废话不多说，直接上代码

地图裁剪器，可以将图片裁剪成瓦片数据，主要用途是将高清卫星图像裁剪成瓦片图，可以做离线地图的开发，基于墨卡托坐标

地图裁剪

package com.wwp.utils.map;
import java.awt.Graphics2D;
import java.awt.Image;
import java.awt.Toolkit;
import java.awt.Transparency;
import java.awt.image.BufferedImage;
import java.awt.image.CropImageFilter;
import java.awt.image.FilteredImageSource;
import java.awt.image.ImageFilter;
import java.io.File;

import javax.imageio.ImageIO;
/**
 * 
 *
 * class name: BMapCut
 * description:
 * authername:wangwenping
 * modified by: xx 
 * modified time:
 * modified info :
 * @version 1.0.0
 *
 */
public class BMapCut {
    private int minlevel;
    private int maxlevel;
    private int piclevel;
    private double mercatorx;
    private double mercatory;
    private String pic;
    private String savepath;

    public BMapCut(String pic, double mercatorx, double mercatory,
            String savepath) {
        this.pic = pic;
        this.mercatorx = mercatorx;
        this.mercatory = mercatory;
        this.savepath = savepath;
    }
/**
 * @param pic 图片路径
 * @param minlevel最小缩放等级
 * @param maxlevel最大缩放等级
 * @param piclevel 原图所处缩放等级 
 * @param mercatorx 墨卡托x坐标
 * @param mercatory墨卡托y坐标
 * @param savepath输出目录
 */
    public BMapCut(String pic, int minlevel, int maxlevel, int piclevel, double mercatorx,
            double mercatory, String savepath) {
        this.pic = pic;
        this.minlevel = minlevel;
        this.maxlevel = maxlevel;
        this.mercatorx = mercatorx;
        this.mercatory = mercatory;
        this.savepath = savepath;
        this.piclevel = piclevel;
    }

    public void cutterall() throws Exception {
        for (int i = minlevel; i <= maxlevel; i++) {
            cutterone(i);
        }
    }

    public void cutterone(int level) throws Exception {
        //图片中心的像素坐标(pixelx,pixely)，图片中心的平面坐标即魔卡托坐标(mercatorx, mercatory)
        //像素坐标  = 平面坐标 * Math.pow(2, level - 18)
        double pixelx = mercatorx * Math.pow(2, level - 18);
        double pixely = mercatory * Math.pow(2, level - 18);
        System.out.println("pixelx : " + pixelx);
        System.out.println("pixely : " + pixely);
        BufferedImage bi = ImageIO.read(new File(pic));
        int width = bi.getWidth();
        int height = bi.getHeight();
        //图片遵循原则：当前图片所属级别piclevel不缩放即像素级别相等。
        //按照公式缩放：当前级别图片长度 = 原图片长度 * Math.pow(2, level - piclevel)
        //minx: 图片左下角x坐标
        //miny: 图片左下角y坐标
        //maxx: 图片右上角x坐标
        //maxy: 图片右上角y坐标
        double minx = pixelx - width * Math.pow(2, level - piclevel) / 2;
        double miny = pixely - height * Math.pow(2, level - piclevel) / 2;
        double maxx = pixelx + width  * Math.pow(2, level - piclevel) / 2;
        double maxy = pixely + height * Math.pow(2, level - piclevel)  / 2;
        System.out.println("(minx,miny) = (" + minx + ", " + miny + ")" );
        System.out.println("(maxx,maxy) = (" + maxx + ", " + maxy + ")" );
        int neatminx = (int) minx / 256;
        int remminx = (int) minx % 256;
        int neatminy = (int) miny / 256;
        int remminy = (int) miny % 256 ;
        
