目前在我正在开发的 Android 应用程序中，我正在循环通过图像的像素来模糊它。这在 640x480 图像上大约需要 30 秒。
在 Android Market 中浏览应用时，我遇到了一个包含模糊功能的应用，它们的模糊速度非常快（例如 5 秒），因此它们必须使用不同的模糊方法。
有谁知道除了循环像素之外更快的方法吗？
【问题讨论】：
标签： java android image-processing renderscript
with Showcase/Benchmark App 和 Source on Github。 还可以查看我目前正在开发的 Blur 框架：Dali。
经过大量试验后，我现在可以安全地为您提供一些可靠的建议，这些建议将使您在使用 Android 框架时在 Android 中的生活更轻松。
切勿使用完整大小的位图。图像越大，需要模糊的越多，模糊半径也需要越高，通常，模糊半径越大，算法所需的时间就越长。
final BitmapFactory.Options options = new BitmapFactory.Options();
options.inSampleSize = 8;
Bitmap blurTemplate = BitmapFactory.decodeResource(getResources(), R.drawable.myImage, options);
这将加载带有inSampleSize 8 的位图，因此只有原始图像的 1/64。测试 inSampleSize 适合您的需求，但保持 2^n (2,4,8,...) 以避免因缩放而降低质量。 See Google doc for more
另一个非常大的优势是位图加载速度非常快。在我早期的模糊测试中，我发现整个模糊过程中最长的时间是图像加载。因此，要从磁盘加载 1920x1080 图像，我的 Nexus 5 需要 500 毫秒，而模糊只需要 250 毫秒左右。
Renderscript 提供ScriptIntrinsicBlur，这是一个高斯模糊滤镜。它具有良好的视觉质量，是您在 Android 上实际获得的最快速度。谷歌声称是"typically 2-3x faster than a multithreaded C implementation and often 10x+ faster than a Java implementation"。 Renderscript 非常复杂（使用最快的处理设备（GPU、ISP 等）等），还有v8 support library for it making it compatible down to 2.2。好吧，至少在理论上，通过我自己的测试和其他开发人员的报告，似乎不可能盲目地使用 Renderscript，因为硬件/驱动程序碎片似乎会导致某些设备出现问题，即使使用更高的 sdk lvl（例如我有4.1 Nexus S 的问题）所以要小心并在很多设备上进行测试。下面是一个简单的示例，可以帮助您入门：
//define this only once if blurring multiple times
RenderScript rs = RenderScript.create(context);
(...)
//this will blur the bitmapOriginal with a radius of 8 and save it in bitmapOriginal
final Allocation input = Allocation.createFromBitmap(rs, bitmapOriginal); //use this constructor for best performance, because it uses USAGE_SHARED mode which reuses memory
final Allocation output = Allocation.createTyped(rs, input.getType());
final ScriptIntrinsicBlur script = ScriptIntrinsicBlur.create(rs, Element.U8_4(rs));
script.setRadius(8f);
script.setInput(input);
script.forEach(output);
output.copyTo(bitmapOriginal);
当使用谷歌"because they include the latest improvements"特别推荐的Gradle v8支持时，你只能need to add 2 lines to your build script和android.support.v8.renderscript与当前的构建工具一起使用(updated syntax for android Gradle plugin v14+)
android {
...
defaultConfig {
...
