_MEDIAN_FILTER )
{
cubicMedianFilter(copy_y, 5);
}
const int count = sizeOfx;
const int count1 = sizeOfx - 1;
const int count2 = sizeOfx - 2;
const int count3 = sizeOfx - 3;
cubicCoeffs = new CubicSplineCoeffs( count1 );
std::vector<double> step_h( count1, 0.0 );
// for m matrix
cv::Mat_<double> m_a(1, count2, 0.0);
cv::Mat_<double> m_b(1, count2, 0.0);
cv::Mat_<double> m_c(1, count2, 0.0);
cv::Mat_<double> m_d(1, count2, 0.0);
cv::Mat_<double> m_part(1, count2, 0.0);
cv::Mat_<double> m_all(1, count, 0.0);
// initial step hi
for ( int idx=0; idx < count1; idx ++ )
{
step_h[idx] = input_x[idx+1] - input_x[idx];
}
// initial coefficients
for ( int idx=0; idx < count3; idx ++ )
{
m_a(idx) = step_h[idx];
m_b(idx) = 2 * (step_h[idx] + step_h[idx+1]);
m_c(idx) = step_h[idx+1];
}
// initial d
for ( int idx =0; idx < count3; idx ++ )
{
m_d(idx) = 6 * (
(copy_y[idx+2] - copy_y[idx+1]) / step_h[idx+1] -
(copy_y[idx+1] - copy_y[idx]) / step_h[idx] );
}
//cv::Mat_<double> matOfm( count2, )
bool isSucceed = caltridiagonalMatrices(m_a, m_b, m_c, m_d, m_part);
if ( !isSucceed )
{
std::cout<<"Calculate tridiagonal matrices failed!"<<std::endl<<
"Location: CubicSplineInterpolation.cpp -> " <<
"caltridiagonalMatrices()"<<std::endl;
return;
}
if ( splineMode == CUBIC_NATURAL )
{
m_all(0) = 0.0;
m_all(count1) = 0.0;
for ( int i=1; i<count1; i++ )
{
m_all(i) = m_part(i-1);
}
for ( int i=0; i<count1; i++ )
{
cubicCoeffs->a[i] = copy_y[i];
cubicCoeffs->b[i] = ( copy_y[i+1] - copy_y[i] ) / step_h[i] -
step_h[i]*( 2*m_all(i) + m_all(i+1) ) / 6;
cubicCoeffs->c[i] = m_all(i) / 2.0;
cubicCoeffs->d[i] = ( m_all(i+1) - m_all(i) ) / ( 6.0 * step_h[i] );
}
}
else
{
std::cout<<"Not define the interpolation mode!"<<std::endl;
}
}
void CubicSplineInterpolation::cubicSplineInterpolation(
CubicSplineCoeffs *&cubicCoeffs,
std::vector<double> &input_x,
std::vector<double> &output_x,
std::vector<double> &output_y,
const double interStep )
{
const int count = input_x.size();
double low = input_x[0];
double high = input_x[count-1];
double interBegin = low;
for ( ; interBegin < high; interBegin += interStep )
{
int index = calInterpolationIndex(interBegin, input_x);
if ( index >= 0 )
{
double dertx = interBegin - input_x[index];
double y = cubicCoeffs->a[index] + cubicCoeffs->b[index] * dertx +
cubicCoeffs->c[index] * dertx * dertx +
cubicCoeffs->d[index] * dertx * dertx * dertx;
output_x.push_back(interBegin);
output_y.push_back(y);
}
}
}
void CubicSplineInterpolation::cubicSplineInterpolation2(
CubicSplineCoeffs *&cubicCoeffs,
std::vector<double> input_x, double x, double &y)
{
const int count = input_x.size();
double low = input_x[0];
double high = input_x[count-1];
if ( x<low || x>high )
{
std::cout<<"The interpolation value is out of range!"<<std::endl;
}
else
{
int index = calInterpolationIndex(x, input_x);
if ( index >= 0 )
{
double dertx = x - input_x[index];
y = cubicCoeffs->a[index] + cubicCoeffs->b[index] * dertx +
cubicCoeffs->c[index] * dertx * dertx +
cubicCoeffs->d[index] * dertx * dertx * dertx;
}
else
{
std::cout<<"Can't find the interpolation range!"<<std::endl;
}
}
}
bool CubicSplineInterpolation::caltridiagonalMatrices(
cv::Mat_<double> &input_a,
cv::Mat_<double> &input_b,
cv::Mat_<double> &input_c,
cv::Mat_<double> &input_d,
cv::Mat_<double> &output_x )
{
int rows = input_a.rows;
int cols = input_a.cols;
if ( ( rows == 1 && cols > rows ) ||
(cols == 1 && rows > cols ) )
{
const int count = ( rows > cols ? rows : cols ) - 1;
output_x = cv::Mat_<double>::zeros(rows, cols);
cv::Mat_<double> cCopy, dCopy;
input_c.copyTo(cCopy);
input_d.copyTo(dCopy);
if ( input_b(0) != 0 )
{
cCopy(0) /= input_b(0);
dCopy(0) /= input_b(0);
}
else
{
return false;
}
for ( int i=1; i < count; i++ )
{
double temp = input_b(i) - input_a(i) * cCopy(i-1);
if ( temp == 0.0 )
{
return false;
}
cCopy(i) /= temp;
dCopy(i) = ( dCopy(i) - dCopy(i-1)*input_a(i) ) / temp;
}
output_x(count) = dCopy(count);
for ( int i=count-2; i > 0; i-- )
{
output_x(i) = dCopy(i) - cCopy(i)*output_x(i+1);
}
return true;
}
else
{
return false;
}
}
int CubicSplineInterpolation::calInterpolationIndex(
double &pt, std::vector<double> &input_x )
{
const int count = input_x.size()-1;
int index = -1;
for ( int i=0; i<count; i++ )
{
if ( pt > input_x[i] && pt <= input_x[i+1] )
{
index = i;
return index;
}
}
return index;
}
void CubicSplineInterpolation::cubicMedianFilter(
std::vector<double> &input, const int filterSize /* = 5 */ )
{
const int count = input.size();
for ( int i=filterSize/2; i<count-filterSize/2; i++ )
{
std::vector<double> temp(filterSize, 0.0);
for ( int j=0; j<filterSize; j++ )
{
temp[j] = input[i+j - filterSize/2];
}
input[i] = cubicSort(temp);
std::vector<double>().swap(temp);
}
for ( int i=0; i<filterSize/2; i++ )
{
std::vector<double> temp(filterSize, 0.0);
for ( int j=0; j<filterSize; j++ )
{
temp[j] = input[j];
}
input[i] = cubicSort(temp);
std::vector<double>().swap(temp);
}
for ( int i=count-filterSize/2; i<count; i++ )
{
std::vector<double> temp(filterSize, 0.0);
for ( int j=0; j<filterSize; j++ )
{
temp[j] = input[j];
}
input[i] = cubicSort(temp);
std::vector<double>().swap(temp);
}
}
double CubicSplineInterpolation::cubicSort( std::vector<double> &input )
{
int iCount = input.size();
for ( int j=0; j<iCount-1; j++ )
{
for ( int k=iCount-1; k>j; k-- )
{
if ( input[k-1] > input[k] )
{
double tp = input[k];
input[k] = input[k-1];
input[k-1] = tp;
}
}
}
return input[iCount/2];
}
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