//图像二值化
private static int[,] BinMap(Bitmap image, InterpreProBar iterprePB)
{
iterprePB.Show();
int[,] idata = new int[image.Width, image.Height]; //存储像元值，用于计算
for (int x = 0; x < image.Width; x++)
{
iterprePB.SetProgressValue(x);
for (int y = 0; y < image.Height; y++)
{
Color pixelColor = image.GetPixel(x, y);
idata[x, y] = (pixelColor.R + pixelColor.G + pixelColor.B) / 3;
if (idata[x, y] != 0)
{
idata[x, y] = 0;
}
else
{
idata[x, y] = 1;
}
}
}
iterprePB.Close();
return(idata);
}
private void VarCal_Click(object sender, EventArgs e)
{
if (tBoxImportData.Text == "" || tBoxExportResult.Text == "")
{
MessageBox.Show("请输入完整的参数和存储路径！", "逐行提取对象大小");
return; //退出函数
}
Bitmap image = new Bitmap(tBoxImportData.Text, true); //读入图片
InterpreProBar iterprePB = new InterpreProBar(0, image.Width); //数据解析进度
int[,] idata = BinMap(image, iterprePB); // 二值化
//提取每行的元素 计算：地物和背景的均值/方差 地物均值/方差 背景均值/方差
double[] bavg = new double[image.Height];//存储每行背景的均值
double[] oavg = new double[image.Height];
double[] bvar = new double[image.Height];//存储每行背景的方差
double[] ovar = new double[image.Height];
double[] OBvar = new double[image.Height]; //存储每行的方差
double[] OBavg = new double[image.Height]; //存储每行的均值
double[] cyclevar = new double[image.Height]; //存储每行的方差
double[] cycleavg = new double[image.Height]; //存储每行的均值
CacuProBar progressForm = new CacuProBar("逐行方差均值计算", 0, image.Height); //计算进度
progressForm.Show(); //开始显示计算进度
for (int i = 0; i < image.Height; i++) //逐行计算
{
progressForm.SetProgressValue(i);
int[] obasize = objBacSizeLine(i, idata);
int bcnt = 0, ocnt = 0;
double bsum = 0; double osum = 0; double OBsum = 0;
//分别计算地物和背景的方差均值
for (int j = 0; j < obasize.Length; j++)
{
OBsum += obasize[j];
if (idata[0, i] == 0) //如果第一个是背景 0 010101010
{
if (j % 2 == 0) //偶数下标就是背景bac长度
{
bsum += obasize[j];
bcnt++;
}
else //奇数数下标就是地物obj长度
{
osum += obasize[j];
ocnt++;
}
}
else //如果第一个是背景 1 101010101
{
if (j % 2 == 0) //偶数下标就是地物obj长度
{
osum += obasize[j];
ocnt++;
}
else
{
bsum += obasize[j];
bcnt++;
}
}
}
progressForm.Close();
OBavg[i] = OBsum / (bcnt + ocnt);
bavg[i] = bsum / bcnt;
oavg[i] = osum / ocnt;
double os = 0; //obj均值与数组元素值得差的平方和
double bs = 0; //bac均值与数组元素值得差的平方和
double OBs = 0; //bac均值与数组元素值得差的平方和
//计算地物和背景的方差
for (int j = 0; j < obasize.Length; j++)
{
OBs += Math.Pow(obasize[j] - OBavg[i], 2);
if (idata[0, i] == 0) //如果第一个是背景 0
{
if (j % 2 == 0)
{
bs += Math.Pow(obasize[j] - bavg[i], 2);
}
else
{
os += Math.Pow(obasize[j] - oavg[i], 2);
}
}
else ////如果第一个是地物 1
{
if (j % 2 == 0)
{
os += Math.Pow(obasize[j] - oavg[i], 2);
}
else
{
bs += Math.Pow(obasize[j] - bavg[i], 2);
}
}
}
OBvar[i] = OBs / (bcnt + ocnt);
bvar[i] = bs / bcnt;
ovar[i] = os / ocnt;