renderscriptTargetApi 19
renderscriptSupportModeEnabled true
}
}
Nexus 5 上的简单基准测试 - 将 RenderScript 与不同的其他 java 和 Renderscript 实现进行比较：
不同图片尺寸下每次模糊的平均运行时间
每秒可模糊的百万像素
每个值是 250 轮的平均值。 RS_GAUSS_FAST 是 ScriptIntrinsicBlur（几乎总是最快的），其他以 RS_ 开头的主要是使用简单内核的卷积实现。 The details of the algorithms can be found here。这并不是纯粹的模糊，因为很大一部分是被测量的垃圾收集。这可以在这里看到（ScriptIntrinsicBlur 在 100x100 的图像上，大约 500 轮）
尖峰是 gc。
你可以自己查，基准应用在playstore里：BlurBenchmark
如果您需要多个模糊来实现实时模糊或类似功能，并且您的内存允许它不会多次从可绘制对象中加载位图，而是将其“缓存”在成员变量中。在这种情况下，请始终尝试使用相同的变量，以尽量减少垃圾收集。
还可以从文件或可绘制对象中检查新的inBitmap option when loading，这将重用位图内存并节省垃圾收集时间。
简单天真的方法就是用2个ImageViews，一个模糊，然后alpha淡化它们。但是，如果您想要一个更复杂的外观，从锐利平滑地消失到模糊，请查看Roman Nurik's post about how to do it like in his Muzei app。
基本上，他解释说他预先模糊了一些具有不同模糊程度的帧，并将它们用作看起来非常流畅的动画中的关键帧。
【讨论】：
renderscriptSupportModeEnabled true 否则它将无法构建！我一直在寻找！
在 i/o 2019 上提出了以下解决方案：
/**
* Blurs the given Bitmap image
* @param bitmap Image to blur
* @param applicationContext Application context
* @return Blurred bitmap image
*/
@WorkerThread
fun blurBitmap(bitmap: Bitmap, applicationContext: Context): Bitmap {
lateinit var rsContext: RenderScript
try {
// Create the output bitmap
val output = Bitmap.createBitmap(
bitmap.width, bitmap.height, bitmap.config)
// Blur the image
rsContext = RenderScript.create(applicationContext, RenderScript.ContextType.DEBUG)
val inAlloc = Allocation.createFromBitmap(rsContext, bitmap)
val outAlloc = Allocation.createTyped(rsContext, inAlloc.type)
val theIntrinsic = ScriptIntrinsicBlur.create(rsContext, Element.U8_4(rsContext))
theIntrinsic.apply {
setRadius(10f)
theIntrinsic.setInput(inAlloc)
theIntrinsic.forEach(outAlloc)
}
outAlloc.copyTo(output)
return output
} finally {
rsContext.finish()
}
}
【讨论】：
对于未来的 Google 员工，这是我从 Quasimondo 移植的一种算法。它是盒状模糊和高斯模糊的混合体，非常漂亮而且速度也非常快。
遇到 ArrayIndexOutOfBoundsException 问题的人的更新： cmets 中的@anthonycr 提供了此信息：
我发现通过将 Math.abs 替换为 StrictMath.abs 或其他一些 abs 实现，不会发生崩溃。
/**
* Stack Blur v1.0 from
* http://www.quasimondo.com/StackBlurForCanvas/StackBlurDemo.html
* Java Author: Mario Klingemann <mario at quasimondo.com>
* http://incubator.quasimondo.com
*
* created Feburary 29, 2004
* Android port : Yahel Bouaziz <yahel at kayenko.com>
* http://www.kayenko.com
* ported april 5th, 2012
*
* This is a compromise between Gaussian Blur and Box blur
* It creates much better looking blurs than Box Blur, but is
* 7x faster than my Gaussian Blur implementation.
*
* I called it Stack Blur because this describes best how this
* filter works internally: it creates a kind of moving stack
* of colors whilst scanning through the image. Thereby it
* just has to add one new block of color to the right side
* of the stack and remove the leftmost color. The remaining
* colors on the topmost layer of the stack are either added on
* or reduced by one, depending on if they are on the right or
* on the left side of the stack.
*
* If you are using this algorithm in your code please add
* the following line:
* Stack Blur Algorithm by Mario Klingemann <mario@quasimondo.com>
*/
public Bitmap fastblur(Bitmap sentBitmap, float scale, int radius) {
int width = Math.round(sentBitmap.getWidth() * scale);
int height = Math.round(sentBitmap.getHeight() * scale);
sentBitmap = Bitmap.createScaledBitmap(sentBitmap, width, height, false);
Bitmap 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];
Log.e("pix", w + " " + h + " " + pix.length);
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;
}
}
Log.e("pix", w + " " + h + " " + pix.length);
bitmap.setPixels(pix, 0, w, 0, 0, w, h);
return (bitmap);
}
【讨论】：
for 循环中，rbs 变量的计算或gsum、rsum 或bsum 变量的计算没有正确完成。我发现通过将Math.abs 替换为StrictMath.abs 或其他一些abs 实现，不会发生崩溃。由于StrictMath.abs 本身委托给Math.abs，看来这一定是一个糟糕的优化。
我发现稍微降低对比度、亮度和饱和度会使模糊的图像更漂亮，所以我结合了堆栈溢出的各种方法并制作了这个Blur Class 处理模糊图像、改变亮度、饱和度，模糊图像的对比度和大小。它还可以将图像从可绘制图像转换为位图，反之亦然。
【讨论】：
这是一个使用 RenderScript 的实时模糊叠加，看起来速度足够快。
【讨论】：
我以前用过这个..
