一行java代码实现高斯模糊效果

本文实例为大家分享了本地图片或者网络图片高斯模糊效果（毛玻璃效果），具体内容如下

首先看效果图

1.本地图片高斯模糊

2.网络图片高斯模糊

github网址：https://github.com/qiushi123/BlurImageQcl

下面是使用步骤

一、实现本地图片或者网络图片的毛玻璃效果特别方便，只需要把下面的FastBlurUtil类复制到你的项目中就行

package com.testdemo.blur_image_lib10;

import android.graphics.Bitmap;
import android.graphics.BitmapFactory;

import java.io.BufferedInputStream;
import java.io.BufferedOutputStream;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.OutputStream;
import java.net.URL;

/**
* Created by qcl on 14/7/15.
*/
public class FastBlurUtil {
/**
 * 根据imagepath获取bitmap
 */
/**
 * 得到本地或者网络上的bitmap url - 网络或者本地图片的绝对路径,比如:
 * <p>
 * A.网络路径: url="http://blog.foreverlove.us/girl2.png" ;
 * <p>
 * B.本地路径:url="file://mnt/sdcard/photo/image.png";
 * <p>
 * C.支持的图片格式 ,png, jpg,bmp,gif等等
 *
 * @param url
 * @return
 */
public static int IO_BUFFER_SIZE = 2 * 1024;
public static Bitmap GetUrlBitmap(String url, int scaleRatio) {
 int blurRadius = 8;//通常设置为8就行。
 if (scaleRatio <= 0) {
  scaleRatio = 10;
 }

Bitmap originBitmap = null;
 InputStream in = null;
 BufferedOutputStream out = null;
 try {
  in = new BufferedInputStream(new URL(url).openStream(), IO_BUFFER_SIZE);
  final ByteArrayOutputStream dataStream = new ByteArrayOutputStream();
  out = new BufferedOutputStream(dataStream, IO_BUFFER_SIZE);
  copy(in, out);
  out.flush();
  byte[] data = dataStream.toByteArray();
  originBitmap = BitmapFactory.decodeByteArray(data, 0, data.length);

Bitmap scaledBitmap = Bitmap.createScaledBitmap(originBitmap,
    originBitmap.getWidth() / scaleRatio,
    originBitmap.getHeight() / scaleRatio,
    false);
  Bitmap blurBitmap = doBlur(scaledBitmap, blurRadius, true);
  return blurBitmap;
 } catch (IOException e) {
  e.printStackTrace();
  return null;
 }
}

private static void copy(InputStream in, OutputStream out)
  throws IOException {
 byte[] b = new byte[IO_BUFFER_SIZE];
 int read;
 while ((read = in.read(b)) != -1) {
  out.write(b, 0, read);
 }
}

// 把本地图片毛玻璃化
public static Bitmap toBlur(Bitmap originBitmap, int scaleRatio) {
 //  int scaleRatio = 10;
 // 增大scaleRatio缩放比，使用一样更小的bitmap去虚化可以到更好的得模糊效果，而且有利于占用内存的减小；
 int blurRadius = 8;//通常设置为8就行。
 //增 * lurRadius，可以得到更高程度的虚化，不过会导致CPU更加intensive

/* 其中前三个参数很明显，其中宽高我们可以选择为原图尺寸的1/10；
 第四个filter是指缩放的效果，filter为true则会得到一个边缘平滑的bitmap，
 反之，则会得到边缘锯齿、pixelrelated的bitmap。
 这里我们要对缩放的图片进行虚化，所以无所谓边缘效果，filter=false。*/
 if (scaleRatio <= 0) {
  scaleRatio = 10;
 }
 Bitmap scaledBitmap = Bitmap.createScaledBitmap(originBitmap,
   originBitmap.getWidth() / scaleRatio,
   originBitmap.getHeight() / scaleRatio,
   false);
 Bitmap blurBitmap = doBlur(scaledBitmap, blurRadius, true);
 return blurBitmap;
}

public static Bitmap doBlur(Bitmap sentBitmap, int radius, boolean canReuseInBitmap) {
 Bitmap bitmap;
 if (canReuseInBitmap) {
  bitmap = sentBitmap;
 } else {
  bitmap = sentBitmap.copy(sentBitmap.getConfig(), true);
 }

if (radius < 1) {
  return (null);
 }

int w = bitmap.getWidth();
 int h = bitmap.getHeight();

int[] pix = new int[w * h];
 bitmap.getPixels(pix, 0, w, 0, 0, w, h);

int wm = w - 1;
 int hm = h - 1;
 int wh = w * h;
 int div = radius + radius + 1;

