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。
  //增大blurRadius，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

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持脚本之家。