public static Bitmap myblur(Bitmap image, Context context) {
final float BITMAP_SCALE = 0.4f;
final float BLUR_RADIUS = 7.5f;
int width = Math.round(image.getWidth() * BITMAP_SCALE);
int height = Math.round(image.getHeight() * BITMAP_SCALE);
Bitmap inputBitmap = Bitmap.createScaledBitmap(image, width, height, false);
Bitmap outputBitmap = Bitmap.createBitmap(inputBitmap);
RenderScript rs = RenderScript.create(context);
ScriptIntrinsicBlur theIntrinsic = ScriptIntrinsicBlur.create(rs, Element.U8_4(rs));
Allocation tmpIn = Allocation.createFromBitmap(rs, inputBitmap);
Allocation tmpOut = Allocation.createFromBitmap(rs, outputBitmap);
theIntrinsic.setRadius(BLUR_RADIUS);
theIntrinsic.setInput(tmpIn);
theIntrinsic.forEach(tmpOut);
tmpOut.copyTo(outputBitmap);
return outputBitmap;
}
【讨论】：
感谢@Yahel 提供代码。 发布具有 alpha 通道模糊 支持的相同方法，因为我花了一些时间使其正常工作，因此它可以节省某人的时间：
/**
* Stack Blur v1.0 from
* http://www.quasimondo.com/StackBlurForCanvas/StackBlurDemo.html
* Java Author: Mario Klingemann <mario at quasimondo.com>
* http://incubator.quasimondo.com
* <p/>
* created Feburary 29, 2004
* Android port : Yahel Bouaziz <yahel at kayenko.com>
* http://www.kayenko.com
* ported april 5th, 2012
* <p/>
* This is a compromise between Gaussian Blur and Box blur
* It creates much better looking blurs than Box Blur, but is
* 7x faster than my Gaussian Blur implementation.
* <p/>
* I called it Stack Blur because this describes best how this
* filter works internally: it creates a kind of moving stack
* of colors whilst scanning through the image. Thereby it
* just has to add one new block of color to the right side
* of the stack and remove the leftmost color. The remaining
* colors on the topmost layer of the stack are either added on
* or reduced by one, depending on if they are on the right or
* on the left side of the stack.
* <p/>
* If you are using this algorithm in your code please add
* the following line:
* Stack Blur Algorithm by Mario Klingemann <mario@quasimondo.com>
*/
public static Bitmap fastblur(Bitmap sentBitmap, float scale, int radius) {
int width = Math.round(sentBitmap.getWidth() * scale);
int height = Math.round(sentBitmap.getHeight() * scale);
sentBitmap = Bitmap.createScaledBitmap(sentBitmap, width, height, false);
Bitmap 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];
Log.e("pix", w + " " + h + " " + pix.length);
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 a[] = new int[wh];
int rsum, gsum, bsum, asum, 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][4];
int stackpointer;
int stackstart;
int[] sir;
int rbs;
int r1 = radius + 1;
int routsum, goutsum, boutsum, aoutsum;
int rinsum, ginsum, binsum, ainsum;
for (y = 0; y < h; y++) {
rinsum = ginsum = binsum = ainsum = routsum = goutsum = boutsum = aoutsum = rsum = gsum = bsum = asum = 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);
sir[3] = 0xff & (p >> 24);
rbs = r1 - Math.abs(i);
rsum += sir[0] * rbs;
gsum += sir[1] * rbs;
bsum += sir[2] * rbs;
asum += sir[3] * rbs;
if (i > 0) {
rinsum += sir[0];
ginsum += sir[1];
binsum += sir[2];
ainsum += sir[3];
} else {
routsum += sir[0];
goutsum += sir[1];
boutsum += sir[2];
aoutsum += sir[3];
}
}
stackpointer = radius;
for (x = 0; x < w; x++) {
r[yi] = dv[rsum];
g[yi] = dv[gsum];
b[yi] = dv[bsum];
a[yi] = dv[asum];
rsum -= routsum;
gsum -= goutsum;
bsum -= boutsum;
asum -= aoutsum;
stackstart = stackpointer - radius + div;
sir = stack[stackstart % div];
