Android-⾼斯模糊处理头像作为背景图的两种⾼效便捷⽅法第⼀种是最简单⽅便的结合强⼤的Glide图⽚加载框架的使⽤（推荐）
先来看看效果图吧！
这种是使⽤头像作为背景模糊背景使⽤的，根据项⽬需求，单独背景什么的都⾏：
个⼈中⼼头像背景图
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 = ByteArray();
originBitmap = BitmapFactory.decodeByteArray(data, 0, data.length);
Bitmap scaledBitmap = ateScaledBitmap(originBitmap,
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 = ateScaledBitmap(originBitmap,
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 = Config(), true);
}
if (radius < 1) {
return (null);
}
int w = Width();
int h = Height();
int[] pix = new int[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;
图片下载站源码gsum -= goutsum;
bsum -= boutsum;
stackstart = stackpointer - radius + div;
sir = stack[stackstart % div];
routsum -= sir[0];
goutsum -= sir[1];
boutsum -= sir[2];

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