/// <summary>
/// 辐射定标。
/// </summary>
/// <param name="InputDS">输入的栅格数据集。</param>
/// <param name="OutDataType">输出的数据类型。</param>
/// <param name="Gain">增益倍数。</param>
/// <param name="Offset">偏移量。</param>
/// <param name="OutPath">输出栅格数据集的位置。</param>
/// <returns>返回操作成功或失败。</returns>
public static bool ApplyGainAndOffset(OSGeo.GDAL.Dataset InputDS, OSGeo.GDAL.DataType OutDataType, List <double> Gain, List <double> Offset, string OutPath)
{
try
{
if (InputDS == null)
{
throw new ArgumentNullException("输入数据集为空。");
}
if (String.IsNullOrWhiteSpace(OutPath.Trim()))
{
throw new ArgumentNullException("输出路径为空或非法。");
}
if ((Gain.Count != InputDS.RasterCount) || (Offset.Count != InputDS.RasterCount))
{
throw new IndexOutOfRangeException("增益数据或偏移数据与输入数据集波段数不符。");
}
OSGeo.GDAL.Driver Dri = OSGeo.GDAL.Gdal.GetDriverByName("Gtiff");
if (Dri == null)
{
throw new Exception("无法获取GDAL Driver。");
}
FrmProgress FP = new FrmProgress()
{
Text = "正在进行辐射定标...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
int xSize = InputDS.RasterXSize;
int ySize = InputDS.RasterYSize;
OSGeo.GDAL.Dataset DS = Dri.Create(OutPath, xSize, ySize, InputDS.RasterCount, OutDataType, null);
FP.Output("已创建输出数据集\"" + OutPath + "\"，数据类型为" + OutDataType.ToString() + "。");
Tools.Common.CopyMetadata(InputDS, DS);
for (int i = 0; i < InputDS.RasterCount; i++) //遍历每个波段
{
FP.SetProgress2("正在处理波段：", i + 1, InputDS.RasterCount, "");
for (int Row = 0; Row < ySize; Row++) //遍历每一行(y)
{
FP.SetProgress1("正在处理：", Row + 1, ySize, "行");
double[] Values = new double[xSize];
//读取DN到数组
InputDS.GetRasterBand(i + 1).ReadRaster(0, Row, xSize, 1, Values, xSize, 1, 0, 0);
for (int Col = 0; Col < xSize; Col++) //对每一个值进行计算
{
Values[Col] = GainOffset(Values[Col], Gain[i], Offset[i]);
}
//写结果到新栅格
DS.GetRasterBand(i + 1).WriteRaster(0, Row, xSize, 1, Values, xSize, 1, 0, 0);
DS.FlushCache();
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
}
FP.Finish();
Dri.Dispose();
DS.Dispose();
return(true);
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
return(false);
}
}
/// <summary>
/// 数据集相除。
/// </summary>
/// <param name="D1">被除数据集。</param>
/// <param name="D2">除数据集。</param>
/// <param name="OutDataType">输出数据集的数据类型。</param>
/// <param name="OutPath">输出路径。</param>
/// <returns>操作成功或失败。</returns>
public static bool Divide(OSGeo.GDAL.Dataset D1, OSGeo.GDAL.Dataset D2, OSGeo.GDAL.DataType OutDataType, string OutPath)
{
try
{
if (D1 == null || D2 == null)
{
throw new ArgumentNullException("输入的数据集不可为空。");
}
if (String.IsNullOrWhiteSpace(OutPath.Trim()))
{
throw new ArgumentNullException("输出路径为空或非法。");
}
OSGeo.GDAL.Driver Dri = OSGeo.GDAL.Gdal.GetDriverByName("Gtiff");
if (Dri == null)
{
throw new Exception("无法获取GDAL Driver。");
}
//取输入的宽、高、波段最小值创建输出数据集。
int Width = Math.Min(D1.RasterXSize, D2.RasterXSize);
int Height = Math.Min(D1.RasterYSize, D2.RasterYSize);
int band = Math.Min(D1.RasterCount, D2.RasterCount);
FrmProgress FP = new FrmProgress()
{
Text = "正在进行数据集除法运算...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
OSGeo.GDAL.Dataset DS = Dri.Create(OutPath, Width, Height, band, OutDataType, null);
FP.Output("已创建输出数据集\"" + OutPath + "\"，数据类型为" + OutDataType.ToString() + "。");
Tools.Common.CopyMetadata(D1, DS);
for (int bandcount = 1; bandcount <= band; bandcount++)
{
FP.SetProgress2("正在处理", bandcount, band, "波段");
for (int row = 0; row < Height; row++)
{
FP.SetProgress1("正在处理：", row + 1, Height, "行");
double[] d1Tmp = new double[Width];
double[] d2Tmp = new double[Width];
double[] dsTmp = new double[Width];
D1.GetRasterBand(bandcount).ReadRaster(0, row, Width, 1, d1Tmp, Width, 1, 0, 0);
D2.GetRasterBand(bandcount).ReadRaster(0, row, Width, 1, d2Tmp, Width, 1, 0, 0);
for (long i = 0; i < Width; i++)
{
if (d2Tmp[i] == 0)
{
dsTmp[i] = 0;
}
else
{
dsTmp[i] = d1Tmp[i] / d2Tmp[i];
}
}
DS.GetRasterBand(bandcount).WriteRaster(0, row, Width, 1, dsTmp, Width, 1, 0, 0);
DS.FlushCache();
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
}
FP.Finish();
Dri.Dispose();
DS.Dispose();
return(true);
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
return(false);
}
}
public static bool CutImage(OSGeo.GDAL.Dataset InputDS, int CutWidth, int CutHeight, OSGeo.GDAL.DataType OutDataType, string OutFolder)
{
try
{
if (InputDS == null)
{
throw new ArgumentNullException("输入的数据集不可为空。");
}
if (String.IsNullOrWhiteSpace(OutFolder))
{
throw new ArgumentNullException("输出路径为空或非法。");
}
OSGeo.GDAL.Driver Dri = OSGeo.GDAL.Gdal.GetDriverByName("Gtiff");
if (Dri == null)
{
throw new Exception("无法获取GDAL Driver。");
}
//取输入的宽、高、波段最小值创建输出数据集。
int Width = InputDS.RasterXSize;
int Height = InputDS.RasterYSize;
