Android实现图片高斯模糊

最近项目设计上需要用到稍微比较模糊的图片,因此我就去百度搜了一下,处理办法大概就是借助神器PS(花千骨看多了,呵呵)。但是在程序猿的眼里,代码可以实现一切。下面我就来实现一个Android高斯模糊。

高斯模糊:高斯模糊(Gaussian Blur)是美国Adobe图像软件公司开发的一个图像处理软件:Adobe Photoshop(系列)中的一个滤镜,具体的位置在:滤镜—模糊——高斯模糊!高斯模糊的原理中,它是根据高斯曲线调节象素色值,它是有选择地模糊图像。说得直白一点,就是高斯模糊能够把某一点周围的像素色值按高斯曲线统计起来,采用数学上加权平均的计算方法得到这条曲线的色值,最后能够留下人物的轮廓,即曲线.是指当 Adobe Photoshop 将加权平均应用于像素时生成的钟形曲线。 在PS中间,你应该知道所有的颜色不过都是数字,各种模糊不过都是算法。把要模糊的像素色值统计,用数学上加权平均的计算方法(高斯函数)得到色值,,对范围、半径等进行模糊,大致就是高斯模糊。

这个比较官方的解释。

原理:所谓”模糊”,可以理解成每一个像素都取周边像素的平均值。 高斯模糊原理的图解

右图中,2是中间点,周边点都是1。 “中间点”取”周围点”的平均值,就会变成1。在数值上,这是一种”平滑化”。在图形上,就相当于产生”模糊”效果,”中间点”失去细节。 显然,计算平均值时,取值范围越大,”模糊效果”越强烈。

RenderScript类:RenderScript 是Android 平台上的一种类C脚本语言。在我们程序上实现RenderScript 渲染功能。

Android的核心代码:

“` public class Blur {

private static final String TAG = “Blur”;@SuppressLint(“NewApi”)public static Bitmap fastblur(Context context, Bitmap sentBitmap, int radius) {if (VERSION.SDK_INT > 16) {Bitmap bitmap = sentBitmap.copy(sentBitmap.getConfig(), true);final RenderScript rs = RenderScript.create(context);final Allocation input = Allocation.createFromBitmap(rs, sentBitmap, Allocation.MipmapControl.MIPMAP_NONE,Allocation.USAGE_SCRIPT);final Allocation output = Allocation.createTyped(rs, input.getType());final ScriptIntrinsicBlur script = ScriptIntrinsicBlur.create(rs, Element.U8_4(rs));script.setRadius(radius /* e.g. 3.f */);script.setInput(input);script.forEach(output);output.copyTo(bitmap);return bitmap;}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);}

} 实现原理其实就是根据高斯函数来实现的。有兴趣大家可以去研究这个函数。

用法根据构造函数将相应的值传入就可以了。

一定要记得挺身而出,即便帮不了忙,安慰也是最大的支持.

Android实现图片高斯模糊

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