Android 高斯模糊效果从319ms到3ms的优化实现

之前做过高斯模糊的的效果,不过依赖一个三方库,今天看到了一篇文章,一个类文件就能解决,感觉窃喜,分享给大家。

三方库android-stackblur:https://github.com/kikoso/android-stackblur

使用:

Glide.with(getActivity()).load(mUser.avatarUrl).asBitmap().into(new SimpleTarget() {
                                @Override
                                public void onResourceReady(Bitmap resource, GlideAnimationsuper Bitmap> glideAnimation) {
                                    if(resource != null) {
                                        StackBlurManager stackBlurManager = new StackBlurManager(resource);
                                        Bitmap bitmap = stackBlurManager.process(20);
                                        mUserContainer.setBackground(new BitmapDrawable(getResources(),bitmap));
                                    }
                                }
                            });

使用简单方便。

正文开始。

我要做的效果就是自定义image大小,自定义高斯模糊的区域,这样才算我要的效果。

先上图分别是优化前和优化后的,大家可想这个优化的作用多么巨大,我直接把这个效果的显示耗时在界面绘制出来了,下面图片中的单位打错了额,是ms。


3ms VS 209ms
Android 高斯模糊效果从319ms到3ms的优化实现_第1张图片

Android 高斯模糊效果从319ms到3ms的优化实现_第2张图片


4ms VS 197ms
Android 高斯模糊效果从319ms到3ms的优化实现_第3张图片

Android 高斯模糊效果从319ms到3ms的优化实现_第4张图片

说下实现吧,那个算法我就没有怎么研究了,直接是个算法类,直接把要模糊的Bitmap传进去返回的就是模糊后的。代码如下:

public class FastBlur {

    public static Bitmap doBlur(Bitmap sentBitmap, int radius, boolean canReuseInBitmap) {

        // Stack Blur v1.0 from
        // http://www.quasimondo.com/StackBlurForCanvas/StackBlurDemo.html
        //
        // Java Author: Mario Klingemann 
        // http://incubator.quasimondo.com
        // created Feburary 29, 2004
        // Android port : Yahel Bouaziz 
        // 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 

        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 (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);
    }
}

接下来就是在代码中去用了。

先上优化前的方法:因为下面红字部分那句的代码把我坑惨了,原来用了matrix,在新建的时候还是要用matrix前的大小,我也是晕的不要不要的了。。。

还有注意要根据演示区域的大小,缩放bitmap的大小后再剪裁,再模糊。
这里顺便熟悉了canvas,drawBitmap,放大缩小的一些方法

public void test(View v) {

        Bitmap srcbitmap = BitmapFactory.decodeResource(getResources(),
                R.drawable.meitu);
        long t1 = System.currentTimeMillis();
        imageView.setBackground(new BitmapDrawable(getResources(), srcbitmap));// 设置大背景

        Bitmap backBitmap = Bitmap.createBitmap(textView.getMeasuredWidth(),// 设置需高斯模糊的背景
                textView.getMeasuredHeight(), Config.RGB_565);

        float f1 = (float) imageView.getMeasuredWidth()
                / (float) srcbitmap.getWidth();
        float f2 = (float) imageView.getMeasuredHeight()
                / (float) srcbitmap.getHeight();
        Matrix matrix = new Matrix();
        matrix.postScale(f1, f2);
        Bitmap desBitmap = Bitmap.createBitmap(srcbitmap, 0, 0,
                srcbitmap.getWidth(), srcbitmap.getHeight(), matrix, true); //因为作为背景的bmp已经缩放,那么需要剪裁的bmp也要缩放----------这里3/4参数是坑

        Bitmap lastBitmap = Bitmap.createBitmap(desBitmap, textView.getLeft(),
                textView.getTop(), textView.getMeasuredWidth(),
                textView.getMeasuredHeight()); // 根据模糊的区域剪裁

        Canvas canvas = new Canvas(backBitmap);
        canvas.drawBitmap(lastBitmap, 0, 0, new Paint());
        backBitmap = FastBlur.doBlur(backBitmap, (int) 20, true);
        textView.setBackground(new BitmapDrawable(getResources(), backBitmap));
        long t2 = System.currentTimeMillis();

        textView.setText((t2 - t1) + "S");// 319S

    }

下面是优化后的方法:
其实现原理是反正效果也是模糊的,先把图片弄小模糊,再把模糊放大,这样就减少了算法的复杂度

public void test2(View v) {

        int rad = 8;

        Bitmap srcbitmap = BitmapFactory.decodeResource(getResources(),
                R.drawable.meitu);
        long t1 = System.currentTimeMillis();
        imageView.setBackground(new BitmapDrawable(getResources(), srcbitmap));// 设置大背景

        Bitmap backBitmap = Bitmap.createBitmap(textView.getMeasuredWidth()/rad,// 设置需高斯模糊的背景
                textView.getMeasuredHeight()/rad, Config.RGB_565);

        float f1 = (float) imageView.getMeasuredWidth()
                / (float) srcbitmap.getWidth();
        float f2 = (float) imageView.getMeasuredHeight()
                / (float) srcbitmap.getHeight();
        Matrix matrix = new Matrix();
        matrix.postScale(f1/8, f2/8);
        Bitmap desBitmap = Bitmap.createBitmap(srcbitmap, 0, 0,
                srcbitmap.getWidth(), srcbitmap.getHeight(), matrix, true); // 因为作为背景的bmp已经缩放,那么需要剪裁的bmp也要缩放----------这里3/4参数是坑

        Bitmap lastBitmap = Bitmap.createBitmap(desBitmap, textView.getLeft()/8,
                textView.getTop()/8, textView.getMeasuredWidth()/8,
                textView.getMeasuredHeight()/8); // 根据模糊的区域剪裁

        Canvas canvas = new Canvas(backBitmap);
        canvas.drawBitmap(lastBitmap, 0, 0, new Paint());
        backBitmap = FastBlur.doBlur(backBitmap, (int) 2, true);
        canvas.scale(1/rad, 1/rad);
        textView.setBackground(new BitmapDrawable(getResources(), backBitmap));
        long t2 = System.currentTimeMillis();

        textView.setText((t2 - t1) + "S");// 2S

    }

摘自:http://blog.csdn.net/scboyhj__/article/details/50273059

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