int Rows = Height / CutHeight;
int Cols = Width / CutWidth;
FrmProgress FP = new FrmProgress()
{
Text = "正在进行影像裁剪...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
FP.Output("输出的目录为：" + OutFolder);
FP.Output("输出的数据类型为：" + OutDataType.ToString());
for (int row = 0; row < Rows; row++)
{
FP.SetProgress2("总进度：", row + 1, Rows, "");
string ParentPath = row.ToString();
Directory.CreateDirectory(Path.Combine(OutFolder, ParentPath));
for (int col = 0; col < Cols; col++)
{
FP.SetProgress1("当前行进度：", col + 1, Cols, "");
string OutName = row.ToString() + "_" + col.ToString() + ".tif";
OSGeo.GDAL.Dataset DS = Dri.Create(Path.Combine(OutFolder, ParentPath, OutName), CutWidth, CutHeight, InputDS.RasterCount, OutDataType, null);
for (int band = 1; band <= InputDS.RasterCount; band++)
{
double[] buf = new double[CutWidth * CutHeight];
InputDS.GetRasterBand(band).ReadRaster(col * CutWidth, row * CutHeight, CutWidth, CutHeight, buf, CutWidth, CutHeight, 0, 0);
DS.GetRasterBand(band).WriteRaster(0, 0, CutWidth, CutHeight, buf, CutWidth, CutHeight, 0, 0);
}
////单行读取写入，防止爆内存。
//for (int cRow = 0; cRow < CutHeight; cRow++)
//{
// double[] buf = new double[CutWidth];
// InputDS.GetRasterBand(band).ReadRaster(col * CutWidth, row * CutHeight + cRow, CutWidth, 1, buf, CutWidth, 1, 0, 0);
// DS.GetRasterBand(band).WriteRaster(0, cRow, CutWidth, 1, buf, CutWidth, 1, 0, 0);
// DS.FlushCache();
// Thread.Sleep(1);
//}
DS.FlushCache();
DS.Dispose();
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
}
FP.Finish();
InputDS.Dispose();
Dri.Dispose();
return(true);
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
return(false);
}
}
/// <summary>
/// Brovey变换融合。融合前会将多光谱数据集的每一波段与全色数据集做直方图匹配。
/// </summary>
/// <param name="PanDS">全色数据集。</param>
/// <param name="MSDS">多光谱数据集</param>
/// <param name="PanCumu">全色数据集的累积概率表。</param>
/// <param name="MSCumu">多光谱数据集的累积概率表。</param>
/// <param name="MSBandList">多光谱数据集的波段组合。</param>
/// <param name="OutDataType">输出数据类型。</param>
/// <param name="OutPath">输出路径。</param>
/// <returns>返回操作成功或失败。</returns>
public static bool Brovey(OSGeo.GDAL.Dataset PanDS, OSGeo.GDAL.Dataset MSDS, double[][] PanCumu, double[][] MSCumu, int[] MSBandList, OSGeo.GDAL.DataType OutDataType, string OutPath)
{
try
{
if (PanDS == null)
{
throw new ArgumentNullException("输入的全色数据集为空。");
}
if (PanDS.RasterCount > 1)
{
throw new RankException("全色数据集波段大于1。");
}
if (MSDS == null)
{
throw new ArgumentNullException("输入的多光谱数据集为空。");
}
if (String.IsNullOrWhiteSpace(OutPath.Trim()))
{
throw new ArgumentNullException("输出路径为空或非法。");
}
OSGeo.GDAL.Driver Dri = OSGeo.GDAL.Gdal.GetDriverByName("Gtiff");
if (Dri == null)
{
throw new Exception("无法获取GDAL Driver。");
}
int panWidth = PanDS.RasterXSize;
int panHeight = PanDS.RasterYSize;
int msWidth = MSDS.RasterXSize;
int msHeight = MSDS.RasterYSize;
//int rat = (int)Math.Ceiling((double)panHeight / msHeight);
if (panWidth < msWidth)
{
throw new RankException("全色数据集宽度小于多光谱数据集宽度。");
}
if (panHeight < msHeight)
{
throw new RankException("全色数据集高度小于多光谱数据集高度。");
}
//if (rat <= 0)
// throw new ArgumentOutOfRangeException("全色高度：多光谱高度小于1。");
FrmProgress FP = new FrmProgress()
{
Text = "正在进行Brovey融合...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
#region 预处理
//创建临时文件，进行直方图匹配。
string HisMatFileName = Tools.Common.GetTempFileName();
OSGeo.GDAL.Dataset MatchingDS = Dri.CreateCopy(HisMatFileName, MSDS, 0, null, null, null);
FP.Output("已创建直方图匹配临时文件\"" + HisMatFileName + "\"");
for (int band = 1; band <= MSDS.RasterCount; band++)
{
FP.Output("正在进行直方图匹配(" + band.ToString() + "/" + MSDS.RasterCount.ToString() + ")...");
Band b = Tools.BaseProcess.HistogramMatching(MSDS.GetRasterBand(band), PanDS.GetRasterBand(1), MSCumu[band - 1], PanCumu[0], OutDataType);
if (b == null)
{
throw new ArgumentNullException("直方图匹配返回波段为空。");
}
for (int row = 0; row < b.YSize; row++)
{
double[] tmp = new double[b.XSize];
b.ReadRaster(0, row, b.XSize, 1, tmp, b.XSize, 1, 0, 0);
MatchingDS.GetRasterBand(band).WriteRaster(0, row, MatchingDS.GetRasterBand(band).XSize, 1, tmp, MatchingDS.GetRasterBand(band).XSize, 1, 0, 0);
MatchingDS.FlushCache();
Thread.Sleep(1);
}
}
//创建临时文件，进行重采样。
double[] resamptmp;
string ResampFileName = Tools.Common.GetTempFileName();
OSGeo.GDAL.Dataset ResampDS = Dri.Create(ResampFileName, panWidth, panHeight, 3, MSDS.GetRasterBand(1).DataType, null);
FP.Output("已创建重采样临时文件\"" + ResampFileName + "\"");
//Tools.Common.CopyMetadata(PanDS, tmpDS);
//Gdal.ReprojectImage(MSDS, tmpDS, null, null, 0, 0, 0, null, null);
//将直方图匹配后的图像重采样。
for (int i = 0; i < 3; i++)
{
FP.Output("正在对直方图匹配后影像进行重采样(" + (i + 1).ToString() + "/" + "3)...");