        int neatmaxx = (int) maxx / 256;
        int remmaxx = 256 - (int) maxx % 256;
        int neatmaxy = (int) maxy / 256;
        int remmaxy = 256 - (int) maxy % 256;
        //(neatminx,neatminy)为图片左下角最近的整数图块坐标,neatminx到neatmaxx即当前级别下切割图块的图块坐标x
        //(neatmaxx,neatmaxy)为图片右上角最近的整数图块坐标,neatminy到neatmaxy即当前级别下切割图块的图块坐标y
        System.out.println("neatminx: " + neatminx);
        System.out.println("neatmaxx: " + neatmaxx);
        System.out.println("neatminy: " + neatminy);
        System.out.println("neatmaxy: " + neatmaxy);
        System.out.println("remminx width remmaxx : " + remminx + " "+ width + " "+ remmaxx );
        System.out.println("remminy height remmaxy : " + remminy + " " +  height +" " + remmaxy );
        
        // 扩充原图片为width * height --- > (remminx + width + remmaxx ) * (remminy +
        // height +remmaxy)
        int extendwidth = (neatmaxx - neatminx + 1 ) * 256;
        int extendheight = (neatmaxy - neatminy + 1 ) * 256;
        System.out.println("extendwidth: " + extendwidth);
        System.out.println("extendheight: " + extendheight);
        
        BufferedImage outputimage = null;
        Graphics2D g = bi.createGraphics();
        BufferedImage extend = g.getDeviceConfiguration().createCompatibleImage(extendwidth, extendheight, Transparency.TRANSLUCENT);
        g.dispose();
        g = extend.createGraphics();
        g.drawImage(extend, 0, 0, extendwidth, extendheight, null);
        g.drawImage(bi.getScaledInstance((int) (width * Math.pow(2, level - piclevel)), (int)(height * Math.pow(2, level - piclevel)), Image.SCALE_SMOOTH), remminx, remmaxy, null);
        
        //切割图片，共( neatmaxx - neatminx + 1) * (neatmaxy - neatminy + 1)份 256*256图片
        String dirname = savepath.substring(0, savepath.lastIndexOf("\\")) + "\\tiles\\" + level;
        System.out.println("dirname : " + dirname);
        
        
        File dir = new File(dirname);
        Image image = extend.getScaledInstance(extendwidth, extendheight, Image.SCALE_DEFAULT);
        if(dir.exists()) {
            System.out.println("创建目录失败！, 目录已存在！");
        } else {
            if(dir.mkdirs()) {
                ImageIO.write(extend, "png", new File(dirname + savepath.substring(savepath.lastIndexOf("\\")) + ".png"));
                System.out.println("savepath : " + dirname + savepath.substring(savepath.lastIndexOf("\\")));
                System.out.println("extend success!");
                int w = neatmaxx - neatminx + 1;
                int h = neatmaxy - neatminy + 1;
                for(int i = 0; i < w; i++) {
                    for(int j = 1; j <= h; j++) {
                        ImageFilter cropfilter = new CropImageFilter(256 * i, 256* (h - j), 256, 256);
                        Image img = Toolkit.getDefaultToolkit().createImage(new FilteredImageSource(image.getSource(),cropfilter));
                        BufferedImage tag = new BufferedImage(256, 256 , BufferedImage.TYPE_INT_BGR);
                        Graphics2D gs = tag.createGraphics();
                        tag = gs.getDeviceConfiguration().createCompatibleImage(256, 256, Transparency.TRANSLUCENT);
                        gs.dispose();
                        gs = tag.createGraphics();
                        gs.drawImage(img, 0, 0, null);
                        g.dispose();
                        String croppicname = dirname + "\\tile" + (neatminx + i) + "_" + (neatminy + j - 1) + ".png"; 
                        ImageIO.write(tag, "png", new File(croppicname));
                    }
                }
                System.out.println("切割图片成功！");
            } else {
                System.out.println("创建目录失败！");
            }
        }

}

public static void main(String[] args) throws Exception{
	    BMapCut a=new BMapCut("C:\\Users\\Administrator\\Desktop\\geo\\123.png",16/*最小缩放等级*/,18/*最大缩放等级*/,18/*原图所处缩放等级*/,12958175/*墨卡托x坐标*/,4825923.77/*墨卡托y坐标*/,"C:\\输出目录");
		a.cutterall();
    }
}