//计算黑白周期长度的均值和方差
for (int j = 0; j < obasize.Length; j++)
{
if (idata[0, i] == 0) //如果第一个是背景 0
{
if (j % 2 == 0)
{
bs += Math.Pow(obasize[j] - bavg[i], 2);
}
else
{
os += Math.Pow(obasize[j] - oavg[i], 2);
}
}
else ////如果第一个是地物 1
{
if (j % 2 == 0)
{
os += Math.Pow(obasize[j] - oavg[i], 2);
}
else
{
bs += Math.Pow(obasize[j] - bavg[i], 2);
}
}
}
}
String str = tBoxExportResult.Text;
//写出计算结果
if (str.Substring(str.LastIndexOf('.'), 3 + 1) == ".txt")//包头不包尾
{
saveCacuResultAsText(tBoxExportResult.Text, bavg, bvar, oavg, ovar, OBavg, OBvar);
}
else
{
saveCacuResultAsExcel(tBoxExportResult.Text, bavg, bvar, oavg, ovar, OBavg, OBvar);
}
MessageBox.Show("OK,计算和保存完成！", "逐行提取对象大小");
this.Dispose();
}
int maxlag; //最大变异距离
private void VarCal_Click(object sender, EventArgs e)
{
if (tBoxImportData.Text == "" || cbxVarOrg.Text == "" ||
cbBMaxLag.Text == "" || tBLag.Text == "" || tBoxExportResult.Text == "")
{
MessageBox.Show("请输入完整的参数和存储路径！", "逐行变异计算");
return; //退出函数
}
image = new Bitmap(tBoxImportData.Text, true); //读入图片
int[,] idata = new int[image.Width, image.Height]; //存储像元值，用于计算
switch (cbBMaxLag.Text)
{
case "1/2图幅":
maxlag = image.Width / 2; //参数lag 为变异距离
break;
case "1/4图幅":
maxlag = image.Width / 4; //参数lag 为变异距离
break;
case "1/8图幅":
maxlag = image.Width / 8; //参数lag 为变异距离
break;
default:
maxlag = image.Width / 2; //参数lag 为变异距离
break;
}
//存储逐行变异值
double[,] dResult = new double[image.Height, maxlag];
string[,] sResult = new string[image.Height, maxlag];
//存储全幅变异值
double [] dMResult = new double[maxlag];
InterpreProBar iterprePB = new InterpreProBar(0, image.Width); //数据解析进度
idata = BinMap(image, iterprePB); // 二值化
//输出二值图像二值数据
string datapath = tBoxBinMap.Text; //存储路径
if (radioButtonYes.Checked)
{
saveBinMap(idata, datapath, image);
}
//变异计算
CacuProBar progressForm = new CacuProBar("变异计算", 0, maxlag); //变异计算进度
progressForm.Show(); //开始显示计算进度
for (int h = 1; h < maxlag; h++) //变异滞后距离
{
progressForm.SetProgressValue(h);
//全幅计算
int cn = 0; //记录运算次数
double sum = 0; //滞后距离差的平方和
if (cbxVarMapOrLine.Text.Trim() == "全幅")
{
if (cbxVarOrg.Text == "W-->E")
{
for (int row = 0; row < image.Height; row++) ////窗口大小与图像行列数关系
{
for (int col = 0; col < image.Width - h; col++) ////窗口大小与图像行列数关系
{
sum += Math.Pow((idata[row, col] - idata[row, col + h]), 2);
cn = cn + 1;
}
}
}
if (cbxVarOrg.Text == "N-->S")
{
}
if (cbxVarOrg.Text == "WS-->EN")
{
}
if (cbxVarOrg.Text == "WN-->ES")
{
}
dMResult[h] = sum / (2 * cn);
}
else if (cbxVarMapOrLine.Text == "逐行") //单行横向计算
{
if (cbxVarOrg.Text == "W-->E")
{
double n = 0; //计算次数
ArrayList p = new ArrayList(); //以h为滞后距离的差的平方
for (int j = 0; j < image.Height; ++j) //每行变异
{
double pp = 0; //差的平方的和
