浅谈Visual C#进行图像处理（读取、保存以及对像素的访问）
这里之所以说“浅谈”是因为我这里只是简单的介绍如何使用Visual C#进行图像的读入、保存以及对像素的访问。而不涉及太多的算法。
一、读取图像
在Visual C#中我们可以使用一个Picture Box控件来显示图片，如下：
private void btnOpenImage_Click(object sender, EventArgs e)
{
OpenFileDialog ofd = new OpenFileDialog();
ofd.Filter = "BMP Files(*.bmp)|*.bmp|JPG Files(*.jpg;*.jpeg)|*.jpg;*.jpeg|All Files(*.*)|*.*";
ofd.CheckFileExists = true;
ofd.CheckPathExists = true;
if (ofd.ShowDialog() == DialogResult.OK)
{
//pbxShowImage.ImageLocation = ofd.FileName;
bmp = new Bitmap(ofd.FileName);
if (bmp==null)
{
MessageBox.Show("加载图片失败!", "错误");
return;
}
pbxShowImage.Image = bmp;
ofd.Dispose();
}
}
其中bmp为类的一个对象：private Bitmap bmp=null;
在使用Bitmap类和BitmapData类之前，需要使用using System.Drawing.Imaging;
二、保存图像
private void btnSaveImage_Click(object sender, EventArgs e)
{
if (bmp == null) return;
SaveFileDialog sfd = new SaveFileDialog();
sfd.Filter = "BMP Files(*.bmp)|*.bmp|JPG Files(*.jpg;*.jpeg)|*.jpg;*.jpeg|All Files(*.*)|*.*";
if (sfd.ShowDialog() == DialogResult.OK)
{
pbxShowImage.Image.Save(sfd.FileName);
MessageBox.Show("保存成功!","提示");
sfd.Dispose();
}
}
三、对像素的访问
我们可以来建立一个GrayBitmapData类来做相关的处理。整个类的程序如下：
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Drawing;
using System.Drawing.Imaging;
using System.Windows.Forms;
namespace ImageElf
{
class GrayBitmapData
{
public byte[,] Data;//保存像素矩阵
public int Width;//图像的宽度
public int Height;//图像的高度
public GrayBitmapData()
{
this.Width = 0;
this.Height = 0;
this.Data = null;
}
public GrayBitmapData(Bitmap bmp)
{
BitmapData bmpData = bmp.LockBits(new Rectangle(0, 0, bmp.Width, bmp.Height), ImageLockMode.ReadOnly, PixelFormat.Format24bppRgb);
this.Width = bmpData.Width;
this.Height = bmpData.Height;
Data = new byte[Height, Width];
unsafe
{
byte* ptr = (byte*)bmpData.Scan0.ToPointer();
for (int i = 0; i < Height; i++)
{
for (int j = 0; j < Width; j++)
{
//将24位的RGB彩色图转换为灰度图
int temp = (int)(0.114 * (*ptr++)) + (int)(0.587 * (*ptr++))+(int)(0.299 * (*ptr++));
Data[i, j] = (byte)temp;
}
ptr += bmpData.Stride - Width * 3;//指针加上填充的空白空间
}
}
bmp.UnlockBits(bmpData);
}
public GrayBitmapData(string path)
: this(new Bitmap(path))
{
}
public Bitmap ToBitmap()
{
Bitmap bmp=new Bitmap(Width,Height,PixelFormat.Format24bppRgb);
BitmapData bmpData=bmp.LockBits(new Rectangle(0,0,Width,Height),ImageLockMode.WriteOnly,PixelFormat.Format24bppRgb);
unsafe
{
byte* ptr=(byte*)bmpData.Scan0.ToPointer();
for(int i=0;i<Height;i++)
{
for(int j=0;j<Width;j++)
{
*(ptr++)=Data[i,j];
*(ptr++)=Data[i,j];
*(ptr++)=Data[i,j];
}
ptr+=bmpData.Stride-Width*3;
}
}
bmp.UnlockBits(bmpData);
return bmp;
}
public void ShowImage(PictureBox pbx)
{
Bitmap b = this.ToBitmap();
pbx.Image = b;
//b.Dispose();
}
public void SaveImage(string path)
{
Bitmap b=ToBitmap();
b.Save(path);
//b.Dispose();
}
//均值滤波
public void AverageFilter(int windowSize)
{
if (windowSize % 2 == 0)
{
return;
}
for (int i = 0; i < Height; i++)
{
for (int j = 0; j < Width; j++)
{
int sum = 0;
for (int g = -(windowSize - 1) / 2; g <= (windowSize - 1) / 2; g++)
{