int r[] = new int[wh];
 int g[] = new int[wh];
 int b[] = new int[wh];
 int rsum, gsum, bsum, x, y, i, p, yp, yi, yw;
 int vmin[] = new int[Math.max(w, h)];

int divsum = (div + 1) >> 1;
 divsum *= divsum;
 int dv[] = new int[256 * divsum];
 for (i = 0; i < 256 * divsum; i++) {
  dv[i] = (i / divsum);
 }

yw = yi = 0;

int[][] stack = new int[div][3];
 int stackpointer;
 int stackstart;
 int[] sir;
 int rbs;
 int r1 = radius + 1;
 int routsum, goutsum, boutsum;
 int rinsum, ginsum, binsum;

for (y = 0; y < h; y++) {
  rinsum = ginsum = binsum = routsum = goutsum = boutsum = rsum = gsum = bsum = 0;
  for (i = -radius; i <= radius; i++) {
   p = pix[yi + Math.min(wm, Math.max(i, 0))];
   sir = stack[i + radius];
   sir[0] = (p & 0xff0000) >> 16;
   sir[1] = (p & 0x00ff00) >> 8;
   sir[2] = (p & 0x0000ff);
   rbs = r1 - Math.abs(i);
   rsum += sir[0] * rbs;
   gsum += sir[1] * rbs;
   bsum += sir[2] * rbs;
   if (i > 0) {
    rinsum += sir[0];
    ginsum += sir[1];
    binsum += sir[2];
   } else {
    routsum += sir[0];
    goutsum += sir[1];
    boutsum += sir[2];
   }
  }
  stackpointer = radius;

for (x = 0; x < w; x++) {

r[yi] = dv[rsum];
   g[yi] = dv[gsum];
   b[yi] = dv[bsum];

rsum -= routsum;
   gsum -= goutsum;
   bsum -= boutsum;

stackstart = stackpointer - radius + div;
   sir = stack[stackstart ％ div];

routsum -= sir[0];
   goutsum -= sir[1];
   boutsum -= sir[2];

if (y == 0) {
    vmin[x] = Math.min(x + radius + 1, wm);
   }
   p = pix[yw + vmin[x]];

sir[0] = (p & 0xff0000) >> 16;
   sir[1] = (p & 0x00ff00) >> 8;
   sir[2] = (p & 0x0000ff);

rinsum += sir[0];
   ginsum += sir[1];
   binsum += sir[2];

rsum += rinsum;
   gsum += ginsum;
   bsum += binsum;

stackpointer = (stackpointer + 1) ％ div;
   sir = stack[(stackpointer) ％ div];

routsum += sir[0];
   goutsum += sir[1];
   boutsum += sir[2];

rinsum -= sir[0];
   ginsum -= sir[1];
   binsum -= sir[2];

yi++;
  }
  yw += w;
 }
 for (x = 0; x < w; x++) {
  rinsum = ginsum = binsum = routsum = goutsum = boutsum = rsum = gsum = bsum = 0;
  yp = -radius * w;
  for (i = -radius; i <= radius; i++) {
   yi = Math.max(0, yp) + x;

sir = stack[i + radius];

sir[0] = r[yi];
   sir[1] = g[yi];
   sir[2] = b[yi];

rbs = r1 - Math.abs(i);

rsum += r[yi] * rbs;
   gsum += g[yi] * rbs;
   bsum += b[yi] * rbs;

if (i > 0) {
    rinsum += sir[0];
    ginsum += sir[1];
    binsum += sir[2];
   } else {
    routsum += sir[0];
    goutsum += sir[1];
    boutsum += sir[2];
   }

if (i < hm) {
    yp += w;
   }
  }
  yi = x;
  stackpointer = radius;
  for (y = 0; y < h; y++) {
   // Preserve alpha channel: ( 0xff000000 & pix[yi] )
   pix[yi] = (0xff000000 & pix[yi]) | (dv[rsum] << 16) | (dv[gsum] << 8) | dv[bsum];

rsum -= routsum;
   gsum -= goutsum;
   bsum -= boutsum;

stackstart = stackpointer - radius + div;
   sir = stack[stackstart ％ div];

routsum -= sir[0];
   goutsum -= sir[1];
   boutsum -= sir[2];

if (x == 0) {
    vmin[y] = Math.min(y + r1, hm) * w;
   }
   p = x + vmin[y];

sir[0] = r[p];
   sir[1] = g[p];
   sir[2] = b[p];

rinsum += sir[0];
   ginsum += sir[1];
   binsum += sir[2];