for (int i = 0; i < image.Width - h; i++) //最大变异宽幅
{
p.Add(Math.Pow(idata[i, j] - idata[i + h, j], 2));
pp += (Double)p[i]; //将h为滞后距离的差的平方相加
}
p.Clear();
n = image.Width - h;
dResult[j, h] = pp / (2 * n);
}
}
if (cbxVarOrg.Text == "N-->S")
{
}
if (cbxVarOrg.Text == "WS-->EN")
{
}
if (cbxVarOrg.Text == "WN-->ES")
{
}
}
}
progressForm.Close();
//写出计算结果
if (cbxVarMapOrLine.Text == "逐行")
{
//平滑消除小波动
smoothSemiVar(dResult, Convert.ToInt32(cbxSmoothWindowSize.Text));
//提取变异前5个峰值和谷值
double[,] semiPeekMax = new double[image.Height, 5];
double[,] semiPeekMin = new double[image.Height, 5];
//提取峰值所在的索引
int[,] semiPeekMaxIndex = new int[image.Height, 5];
int[,] semiPeekMinIndex = new int[image.Height, 5];
semiPeekMax = getSemiVarPeekMax(dResult);
semiPeekMin = getSemiVarPeekMin(dResult);
semiPeekMaxIndex = getSemiVarPeekMaxIndex(dResult);
semiPeekMinIndex = getSemiVarPeekMinIndex(dResult);
saveLineCacuResultAsText(tBoxExportResult.Text, dResult, semiPeekMaxIndex, semiPeekMinIndex, semiPeekMax, semiPeekMin);
}
else if (cbxVarMapOrLine.Text == "全幅")
{
saveMapCacuResultAsText(tBoxExportResult.Text, dMResult);
}
MessageBox.Show("变异计算完成！", "变异计算");
this.Dispose();
}
private void VarCal_Click(object sender, EventArgs e)
{
if (tBoxImportData.Text == "" || cbxVarOrg.Text == "" || tBoxExportResult.Text == "")
{
MessageBox.Show("请输入完整的参数和存储路径！", "逐行方差计算");
return; //退出函数
}
image = new Bitmap(tBoxImportData.Text, true); //读入图片
int x, y;
int[,] idata = new int[image.Width, image.Height]; //存储像元值，用于计算
string[,] sdata = new string[image.Width, image.Height]; //存储像元值，用于写出
InterpreProBar iterprePB = new InterpreProBar(0, image.Width); //数据解析进度
iterprePB.Show();
// 二值化
for (x = 0; x < image.Width; x++)
{
iterprePB.SetProgressValue(x);
for (y = 0; y < image.Height; y++)
{
Color pixelColor = image.GetPixel(x, y);
idata[x, y] = (pixelColor.R + pixelColor.G + pixelColor.B) / 3;
if (idata[x, y] != 0)
{
idata[x, y] = 0;
}
else
{
idata[x, y] = 1;
}
}
}
iterprePB.Close();
avg = new double[idata.GetLength(1)];
var2 = new double[idata.Length];//存储每行的方差
//逐行方差计算
for (int line = 0; line < idata.GetLength(0); line++)
{
double sum = 0;//均值与数组元素值得差的平方和
avg[line] = average2D(idata, line);
for (int j = 0; j < idata.GetLength(1); j++)
{
sum += Math.Pow(idata[line, j] - avg[line], 2);
}
var2[line] = sum / idata.GetLength(1);
}
//结果输出变异结果
string path = tBoxExportResult.Text; //存储路径
using (FileStream fs = File.Create(path)) {
AddText(fs, "行号 均值 方差 \r\n");
for (int i = 0; i < idata.GetLength(0); i++)
{
AddText(fs, String.Format("{0,6:D6}", i) + " " +
String.Format("{0:N6}", avg[i]) + " " +
String.Format("{0:N6}", var2[i]) + "\r\n ");
}
}
MessageBox.Show("逐行方差计算完成！", "方差计算");
this.Dispose();
}
