下面給大家介紹JAVA代碼怎么實現(xiàn)圖像六邊形網(wǎng)格分割效果，希望能給大家提供幫助。

一：原理

根據(jù)輸入?yún)?shù)blockSize的大小，將圖像分塊，決定每塊的中心通過該像素塊內(nèi)所有像素之和的均值與該塊內(nèi)部每個像素比較，RGB值之間幾何距離最小為新的中心，迭代更新運算，直到達到輸入?yún)?shù)聲明的最大循環(huán)次數(shù)為止，然后輸出結(jié)果圖像即可。

二：程序?qū)崿F(xiàn)

類MyCluster，存儲每個像素塊中心的信息，計算中心位置。

類SuperPixelsFilter, 濾鏡實現(xiàn)，完成六邊形網(wǎng)格分割的主要功能，其中距離計算，基于歐幾里德距離公式。

三：效果

原圖：

效果：

四：完全源代碼

package?com.gloomyfish.image.cluster.effect;

import?java.awt.image.BufferedImage;

import?java.util.ArrayList;

import?java.util.Arrays;

import?java.util.List;

import?com.gloomyfish.filter.study.AbstractBufferedImageOp;

public?class?SuperPixelsFilter?extends?AbstractBufferedImageOp?{

private?double[]?distances;

private?int[]?labels;

private?MyCluster[]?clusters;

private?intmaxClusteringLoops=50;

private?double?blockSize;

private?double?modifier;

public?SuperPixelsFilter()

{

blockSize=16;

modifier=130;

}

public?double?getBlockSize()?{

return?blockSize;

}

public?void?setBlockSize(double?blockSize)?{

this.blockSize=?blockSize;

}

public?double?getModifier()?{

return?modifier;

}

public?void?setModifier(double?modifier)?{

this.modifier=?modifier;

}

@Override

public?BufferedImage?filter(BufferedImage?src,?BufferedImage?dest)?{

intwidth=src.getWidth();

intheight=src.getHeight();

if?(dest==?null?)

dest=createCompatibleDestImage(?src,?null?);

int[]inPixels=newint[width*height];

getRGB(?src,?0,?0,?width,?height,?inPixels?);

intindex=0;

//?initialization

distances=newdouble[width*height];

labels=newint[width*height];

Arrays.fill(distances,?Integer.MAX_VALUE);

Arrays.fill(labels,?-1);

initClusters(width,?height,?inPixels,?blockSize,?modifier);

//?loop?to?get?all?block/cells,?image?segmentation

intloops=0;

booleanpixelChangedCluster=true;

while?(pixelChangedCluster&&loops

pixelChangedCluster=false;

loops++;

//?for?each?cluster?center?C

for?(inti=0;i

MyClusterc=clusters[i];

//?for?each?pixel?i?in?2S?region?around

//?cluster?center

intxs=Math.max((int)(c.avg_x-blockSize),0);

intys=Math.max((int)(c.avg_y-blockSize),0);

intxe=Math.min((int)(c.avg_x+blockSize),width);

intye=Math.min((int)(c.avg_y+blockSize),height);

for?(inty=ys;y

for?(intx=xs;x

intpos=x+width*y;

inttr=?(inPixels[pos]>>16)?&?0xff;

inttg=?(inPixels[pos]>>8)?&?0xff;

inttb=inPixels[pos]?&?0xff;

doubleD=c.distance(x,?y,?tr,

tg,

tb,

blockSize,?modifier,?width,?height);

if?((D

distances[pos]?????????=?D;

labels[pos]????????????=?c.id;

pixelChangedCluster=true;

}

}?//?end?for?x

}?//?end?for?y

}?//?end?for?clusters

//?reset?clusters

for?(index=0;index

clusters[index].reset();

}

//?add?every?pixel?to?cluster?based?on?label

for?(inty=0;y

for?(intx=0;x

intpos=x+y*width;

inttr=?(inPixels[pos]>>16)?&?0xff;

inttg=?(inPixels[pos]>>8)?&?0xff;

inttb=inPixels[pos]?&?0xff;

clusters[labels[pos]].addPixel(x,?y,

tr,?tg,?tb);

}

}

//?calculate?centers

for?(index=0;index

clusters[index].calculateCenter();

}

}

//?Create?output?image?with?pixel?edges

for?(inty=1;y

for?(intx=1;x

intid1=labels[x+y*width];

intid2=labels[(x+1)+y*width];

intid3=labels[x+(y+1)*width];

if?(id1!=id2||id1!=id3)?{

intpos=x+y*width;

inPixels[pos]?=?(255<<24)?|?(0<<16)?|?(0<<8)?|?0;

