Android毛玻璃处理代码(Blur)

　　以下为将bitmap图像处理为毛玻璃效果的图像的工具类：

public class FastBlurUtil {
 
    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);
    }
 
}

　　可以看出，使用方法非常简单，传入待续话的bitmap、虚化程序（一般为8），和是否重用flag。

　　然后，对于大图，往往会出现OOM异常的报错，那是因为当虚化开始时，虚拟机开始不断进行内存回收，包括所有软引用的回收。然后，仍然出现了内存溢出。那就意味着我们只能对小图进行虚化，这样才能防止内存溢出。但我并不想换其他图，那么，我们应该把这张图先进性缩放。

缩放方法：

public static Bitmap createScaledBitmap(Bitmap src, int dstWidth, int dstHeight, boolean filter)

　　第四个输入输入的参数filter，是指缩放边缘效果，filter为true则会得到一个边缘平滑的bitmap，反之，则会得到一个边缘锯齿、pixelrelated的bitmap。这里，我们对图片进行虚化，无所谓边缘效果，所以filter=false。

　　那么，怎么组合运行虚化代码实现大图虚化呢？以下为具体实现代码：

int scaleRatio = 10;
int blurRadius = 8;
Bitmap scaledBitmap = Bitmap.createScaledBitmap(originBitmap,
    originBitmap.getWidth() / scaleRatio,
    originBitmap.getHeight() / scaleRatio,
    false);
Bitmap blurBitmap = FastBlur.doBlur(scaledBitmap, blurRadius, true);
imageView.setScaleType(ImageView.ScaleType.CENTER_CROP);
imageView.setImageBitmap(blurBitmap);

　　如果图片的虚化效果较弱或者并不是很明显，提供增强虚化效果的方法：

1、增大scaleRatio的数值（增大缩放比），使用更小的bitmap去虚化，这样可以得到更好的虚化效果，而且有利于减小内存消耗。

2、增大blurRadius的数值，这样可以提高续话层度，不过会导致cpu更加intensive。

参考资料：实现虚化、bitmap代码地址