routsum -= sir[0];
goutsum -= sir[1];
boutsum -= sir[2];
aoutsum -= sir[3];
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);
sir[3] = 0xff & (p >> 24);
rinsum += sir[0];
ginsum += sir[1];
binsum += sir[2];
ainsum += sir[3];
rsum += rinsum;
gsum += ginsum;
bsum += binsum;
asum += ainsum;
stackpointer = (stackpointer + 1) % div;
sir = stack[(stackpointer) % div];
routsum += sir[0];
goutsum += sir[1];
boutsum += sir[2];
aoutsum += sir[3];
rinsum -= sir[0];
ginsum -= sir[1];
binsum -= sir[2];
ainsum -= sir[3];
yi++;
}
yw += w;
}
for (x = 0; x < w; x++) {
rinsum = ginsum = binsum = ainsum = routsum = goutsum = boutsum = aoutsum = rsum = gsum = bsum = asum = 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];
sir[3] = a[yi];
rbs = r1 - Math.abs(i);
rsum += r[yi] * rbs;
gsum += g[yi] * rbs;
bsum += b[yi] * rbs;
asum += a[yi] * rbs;
if (i > 0) {
rinsum += sir[0];
ginsum += sir[1];
binsum += sir[2];
ainsum += sir[3];
} else {
routsum += sir[0];
goutsum += sir[1];
boutsum += sir[2];
aoutsum += sir[3];
}
if (i < hm) {
yp += w;
}
}
yi = x;
stackpointer = radius;
for (y = 0; y < h; y++) {
pix[yi] = (dv[asum] << 24) | (dv[rsum] << 16) | (dv[gsum] << 8) | dv[bsum];
rsum -= routsum;
gsum -= goutsum;
bsum -= boutsum;
asum -= aoutsum;
stackstart = stackpointer - radius + div;
sir = stack[stackstart % div];
routsum -= sir[0];
goutsum -= sir[1];
boutsum -= sir[2];
aoutsum -= sir[3];
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];
sir[3] = a[p];
rinsum += sir[0];
ginsum += sir[1];
binsum += sir[2];
ainsum += sir[3];
rsum += rinsum;
gsum += ginsum;
bsum += binsum;
asum += ainsum;
stackpointer = (stackpointer + 1) % div;
sir = stack[stackpointer];
routsum += sir[0];
goutsum += sir[1];
boutsum += sir[2];
aoutsum += sir[3];
rinsum -= sir[0];
ginsum -= sir[1];
binsum -= sir[2];
ainsum -= sir[3];
yi += w;
}
}
Log.e("pix", w + " " + h + " " + pix.length);
bitmap.setPixels(pix, 0, w, 0, 0, w, h);
return (bitmap);
}
【讨论】：
这对我来说很好用：How to Blur Images Efficiently with Android's RenderScript
public class BlurBuilder {
private static final float BITMAP_SCALE = 0.4f;
private static final float BLUR_RADIUS = 7.5f;
@SuppressLint("NewApi")
public static Bitmap blur(Context context, Bitmap image) {
int width = Math.round(image.getWidth() * BITMAP_SCALE);
int height = Math.round(image.getHeight() * BITMAP_SCALE);
Bitmap inputBitmap = Bitmap.createScaledBitmap(image, width, height,
false);
Bitmap outputBitmap = Bitmap.createBitmap(inputBitmap);
RenderScript rs = RenderScript.create(context);
ScriptIntrinsicBlur theIntrinsic = ScriptIntrinsicBlur.create(rs,
Element.U8_4(rs));
Allocation tmpIn = Allocation.createFromBitmap(rs, inputBitmap);
Allocation tmpOut = Allocation.createFromBitmap(rs, outputBitmap);
theIntrinsic.setRadius(BLUR_RADIUS);
theIntrinsic.setInput(tmpIn);
theIntrinsic.forEach(tmpOut);
tmpOut.copyTo(outputBitmap);
return outputBitmap;
}
}
【讨论】：
来自 Mario Viviani 的博客，可以从 17 Android 版本开始使用此解决方案：
https://plus.google.com/+MarioViviani/posts/fhuzYkji9zz
或
【讨论】：
这适用于所有需要增加ScriptIntrinsicBlur 的半径以获得更硬的高斯模糊的人。
您可以缩小图像并获得相同的结果，而不是将半径设置为超过 25。我写了一个名为GaussianBlur 的类。下面你可以看到如何使用，以及整个类的实现。
用法：
GaussianBlur gaussian = new GaussianBlur(context);
gaussian.setMaxImageSize(60);
gaussian.setRadius(25); //max
Bitmap output = gaussian.render(<your bitmap>,true);
Drawable d = new BitmapDrawable(getResources(),output);
类：
public class GaussianBlur {
private final int DEFAULT_RADIUS = 25;