for (int k = -(windowSize - 1) / 2; k <= (windowSize - 1) / 2; k++)
{
int a = i + g, b = j + k;
if (a < 0) a = 0;
if (a > Height - 1) a = Height - 1;
if (b < 0) b = 0;
if (b > Width - 1) b = Width - 1;
sum += Data[a, b];
}
}
Data[i,j]=(byte)(sum/(windowSize*windowSize));
}
}
}
//中值滤波
public void MidFilter(int windowSize)
{
if (windowSize % 2 == 0)
{
return;
}
int[] temp = new int[windowSize * windowSize];
byte[,] newdata = new byte[Height, Width];
for (int i = 0; i < Height; i++)
{
for (int j = 0; j < Width; j++)
{
int n = 0;
for (int g = -(windowSize - 1) / 2; g <= (windowSize - 1) / 2; g++)
{
for (int k = -(windowSize - 1) / 2; k <= (windowSize - 1) / 2; k++)
{
int a = i + g, b = j + k;
if (a < 0) a = 0;
if (a > Height - 1) a = Height - 1;
if (b < 0) b = 0;
if (b > Width - 1) b = Width - 1;
temp[n++]= Data[a, b];
}
}
newdata[i, j] = GetMidValue(temp,windowSize*windowSize);
}
}
for (int i = 0; i < Height; i++)
{
for (int j = 0; j < Width; j++)
{
Data[i, j] = newdata[i, j];
}
}
}
//获得一个向量的中值
private byte GetMidValue(int[] t, int length)
{
int temp = 0;
for (int i = 0; i < length - 2; i++)
{
for (int j = i + 1; j < length - 1; j++)
{
if (t[i] > t[j])
{
temp = t[i];
t[i] = t[j];
t[j] = temp;
}
}
}
return (byte)t[(length - 1) / 2];
}
//一种新的滤波方法，是亮的更亮、暗的更暗
public void NewFilter(int windowSize)
{
if (windowSize % 2 == 0)
{
return;
}
for (int i = 0; i < Height; i++)
{
for (int j = 0; j < Width; j++)
{
int sum = 0;
for (int g = -(windowSize - 1) / 2; g <= (windowSize - 1) / 2; g++)
{
for (int k = -(windowSize - 1) / 2; k <= (windowSize - 1) / 2; k++)
{
int a = i + g, b = j + k;
if (a < 0) a = 0;
if (a > Height - 1) a = Height - 1;
if (b < 0) b = 0;
if (b > Width - 1) b = Width - 1;
sum += Data[a, b];
}
}
double avg = (sum+0.0) / (windowSize * windowSize);
if (avg / 255 < 0.5)
{
Data[i, j] = (byte)(2 * avg / 255 * Data[i, j]);
}
else
{
Data[i,j]=(byte)((1-2*(1-avg/255.0)*(1-Data[i,j]/255.0))*255);
}
}
}
}
//直方图均衡
public void HistEqual()
{
double[] num = new double[256] ;
for(int i=0;i<256;i++) num[i]=0;
for (int i = 0; i < Height; i++)
{
for (int j = 0; j < Width; j++)
{
num[Data[i, j]]++;
}
}
double[] newGray = new double[256];
double n = 0;
for (int i = 0; i < 256; i++)
{
n += num[i];
newGray[i] = n * 255 / (Height * Width);
}
for (int i = 0; i < Height; i++)
{
for (int j = 0; j < Width; j++)
{
Data[i,j]=(byte)newGray[Data[i,j]];
}
}
}
}
}
在GrayBitmapData类中，只要我们对一个二维数组Data进行一系列的操作就是对图片的操作处理。在窗口上，我们可以使用
一个按钮来做各种调用：
//均值滤波
private void btnAvgFilter_Click(object sender, EventArgs e)
{
if (bmp == null) return;
GrayBitmapData gbmp = new GrayBitmapData(bmp);
gbmp.AverageFilter(3);
gbmp.ShowImage(pbxShowImage);
}
//转换为灰度图
private void btnToGray_Click(object sender, EventArgs e)
{
if (bmp == null) return;
GrayBitmapData gbmp = new GrayBitmapData(bmp);
gbmp.ShowImage(pbxShowImage);
}
四、总结
在Visual c#中对图像进行处理或访问，需要先建立一个Bitmap对象，然后通过其LockBits方法来获得一个BitmapData类的对象，然后通过获得其像素数据的首地址来对Bitmap对象的像素数据进行操作。当然，一种简单但是速度慢的方法是用Bitmap类的GetPixel和SetPixel方法。其中BitmapData类的Stride属性为每行像素所占的字节。
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