Opencv 三次样条曲线(Cubic Spline)插值
本系列文章由 @YhL_Leo 出品，转载请注明出处。
文章链接： http://blog.csdn.net/yhl_leo/article/details/47707679
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)
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，求解方程组可写为：
⎡⎣⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢1h00⋮002(h0+h1)h2…0h12(h1+h2)⋱00h2⋱hk−20…0⋱2(hk−2+hk−1)00⋮hk−11⎤⎦⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎡⎣⎢⎢⎢⎢⎢⎢⎢⎢⎢m0m1m2⋮mk−1mk⎤⎦⎥⎥⎥⎥⎥⎥⎥⎥⎥=6⎡⎣⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢0z2−z1h1−z1−z0h0z3−z2h2−z2−z1h1⋮zk−zk−1hk−1−zk−1−zk−2hk−20⎤⎦⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥(13)
其系数矩阵为三对角线矩阵，在该篇博客内会有其讲解。
3.Code
// CubicSplineInterpolation.h
/*
Cubic spline interpolation class.
- Editor: Yahui Liu.
- Data: 2015-08-16
- Email: yahui.cvrs@gmail.com
- Address: Computer Vision and Remote Sensing(CVRS), Lab.
*/
#ifndef CUBIC_SPLINE_INTERPOLATION_H
#pragma once
#define CUBIC_SPLINE_INTERPOLATION_H
#include <iostream>
#include <vector>
#include <math.h>
#include <cv.h>
#include <highgui.h>
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 // CUBIC_SPLINE_INTERPOLATION_H// 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];
}// main.cpp
#include "CubicSplineInterpolation.h"
void main()
{
double x[22] = {
926.500000,
928.000000,
929.500000,
931.000000,
932.500000,
934.000000,
935.500000,
937.000000,
938.500000,
940.000000,
941.500000,
943.000000,
944.500000,
946.000000,
977.500000,
980.500000,
982.000000,
983.500000,
985.000000,
986.500000,
988.000000,
989.500000};
double y[22] = {
381.732239,
380.670530,
380.297786,
379.853896,
379.272647,
378.368584,
379.319757,
379.256485,
380.233150,
378.183257,
377.543639,
376.948999,
376.253935,
198.896327,
670.369434,
374.273702,
372.498821,
373.149402,
372.139661,
372.510891,
372.772791,
371.360553};
std::vector<double> input_x(22), input_y(22);
for ( int i=0; i<22; i++)
{
input_x[i] = x[i];
input_y[i] = y[i];
}
CubicSplineCoeffs *cubicCoeffs;
CubicSplineInterpolation cubicSpline;
cubicSpline.calCubicSplineCoeffs(input_x, input_y, cubicCoeffs, CUBIC_NATURAL, CUBIC_MEDIAN_FILTER);
std::vector<double> output_x, output_y;
cubicSpline.cubicSplineInterpolation( cubicCoeffs, input_x, output_x, output_y );
double xx(946.0), yy(0.0);
cubicSpline.cubicSplineInterpolation2(cubicCoeffs, input_x, xx, yy);
std::cout<<yy<<std::endl;
std::ofstream outfile( "E:\\test.txt", std::ios::out );
if ( outfile )
{
for ( int i=0; i<output_y.size(); i++ )
{
outfile<<std::fixed<<setprecision(3)<<output_x[i]<<" "<<output_y[i]<<std::endl;
}
}
outfile.close();
}运行结果：
插值点集如图所示：
其中单独点插值的运行结果分别为：
198.896 // yy, CUBIC_WITHOUT_FILTER
376.949 // yy, CUBIC_MEDIAN_FILTER参考文献：
1.https://en.wikipedia.org/wiki/Spline_(mathematics)
2.http://www.cnblogs.com/xpvincent/archive/2013/01/26/2878092.html
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