C++——bmp图像+中值滤波

1、中值滤波

中值滤波是对一个滑动窗口内的诸像素灰度值排序，用其中值代替窗口中心象素的原来灰度值，它是一种非线性的图像平滑法，它对脉冲干扰级椒盐噪声的抑制效果好，在抑制随机噪声的同时能有效保护边缘少受模糊。

二维中值滤波算法是：对于一幅图像的象素矩阵，取以目标象素为中心的一个子矩阵窗口，这个窗口可以是3*3 ，5*5 等根据需要选取，对窗口内的象素灰度排序，取中间一个值作为目标象素的新灰度值。

步骤：

1：通过从图像中的某个采样窗口取出奇数个数据进行排序

在这里，我们选用的排序方法是冒泡排序

2：用排序后的中值取代要处理的数据即可

一般的，中值滤波对图像的边界用0做扩张，所以对边界可能会出现扭曲。在这里，我对边界进行了填充，用里圈的值来填充外圈的值。若要用0填充外圈，可将imagedatafilter初始化为0：

memset(imagedatafilter,0,linebyte*bmpHeight);

如果这样，那填充的那个循环就可以去掉不要了，具体代码如下：

#include <cstring>
#include <windows.h>
#include"readbmp.h"
#include"savebmp.h"
#include<assert.h>

#define iFilterW 3
#define iFilterH 3


unsigned char GetMedianNum(int * bArray, int iFilterLen)
{
	int i, j;// 循环变量  
	unsigned char bTemp;

	// 用冒泡法对数组进行排序  
	for (j = 0; j < iFilterLen - 1; j++)
	{
		for (i = 0; i < iFilterLen - j - 1; i++)
		{
			if (bArray[i] > bArray[i + 1])
			{
				// 互换  
				bTemp = bArray[i];
				bArray[i] = bArray[i + 1];
				bArray[i + 1] = bTemp;
			}
		}
	}

	// 计算中值  
	if ((iFilterLen & 1) > 0)
	{
		// 数组有奇数个元素，返回中间一个元素  
		bTemp = bArray[(iFilterLen + 1) / 2];
	}
	else
	{
		// 数组有偶数个元素，返回中间两个元素平均值  
		bTemp = (bArray[iFilterLen / 2] + bArray[iFilterLen / 2 + 1]) / 2;
	}

	return bTemp;
}


void image_filter_median()
{
	char readPath[] = "D:\\C++_file\\image_deal_C++\\IMAGE_JIEQU\\jiaoyan.bmp";
	readBmp(readPath);

	unsigned char *imagedatafilter;
	unsigned char *imagedata;
	imagedata = pBmpBuf;
	int  aValue[iFilterH*iFilterW];          // 指向滤波器数组的指针  

	int lineByte = (bmpWidth * biBitCount / 8 + 3) / 4 * 4;
	imagedatafilter = new unsigned char[lineByte * bmpHeight];
	int iFilterHM= (iFilterH - 1)/ 2;
	int iFilterWM = (iFilterW - 1) / 2;


	for (int i = iFilterHM; i < bmpHeight - iFilterHM; i++)
		for (int j = iFilterWM; j < bmpWidth - iFilterWM; j++)
			for (int k = 0; k < 3; k++)
			{
				
				for (int m  = 0; m< iFilterH; m++)
					for (int n = 0; n < iFilterW; n++)
						{
							aValue[m * iFilterW + n] = *(imagedata + lineByte* (i+m-1) + (j + n-1) * 3 + k);	
						}
				*(imagedatafilter + bmpWidth * 3 * i + j * 3 + k) = GetMedianNum(aValue, iFilterH * iFilterW); 
				
			}

	for (int i = 0; i < bmpHeight; i++)
		for (int j = 0; j < bmpWidth; j++)
				for (int k = 0; k < 3; k++)
				{

					
					if ((i<iFilterHM) && (j<iFilterWM))
								*(imagedatafilter + lineByte * i + j * 3 + k) = *(imagedatafilter + lineByte* (i + iFilterHM) + (j + iFilterWM) * 3 + k);
					else if ((i<iFilterHM) && (j>=iFilterWM)&&(j<(bmpWidth - iFilterWM)))
						*(imagedatafilter + lineByte * i + j * 3 + k) = *(imagedatafilter + lineByte* (i + iFilterHM) + j  * 3 + k);
					else if ((i<iFilterHM) && ( j >= (bmpWidth - iFilterWM)))
						*(imagedatafilter + lineByte * i + j * 3 + k) = *(imagedatafilter + lineByte* (i + iFilterHM) + (j - iFilterWM) * 3 + k);
					else if ((i>=iFilterHM) && i <(bmpHeight - iFilterHM) && (j< iFilterWM))
						*(imagedatafilter + lineByte * i + j * 3 + k) = *(imagedatafilter + lineByte* i + (j + iFilterWM) * 3 + k);
					else if ((i>=iFilterHM) && i < (bmpHeight - iFilterHM) && (j >= (bmpWidth - iFilterWM)))
						*(imagedatafilter + lineByte * i + j * 3 + k) = *(imagedatafilter + lineByte* i + (j - iFilterWM) * 3 + k);
					else if ((i >= (bmpHeight - iFilterHM)) && (j< iFilterWM))
						*(imagedatafilter + lineByte * i + j * 3 + k) = *(imagedatafilter + lineByte* (i - iFilterHM) + (j + iFilterWM) * 3 + k);
					else if ((i >= (bmpHeight - iFilterHM)) && (j>= iFilterWM)&&(j<(bmpWidth - iFilterWM)))
								*(imagedatafilter + lineByte * i + j * 3 + k) = *(imagedatafilter + lineByte* (i - iFilterHM) + j * 3 + k);
					else if ((i >= (bmpHeight - iFilterHM)) && ( j >= (bmpWidth - iFilterWM)))
						*(imagedatafilter + lineByte * i + j * 3 + k) = *(imagedatafilter + lineByte* (i - iFilterHM) + (j - iFilterWM) * 3 + k);
				
					
				}


	char writePath[] = "D:\\C++_file\\image_deal_C++\\IMAGE_JIEQU\\mm.bmp";
	saveBmp(writePath, imagedatafilter, bmpWidth, bmpHeight, biBitCount, pColorTable);
	printf("中值滤波操作完成，请查看bmp文件。\n\n");
	
}

原图：

滤波后：

C++——bmp图像+中值滤波

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