private final float DEFAULT_MAX_IMAGE_SIZE = 400;
private Context context;
private int radius;
private float maxImageSize;
public GaussianBlur(Context context) {
this.context = context;
setRadius(DEFAULT_RADIUS);
setMaxImageSize(DEFAULT_MAX_IMAGE_SIZE);
}
public Bitmap render(Bitmap bitmap, boolean scaleDown) {
RenderScript rs = RenderScript.create(context);
if (scaleDown) {
bitmap = scaleDown(bitmap);
}
Bitmap output = Bitmap.createBitmap(bitmap.getWidth(), bitmap.getHeight(), Config.ARGB_8888);
Allocation inAlloc = Allocation.createFromBitmap(rs, bitmap, Allocation.MipmapControl.MIPMAP_NONE, Allocation.USAGE_GRAPHICS_TEXTURE);
Allocation outAlloc = Allocation.createFromBitmap(rs, output);
ScriptIntrinsicBlur script = ScriptIntrinsicBlur.create(rs, inAlloc.getElement()); // Element.U8_4(rs));
script.setRadius(getRadius());
script.setInput(inAlloc);
script.forEach(outAlloc);
outAlloc.copyTo(output);
rs.destroy();
return output;
}
public Bitmap scaleDown(Bitmap input) {
float ratio = Math.min((float) getMaxImageSize() / input.getWidth(), (float) getMaxImageSize() / input.getHeight());
int width = Math.round((float) ratio * input.getWidth());
int height = Math.round((float) ratio * input.getHeight());
return Bitmap.createScaledBitmap(input, width, height, true);
}
public int getRadius() {
return radius;
}
public void setRadius(int radius) {
this.radius = radius;
}
public float getMaxImageSize() {
return maxImageSize;
}
public void setMaxImageSize(float maxImageSize) {
this.maxImageSize = maxImageSize;
}
}
【讨论】：
对于那些仍然对 x86 芯片组上的 Renderscript 支持库有问题的人，请查看库创建者的这篇文章。看起来他准备的修复并没有以某种方式进入 Build Tools v20.0.0，因此他提供了手动修复它的文件并简要说明了如何进行修复。
【讨论】：
这段代码非常适合我
Bitmap tempbg = BitmapFactory.decodeResource(getResources(),R.drawable.b1); //Load a background.
Bitmap final_Bitmap = BlurImage(tempbg);
@SuppressLint("NewApi")
Bitmap BlurImage (Bitmap input)
{
try
{
RenderScript rsScript = RenderScript.create(getApplicationContext());
Allocation alloc = Allocation.createFromBitmap(rsScript, input);
ScriptIntrinsicBlur blur = ScriptIntrinsicBlur.create(rsScript, Element.U8_4(rsScript));
blur.setRadius(21);
blur.setInput(alloc);
Bitmap result = Bitmap.createBitmap(input.getWidth(), input.getHeight(), Bitmap.Config.ARGB_8888);
Allocation outAlloc = Allocation.createFromBitmap(rsScript, result);
blur.forEach(outAlloc);
outAlloc.copyTo(result);
rsScript.destroy();
return result;
}
catch (Exception e) {
// TODO: handle exception
return input;
}
}
【讨论】：
Bitmap，所以首先从一个视图中复制位图，然后调用BlurImage(bitmap)。
我们尝试在不同的答案中实现上面提到的 RenderScript 模糊。我们被限制使用 v8 RenderScript 版本，这给我们带来了很多麻烦。
我想分享我们肮脏的纯 Java 版本，它很慢，应该在单独的线程上完成，如果可能，在使用之前完成，因此会持续存在。
private final Paint mPaint = new Paint();
public Bitmap blur(final String pathToBitmap) {
final BitmapFactory.Options options = new BitmapFactory.Options();
final Bitmap normalOne = BitmapFactory.decodeFile(pathToBitmap, options);
final Bitmap resultBitmap = Bitmap.createBitmap(options.outWidth, options.outHeight, Bitmap.Config.ARGB_8888);
Canvas canvas = new Canvas(resultBitmap);
mPaint.setAlpha(180);
canvas.drawBitmap(normalOne, 0, 0, mPaint);
int blurRadius = 12;
for (int row = -blurRadius; row < blurRadius; row += 2) {
for (int col = -blurRadius; col < blurRadius; col += 2) {
if (col * col + row * row <= blurRadius * blurRadius) {
mPaint.setAlpha((blurRadius * blurRadius) / ((col * col + row * row) + 1) * 2);
canvas.drawBitmap(normalOne, row, col, mPaint);
}
}
}
normalOne.recycle();
