Android图片处理之高斯模糊示例——仿微信朋友圈照片模糊效果

微信朋友圈最近出了一个模糊照片效果,一看之下很有新意。

这里就是仿微信朋友圈的一个图片模糊效果实现。使用了一个开源的FastBlur(高斯模糊——毛玻璃效果)。

实现的方法很简单,只要一句代码即可。

Bitmap bitmap= FastBlur.doBlur(BitmapFactory.decodeResource(getResources(), R.drawable.blur), 10, false);
效果如下:



FastBlur中,没有对代码做注释,这里简单解释下doBlur中三个参数的含义:

第一个:图片资源的bitmap格式;

第二个:模糊程度(权重)——取值范围从0开始的整数,一般不取过大的数。取值如10、15、25等,假如你传值1000,会导致OOM错误;

第三个:是否可复用的bitmap。一般传false即可。因为可复用的bitmap对API的level有要求,level等不符合要求,会导致出错。


看一下FastBlur的源码:

package com.example.blur_csdn;
import android.graphics.Bitmap;

/**
 * Created by paveld on 3/6/14.
 * guss
 */
public class FastBlur {

	public static Bitmap doBlur(Bitmap sentBitmap, int radius,boolean canReuseInBitmap) 
	{
		Bitmap bitmap;
		if (canReuseInBitmap) {
			//可复用视图
			bitmap = sentBitmap;
		} else {
			
			bitmap = sentBitmap.copy(sentBitmap.getConfig(), true);
		}
        /**
         * 权重为0时,原样输出。
         * 源码原来的判断值时radius<1,这里改为以下的radius<0
         * 主要是为了让权重为0时,可输出
         */
		if (radius < 0) {
			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);
	}
}


以上就是实现高斯图片模糊的主要方法。

高斯模糊原理,可

参考:

http://www.zhihu.com/question/32232584

http://baike.baidu.com/link?url=L2-0e-mbxhZ_PFe0GFR3Spb5t82NntthEeKoWd0N6H_6gHPqgKoqZvpN8WK6VHG7rpz41oYQn_fU4caKFkkT9a


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转载自blog.csdn.net/yangzhaomuma/article/details/50618063