该算法实现抽稀的过程是：
1）对曲线的首末点虚连一条直线，求曲线上所有点与直线的距离，并找出最大距离值dmax，用dmax与事先给定的阈值D相比：
2）若dmax<D，则将这条曲线上的中间点全部舍去；则该直线段作为曲线的近似，该段曲线处理完毕。
若dmax≥D，保留dmax对应的坐标点，并以该点为界，把曲线分为两部分，对这两部分重复使用该方法，即重复1），2）步，直到所有dmax均<D，即完成对曲线的抽稀。
显然，本算法的抽稀精度也与阈值相关，阈值越大，简化程度越大，点减少的越多，反之，化简程度越低，点保留的越多，形状也越趋于原曲线。
Point.java
package com.mapbar.jts;
/**
* Class Point.java
* Description
* Company mapbar
* author Chenll E-mail: Chenll@mapbar.com
* Version 1.0
* Date 2012-6-28 下午05:51:09
*/
public class Point {
/**
* 点的X坐标
*/
private double x = 0;
/**
* 点的Y坐标
*/
private double y = 0;
/**
* 点所属的曲线的索引
*/
private int index = 0;
public double getX() {
return x;
}
public void setX(double x) {
this.x = x;
}
public double getY() {
return y;
}
public void setY(double y) {
this.y = y;
}
public int getIndex() {
return index;
}
public void setIndex(int index) {
this.index = index;
}
/**
* 点数据的构造方法
*
* @param x
* 点的X坐标
* @param y
* 点的Y坐标
* @param index点所属的曲线的索引
*/
public Point(double x, double y, int index) {
this.x = x;
this.y = y;
this.index = index;
}
}
Douglas.java
package com.mapbar.jts;
import java.util.ArrayList;
import java.util.List;
import com.vividsolutions.jts.geom.Coordinate;
import com.vividsolutions.jts.geom.Geometry;
import com.vividsolutions.jts.io.ParseException;
import com.vividsolutions.jts.io.WKTReader;
/**
*
* Class Douglas.java
*
* Description
*
* Company mapbar
*
* author Chenll E-mail: Chenll@mapbar.com
*
* Version 1.0
*
* Date 2012-6-28 下午02:53:58
*/
public class Douglas {
/**
* 存储采样点数据的链表
*/
public List<Point> points = new ArrayList<Point>();
/**
* 控制数据压缩精度的极差
*/
private static final double D = 1;
private WKTReader reader;
/**
* 构造Geometry
*
* @param str
* @return
*/
public Geometry buildGeo(String str) {
try {
if (reader == null) {
reader = new WKTReader();
}
return reader.read(str);
} catch (ParseException e) {
throw new RuntimeException("buildGeometry Error", e);
}
}
/**
* 读取采样点
*/
public void readPoint() {
Geometry g = buildGeo("LINESTRING (1 4,2 3,4 2,6 6,7 7,8 6,9 5,10 10)");
Coordinate[] coords = g.getCoordinates();
for (int i = 0; i < coords.length; i++) {
Point p = new Point(coords[i].x, coords[i].y, i);
points.add(p);
}
}
/**
* 对矢量曲线进行压缩
*
* @param from
* 曲线的起始点
* @param to
* 曲线的终止点
*/
public void compress(Point from, Point to) {
/**
* 压缩算法的开关量
*/
boolean switchvalue = false;
/**
* 由起始点和终止点构成的直线方程一般式的系数
*/
System.out.println(from.getY());
System.out.println(to.getY());
double A = (from.getY() - to.getY())
/ Math.sqrt(Math.pow((from.getY() - to.getY()), 2)
+ Math.pow((from.getX() - to.getX()), 2));
/**
* 由起始点和终止点构成的直线方程一般式的系数
*/
double B = (to.getX() - from.getX())
/ Math.sqrt(Math.pow((from.getY() - to.getY()), 2)
+ Math.pow((from.getX() - to.getX()), 2));
/**
* 由起始点和终止点构成的直线方程一般式的系数
*/
double C = (from.getX() * to.getY() - to.getX() * from.getY())
/ Math.sqrt(Math.pow((from.getY() - to.getY()), 2)
+ Math.pow((from.getX() - to.getX()), 2));
double d = 0;
double dmax = 0;
int m = points.indexOf(from);
int n = points.indexOf(to);
if (n == m + 1)
return;
Point middle = null;
List<Double> distance = new ArrayList<Double>();
for (int i = m + 1; i < n; i++) {
d = Math.abs(A * (points.get(i).getX()) + B
* (points.get(i).getY()) + C)
/ Math.sqrt(Math.pow(A, 2) + Math.pow(B, 2));
distance.add(d);
}
dmax = distance.get(0);
for (int j = 1; j < distance.size(); j++) {
if (distance.get(j) > dmax)
dmax = distance.get(j);
}
if (dmax > D)
switchvalue = true;
else
switchvalue = false;
if (!switchvalue) {
// 删除Points(m,n)内的坐标
for (int i = m + 1; i < n; i++) {
points.get(i).setIndex(-1);
}
} else {
for (int i = m + 1; i < n; i++) {
if ((Math.abs(A * (points.get(i).getX()) + B
* (points.get(i).getY()) + C)
/ Math.sqrt(Math.pow(A, 2) + Math.pow(B, 2)) == dmax))
middle = points.get(i);
}
compress(from, middle);
compress(middle, to);
}
}
public static void main(String[] args) {
Douglas d = new Douglas();
d.readPoint();
d.compress(d.points.get(0), d.points.get(d.points.size() - 1));
for (int i = 0; i < d.points.size(); i++) {
Point p = d.points.get(i);
if (p.getIndex() > -1) {
System.out.print(p.getX() + " " + p.getY() + ",");
}
}
}
}
输出结果：1.0 4.0,4.0 2.0,7.0 7.0,9.0 5.0,10.0 10.0，其中2 3，6 6，8 6两个坐标被抽稀掉了。
示意图：
