有時候爲了美觀，背景圖片會加上模糊處理。一張圖片其實是由若干個像素組成，每個像素都可以用一個矩陣表示，然而，所謂的模糊，就是將矩陣的值縮小一定的倍數，讓像素值變小。
百度一下，發現有很多介紹圖像高斯模糊的，我想說的是，這些資料都很棒，所以本人就隨便提一下兩種高斯模糊寫法： Java版本的高斯模糊實現和RenderScript的高斯模糊實現。
效果如下：
（1）Java版本的高斯模糊的簡單實現
這種寫法的時間複雜度爲O(m2 * n2)。
代碼實現如下：
BlurTransform.java
public class BlurTransform extends BitmapTransformation {
//模糊程度
private int radius;
public BlurTransform(){
}
public BlurTransform(int radius){
this.radius = radius;
}
@Override
protected Bitmap transform(@NonNull BitmapPool pool, @NonNull Bitmap source, int outWidth, int outHeight) {
return doBlur(source, radius, true);
}
@Override
public void updateDiskCacheKey(@NonNull MessageDigest messageDigest) {
}
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) {
radius = 1;
}
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);
}
}
Glide.with(MainActivity.this)
.load(R.mipmap.pic4)
.transform(new BlurTransform(100))
.into(iv_image);
構造方法BlurTransform的參數radius表示模糊程度，數值越大越模糊，它的區間是[1,正無窮)。
（2）RenderScript的高斯模糊實現（比第一種快）
這種方法實現只支持API17以上的版本，API17以下的版本不支持，當然，自從Android9.0問世之後，也就移位了API17之前的手機已經完全淘汰了，所以這種方案可以放心使用。
代碼實現如下：
BlurTransform.java
public class BlurTransform extends BitmapTransformation {
//模糊程度
private int radius;
private Context mContext;
public BlurTransform(Context mContext){
this.mContext = mContext;
}
public BlurTransform(Context mContext, int radius){
this.mContext = mContext;
if(radius < 1){
this.radius = 1;
}else if(radius >25){
this.radius = 25;
}else{
this.radius = radius;
}
}
@Override
protected Bitmap transform(@NonNull BitmapPool pool, @NonNull Bitmap source, int outWidth, int outHeight) {
return getBlurBitmap(mContext, pool, source, radius);
}
@Override
public void updateDiskCacheKey(@NonNull MessageDigest messageDigest) {
}
/**
* 得到模糊後的bitmap
*
* @param context
* @param inputBitmap
* @param radius
* @return
*/
private Bitmap getBlurBitmap(Context context, BitmapPool pool, Bitmap inputBitmap, int radius) {
if(inputBitmap == null){
return null;
}
// 創建一張渲染後的輸出圖片。
Bitmap outputBitmap = pool.get(inputBitmap.getWidth(), inputBitmap.getHeight(), inputBitmap.getConfig());
// 創建RenderScript內核對象
RenderScript rs = RenderScript.create(context);
// 創建一個模糊效果的RenderScript的工具對象
ScriptIntrinsicBlur blurScript = ScriptIntrinsicBlur.create(rs, Element.U8_4(rs));
// 由於RenderScript並沒有使用VM來分配內存,所以需要使用Allocation類來創建和分配內存空間。
// 創建Allocation對象的時候其實內存是空的,需要使用copyTo()將數據填充進去。
Allocation tmpIn = Allocation.createFromBitmap(rs, inputBitmap);
Allocation tmpOut = Allocation.createFromBitmap(rs, outputBitmap);
// 設置渲染的模糊程度
blurScript.setRadius(radius);
// 設置blurScript對象的輸入內存
blurScript.setInput(tmpIn);
// 將輸出數據保存到輸出內存中
blurScript.forEach(tmpOut);
// 將數據填充到Allocation中
tmpOut.copyTo(outputBitmap);
return outputBitmap;
}
}
Glide.with(MainActivity.this)
.load(R.mipmap.pic4)
.transform(new BlurTransform(MainActivity.this, 10))
.into(iv_image);
參考：
本篇文字描述比較少，因爲網上好博客很多很多，所以感覺沒必要做重複的描述了。
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