移动开发|Android图片高斯模糊的一些方法移动开发|java

高斯模糊高斯模糊就是将指定像素变换为其与周边像素加权平均后的值，权重就是高斯分布函数计算出来的值。
一种实现点击打开链接<-这里是一片关于高斯模糊算法的介绍，我们需要首先根据高斯分布函数计算权重值，为了提高效率我们采用一维高斯分布函数，然后处理图像的时候在横向和纵向进行两次计算得到结果。下面是一种实现

[java]view plain copy print ?

public static void gaussBlur(int[] data, int width, int height, int radius,
float sigma) {
float pa = (float) (1 / (Math.sqrt(2 * Math.PI) * sigma));
float pb = -1.0f / (2 * sigma * sigma);
// generate the Gauss Matrix
float[] gaussMatrix = new float[radius * 2 + 1];
float gaussSum = 0f;
for (int i = 0, x = -radius; x <= radius; ++x, ++i) {
float g = (float) (pa * Math.exp(pb * x * x));
gaussMatrix[i] = g;
gaussSum += g;
}
for (int i = 0, length = gaussMatrix.length; i < length; ++i) {
gaussMatrix[i] /= gaussSum;
}
// x direction
for (int y = 0; y < height; ++y) {
for (int x = 0; x < width; ++x) {
float r = 0, g = 0, b = 0;
gaussSum = 0;
for (int j = -radius; j <= radius; ++j) {
int k = x + j;
if (k >= 0 && k < width) {
int index = y * width + k;
int color = data[index];
int cr = (color & 0x00ff0000) >> 16;
int cg = (color & 0x0000ff00) >> 8;
int cb = (color & 0x000000ff);
r += cr * gaussMatrix[j + radius];
g += cg * gaussMatrix[j + radius];
b += cb * gaussMatrix[j + radius];
gaussSum += gaussMatrix[j + radius];
}
}
int index = y * width + x;
int cr = (int) (r / gaussSum);
int cg = (int) (g / gaussSum);
int cb = (int) (b / gaussSum);
data[index] = cr << 16 | cg << 8 | cb | 0xff000000;
}
}
// y direction
for (int x = 0; x < width; ++x) {
for (int y = 0; y < height; ++y) {
float r = 0, g = 0, b = 0;
gaussSum = 0;
for (int j = -radius; j <= radius; ++j) {
int k = y + j;
if (k >= 0 && k < height) {
int index = k * width + x;
int color = data[index];
int cr = (color & 0x00ff0000) >> 16;
int cg = (color & 0x0000ff00) >> 8;
int cb = (color & 0x000000ff);
r += cr * gaussMatrix[j + radius];
g += cg * gaussMatrix[j + radius];
b += cb * gaussMatrix[j + radius];
gaussSum += gaussMatrix[j + radius];
}
}
int index = y * width + x;
int cr = (int) (r / gaussSum);
int cg = (int) (g / gaussSum);
int cb = (int) (b / gaussSum);
data[index] = cr << 16 | cg << 8 | cb | 0xff000000;
}
}
}

实际测试会发现这种计算方式是很耗时间的，而且模糊半径越大，从原理也可以看到计算量是平方增长的，所以计算时间也越长。

RenderScript RenderScript是Android在API 11之后加入的，用于高效的图片处理，包括模糊、混合、矩阵卷积计算等，代码示例如下

[java]view plain copy print ?

public Bitmap blurBitmap(Bitmap bitmap){
//Let's create an empty bitmap with the same size of the bitmap we want to blur
Bitmap outBitmap = Bitmap.createBitmap(bitmap.getWidth(), bitmap.getHeight(), Config.ARGB_8888);
//Instantiate a new Renderscript
RenderScript rs = RenderScript.create(getApplicationContext());
//Create an Intrinsic Blur Script using the Renderscript
ScriptIntrinsicBlur blurScript = ScriptIntrinsicBlur.create(rs, Element.U8_4(rs));
//Create the Allocations (in/out) with the Renderscript and the in/out bitmaps
Allocation allIn = Allocation.createFromBitmap(rs, bitmap);
Allocation allOut = Allocation.createFromBitmap(rs, outBitmap);
//Set the radius of the blur
blurScript.setRadius(25.f);
//Perform the Renderscript
blurScript.setInput(allIn);
blurScript.forEach(allOut);
//Copy the final bitmap created by the out Allocation to the outBitmap
allOut.copyTo(outBitmap);
//recycle the original bitmap
bitmap.recycle();
//After finishing everything, we destroy the Renderscript.
rs.destroy();
return outBitmap;
}

（示例来源 https://gist.github.com/Mariuxtheone/903c35b4927c0df18cf8）

FastBlur [java]view plain copy print ?

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);
}

这里的方法也可以实现高斯模糊的效果，但使用了特殊的算法，比第一种可以快很多，但比起RenderScript还是慢一些（示例来源Android高级模糊技术）实现YAHOO天气的动态模糊效果 YAHOO天气中的背景会随着手指上滑模糊程度加深，实际使用中发现怎么都达不到那样流畅的效果，因为手势刷新的速度很快，每一帧都去重新模糊计算一遍，还是会有延迟，造成页面卡顿。后来在一次偶然的开发中发现其实不需要每一帧都重新去模糊一遍，而是将图片最大程度模糊一次，之后和原图叠加，通过改变叠加的模糊图片的alpha值来达到不同程度的模糊效果。下面是一个例子，可以看到随着模糊图片alpha值的变化，叠加后产生不同程度的模糊效果。

文章图片

随滑动变换alpha值的代码如下

[java]view plain copy print ?

mBlurImage.setOnTouchListener(new OnTouchListener() {
private float mLastY;
@Override
public boolean onTouch(View v, MotionEvent event) {
switch (event.getAction()) {
case MotionEvent.ACTION_DOWN:
mLastY = event.getY();
break;
case MotionEvent.ACTION_MOVE:
float y = event.getY();
float alphaDelt = (y - mLastY) / 1000;
float alpha = mBlurImage.getAlpha() + alphaDelt;
if (alpha > 1.0) {
alpha = 1.0f;
} else if (alpha < 0.0) {
alpha = 0.0f;
}
mTextView.setText(String.valueOf(alpha));
mBlurImage.setAlpha(alpha);
break;
case MotionEvent.ACTION_UP:
break;
}
return true;
}
});

示例代码下载 http://download.csdn.net/detail/xu_fu/7628139
来自 : http://blog.csdn.net/xu_fu/article/details/23131241
【移动开发|Android图片高斯模糊的一些方法】转载于:https://www.cnblogs.com/MMLoveMeMM/articles/4850305.html