resamptmp = new double[panWidth * panHeight];
MatchingDS.GetRasterBand(MSBandList[i]).ReadRaster(0, 0, msWidth, msHeight, resamptmp, panWidth, panHeight, 0, 0);
ResampDS.GetRasterBand(i + 1).WriteRaster(0, 0, panWidth, panHeight, resamptmp, panWidth, panHeight, 0, 0);
ResampDS.FlushCache();
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
//释放直方图匹配图像资源。
MatchingDS.Dispose();
if (File.Exists(HisMatFileName))
{
File.Delete(HisMatFileName);
}
FP.Output("已删除直方图匹配临时文件");
#endregion
//创建输出数据集。
OSGeo.GDAL.Dataset DS = Dri.Create(OutPath, panWidth, panHeight, 3, OutDataType, null);
FP.Output("已创建输出数据集\"" + OutPath + "\"，数据类型为" + OutDataType.ToString() + "。");
Tools.Common.CopyMetadata(PanDS, DS);
double[] p;
double[][] ms;
double[] ds;
for (int row = 0; row < panHeight; row++)
{
FP.SetProgress2("正在处理", row + 1, panHeight, "行");
//将全色波段行读取进数组。
p = new double[panWidth];
PanDS.GetRasterBand(1).ReadRaster(0, row, panWidth, 1, p, panWidth, 1, 0, 0);
//将重采样后的多光谱行读取进数组。
ms = new double[3][];
ms[0] = new double[panWidth];
ms[1] = new double[panWidth];
ms[2] = new double[panWidth];
ResampDS.GetRasterBand(1).ReadRaster(0, row, panWidth, 1, ms[0], panWidth, 1, 0, 0);
ResampDS.GetRasterBand(2).ReadRaster(0, row, panWidth, 1, ms[1], panWidth, 1, 0, 0);
ResampDS.GetRasterBand(3).ReadRaster(0, row, panWidth, 1, ms[2], panWidth, 1, 0, 0);
//遍历三波段
for (int bandcount = 0; bandcount < 3; bandcount++)
{
FP.SetProgress1("正在处理", bandcount + 1, 3, "波段");
ds = new double[panWidth]; //临时数组
for (long i = 0; i < panWidth; i++)
{
ds[i] = p[i] * ms[bandcount][i] / (ms[0][i] + ms[1][i] + ms[2][i]); //Brovey公式
}
DS.GetRasterBand(bandcount + 1).WriteRaster(0, row, panWidth, 1, ds, panWidth, 1, 0, 0); //计算完后的数据写入
DS.FlushCache();
}
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
//释放重采样图像资源。
ResampDS.Dispose();
if (File.Exists(ResampFileName))
{
File.Delete(ResampFileName);
}
FP.Output("已删除重采样临时文件");
/*一次性读取一时爽，遇到大文件爆内存。
* 一次性读取一时爽，遇到大文件爆内存。
* 一次性读取一时爽，遇到大文件爆内存。*/
//p = new double[panWidth * panHeight];
//ms = new double[3][];
//ms[0] = new double[panWidth * panHeight];
//ms[1] = new double[panWidth * panHeight];
//ms[2] = new double[panWidth * panHeight];
//PanDS.GetRasterBand(1).ReadRaster(0, 0, panWidth, panHeight, p, panWidth, panHeight, 0, 0);
//MSDS.GetRasterBand(MSBandList[0]).ReadRaster(0, 0, msWidth, msHeight, ms[0], panWidth, panHeight, 0, 0);
//MSDS.GetRasterBand(MSBandList[1]).ReadRaster(0, 0, msWidth, msHeight, ms[1], panWidth, panHeight, 0, 0);
//MSDS.GetRasterBand(MSBandList[2]).ReadRaster(0, 0, msWidth, msHeight, ms[2], panWidth, panHeight, 0, 0);
//for (int bandcount = 0; bandcount < 3; bandcount++)
//{
// ds = new double[panWidth * panHeight];
// for (int row = 0; row < panHeight; row++)
// {
// for (int col = 0; col < panWidth; col++)
// {
// ds[row * panWidth + col] = p[row * panWidth + col] * ms[bandcount][row * panWidth + col] / (ms[0][row * panWidth + col] + ms[1][row * panWidth + col] + ms[2][row * panWidth + col]);
// }
// }
// DS.GetRasterBand(bandcount + 1).WriteRaster(0, 0, panWidth, panHeight, ds, panWidth, panHeight, 0, 0);
// DS.FlushCache();
//}
FP.Finish();
Dri.Dispose();
DS.Dispose();
return(true);
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
return(false);
}
}
/// <summary>
/// 影像直方图匹配。
/// </summary>
/// <param name="InputDS">输入的数据集。</param>
/// <param name="MatchDS">要匹配到的数据集。</param>
/// <param name="InputCumu">输入的数据集的累积概率表。</param>
/// <param name="MatchingCumu">要匹配到的数据集的累积概率表。</param>
/// <param name="OutDataType">输出的数据类型。</param>
/// <param name="OutPath">输出栅格数据集的位置。</param>
/// <returns>操作成功或失败。</returns>
public static bool HistogramMatching(OSGeo.GDAL.Dataset InputDS, OSGeo.GDAL.Dataset MatchDS, double[][] InputCumu, double[][] MatchingCumu, OSGeo.GDAL.DataType OutDataType, string OutPath)
{
try
{
if (InputDS.RasterCount != MatchDS.RasterCount)
{
throw new ArgumentException("数据集波段数不一致。");
}
FrmProgress FP = new FrmProgress()
{
Text = "正在进行影像直方图匹配...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
int[][] LUT = new int[InputDS.RasterCount][];
FP.Output("正在计算查找表...");
for (int i = 0; i < InputDS.RasterCount; i++)
{
LUT[i] = HistogramMatching(InputCumu[i], MatchingCumu[i]);
}
OSGeo.GDAL.Driver Dri = OSGeo.GDAL.Gdal.GetDriverByName("Gtiff");
if (Dri == null)
{
throw new Exception("无法获取GDAL Driver。");
}
int xSize = InputDS.RasterXSize;
int ySize = InputDS.RasterYSize;
OSGeo.GDAL.Dataset DS = Dri.Create(OutPath, xSize, ySize, InputDS.RasterCount, OutDataType, null);
FP.Output("已创建输出数据集\"" + OutPath + "\"，数据类型为" + OutDataType.ToString() + "。");
Tools.Common.CopyMetadata(InputDS, DS);
