目前在我正在开发的Android应用程序中,我循环遍历图像的像素以模糊它。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,并且模糊效果非常快(例如5秒),因此他们必须使用不同的模糊方法。
除了循环像素之外,任何人都知道更快的方法吗?
答案 0 :(得分:295)
对于未来的Google员工,这是我从Quasimondo移植的算法。它是盒子模糊和高斯模糊之间的混合,非常漂亮也很快。
遇到ArrayIndexOutOfBoundsException问题的人的更新:评论中的@anthonycr提供了以下信息:
我发现通过用StrictMath.abs或其他方法替换Math.abs abs实现,崩溃不会发生。
/**
* 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);
}
答案 1 :(得分:250)
with Showcase/Benchmark App和Source on Github。 另请查看我目前正在处理的Blur框架:Dali。
经过大量实验后,我现在可以安全地为您提供一些可靠的建议,让您在使用Android框架时在Android中的生活更轻松。
永远不要使用完整大小的位图。图像越大,需要模糊得越多,模糊半径也越大,通常,模糊半径越大,算法越慢。
final BitmapFactory.Options options = new BitmapFactory.Options();
options.inSampleSize = 8;
Bitmap blurTemplate = BitmapFactory.decodeResource(getResources(), R.drawable.myImage, options);
这将使用inSampleSize 8加载位图,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,我认为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,而模糊仅花费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fastes处理设备(GPU,ISP等)等),还有v8 support library for it making it compatible down to 2.2。至少在理论上,通过我自己的测试和来自其他开发者的报告,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,即使有更高的sdk lvl(例如我有使用4.1 Nexus S时遇到麻烦,所以要小心并在很多设备上进行测试。这是一个简单的例子,可以让你开始
//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);
使用Gradle支持的v8支持(由Google "because they include the latest improvements"特别推荐)时,您只需need to add 2 lines to your build script并使用android.support.v8.renderscript
和当前的构建工具(updated syntax for android gradle plugin v14+)
android {
...
defaultConfig {
...
renderscriptTargetApi 19
renderscriptSupportModeEnabled true
}
}
Nexus 5上的简单基准 - 将RenderScript与其他不同的java和renderscript实现进行比较:
不同pic尺寸下每个模糊的平均运行时间
每秒可以模糊的百万像素
每个值是250轮的平均值。 RS_GAUSS_FAST是ScriptIntrinsicBlur
(并且几乎总是最快),其他以RS_开头的主要是具有简单内核的卷积实现。 The details of the algorithms can be found here。这不仅仅是模糊,但很大一部分是测量的垃圾收集。这可以在这里看到(ScriptIntrinsicBlur
在100x100图像上,大约500轮)
尖峰是gc。
您可以自行检查,基准应用程序位于Playstore中:BlurBenchmark
如果您需要多次模糊以进行实时模糊或类似操作,并且您的内存允许它不会多次从drawable中加载位图,而是保持&#34;缓存&#34;在成员变量中。在这种情况下,总是尝试使用相同的变量,以尽量减少垃圾收集。
同时从文件或drawable中检出新的"inBitmap" option when loading,它将重用位图内存并节省垃圾收集时间。
简单而天真的方法就是使用2个图像视图,一个模糊,alpha淡化它们。但是如果你想要一个更加复杂的外观,从锐利到模糊,那么请查看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扩展的帧,并将它们用作动画中的关键帧,看起来非常流畅
答案 2 :(得分:75)
这是在黑暗中拍摄的照片,但您可以尝试缩小图像然后再将其放大。这可以使用Bitmap.createScaledBitmap(Bitmap src, int dstWidth, int dstHeight, boolean filter)
完成。确保并将filter参数设置为true。它将以本机代码运行,因此可能更快。
答案 3 :(得分:53)
编辑(2014年4月):这是一个问题/答案页面,看起来仍然有很多点击。我知道我总是对这篇文章赞不绝口。但是如果你正在阅读这篇文章,你需要意识到这里发布的答案(我的和已接受的答案都已过时)。如果你想实现有效的模糊今天,you should use RenderScript而不是NDK或Java。 RenderScript在Android 2.2+上运行(使用Android Support Library),因此没有理由不使用它。
旧的答案如下,但要注意它已经过时了。
