Android软件开发之高斯模糊问题

之前看到Android软件中用到和IOS系统类似的模糊效果,自己琢磨着也想做一个,于是在网上搜索了很多的相关资料,发现这篇博客《Android高级模糊技术》写得特别好,所以就开始好好地研究。

等到我把这个功能做到软件上,问题出现了,什么问题呢?

本来是准备用模糊图片来作为软件全屏界面的背景,可是布局显示的模糊图片在右下边缘一直出现黑色的边,不能铺满整个屏幕。一开始以为是模糊的参数需要调整,模糊后的图片变小了,但是把模糊后的图片的height和width打印出来,发没有问题。

后来我想到,实际使用的图片比屏幕的尺寸小一点,而模糊处理的过程之前并没有对图片大小进行调整,导致输出的模糊图片虽然和视图(屏幕)大小一致,但是图片的模糊区域却和原图片相同大小,从而留下了空余的部分——黑色的边缘。于是又写了一个缩放图片的工具类,在模糊处理之前来同步图片和视图(屏幕)的大小,发现问题解决!

FastBlur.java

 该文件是图片模糊的像素处理类,直接放入工程中

package com.kuk.tools;



import android.graphics.Bitmap;



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 <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>



        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);

    }

}
FastBlur

 

PictureZoom.java

此文件是缩放图片类

 1 import android.content.Context;

 2 import android.graphics.Bitmap;

 3 import android.graphics.Matrix;

 4 

 5 /**

 6  * 此类的功能是用来缩放图片

 7  * <p>

 8  * 防止图片大小和屏幕大小不一致,造成模糊处理后会出现图片显示异常

 9  * </p>

10  * @author Macneil.Gu

11  */

12 public class PictureZoom {

13 

14     private Context context;

15 

16     public PictureZoom(Context context) {

17         this.context = context;

18     }

19     

20     /**

21      * 缩放图片至指定的大小

22      * 

23      * @param bitmap Bitmap格式的图片

24      * @param x 指定的宽

25      * @param y 指定的长

26      * @return 缩放后的指定大小图片

27      */

28     public Bitmap Zoom(Bitmap bitmap, float x, float y) {

29         //图片的宽和高

30         int width = bitmap.getWidth();

31         int height = bitmap.getHeight();

32         

33         //原图片和指定图片宽高比(缩放率),指定/原

34         float sx = x / width;

35         float sy = y / height;

36         

37         //缩放图片动作

38         Matrix mtr = new Matrix();

39         mtr.postScale(sx, sy);

40         

41         //创建新的图片

42         Bitmap bm = Bitmap.createBitmap(bitmap, 0, 0, width, height, mtr, true);

43         return bm;

44     }

45 

46 }

 

MainActivity.java

高斯模糊处理函数,这里对原来的函数修改了一点点

 1     /**

 2      * 高斯模糊处理

 3      * <p>

 4      * <code>将图片剪裁成1/8后进行模糊处理,可以大大减少模糊处理的时间,提高代码执行效率</code>

 5      * </p>

 6      * @param bitmap 需要模糊处理的图片

 7      * @param view 显示图片的视图

 8      */

 9     private void blur(Bitmap bitmap, View view) {

10         float scaleFactor = 8;

11         float radius = 2;

12 

13         Bitmap overlay = Bitmap.createBitmap(

14                 (int) (view.getMeasuredWidth() / scaleFactor),

15                 (int) (view.getMeasuredHeight() / scaleFactor),

16                 Bitmap.Config.ARGB_8888);

17 

18         Canvas canvas = new Canvas(overlay);

19         canvas.translate(-view.getLeft() / scaleFactor, -view.getTop()

20                 / scaleFactor);

21         canvas.scale(1 / scaleFactor, 1 / scaleFactor);

22         Paint paint = new Paint();

23         paint.setFlags(Paint.FILTER_BITMAP_FLAG); // 双缓冲机制

24         canvas.drawBitmap(bitmap, 0, 0, paint);

25 

26         overlay = FastBlur.doBlur(overlay, (int) radius, true);

27         view.setBackgroundDrawable(new BitmapDrawable(getResources(), overlay));

28     }

>>原博文的注解:

● scaleFactor提供了需要缩小的等级,在代码中我把bitmap的尺寸缩小到原图的1/8。因为这个bitmap在模糊处理时会先被缩小然后再放大,所以在我的模糊算法中就不用radius这个参数了,所以把它设成2。

● 接着需要创建bitmap,这个bitmap比最后需要的小八倍。

● 请注意我给Paint提供了FILTER_BITMAP_FLAG标示,这样的话在处理bitmap缩放的时候,就可以达到双缓冲的效果,模糊处理的过程就更加顺畅了。

● 接下来和之前一样进行模糊处理操作,这次的图片小了很多,幅度也降低了很多,所以模糊过程非常快。

● 把模糊处理后的图片作为背景,它会自动进行放大操作的。

 

调用上述的模糊处理函数,对指定图片模糊处理,并显示到布局的ImageView上。

 1  // 获取窗口服务

 2  WindowManager wm = (WindowManager) getSystemService(Context.WINDOW_SERVICE);

 3  

 4  // 缩放图片

 5  PictureZoom pz = new PictureZoom(this);

 6  // 把图片缩放到窗口的长宽

 7  Bitmap mybm = pz.Zoom(bm, wm.getDefaultDisplay().getWidth(), wm.getDefaultDisplay().getHeight()); 

 8 

 9  // 模糊处理,blurImage是ImageView控件,这里是作为背景显示的

10  blur(mybm, blurImage);

 

>>将上述的三个文件放在同一个包下使用,否则需要导入文件使用。如果大家喜欢剖根究底,可以仔细阅读原博文。

原博文出处:Android高级模糊技术

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