for (int bandcount = 0; bandcount < InputDS.RasterCount; bandcount++)
{
FP.SetProgress2("正在处理", bandcount + 1, InputDS.RasterCount, "波段");
Tools.Common.GetMinimum(InputDS.GetRasterBand(bandcount + 1), out double inputDSBandMin);
Tools.Common.GetMinimum(MatchDS.GetRasterBand(bandcount + 1), out double matchDSBandMin);
for (int Row = 0; Row < ySize; Row++)
{
FP.SetProgress1("正在处理", Row + 1, ySize, "行");
double[] Values = new double[xSize];
//读取DN到数组
InputDS.GetRasterBand(bandcount + 1).ReadRaster(0, Row, xSize, 1, Values, xSize, 1, 0, 0);
for (int Col = 0; Col < xSize; Col++)
{
//防止GDAL自带方法算出的统计数据越界。
if ((Values[Col] - inputDSBandMin) <= 0)
{
Values[Col] = matchDSBandMin + LUT[bandcount][0];
continue;
}
if ((Values[Col] - inputDSBandMin) >= LUT[bandcount].Length - 1)
{
Values[Col] = matchDSBandMin + LUT[bandcount][LUT[bandcount].Length - 1];
continue;
}
Values[Col] = matchDSBandMin + LUT[bandcount][(int)(Values[Col] - inputDSBandMin)];
}
//写结果到新栅格
DS.GetRasterBand(bandcount + 1).WriteRaster(0, Row, xSize, 1, Values, xSize, 1, 0, 0);
DS.FlushCache();
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
}
FP.Finish();
Dri.Dispose();
DS.Dispose();
return(true);
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
return(false);
}
}
public static bool CalculateFloodArea(string InDir, string OutDir)
{
try
{
if (!Directory.Exists(InDir))
{
throw new FileNotFoundException("输入路径不存在。");
}
if (!Directory.Exists(OutDir))
{
Directory.CreateDirectory(OutDir);
}
OSGeo.GDAL.Driver Dri = OSGeo.GDAL.Gdal.GetDriverByName("Gtiff");
if (Dri == null)
{
throw new Exception("无法获取GDAL Driver。");
}
FrmProgress FP = new FrmProgress()
{
Text = "正在处理洪水范围...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
bool createFlag = true;
string[] ascFiles = Directory.GetFiles(InDir);
int xSize = 0;
int ySize = 0;
OSGeo.GDAL.Dataset rangeDS = new OSGeo.GDAL.Dataset(IntPtr.Zero, false, null);
OSGeo.GDAL.Dataset depthDS = new OSGeo.GDAL.Dataset(IntPtr.Zero, false, null);
OSGeo.GDAL.Dataset timeDS = new OSGeo.GDAL.Dataset(IntPtr.Zero, false, null);
for (int i = 0; i < ascFiles.Length; i++)
{
FP.SetProgress2("正在处理文件：", i + 1, ascFiles.Length, "");
string tmpPath = ascFiles[i];
FP.Output("正在处理：" + (i + 1).ToString() + ". " + tmpPath);
if (tmpPath.Substring(tmpPath.LastIndexOf(".")) != ".txt")
{
FP.Output(tmpPath + "不是txt文件。");
continue;
}
OSGeo.GDAL.Dataset tmpDS = OSGeo.GDAL.Gdal.Open(tmpPath, OSGeo.GDAL.Access.GA_ReadOnly);
if (createFlag)
{
xSize = tmpDS.RasterXSize;
ySize = tmpDS.RasterYSize;
string inDirName = Path.GetDirectoryName(tmpPath).Substring(Path.GetDirectoryName(tmpPath).LastIndexOf("\\") + 1);
rangeDS = Dri.Create(Path.Combine(OutDir, inDirName + "_floodRange.tiff"), xSize, ySize, 1, OSGeo.GDAL.DataType.GDT_Float32, null);
Tools.Common.CopyMetadata(tmpDS, rangeDS);
FP.Output("已创建输出数据集\"" + Path.Combine(OutDir, inDirName + "_floodRange.tiff") + "\"。");
depthDS = Dri.Create(Path.Combine(OutDir, inDirName + "_floodDepth.tiff"), xSize, ySize, 1, OSGeo.GDAL.DataType.GDT_Float32, null);
Tools.Common.CopyMetadata(tmpDS, depthDS);
FP.Output("已创建输出数据集\"" + Path.Combine(OutDir, inDirName + "_floodDepth.tiff") + "\"。");
timeDS = Dri.Create(Path.Combine(OutDir, inDirName + "_floodTime.tiff"), xSize, ySize, 1, OSGeo.GDAL.DataType.GDT_Float32, null);
Tools.Common.CopyMetadata(tmpDS, timeDS);
FP.Output("已创建输出数据集\"" + Path.Combine(OutDir, inDirName + "_floodTime.tiff") + "\"。");
createFlag = false;
}
for (int Row = 0; Row < ySize; Row++)
{
double[] tmpValues = new double[xSize];
double[] rangeValues = new double[xSize];
double[] depthValues = new double[xSize];
double[] timeValues = new double[xSize];
tmpDS.GetRasterBand(1).ReadRaster(0, Row, xSize, 1, tmpValues, xSize, 1, 0, 0);
rangeDS.GetRasterBand(1).ReadRaster(0, Row, xSize, 1, rangeValues, xSize, 1, 0, 0);
depthDS.GetRasterBand(1).ReadRaster(0, Row, xSize, 1, depthValues, xSize, 1, 0, 0);
timeDS.GetRasterBand(1).ReadRaster(0, Row, xSize, 1, timeValues, xSize, 1, 0, 0);
for (int Col = 0; Col < xSize; Col++)
{
//计算洪水范围
if (Math.Abs(tmpValues[Col]) <= 1e-7) //Nodata
{
continue;
}
else
{
rangeValues[Col] = 1;
if (tmpValues[Col] > depthValues[Col])
{
depthValues[Col] = tmpValues[Col];
}
timeValues[Col] += 1;
}
}
rangeDS.GetRasterBand(1).WriteRaster(0, Row, xSize, 1, rangeValues, xSize, 1, 0, 0);
rangeDS.FlushCache();
depthDS.GetRasterBand(1).WriteRaster(0, Row, xSize, 1, depthValues, xSize, 1, 0, 0);
depthDS.FlushCache();
timeDS.GetRasterBand(1).WriteRaster(0, Row, xSize, 1, timeValues, xSize, 1, 0, 0);
timeDS.FlushCache();
}
tmpDS.Dispose();
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
