Android本地图片或者网络图片高斯模糊效果（毛玻璃效果）图片模糊效果一行代码搞定

        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 (