return resultBitmap;
}
此解决方案远非完美，但基于以下事实创建了合理的模糊效果，即在几乎不透明的“锐利”版本之上绘制同一图像的高度透明版本。 alpha 取决于到原点的距离。
您可以根据需要调整一些“神奇数字”。 我只是想为所有对 RenderScript v8 支持版本有问题的人分享这个“解决方案”。
【讨论】：
Nicolas POMEPUY 的建议。我认为这个链接会有所帮助：Blur effect for Android design
github的示例项目
@TargetApi(Build.VERSION_CODES.JELLY_BEAN_MR1)
private static Bitmap fastblur16(Bitmap source, int radius, Context ctx) {
Bitmap bitmap = source.copy(source.getConfig(), true);
RenderScript rs = RenderScript.create(ctx);
Allocation input = Allocation.createFromBitmap(rs, source, Allocation.MipmapControl.MIPMAP_NONE, Allocation.USAGE_SCRIPT);
Allocation output = Allocation.createTyped(rs, input.getType());
ScriptIntrinsicBlur script = ScriptIntrinsicBlur.create(rs, Element.U8_4(rs));
script.setRadius(radius);
script.setInput(input);
script.forEach(output);
output.copyTo(bitmap);
return bitmap;
}
【讨论】：
编辑（2014 年 4 月）：这是一个问题/答案页面，看起来仍然获得了很多点击。我知道我总是为这篇文章获得支持。但是，如果您正在阅读本文，您需要意识到此处发布的答案（我的答案和已接受的答案）都已过时。如果您想实现高效模糊今天、you should use RenderScript 而不是 NDK 或 Java。 RenderScript 在 Android 2.2+ 上运行（使用 Android Support Library），所以没有理由不使用它。
下面是旧答案，但要小心，因为它已经过时了。
对于未来² Google 员工，这是我从 Yahel 的 Quasimondo 算法端口移植而来的算法，但使用的是 NDK。当然，这是基于 Yahel 的回答。但这是运行本机 C 代码，因此速度更快。快多了。比如，快 40 倍。
我发现使用 NDK 是应该在 Android 上完成所有图像处理的方式......起初实现有点烦人（阅读关于使用 JNI 和 NDK here 的精彩教程），但要好得多，并且很多事情都是近乎实时的。
作为参考，使用 Yahel 的 Java 函数，模糊半径为 10 的 480x532 像素图像需要 10 秒。但使用原生 C 版本需要 250 毫秒。而且我很确定它仍然可以进一步优化......我只是对java代码做了一个愚蠢的转换，可能有一些可以缩短的操作，不想花太多时间重构整个事情。
#include <jni.h>
#include <string.h>
#include <math.h>
#include <stdio.h>
#include <android/log.h>
#include <android/bitmap.h>
#define LOG_TAG "libbitmaputils"
#define LOGI(...) __android_log_print(ANDROID_LOG_INFO,LOG_TAG,__VA_ARGS__)
#define LOGE(...) __android_log_print(ANDROID_LOG_ERROR,LOG_TAG,__VA_ARGS__)
typedef struct {
uint8_t red;
uint8_t green;
uint8_t blue;
uint8_t alpha;
} rgba;
JNIEXPORT void JNICALL Java_com_insert_your_package_ClassName_functionToBlur(JNIEnv* env, jobject obj, jobject bitmapIn, jobject bitmapOut, jint radius) {
LOGI("Blurring bitmap...");
// Properties
AndroidBitmapInfo infoIn;
void* pixelsIn;
AndroidBitmapInfo infoOut;
void* pixelsOut;
int ret;
// Get image info
if ((ret = AndroidBitmap_getInfo(env, bitmapIn, &infoIn)) < 0 || (ret = AndroidBitmap_getInfo(env, bitmapOut, &infoOut)) < 0) {
LOGE("AndroidBitmap_getInfo() failed ! error=%d", ret);
return;
}
// Check image
if (infoIn.format != ANDROID_BITMAP_FORMAT_RGBA_8888 || infoOut.format != ANDROID_BITMAP_FORMAT_RGBA_8888) {
LOGE("Bitmap format is not RGBA_8888!");
LOGE("==> %d %d", infoIn.format, infoOut.format);
return;
}
// Lock all images
if ((ret = AndroidBitmap_lockPixels(env, bitmapIn, &pixelsIn)) < 0 || (ret = AndroidBitmap_lockPixels(env, bitmapOut, &pixelsOut)) < 0) {
LOGE("AndroidBitmap_lockPixels() failed ! error=%d", ret);
}
int h = infoIn.height;
int w = infoIn.width;
LOGI("Image size is: %i %i", w, h);
rgba* input = (rgba*) pixelsIn;
rgba* output = (rgba*) pixelsOut;
int wm = w - 1;
int hm = h - 1;
int wh = w * h;
int whMax = max(w, h);
int div = radius + radius + 1;
int r[wh];
int g[wh];
int b[wh];
int rsum, gsum, bsum, x, y, i, yp, yi, yw;
rgba p;
int vmin[whMax];
int divsum = (div + 1) >> 1;
divsum *= divsum;
int dv[256 * divsum];
for (i = 0; i < 256 * divsum; i++) {
dv[i] = (i / divsum);
}
yw = yi = 0;
int stack[div][3];
int stackpointer;
int stackstart;
int rbs;
int ir;
int ip;