}

}

}

setRGB(?dest,?0,?0,?width,?height,?inPixels?);

return?dest;

}

public?void?initClusters(int?width,?int?height,?int[]?input,

double?S,?double?m)?{

Listtemp=newArrayList();

booleaneven=false;

doublexstart=0;

intid=0;

for?(doubley=S/?2;?y

//?創(chuàng)建六邊形網(wǎng)格

if?(even)?{

xstart=S/?2.0;

even=false;

}?else?{

xstart=S;

even=true;

}

for?(doublex=xstart;?x

intindex=?(int)?(x?+?y?*?width);

inttr=?(input[index]>>16)?&?0xff;

inttg=?(input[index]>>8)?&?0xff;

inttb=input[index]?&?0xff;

MyClusterc=newMyCluster(id,?tr,?tg,?tb,

(int)?x,?(int)?y,?S,?m);

temp.add(c);

id++;

}

}

clusters=newMyCluster[temp.size()];

for?(inti=0;?i

clusters[i]?=?temp.get(i);

}

}

}

MyCluster類代碼：

package?com.gloomyfish.image.cluster.effect;

public?class?MyCluster?{

int?id;

doubleinv=0;?//?inv?variable?for?optimization

double?pixelCount;?//?pixels?in?this?cluster

double?avg_red;?//?average?red?value

double?avg_green;?//?average?green?value

double?avg_blue;?//?average?blue?value

double?sum_red;?//?sum?red?values

double?sum_green;?//?sum?green?values

double?sum_blue;?//?sum?blue?values

double?sum_x;?//?sum?x

double?sum_y;?//?sum?y

double?avg_x;?//?average?x

double?avg_y;?//?average?y

public?MyCluster(int?id,?int?in_red,?int?in_green,?int?in_blue,?int?x,

int?y,?double?S,?double?m)?{

//?inverse?for?distance?calculation

this.inv=1.0?/?((S?/?m)?*?(S?/?m));

this.id=?id;

addPixel(x,?y,?in_red,?in_green,?in_blue);

//?calculate?center?with?initial?one?pixel

calculateCenter();

}

public?void?reset()?{

avg_red=0;

avg_green=0;

avg_blue=0;

sum_red=0;

sum_green=0;

sum_blue=0;

pixelCount=0;

avg_x=0;

avg_y=0;

sum_x=0;

sum_y=0;

}

/*

*?Add?pixel?color?values?to?sum?of?previously?added?color?values.

*/

void?addPixel(int?x,?int?y,?int?in_red,?int?in_green,?int?in_blue)?{

sum_x?+=?x;

sum_y?+=?y;

sum_red?+=?in_red;

sum_green?+=?in_green;

sum_blue?+=?in_blue;

pixelCount++;

}

public?void?calculateCenter()?{

//?Optimization:?using?"inverse"

//?to?change?divide?to?multiply

doubleinv=1/?pixelCount;

avg_red=sum_red*?inv;

avg_green=sum_green*?inv;

avg_blue=sum_blue*?inv;

avg_x=sum_x*?inv;

avg_y=sum_y*?inv;

}

double?distance(int?x,?int?y,?int?red,?int?green,?int?blue,?double?S,

double?m,?int?w,?int?h)?{

//?power?of?color?difference?between

//?given?pixel?and?cluster?center

doubledx_color=?(avg_red?-?red)?*?(avg_red?-?red)

+?(avg_green?-?green)?*?(avg_green?-?green)?+?(avg_blue?-?blue)

*?(avg_blue?-?blue);

//?power?of?spatial?difference?between

//?given?pixel?and?cluster?center

doubledx_spatial=?(avg_x?-?x)?*?(avg_x?-?x)?+?(avg_y?-?y)

*?(avg_y?-?y);

//?Calculate?approximate?distance?D

//?doubleD=dx_color+dx_spatial*inv;

//?Calculate?squares?to?get?more?accurate?results

doubleD=Math.sqrt(dx_color)?+?Math.sqrt(dx_spatial?*?inv);

return?D;

}

}

五：參考這里

該濾鏡是SuperPixel算法的簡單應(yīng)用，多數(shù)時候，我們可能更熟悉K-Means等圖像分割算法，其實SuperPixel是圖像分割算法之一。

(責(zé)任編輯：6g下載網(wǎng))

總結(jié)

以上是生活随笔為你收集整理的java 绘制六边形_JAVA代码怎么实现图像六边形网格分割效果的全部內(nèi)容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網(wǎng)站內(nèi)容還不錯，歡迎將生活随笔推薦給好友。