多核程序设计的相关基础知识----以误差扩散算法为例

// ERROR-diffusion.cpp : 定义控制台应用程序的入口点。
//

#include "stdafx.h"
#include "omp.h"
#include "windows.h"
#include <iostream>

#include <opencv2/core/core.hpp>    
#include <opencv2/highgui/highgui.hpp>  


#pragma comment(lib,"opencv_core2410d.lib")                  
#pragma comment(lib,"opencv_highgui2410d.lib")                  
#pragma comment(lib,"opencv_imgproc2410d.lib")     

using namespace std;  
using namespace cv;  

void error_diffusion(unsigned int width,
					 unsigned int height,
					 unsigned short **InputImage,
					 unsigned short **OutputImage
	)

{

	for (unsigned int i = 0;i < height-1; i++)
	{
		for(unsigned int j = 1;j < width-1; j++)
		{
			//计算输出像素的值
			if (InputImage[i][j]<128)
			{
				OutputImage[i][j] = 0;
			}
			else{ OutputImage[i][j] = 1;}

			//计算误差值
			int err = InputImage[i][j] - 255*OutputImage[i][j];
			//扩散误差
			int v;
			v=(int)InputImage[i  ][j+1];v+=err*7/16;if (v>255) v=255; if (v<0) v=0;InputImage[i  ][j+1]=(unsigned short)v;
			v=(int)InputImage[i+1][j-1];v+=err*3/16;if (v>255) v=255; if (v<0) v=0;InputImage[i+1][j-1]=(unsigned short)v;
			v=(int)InputImage[i+1][j  ];v+=err*5/16;if (v>255) v=255; if (v<0) v=0;InputImage[i+1][j  ]=(unsigned short)v;
			v=(int)InputImage[i+1][j+1];v+=err*1/16;if (v>255) v=255; if (v<0) v=0;InputImage[i+1][j+1]=(unsigned short)v;
		}
	}
}

int row = 288;
//int col = width;

void error_diffusion_omp(unsigned int width,
	unsigned int height,
	unsigned short **InputImage,
	unsigned short **OutputImage
	)

{
	int cpu_num = omp_get_num_procs();//cpu数
	 
	int col = width;
#pragma omp parallel private(row , col)//并行域
	{
		int thread_id = omp_get_num_threads();//每个线程的线程号
		Sleep(20*thread_id);//根据线程短延迟
	
#pragma omp for
		for (int i = 0; i<(height/cpu_num);i++)
		{
			 row  = row*cpu_num + thread_id;

			for ( col = 0;col<width;col++)
			{
				//计算输出像素的值
				if (InputImage[i][col]<128)
				{
					OutputImage[i][col] = 0;
				}
				else{ OutputImage[i][col] = 1;}

				//计算误差值
				int err = InputImage[i][col] - 255*OutputImage[i][col];
				//扩散误差
				InputImage[i][col+1] += err * 7/16;
				InputImage[i+1][col-1] += err * 7/16;
				InputImage[i+1][col] += err * 7/16;
				InputImage[i+1][col+1] += err * 7/16;

			}
		}

	

	}
}



int _tmain(int argc, _TCHAR* argv[])
{
	string str_name = "result.pgm";  
	

	Mat image_src = imread(str_name,0);
	imshow("original image",image_src);

	unsigned short **InputImage = new unsigned short *[image_src.rows];
	for (int i = 0;i<image_src.rows;i++)
	{
		InputImage[i] = new unsigned short [image_src.cols];
	}
	unsigned short **OutputImage = new unsigned short *[image_src.rows];
	for (int i = 0;i<image_src.rows;i++)
	{
		OutputImage[i] = new unsigned short [image_src.cols];
	}

	cout<<image_src.rows;
	cout<<image_src.cols;
	Mat image_dst(image_src.rows,image_src.cols,CV_8U);

	for(int y = 0;y < image_src.rows;y++)  
	{  
		uchar *ptr= image_src.ptr<uchar>(y); 
		
		for(int x = 0;x < image_src.cols;x++)  
		{  
			
			InputImage[y][x] = ptr[x];
			OutputImage[y][x] = 0;
			
		}  
	} 


	error_diffusion(image_src.cols,image_src.rows,InputImage,OutputImage);
	//error_diffusion_omp(image_src.cols,image_src.rows,InputImage,OutputImage);

	for(int y = 0;y < image_src.rows;y++)  
	{  
		uchar *ptr= image_dst.ptr<uchar>(y); 

		for(int x = 0;x < image_src.cols;x++)  
		{  
			if (OutputImage[y][x]==1)
			{
				ptr[x] = 255;
			}
			else
				ptr[x] = 0;

		}  
	} 
	imshow("error diffusion",image_dst);
	imwrite("result.bmp",image_dst);

	waitKey(0);


	return 0;
}