[Android]-图片JNI(C++\Java)高斯模糊的实现与比較

前几天一直在弄android上的图片模糊效果的实现!

一直找不到方法,看别人说都是调用JNI,可是JNI这个东西我还真不熟悉啊!

仅仅好从零開始了!这里不讲JNI的平台搭建,仅仅讲JNI的关键代码,详细的项目我会共享出来给大家!

对于JNI下使用C++来模糊图片这个我真的没找到,仅仅好自己写C++的来实现了。

在国外的一个项目中找到了一个”堆栈模糊效果“,原型例如以下:

// Stack Blur v1.0
//
// Author: Mario Klingemann <mario@quasimondo.com>
// http://incubator.quasimondo.com
// created Feburary 29, 2004


// 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>

PImage a;
PImage b;

void setup()
{
  a=loadImage("dog.jpg");
  size(a.width, a.height);
  b=new PImage(a.width, a.height);
  fill(255);
  noStroke();
  frameRate(25);
}

void draw()
{
  System.arraycopy(a.pixels,0,b.pixels,0,a.pixels.length);
  fastblur(b,mouseY/4);
  image(b, 0, 0);
}

void fastblur(PImage img,int radius){

  if (radius<1){
    return;
  }
  int[] pix=img.pixels;
  int w=img.width;
  int h=img.height;
  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[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+min(wm,max(i,0))];
      sir=stack[i+radius];
      sir[0]=(p & 0xff0000)>>16;
      sir[1]=(p & 0x00ff00)>>8;
      sir[2]=(p & 0x0000ff);
      rbs=r1-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]=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=max(0,yp)+x;
     
       sir=stack[i+radius];
      
      sir[0]=r[yi];
      sir[1]=g[yi];
      sir[2]=b[yi];
     
      rbs=r1-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++){
      pix[yi]=0xff000000 | (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]=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;
    }
  }
  
  img.updatePixels();
}

同一时候找到一个借鉴这个所改进后成为Java的代码,详细例如以下:

    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);
    }

借鉴于此我弄了一个C的代码,基本上的总体过程都没有变化,仅仅是改变成了C(C++也可已)的而已:

文件名称:ImageBlur.c

/*************************************************
Copyright:  Copyright QIUJUER 2013.
Author:		Qiujuer
Date:		2014-04-18
Description:实现图片模糊处理
**************************************************/
#include<malloc.h>

#define ABS(a) ((a)<(0)?(-a):(a))
#define MAX(a,b) ((a)>(b)?(a):(b))
#define MIN(a,b) ((a)<(b)?(a):(b))

/*************************************************
Function:		StackBlur(堆栈模糊)
Description:    使用堆栈方式进行图片像素模糊处理
Calls:          malloc
Table Accessed: NULL
Table Updated:	NULL
Input:          像素点集合,图片宽,图片高,模糊半径
Output:         返回模糊后的像素点集合
Return:         返回模糊后的像素点集合
Others:         NULL
*************************************************/
static int* StackBlur(int* pix, int w, int h, int radius) {
	int wm = w - 1;
	int hm = h - 1;
	int wh = w * h;
	int div = radius + radius + 1;

	int *r = (int *)malloc(wh * sizeof(int));
	int *g = (int *)malloc(wh * sizeof(int));
	int *b = (int *)malloc(wh * sizeof(int));
	int rsum, gsum, bsum, x, y, i, p, yp, yi, yw;

	int *vmin = (int *)malloc(MAX(w,h) * sizeof(int));

	int divsum = (div + 1) >> 1;
	divsum *= divsum;
	int *dv = (int *)malloc(256 * divsum * sizeof(int));
	for (i = 0; i < 256 * divsum; i++) {
		dv[i] = (i / divsum);
	}

	yw = yi = 0;

	int(*stack)[3] = (int(*)[3])malloc(div * 3 * sizeof(int));
	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 + (MIN(wm, MAX(i, 0)))];
			sir = stack[i + radius];
			sir[0] = (p & 0xff0000) >> 16;
			sir[1] = (p & 0x00ff00) >> 8;
			sir[2] = (p & 0x0000ff);

			rbs = r1 - 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] = 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 = MAX(0, yp) + x;

			sir = stack[i + radius];

			sir[0] = r[yi];
			sir[1] = g[yi];
			sir[2] = b[yi];

			rbs = r1 - 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] = 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;
		}
	}

	free(r);
	free(g);
	free(b);
	free(vmin);
	free(dv);
	free(stack);
	return(pix);
}
在改为这个的过程中还遇到 了一个非常喜剧的问题,我发现我使用这个来进行调用后结果程序内存一直增大,直到500多M,直接卡死。我知道是我写的有内存泄漏了!

然后找了一下,发现果然是。仅仅好进行free了。然后一下就好了,发现内存占用的确比Java的要少,速度也是要快一些!

在JNI中的实现我使用了两种方案,一种是直接传递文件,一直是传递像素点集合进行模糊!分别例如以下:

/*
 * Class:     com_accumulation_imageblurring_app_jni_ImageBlur
 * Method:    blurIntArray
 * Signature: ([IIII)V
 */
JNIEXPORT void JNICALL Java_com_accumulation_imageblurring_app_jni_ImageBlur_blurIntArray
  (JNIEnv *, jclass, jintArray, jint, jint, jint);

/*
 * Class:     com_accumulation_imageblurring_app_jni_ImageBlur
 * Method:    blurBitMap
 * Signature: (Landroid/graphics/Bitmap;I)V
 */
JNIEXPORT void JNICALL Java_com_accumulation_imageblurring_app_jni_ImageBlur_blurBitMap
  (JNIEnv *, jclass, jobject, jint);

相应的Java调用:

public class ImageBlur {
    public static native void blurIntArray(int[] pImg, int w, int h, int r);

    public static native void blurBitMap(Bitmap bitmap, int r);

    static {
        System.loadLibrary("JNI_ImageBlur");
    }
}

///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

此时我做了3种測试,一种是直接在Java层实现,一种是传递像素点集合模糊,还有就是直接传递图片进行模糊,结果例如以下:

[Android]-图片JNI(C++\Java)高斯模糊的实现与比較

[Android]-图片JNI(C++\Java)高斯模糊的实现与比較

[Android]-图片JNI(C++\Java)高斯模糊的实现与比較

通过上面的比較我们能够得出这种结论:

1.Java的确最慢,可是事实上也慢不了多少,虚拟机优化好了一样猛。

2.C中直接传递像素集合的速度最快(第一次启动)

3.在我多次切换界面后发现,直接传递像素点集合的耗时会添加?,从60多到120多。

4.多次切换后发现,事实上直接传递像素点的速度与传递图片过去的速度差点儿一样。

5.多次操作后发现传递文件的波动较小,在100~138之间,其次是传递像素点集合的波动较大,java的波动最大!

以上就是我的结论,可能有些不对,可是在我的机器上的确是这样!

注:勾选选择框“Downscale before blur”会先压缩图片后模糊然后放大图片,这种情况下,模糊效果会略微损失一些效果,可是其速度确实无法比拟的。

其耗时在:1~10ms内可运算完毕。当然与你要模糊的大小有关系!


最后:项目地址:GitHub

原创作品,转载请注明出处!

    QIUJUER(qiujuer@live.cn)


[Android]-图片JNI(C++\Java)高斯模糊的实现与比較,布布扣,bubuko.com

[Android]-图片JNI(C++\Java)高斯模糊的实现与比較

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