FP.Finish();
rangeDS.Dispose();
depthDS.Dispose();
timeDS.Dispose();
return(true);
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
return(false);
}
}
/// <summary>
/// 导出当前视图。
/// </summary>
/// <param name="InputImg">影像对象。</param>
/// <param name="OutDataType">输出数据类型。</param>
/// <param name="OutPath">输出路径。</param>
/// <returns>返回操作成功或失败。</returns>
public static bool ExportView(Img InputImg, OSGeo.GDAL.DataType OutDataType, string OutPath)
{
try
{
if (OutPath == InputImg.Path)
{
throw new Exception("输出路径与源文件相同。");
}
if (InputImg.GDALDataset == null)
{
throw new ArgumentNullException("输入数据集为空。");
}
if (String.IsNullOrWhiteSpace(OutPath.Trim()))
{
throw new ArgumentNullException("输出路径为空或非法。");
}
OSGeo.GDAL.Driver Dri = OSGeo.GDAL.Gdal.GetDriverByName("Gtiff");
if (Dri == null)
{
throw new Exception("无法获取GDAL Driver。");
}
int xSize = InputImg.Width;
int ySize = InputImg.Height;
int Bandnum = 3;
if (InputImg.IsGrayscale)
{
Bandnum = 1;
}
else
{
Bandnum = 3;
}
FrmProgress FP = new FrmProgress()
{
Text = "正在导出影像...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
OSGeo.GDAL.Dataset DS = Dri.Create(OutPath, xSize, ySize, Bandnum, OutDataType, null);
FP.Output("已创建输出数据集\"" + OutPath + "\"，数据类型为" + OutDataType.ToString() + "。");
Tools.Common.CopyMetadata(InputImg.GDALDataset, DS);
for (int i = 0; i < Bandnum; i++) //遍历每个波段
{
FP.SetProgress2("正在处理", i + 1, Bandnum, "波段");
for (int Row = 0; Row < ySize; Row++) //遍历每一行(y)
{
FP.SetProgress1("正在处理", Row + 1, ySize, "行");
double[] Values = new double[xSize];
//读取DN到数组
InputImg.GDALDataset.GetRasterBand(InputImg.BandList[i]).ReadRaster(0, Row, xSize, 1, Values, xSize, 1, 0, 0);
for (int Col = 0; Col < xSize; Col++) //对每一个值进行计算
{
//无拉伸不做处理直接导出
if (InputImg.StretchMode == 0)
{
break;
}
//已经有处理的情形
switch (InputImg.StretchMode)
{
case 1:
case 2:
case 3:
case 4:
case 9:
{
//线性
Values[Col] = LinearStretch(Values[Col], InputImg.StretchInfo[InputImg.BandList[i] - 1].Item1, InputImg.StretchInfo[InputImg.BandList[i] - 1].Item2);
break;
}
case 5:
{
//直方图均衡
Values[Col] = EqualizationStretch(Values[Col], InputImg.CumulativeProbability[InputImg.BandList[i] - 1], InputImg.Min[InputImg.BandList[i] - 1], InputImg.Max[InputImg.BandList[i] - 1]);
break;
}
case 6:
{
//高斯
Values[Col] = GaussianStretch(Values[Col], InputImg.CumulativeProbability[InputImg.BandList[i] - 1], InputImg.Min[InputImg.BandList[i] - 1], InputImg.Mean[InputImg.BandList[i] - 1], InputImg.Stddev[InputImg.BandList[i] - 1]);
break;
}
case 7:
{
//平方根
Values[Col] = SquarerootStretch(Values[Col], InputImg.Min[InputImg.BandList[i] - 1], InputImg.Max[InputImg.BandList[i] - 1]);
break;
}
case 8:
{
//对数
Values[Col] = LinearStretch(LogarithmicStretch(Values[Col], InputImg.Min[InputImg.BandList[i] - 1], InputImg.Max[InputImg.BandList[i] - 1]), InputImg.Min[InputImg.BandList[i] - 1], InputImg.Max[InputImg.BandList[i] - 1]);
break;
}
default:
{
//不是0-9还能是啥？
throw new Exception("拉伸模式未知。");
}
}
}
//写结果到新栅格
DS.GetRasterBand(i + 1).WriteRaster(0, Row, xSize, 1, Values, xSize, 1, 0, 0);
DS.FlushCache();
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
}
FP.Finish();
Dri.Dispose();
DS.Dispose();
return(true);
}
catch (Exception err)
{
MessageBox.Show(err.Message);
return(false);
}
}
/// <summary>
/// 平滑锐化算法。
/// </summary>
/// <param name="InputDS">输入的栅格数据集。</param>
/// <param name="OutDataType">输出的数据类型。</param>
/// <param name="Method">平滑锐化方法。</param>
/// <param name="OutPath">输出栅格数据集的位置。</param>
/// <returns>返回操作成功或失败。</returns>
public static bool SmoothSharpening(OSGeo.GDAL.Dataset InputDS, OSGeo.GDAL.DataType OutDataType, SmoothShapeninngMethods Method, string OutPath)
{
try
{
if (InputDS == null)
{
throw new ArgumentNullException("输入数据集为空。");
}
if (String.IsNullOrWhiteSpace(OutPath.Trim()))
{
throw new ArgumentNullException("输出路径为空或非法。");
}
OSGeo.GDAL.Driver Dri = OSGeo.GDAL.Gdal.GetDriverByName("Gtiff");
if (Dri == null)
{
throw new Exception("无法获取GDAL Driver。");
}
int xSize = InputDS.RasterXSize;
int ySize = InputDS.RasterYSize;
FrmProgress FP = new FrmProgress()
{
Text = "正在进行平滑锐化操作...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
FP.Output("选择的平滑/锐化方法为：\"" + (typeof(SmoothShapeninngMethods).GetField((Method).ToString()).GetCustomAttributes(false)[0] as DescriptionAttribute).Description + "\"");
OSGeo.GDAL.Dataset DS = Dri.Create(OutPath, xSize, ySize, InputDS.RasterCount, OutDataType, null);
FP.Output("已创建输出数据集\"" + OutPath + "\"，数据类型为" + OutDataType.ToString() + "。");
Tools.Common.CopyMetadata(InputDS, DS);
for (int band = 0; band < InputDS.RasterCount; band++) //遍历每个波段
{
FP.SetProgress1("正在处理", band + 1, InputDS.RasterCount, "波段");