rsum += rinsum;
   gsum += ginsum;
   bsum += binsum;

stackpointer = (stackpointer + 1) ％ div;
   sir = stack[stackpointer];

routsum += sir[0];
   goutsum += sir[1];
   boutsum += sir[2];

rinsum -= sir[0];
   ginsum -= sir[1];
   binsum -= sir[2];

yi += w;
  }
 }

bitmap.setPixels(pix, 0, w, 0, 0, w, h);

return (bitmap);
}

}

二、使用实例

package com.testdemo;

import android.app.Activity;
import android.content.res.Resources;
import android.graphics.Bitmap;
import android.graphics.BitmapFactory;
import android.os.Bundle;
import android.text.TextUtils;
import android.view.View;
import android.widget.EditText;
import android.widget.ImageView;

import com.testdemo.blur_image_lib10.FastBlurUtil;

public class MainActivity10_BlurImage extends Activity {
 ImageView image;
 EditText edit;

@Override
 protected void onCreate(Bundle savedInstanceState) {
  super.onCreate(savedInstanceState);
  setContentView(R.layout.activity_main10_blur_image);
  image = (ImageView) findViewById(R.id.image);
  edit = (EditText) findViewById(R.id.edit);

findViewById(R.id.button2).setOnClickListener(new View.OnClickListener() {
   @Override
   public void onClick(View v) {
    String pattern = edit.getText().toString();
    int scaleRatio = 0;
    if (TextUtils.isEmpty(pattern)) {
     scaleRatio = 0;
    } else if (scaleRatio < 0) {
     scaleRatio = 10;
    } else {
     scaleRatio = Integer.parseInt(pattern);
    }

//  获取需要被模糊的原图bitmap
    Resources res = getResources();
    Bitmap scaledBitmap = BitmapFactory.decodeResource(res, R.drawable.filter);

//  scaledBitmap为目标图像，10是缩放的倍数（越大模糊效果越高）
    Bitmap blurBitmap = FastBlurUtil.toBlur(scaledBitmap, scaleRatio);
    image.setScaleType(ImageView.ScaleType.CENTER_CROP);
    image.setImageBitmap(blurBitmap);
   }
  });

findViewById(R.id.button).setOnClickListener(new View.OnClickListener() {
   @Override
   public void onClick(View v) {
    //url为网络图片的url，10 是缩放的倍数（越大模糊效果越高）
    final String pattern = edit.getText().toString();

final String url =
      //  "http://imgs.duwu.me/duwu/doc/cover/201601/18/173040803962.jpg";
      "http://b.hiphotos.baidu.com/album/pic/item/caef76094b36acafe72d0e667cd98d1000e99c5f.jpg?psign=e72d0e667cd98d1001e93901213fb80e7aec54e737d1b867";
    new Thread(new Runnable() {
     @Override
     public void run() {
      int scaleRatio = 0;
      if (TextUtils.isEmpty(pattern)) {
       scaleRatio = 0;
      } else if (scaleRatio < 0) {
       scaleRatio = 10;
      } else {
       scaleRatio = Integer.parseInt(pattern);
      }
//      下面的这个方法必须在子线程中执行
      final Bitmap blurBitmap2 = FastBlurUtil.GetUrlBitmap(url, scaleRatio);

//      刷新ui必须在主线程中执行
       APP.runOnUIThread(new Runnable() {//这个是我自己封装的在主线程中刷新ui的方法。
       @Override
       public void run() {
        image.setScaleType(ImageView.ScaleType.CENTER_CROP);
        image.setImageBitmap(blurBitmap2);

}
      });
     }
    }).start();

}
  });

}

}  

下面是上面的布局文件

<LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:orientation="vertical">

<ImageView
android:id="@+id/image2"
android:layout_width="match_parent"
android:layout_height="220dp"
android:background="@drawable/filter"/>

<LinearLayout
android:layout_width="match_parent"
android:layout_height="wrap_content"
android:orientation="horizontal">

<EditText
android:id="@+id/edit"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_marginTop="15dp"
android:hint="输入模糊度"
/>

<Button
android:id="@+id/button2"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:text="转化毛玻璃"/>

<Button
android:id="@+id/button"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_marginLeft="4dp"
android:text="转化网络图片毛玻璃"/>
</LinearLayout>

<ImageView
android:id="@+id/image"
android:layout_width="match_parent"
android:layout_height="220dp"
android:layout_below="@+id/image2"
/>
</LinearLayout>

三、注意事项

1.一定不要忘记intent权限
2.加载网络图片时一定要在子线程中执行。

github网址：https://github.com/qiushi123/BlurImageQcl