【c++&GDAL】均值滤波+中值滤波
实现3*3的均值滤波和中值滤波
文章目录
-
- 【c++&GDAL】均值滤波+中值滤波
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- [1. 均值滤波](#1. 均值滤波)
- [2. 中值滤波：](#2. 中值滤波：)
- [3. 完整程序](#3. 完整程序)
1. 均值滤波
使用一个M×N的窗口（又称滤波窗口、模板、掩膜），根据一定准则计算窗口内所有像元均值，然后赋予窗口中心像元，作为窗口中心像元滤波后的值。
再逐行或逐列移动窗口，并按上述方法计算，直至每个像元计算完毕。
cpp
void MeanFilter(unsigned char* in, unsigned char* out, int W, int H)
{
/*
memcpy(void *dest,void *src,unsigned int count
由src所指内存区赋值count个字节到dest所指内存区
*/
int sum = W * H * sizeof(unsigned char); //图像所占容量
memcpy((unsigned char *)out, (unsigned char*)in, sum);
for (int j = 1; j < H - 1; j++)
{
for (int i = 1; i < W - 1; i++)
{
out[j*W + i] = (in[(j - 1)*W + (i - 1)] + in[(j - 1)*W + i] + in[(j - 1)*W + (i + 1)] +
in[(j)*W + (i - 1)] + in[(j)*W + i] + in[(j)*W + (i + 1)] +
in[(j + 1)*W + (i - 1)] + in[(j + 1)*W + i] + in[(j + 1)*W + (i + 1)]) / 9;
}
}
cout << "使用<均值滤波>完成图像平滑" << endl;
}因为窗口中涉及j-1,j+1,i-1,i+1,所以i和j的范围是从[1,W/H-1).
2. 中值滤波：
基本原理与均值滤波相同，不同的是使用窗口内各点的中值代替窗口中心点的值（一般为奇数窗口）。
代码：
cpp
void MedianFilter(unsigned char* in, unsigned char* out, int W, int H)
{
int sum = W * H * sizeof(unsigned char); //图像所占容量
memcpy((unsigned char *)out, (unsigned char*)in, sum);
for (int j = 1; j < H - 1; j++)
{
for (int i = 1; i < W - 1; i++)
{
int k = 0;
unsigned char win[9];
for (int jj = j - 1; jj < j + 2; jj++)
{
for (int ii = i - 1; ii < i + 2; ii++)
{
win[k++] = in[jj*W + ii]; //将窗口的九个元素记录到一个数组中
}
//排序函数，第5个为中值
for (int m = 0; m < 5; m++)
{
int min = m;
for (int n = m + 1; n < 9; n++)
{
if (win[n] < win[min])
min = n;
}
unsigned char temp = win[m];
win[m] = win[min];
win[min] = temp;
}
out[j*W + i] = win[4];
}
}
}
cout << "使用<中值滤波>完成图像平滑" << endl;
}3. 完整程序
cpp
#include<iostream>
#include<math.h>
#include "gdal_priv.h"
#include "gdalwarper.h"
using namespace std;
void MeanFilter(unsigned char* in, unsigned char* out, int W, int H)
{
/*
memcpy(void *dest,void *src,unsigned int count
由src所指内存区赋值count个字节到dest所指内存区
*/
int sum = W * H * sizeof(unsigned char); //图像所占容量
memcpy((unsigned char *)out, (unsigned char*)in, sum);
for (int j = 1; j < H - 1; j++)
{
for (int i = 1; i < W - 1; i++)
{
out[j*W + i] = (in[(j - 1)*W + (i - 1)] + in[(j - 1)*W + i] + in[(j - 1)*W + (i + 1)] +
in[(j)*W + (i - 1)] + in[(j)*W + i] + in[(j)*W + (i + 1)] +
in[(j + 1)*W + (i - 1)] + in[(j + 1)*W + i] + in[(j + 1)*W + (i + 1)]) / 9;
}
}
cout << "使用<均值滤波>完成图像平滑" << endl;
}
void MedianFilter(unsigned char* in, unsigned char* out, int W, int H)
{
int sum = W * H * sizeof(unsigned char); //图像所占容量
memcpy((unsigned char *)out, (unsigned char*)in, sum);
for (int j = 1; j < H - 1; j++)
{
for (int i = 1; i < W - 1; i++)
{
int k = 0;
unsigned char win[9];
for (int jj = j - 1; jj < j + 2; jj++)
{
for (int ii = i - 1; ii < i + 2; ii++)
{
win[k++] = in[jj*W + ii]; //将窗口的九个元素记录到一个数组中
}
//排序函数，第5个为中值
for (int m = 0; m < 5; m++)
{
int min = m;
for (int n = m + 1; n < 9; n++)
{
if (win[n] < win[min])
min = n;
}
unsigned char temp = win[m];
win[m] = win[min];
win[min] = temp;
}
out[j*W + i] = win[4];
}
}
}
cout << "使用<中值滤波>完成图像平滑" << endl;
}
void main()
{
//注册所有的格式驱动
GDALAllRegister();
//支持中文路径
CPLSetConfigOption("GDAL_FILENAME_IS_UTF8", "NO");
//打开图像
const char* filepath = "Img.tif";
GDALDataset* image = (GDALDataset *)GDALOpen(filepath, GA_ReadOnly);
if (image == NULL)
{
//AfxMessageBox("读取图像失败")；
cout << "读取图像失败";
}
else
cout << "读取成功" << endl;
//定义图像的长宽
int W = image->GetRasterXSize();
int H = image->GetRasterYSize();
int C = image->GetRasterCount();
GDALDataType ImgType = image->GetRasterBand(1)->GetRasterDataType(); //数字图像类型
GDALRasterBand *band1 = image->GetRasterBand(1); //第一个波段的影像读入到数据之中
unsigned char* bdata = new unsigned char[W*H]; //创建存放数据的内存
band1->RasterIO(GF_Read, 0, 0, W, H, bdata, W, H, ImgType, 0, 0); //GDALRasterBand
//创建保存影像数据集
GDALDriver* imgDriver = GetGDALDriverManager()->GetDriverByName("GTiff"); //获取驱动
const char* outFilename1 = "MeanFilter.tif";
const char* outFilename2 = "MedianFilter.tif";
GDALDataset* outIMG1 = imgDriver->Create(outFilename1, W, H, 1, ImgType, NULL);
GDALDataset* outIMG2 = imgDriver->Create(outFilename2, W, H, 1, ImgType, NULL);
unsigned char* newdata = new unsigned char[W*H];
MeanFilter(bdata,newdata, W, H);
outIMG1->GetRasterBand(1)->RasterIO(GF_Write, 0, 0, W, H, newdata, W, H, ImgType, 0, 0);
MedianFilter(bdata, newdata, W, H);
outIMG2->GetRasterBand(1)->RasterIO(GF_Write, 0, 0, W, H, newdata, W, H, ImgType, 0, 0);
//保存影像
GDALClose(image);
GDALClose(outIMG1);
GDALClose(outIMG2);
delete bdata;
delete newdata;
system("pause");
}