for (int Row = 0; Row < ySize - 2; Row++) //从第1行遍历至倒数第三行
{
FP.SetProgress2("正在处理", Row, ySize - 2, "行");
double[] Values = new double[3 * xSize]; //读取的数值
double[] Result = new double[xSize]; //结果数值
InputDS.GetRasterBand(band + 1).ReadRaster(0, Row, xSize, 3, Values, xSize, 3, 0, 0); //读取3行
Array.Copy(Values, xSize, Result, 0, xSize); //
for (int Col = 0; Col < xSize - 2; Col++) //对每一个值进行计算
{
double[,] Input = new double[3, 3];
for (int i = 0; i < 3; i++)
{
Input[i, 0] = Values[Col + i * xSize];
Input[i, 1] = Values[Col + i * xSize + 1];
Input[i, 2] = Values[Col + i * xSize + 2];
}
Result[Col + 1] = SmoothSharpening(Input, Method); //计算输入数据中心像元的值
}
//写结果到新栅格
DS.GetRasterBand(band + 1).WriteRaster(0, Row + 1, xSize, 1, Result, xSize, 1, 0, 0);
}
if ((Method.ToString()).Contains("Smooth"))
{
double[] row = new double[xSize];
InputDS.GetRasterBand(band + 1).ReadRaster(0, 0, xSize, 1, row, xSize, 1, 0, 0); //读取第一行
DS.GetRasterBand(band + 1).WriteRaster(0, 0, xSize, 1, row, xSize, 1, 0, 0);
InputDS.GetRasterBand(band + 1).ReadRaster(0, ySize - 1, xSize, 1, row, xSize, 1, 0, 0); //读取最后一行
DS.GetRasterBand(band + 1).WriteRaster(0, ySize - 1, xSize, 1, row, xSize, 1, 0, 0);
}
DS.FlushCache();
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
FP.Finish();
Dri.Dispose();
DS.Dispose();
return(true);
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
return(false);
}
}
/// <summary>
/// 迭代阈值法寻找分割阈值。
/// </summary>
/// <param name="InputDS">输入的数据集。</param>
/// <param name="ThresholdDiff">前后阈值之差的变化限值，小于此值则终止循环。</param>
/// <returns>最优阈值。</returns>
public static double IterateThreshold(OSGeo.GDAL.Dataset InputDS, double ThresholdDiff = 1)
{
try
{
if (InputDS == null)
{
throw new ArgumentNullException("输入数据集为空。");
}
if (InputDS.RasterCount != 1)
{
throw new ArgumentException("输入的数据集波段大于1。");
}
FrmProgress FP = new FrmProgress()
{
Text = "正在使用迭代阈值法寻找分割阈值...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
FP.Output("正在计算影像统计数据...");
Tools.Common.ComputeRasterMinMax(InputDS.GetRasterBand(1), out double Min, out double Max);
//初始阈值及新阈值。
double tmpThreshold = (Min + Max) / 2.0;
double newThreshold = 1000000;
double Diff = 1000000; //迭代T值之差。
FP.Output("最小值：" + Min.ToString() + "\r\n最大值：" + Max.ToString() + "\r\n变化阈值：" + ThresholdDiff.ToString());
while (Diff >= ThresholdDiff)
{
FP.SetProgress1("阈值变化", ThresholdDiff, Diff, "");
//前景、背景像元平均值及计数。
double foregroundAvg = 0.0, backgroundAvg = 0.0;
int foregroundCount = 0, backgroundCount = 0;
for (int row = 0; row < InputDS.RasterYSize; row++)
{
FP.SetProgress2("迭代已处理", row + 1, InputDS.RasterYSize, "行");
double[] tmp = new double[InputDS.RasterXSize];
InputDS.GetRasterBand(1).ReadRaster(0, row, InputDS.RasterXSize, 1, tmp, InputDS.RasterXSize, 1, 0, 0);
for (int col = 0; col < InputDS.RasterXSize; col++)
{
//逐像元累加前、背景计数和总和。
if (ThresholdCheck(tmp[col], tmpThreshold))
{
foregroundCount++;
foregroundAvg += tmp[col];
}
else
{
backgroundCount++;
backgroundAvg += tmp[col];
}
}
}
foregroundAvg /= foregroundCount;
backgroundAvg /= backgroundCount;
newThreshold = (foregroundAvg + backgroundAvg) / 2.0;
Diff = Math.Abs(newThreshold - tmpThreshold); //阈值差
tmpThreshold = newThreshold;
FP.Output("新的阈值：" + newThreshold.ToString());
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
FP.Finish();
return(newThreshold);
}
catch (Exception err)
{
MessageBox.Show(err.Message);
return(0);
}
}
/// <summary>
/// Otsu（最大类间方差法）寻找分割阈值。
/// </summary>
/// <param name="InputDS">输入的数据集。</param>
/// <param name="Divide">将最大最小值区间内分割为的份数。</param>
/// <returns>最优阈值。</returns>
public static double Otsu(OSGeo.GDAL.Dataset InputDS, int Divide = 256)
{
try
{
if (InputDS == null)
{
throw new ArgumentNullException("输入数据集为空。");
}
if (InputDS.RasterCount != 1)
{
throw new ArgumentException("输入的数据集波段大于1。");
}
double[] g = new double[Divide];
FrmProgress FP = new FrmProgress()
{
Text = "正在使用Otsu法寻找分割阈值...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
FP.Output("正在计算影像统计数据...");
Tools.Common.ComputeRasterMinMax(InputDS.GetRasterBand(1), out double Min, out double Max);
FP.Output("最小值：" + Min.ToString() + "\r\n最大值：" + Max.ToString() + "\r\n分割段数：" + Divide.ToString());
for (int i = 1; i <= Divide; i++)
{
FP.SetProgress2("正在计算：", i, Divide, "区间");
double foregroundRatio = 0.0, foregroundAvg = 0.0, backgroundRatio = 0.0, backgroundAvg = 0.0;
int foregroundCount = 0, backgroundCount = 0;
double tmpThreshold = Min + (Max - Min) * ((double)i / Divide);
for (int row = 0; row < InputDS.RasterYSize; row++)
{
FP.SetProgress1("正在处理：", row + 1, InputDS.RasterYSize, "行");
double[] tmp = new double[InputDS.RasterXSize];