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 = input[yi + min(wm, max(i, 0))];
ir = i + radius; // same as sir
stack[ir][0] = p.red;
stack[ir][1] = p.green;
stack[ir][2] = p.blue;
rbs = r1 - abs(i);
rsum += stack[ir][0] * rbs;
gsum += stack[ir][1] * rbs;
bsum += stack[ir][2] * rbs;
if (i > 0) {
rinsum += stack[ir][0];
ginsum += stack[ir][1];
binsum += stack[ir][2];
} else {
routsum += stack[ir][0];
goutsum += stack[ir][1];
boutsum += stack[ir][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;
ir = stackstart % div; // same as sir
routsum -= stack[ir][0];
goutsum -= stack[ir][1];
boutsum -= stack[ir][2];
if (y == 0) {
vmin[x] = min(x + radius + 1, wm);
}
p = input[yw + vmin[x]];
stack[ir][0] = p.red;
stack[ir][1] = p.green;
stack[ir][2] = p.blue;
rinsum += stack[ir][0];
ginsum += stack[ir][1];
binsum += stack[ir][2];
rsum += rinsum;
gsum += ginsum;
bsum += binsum;
stackpointer = (stackpointer + 1) % div;
ir = (stackpointer) % div; // same as sir
routsum += stack[ir][0];
goutsum += stack[ir][1];
boutsum += stack[ir][2];
rinsum -= stack[ir][0];
ginsum -= stack[ir][1];
binsum -= stack[ir][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 = max(0, yp) + x;
ir = i + radius; // same as sir
stack[ir][0] = r[yi];
stack[ir][1] = g[yi];
stack[ir][2] = b[yi];
rbs = r1 - abs(i);
rsum += r[yi] * rbs;
gsum += g[yi] * rbs;
bsum += b[yi] * rbs;
if (i > 0) {
rinsum += stack[ir][0];
ginsum += stack[ir][1];
binsum += stack[ir][2];
} else {
routsum += stack[ir][0];
goutsum += stack[ir][1];
boutsum += stack[ir][2];
}
if (i < hm) {
yp += w;
}
}
yi = x;
stackpointer = radius;
for (y = 0; y < h; y++) {
output[yi].red = dv[rsum];
output[yi].green = dv[gsum];
output[yi].blue = dv[bsum];
rsum -= routsum;
gsum -= goutsum;
bsum -= boutsum;
stackstart = stackpointer - radius + div;
ir = stackstart % div; // same as sir
routsum -= stack[ir][0];
goutsum -= stack[ir][1];
boutsum -= stack[ir][2];
if (x == 0) vmin[y] = min(y + r1, hm) * w;
ip = x + vmin[y];
stack[ir][0] = r[ip];
stack[ir][1] = g[ip];
stack[ir][2] = b[ip];
rinsum += stack[ir][0];
ginsum += stack[ir][1];
binsum += stack[ir][2];
rsum += rinsum;
gsum += ginsum;
bsum += binsum;
stackpointer = (stackpointer + 1) % div;
ir = stackpointer; // same as sir
routsum += stack[ir][0];
goutsum += stack[ir][1];
boutsum += stack[ir][2];
rinsum -= stack[ir][0];
ginsum -= stack[ir][1];
binsum -= stack[ir][2];
yi += w;
}
}
// Unlocks everything
AndroidBitmap_unlockPixels(env, bitmapIn);
AndroidBitmap_unlockPixels(env, bitmapOut);
LOGI ("Bitmap blurred.");
}
int min(int a, int b) {
return a > b ? b : a;
}
int max(int a, int b) {
return a > b ? a : b;
}
然后像这样使用它（考虑一个名为 com.insert.your.package.ClassName 的类和一个名为 functionToBlur 的本机函数，如上面的代码所述）：
// Create a copy
Bitmap bitmapOut = bitmapIn.copy(Bitmap.Config.ARGB_8888, true);
// Blur the copy
functionToBlur(bitmapIn, bitmapOut, __radius);
它需要一个 RGB_8888 位图！
要使用 RGB_565 位图，请在传递参数之前创建一个转换后的副本 (yuck)，或者更改函数以使用新的 rgb565 类型而不是 rgba：
typedef struct {
uint16_t byte0;
} rgb565;
问题是，如果您这样做，您将无法再读取像素的.red、.green 和.blue，您需要正确读取字节，呵呵。当我以前需要它时，我这样做了：
r = (pixels[x].byte0 & 0xF800) >> 8;
g = (pixels[x].byte0 & 0x07E0) >> 3;
b = (pixels[x].byte0 & 0x001F) << 3;
但可能有一些不那么愚蠢的方法。恐怕我不是一个低级 C 编码器。
【讨论】：
r[wh]、g[wh]和b[wh]的类型更改为uint8_t。
pastebin.com
您现在可以使用 RenderScript 库中的 ScriptIntrinsicBlur 快速模糊。 Here 是如何访问 RenderScript API。以下是我为模糊视图和位图制作的一个类：
public class BlurBuilder {
private static final float BITMAP_SCALE = 0.4f;
private static final float BLUR_RADIUS = 7.5f;
