利用Matlab实现迭代适应点算法

function nPntSet=dp(pntSet,TH)
% @author : slandarer
% pntSet  : 二维数据点
% TH      : 距离阈值

% 向量运算:计算所有点到首位两点连线距离
vertV=[pntSet(end,2)-pntSet(1,2),-pntSet(end,1)+pntSet(1,1)];
baseL=abs(sum((pntSet-pntSet(1,:)).*vertV./norm(vertV),2));
if max(baseL)<TH 
    % 若距离小于阈值则返回首尾点
    nPntSet=[pntSet(1,:);pntSet(end,:)]; 
else
    % 若距离大于阈值则左右两分支分别计算后拼接
    maxPos=find(baseL==max(baseL));maxPos=maxPos(1);
    L_PntSet=pntSet(1:maxPos,:);nL_PntSet=dp(L_PntSet,TH);
    R_PntSet=pntSet(maxPos:end,:);nR_PntSet=dp(R_PntSet,TH);
    nPntSet=[nL_PntSet;nR_PntSet(2:end,:)];
end
end

% 构造一组数据
X=linspace(0,25,10)';
Y=randi([0,10],[10,1]);
pntSet=[X,Y];

% 阈值为2的dp算法
nPntSet=dp(pntSet,2);

% 坐标区域修饰
hold on
grid on
ax=gca;
ax.YLim=[0,10];
ax.DataAspectRatio=[1,1,1];
ax.Color=[1,1,1];
ax.XColor=[1,1,1].*.3;
ax.YColor=[1,1,1].*.3;
ax.LineWidth=1.5;
ax.FontName='cambria';
ax.GridLineStyle='--';

% 绘制原始数据曲线
plot(pntSet(:,1),pntSet(:,2),'Color',[0 0.4470 0.7410],'LineWidth',2,'Marker','*');
% 绘制新数据曲线
plot(nPntSet(:,1),nPntSet(:,2),'Color',[0.6350 0.0780 0.1840 .7],'LineWidth',2,'Marker','s');

legend('original-curve','feature-curve')