InputDS.GetRasterBand(1).ReadRaster(0, row, InputDS.RasterXSize, 1, tmp, InputDS.RasterXSize, 1, 0, 0);
for (int col = 0; col < InputDS.RasterXSize; col++)
{
//逐像元累加前、背景计数和总和。
if (ThresholdCheck(tmp[col], tmpThreshold))
{
foregroundCount++;
foregroundAvg += tmp[col];
}
else
{
backgroundCount++;
backgroundAvg += tmp[col];
}
}
}
foregroundRatio = (double)foregroundCount / (foregroundCount + backgroundCount);
foregroundAvg /= foregroundCount;
backgroundRatio = (double)backgroundCount / (foregroundCount + backgroundCount);
backgroundAvg /= backgroundCount;
double totalGrayAvg = foregroundRatio * foregroundAvg + backgroundRatio * backgroundAvg;
g[i - 1] = foregroundRatio * backgroundRatio * Math.Pow(foregroundAvg - backgroundAvg, 2);
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
//找一个最小值
int index = 0;
double max = -100000000;
for (int i = 0; i < Divide; i++)
{
if (g[i] > max)
{
max = g[i];
index = i;
}
}
FP.Finish();
return(Min + (Max - Min) * ((double)index / (Divide - 1)));
}
catch (Exception err)
{
MessageBox.Show(err.Message);
return(0);
}
}
/// <summary>
/// ISO Data分类算法。
/// </summary>
/// <param name="InputDS">输入的数据集。</param>
/// <param name="MinKind">最小分类数。</param>
/// <param name="MaxKind">最大分类数。</param>
/// <param name="MaxItera">最大迭代次数。</param>
/// <param name="CenterDiff">最大中心变化率</param>
/// <param name="MinPixelNumInClass">类内最小像元数。</param>
/// <param name="MaxClassStddev">最大类内标准差</param>
/// <param name="MinClassDist">最小类间距离。</param>
/// <param name="OutPath">结果数据集输出路径。</param>
/// <returns>操作成功或失败。</returns>
public static bool IsoData(OSGeo.GDAL.Dataset InputDS, int MinKind, int MaxKind, int MaxItera, double CenterDiff, int MinPixelNumInClass, double MaxClassStddev, double MinClassDist, string OutPath)
{
try
{
if (InputDS == null)
{
throw new ArgumentNullException("输入数据集为空。");
}
if (String.IsNullOrWhiteSpace(OutPath.Trim()))
{
throw new ArgumentNullException("输出路径为空或非法。");
}
OSGeo.GDAL.Driver Dri = OSGeo.GDAL.Gdal.GetDriverByName("Gtiff");
if (Dri == null)
{
throw new Exception("无法获取GDAL Driver。");
}
int bandNum = InputDS.RasterCount;
int xSize = InputDS.RasterXSize;
int ySize = InputDS.RasterYSize;
FrmProgress FP = new FrmProgress()
{
Text = "正在进行ISO Data分类...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
OSGeo.GDAL.Dataset DS = Dri.Create(OutPath, xSize, ySize, 1, OSGeo.GDAL.DataType.GDT_Byte, null);
FP.Output("已创建输出数据集\"" + OutPath + "\"，数据类型为GDT_Byte。");
Tools.Common.CopyMetadata(InputDS, DS);
int tmpItera = 1;
bool tmpContinue = true;
double[] min = new double[bandNum];
double[] max = new double[bandNum];
double[] mean = new double[bandNum];
double[] stddev = new double[bandNum];
int InitKind = (MinKind + MaxKind) / 2;
List <ClusterCenter> ICenter = new List <ClusterCenter>();
//计算数据集各波段统计数据
for (int i = 0; i < bandNum; i++)
{
Tools.Common.GetStatistics(InputDS.GetRasterBand(i + 1), out min[i], out max[i], out mean[i], out stddev[i]);
}
//初始化聚类中心
for (int i = 0; i < InitKind; i++)
{
ICenter.Add(new ClusterCenter(bandNum));
for (int band = 0; band < bandNum; band++)
{
ICenter[i].NewCenter[band] = ICenter[i].OldCenter[band] = mean[band] + stddev[band] - 2 * i * stddev[band] / InitKind;
}
}
//循环体
while (tmpContinue)
{
FP.Output("正在迭代第" + tmpItera.ToString() + "次...");
FP.SetProgress2("正在迭代：", tmpItera, MaxItera, "次");
//清空所有聚类中心的和、平均值、标准差、像元列表
foreach (ClusterCenter C in ICenter)
{
C.ResetAll();
}
//重置所有类的像元计数为0
for (int i = 0; i < ICenter.Count; i++)
{
ICenter[i].PixelCount = 0;
}
for (int i = 0; i < ICenter.Count; i++)
{
string tmpCenter = "第" + (i + 1).ToString() + "类中心：";
for (int band = 0; band < bandNum; band++)
{
tmpCenter += ICenter[i].OldCenter[band] + ", ";
}
FP.Output(tmpCenter);
}
//遍历数据集每一行
for (int row = 0; row < ySize; row++)
{
FP.SetProgress1("正在处理：", row + 1, ySize, "行");
double[][] tmpInput = new double[bandNum][]; //用于存储输入像元的交错数组
//将一行的所有波段像元值读取入交错数组
for (int band = 0; band < bandNum; band++)
{
tmpInput[band] = new double[xSize];
InputDS.GetRasterBand(band + 1).ReadRaster(0, row, xSize, 1, tmpInput[band], xSize, 1, 0, 0);
}
byte[] tmpOut = new byte[xSize]; //用于存储输出像元的数组
//遍历一行的每一列，对像元分类
for (int col = 0; col < xSize; col++)
{
double[] tmpPix = new double[bandNum]; //临时存储单个像元所有波段的数组
//将指定行列的所有波段像元转储到数组
for (int band = 0; band < bandNum; band++)
{
tmpPix[band] = tmpInput[band][col];
}
double[] tmpDis = new double[ICenter.Count]; //单个像元到不同聚类中心的距离数组
//计算像元到不同聚类中心的距离
for (int i = 0; i < ICenter.Count; i++)
{
tmpDis[i] = Distance(tmpPix, ICenter[i].OldCenter);
}
double tmpMinDis = tmpDis[0]; //最小距离
int tmpClass = 0; //分类
//计算最小值及分类
for (int i = 1; i < ICenter.Count; i++)