public static Bitmap blur(View v) {
return blur(v.getContext(), getScreenshot(v));
}
public static Bitmap blur(Context ctx, Bitmap image) {
int width = Math.round(image.getWidth() * BITMAP_SCALE);
int height = Math.round(image.getHeight() * BITMAP_SCALE);
Bitmap inputBitmap = Bitmap.createScaledBitmap(image, width, height, false);
Bitmap outputBitmap = Bitmap.createBitmap(inputBitmap);
RenderScript rs = RenderScript.create(ctx);
ScriptIntrinsicBlur theIntrinsic = ScriptIntrinsicBlur.create(rs, Element.U8_4(rs));
Allocation tmpIn = Allocation.createFromBitmap(rs, inputBitmap);
Allocation tmpOut = Allocation.createFromBitmap(rs, outputBitmap);
theIntrinsic.setRadius(BLUR_RADIUS);
theIntrinsic.setInput(tmpIn);
theIntrinsic.forEach(tmpOut);
tmpOut.copyTo(outputBitmap);
return outputBitmap;
}
private static Bitmap getScreenshot(View v) {
Bitmap b = Bitmap.createBitmap(v.getWidth(), v.getHeight(), Bitmap.Config.ARGB_8888);
Canvas c = new Canvas(b);
v.draw(c);
return b;
}
}
【讨论】：
onCreate 中的观看次数。我们应该在短暂的延迟后执行此操作。
【讨论】：
对于选择 NDK 方法的未来 Google 员工 - 我发现提到的 stackblur 算法是可靠的。我在这里找到了不依赖于 SSE 的 C++ 实现 - http://www.antigrain.com/__code/include/agg_blur.h.html#stack_blur_rgba32 其中包含一些使用静态表的优化，例如：
static unsigned short const stackblur_mul[255] =
{
512,512,456,512,328,456,335,512,405,328,271,456,388,335,292,512,
454,405,364,328,298,271,496,456,420,388,360,335,312,292,273,512,
482,454,428,405,383,364,345,328,312,298,284,271,259,496,475,456,
437,420,404,388,374,360,347,335,323,312,302,292,282,273,265,512,
497,482,468,454,441,428,417,405,394,383,373,364,354,345,337,328,
320,312,305,298,291,284,278,271,265,259,507,496,485,475,465,456,
446,437,428,420,412,404,396,388,381,374,367,360,354,347,341,335,
329,323,318,312,307,302,297,292,287,282,278,273,269,265,261,512,
505,497,489,482,475,468,461,454,447,441,435,428,422,417,411,405,
399,394,389,383,378,373,368,364,359,354,350,345,341,337,332,328,
324,320,316,312,309,305,301,298,294,291,287,284,281,278,274,271,
268,265,262,259,257,507,501,496,491,485,480,475,470,465,460,456,
451,446,442,437,433,428,424,420,416,412,408,404,400,396,392,388,
385,381,377,374,370,367,363,360,357,354,350,347,344,341,338,335,
332,329,326,323,320,318,315,312,310,307,304,302,299,297,294,292,
289,287,285,282,280,278,275,273,271,269,267,265,263,261,259
};
static unsigned char const stackblur_shr[255] =
{
9, 11, 12, 13, 13, 14, 14, 15, 15, 15, 15, 16, 16, 16, 16, 17,
17, 17, 17, 17, 17, 17, 18, 18, 18, 18, 18, 18, 18, 18, 18, 19,
19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 20, 20, 20,
20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 21,
21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21,
21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 22, 22, 22, 22, 22, 22,
22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22,
22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 23,
23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23,
23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23,
23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23,
23, 23, 23, 23, 23, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24
};
我对多核系统的 stackblur 算法进行了修改 - 可以在这里找到 http://vitiy.info/stackblur-algorithm-multi-threaded-blur-for-cpp/ 随着越来越多的设备具有 4 个内核 - 优化带来了 4 倍的速度优势。
【讨论】：
这是在黑暗中拍摄的，但您可以尝试缩小图像，然后再次放大。这可以通过Bitmap.createScaledBitmap(Bitmap src, int dstWidth, int dstHeight, boolean filter) 完成。确保并将过滤器参数设置为 true。它将以本机代码运行，因此可能会更快。
【讨论】：