对于未来的Google员工,这里是我从Yahel的Quasimondo算法端口移植的算法,但是使用了NDK。当然,这是基于Yahel的答案。但这是运行本机C代码,所以它更快。快多了。比如,快40倍。
我发现使用NDK是如何在Android上完成所有图像处理的......首先实现它有点烦人(阅读使用JNI和NDK here的精彩教程),但更好,并且接近实时的很多事情。
作为参考,使用Yahel的Java函数,模糊半径为10的模糊480x532像素需要10秒钟。但使用原生C版本需要250ms。而且我很确定它仍然可以进一步优化...我只是对java代码进行了愚蠢的转换,可能有一些操作可以缩短,不想花太多时间重构整个事情。 / p>
#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(yuck)之前创建转换后的副本,或者将函数更改为使用新的rgb565
类型而不是rgba
:
typedef struct {
uint16_t byte0;
} rgb565;
问题在于,如果你这样做,你就无法再阅读像素的.red
,.green
和.blue
,你需要正确读取字节,呃。当我以前需要时,我这样做了:
r = (pixels[x].byte0 & 0xF800) >> 8;
g = (pixels[x].byte0 & 0x07E0) >> 3;
b = (pixels[x].byte0 & 0x001F) << 3;
但是这样做可能不那么愚蠢。我恐怕不是一个低级别的C编码员。
答案 4 :(得分:14)
此代码非常适合我
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;
}
}
答案 5 :(得分:12)
现在,您可以使用RenderScript库中的ScriptIntrinsicBlur快速模糊。 Here是访问RenderScript API的方法。以下是我用来模糊视图和位图的课程:
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;
}
}
答案 6 :(得分:7)
这对我来说很好: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;
}
}
答案 7 :(得分:4)
答案 8 :(得分:4)
这适用于所有需要增加ScriptIntrinsicBlur
半径以获得更高硬度模糊的人。
您可以缩小图像并获得相同的结果,而不是将半径设置为大于25。我写了一个名为GaussianBlur
的课程。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);
类别:
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;
}
}
答案 9 :(得分:4)
感谢@Yahel的代码。 使用 Alpha渠道模糊支持发布相同的方法,因为我花了一些时间使其正常工作,这样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);
}
答案 10 :(得分:4)
我以前用过..
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;
}
答案 11 :(得分:2)
对于选择NDK方法的未来Google员工 - 我找到了可靠的stackblur算法。我发现C ++实现不依赖于SSE - http://www.antigrain.com/__code/include/agg_blur.h.html#stack_blur_rgba32包含一些使用静态表的优化,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
};
我为多核系统修改了stackblur算法 - 可以在http://vitiy.info/stackblur-algorithm-multi-threaded-blur-for-cpp/找到它 随着越来越多的设备拥有4个内核 - 优化可以提供4倍的速度优势。
答案 12 :(得分:1)
Nicolas POMEPUY的建议。我认为此链接会有所帮助:Blur effect for Android design
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;
}
答案 13 :(得分:1)
我们尝试在不同的答案中实现如上所述的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。
我想分享我们的脏Java版本,这个版本很慢,应该在一个单独的线程上完成,如果可能的话,在使用之前,因此保持不变。
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;
}
这个解决方案远非完美,但基于这样一个事实创造了一种合理的模糊效果,即在几乎不透明的&#34;锐利&#34;之上绘制相同图像的高度透明版本。版。 alpha取决于到原点的距离。
你可以调整一些魔法数字&#34;满足您的需求。 我只是想分享那个&#34;解决方案&#34;对于每个遇到v8支持版RenderScript问题的人。
答案 14 :(得分:0)
对于那些仍然在x86芯片组上遇到Renderscript支持库问题的人,请查看该库的创建者的这篇文章。看起来他准备的修复程序并没有以某种方式使它成为Build Tools v20.0.0,因此他提供了手动修复它的文件以及如何操作的简要说明。
答案 15 :(得分:0)
答案 16 :(得分:0)
这是使用RenderScript的实时模糊叠加,这似乎足够快。
答案 17 :(得分:0)
我发现降低对比度,亮度和饱和度会使模糊图像变得更加漂亮所以我将各种方法与堆栈溢出结合起来并制作了Blur Class来处理模糊图像,改变亮度,饱和度,对比度和模糊图像的大小。它还可以将图像从可绘制转换为位图,反之亦然。
答案 18 :(得分:0)
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()
}
}