{
if (tmpDis[i] < tmpMinDis)
{
tmpMinDis = tmpDis[i];
tmpClass = i;
}
}
//将该像元添加到对应聚类的列表中
ICenter[tmpClass].CenterList.Add(tmpPix);
//写入分类并增加对应类的像元计数
tmpOut[col] = (byte)(tmpClass + 1);
ICenter[tmpClass].PixelCount += 1;
}
DS.GetRasterBand(1).WriteRaster(0, row, xSize, 1, tmpOut, xSize, 1, 0, 0);
DS.FlushCache();
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
//重新计算每个集群的均值和方差
foreach (ClusterCenter c in ICenter)
{
c.GetStddev(); //计算方差之前会自动求和和平均值
//将聚类中所有像元的平均值作为聚类的新中心？
for (int band = 0; band < bandNum; band++)
{
c.NewCenter[band] = c.CenterMean[band];
}
}
for (int i = 0; i < ICenter.Count; i++)
{
string tmpCenter = "聚类后第" + (i + 1).ToString() + "类：";
tmpCenter += "\r\n\t像元数：" + ICenter[i].PixelCount + ", ";
tmpCenter += "\r\n\t和：";
for (int band = 0; band < bandNum; band++)
{
tmpCenter += ICenter[i].CenterTotal[band] + ", ";
}
tmpCenter += "\r\n\t平均中心：";
for (int band = 0; band < bandNum; band++)
{
tmpCenter += ICenter[i].CenterMean[band] + ", ";
}
tmpCenter += "\r\n\t标准差：";
for (int band = 0; band < bandNum; band++)
{
tmpCenter += ICenter[i].CenterStddev[band] + ", ";
}
FP.Output(tmpCenter);
}
bool tmpCenterModified = false; //判断是否有聚类中心数量的变动
Delete:
//删除像元数在阈值以下的聚类
for (int i = 0; i < ICenter.Count; i++)
{
if (ICenter[i].PixelCount < MinPixelNumInClass)
{
FP.Output("第" + (i + 1).ToString() + "类像元数只有" + ICenter[i].PixelCount.ToString() + "个，将被删除。");
if (ICenter.Count - 1 >= MinKind)
{
tmpCenterModified = true;
ICenter.RemoveAt(i);
goto Delete;
}
else
{
FP.Output("第" + (i + 1).ToString() + "类删除失败，已达到最小分类数。");
goto EndDelete;
}
}
}
EndDelete :;
//合并与分裂
List <ClusterCenter> tmpChangeCenter = new List <ClusterCenter>(); //用于暂存对全局列表的更改
//偶次合并
if (tmpItera % 2 == 0)
{
Combine:
for (int i = 0; i < ICenter.Count; i++)
{
for (int j = 0; j < ICenter.Count; j++)
{
//不与自身比较
if (i == j)
{
continue;
}
//类间距离小于设定阈值，进行合并
if (Distance(ICenter[i].CenterMean, ICenter[j].CenterMean) < MinClassDist)
{
FP.Output("第" + (i + 1).ToString() + "类和第" + (j + 1).ToString() + "类的距离过小，为" + Distance(ICenter[i].CenterMean, ICenter[j].CenterMean) + "，将被合并。");
if (ICenter.Count - 1 >= MinKind)
{
tmpCenterModified = true;
tmpChangeCenter.Add(new ClusterCenter(ICenter[i], ICenter[j])); //合并两类并在临时列表中新建中心。
//考虑i、j的大小，依次删除全局列表中对应索引处的中心（从大的开始删除）。
if (i > j)
{
ICenter.RemoveAt(i);
ICenter.RemoveAt(j);
}
else
{
ICenter.RemoveAt(j);
ICenter.RemoveAt(i);
}
//每次迭代是只合并一次嘛？如果是的话就不需要goto
goto Combine;
}
else
{
FP.Output("第" + (i + 1).ToString() + "类和第" + (j + 1).ToString() + "类合并失败，已达到最小分类数。");
goto EndCombine;
}
}
}
}
EndCombine :;
}
else //奇次分裂
{
Split :
for (int i = 0; i < ICenter.Count; i++)
{
if (ICenter[i].MaxStddev > MaxClassStddev)
{
FP.Output("第" + (i + 1).ToString() + "类的类内最大方差为" + ICenter[i].MaxStddev.ToString() + "，将被分裂。");
if (ICenter.Count + 1 <= MaxKind)
{
tmpCenterModified = true;
ClusterCenter C1 = new ClusterCenter(bandNum);
ClusterCenter C2 = new ClusterCenter(bandNum);
//新建两聚类，中心为旧中心加减方差的一半
//分裂后中心的参数怎么算？
for (int band = 0; band < bandNum; band++)
{
//只改变大于标准差的中心值，若不大于则保持不变。
if (ICenter[i].CenterStddev[band] > MaxClassStddev)
{
C1.OldCenter[band] = C1.NewCenter[band] = ICenter[i].NewCenter[band] + ICenter[i].CenterStddev[band] / 2;
C2.OldCenter[band] = C2.NewCenter[band] = ICenter[i].NewCenter[band] - ICenter[i].CenterStddev[band] / 2;
}
else
{
C1.OldCenter[band] = C1.NewCenter[band] = ICenter[i].NewCenter[band];
C2.OldCenter[band] = C2.NewCenter[band] = ICenter[i].NewCenter[band];
}
//C1.OldCenter[band] = C1.NewCenter[band] = ICenter[i].NewCenter[band] + MaxClassStddev / 2;
//C2.OldCenter[band] = C2.NewCenter[band] = ICenter[i].NewCenter[band] - MaxClassStddev / 2;
}
tmpChangeCenter.Add(C1);
tmpChangeCenter.Add(C2);
ICenter.RemoveAt(i);
goto Split;
}
else
{
FP.Output("第" + (i + 1).ToString() + "类分裂失败，已达到最大分类数。");
goto EndSplit;
}
}
}
EndSplit :;
}
double tmpCenterChangeMax = 100000000;
//仅在聚类中心数量没有变化的时候才计算中心变化率
if (!tmpCenterModified)
{
double[] tmpCenterChange = new double[ICenter.Count];
//计算聚类中心变化率
for (int i = 0; i < ICenter.Count; i++)
{
for (int band = 0; band < bandNum; band++)
{
if (Math.Abs(ICenter[i].OldCenter[band]) <= 1e-7) //分母为0
{
tmpCenterChange[i] += Math.Abs(ICenter[i].NewCenter[band] - ICenter[i].OldCenter[band]) / 0.0001;
}
else
{
tmpCenterChange[i] += Math.Abs(ICenter[i].NewCenter[band] - ICenter[i].OldCenter[band]) / ICenter[i].OldCenter[band];
}
}
tmpCenterChange[i] /= bandNum;
}
//计算最大变化率
tmpCenterChangeMax = tmpCenterChange[0];
for (int i = 1; i < ICenter.Count; i++)
{
if (tmpCenterChange[i] > tmpCenterChangeMax)
{
tmpCenterChangeMax = tmpCenterChange[i];
}
}
FP.Output("中心变化率：" + tmpCenterChangeMax + "，阈值：" + CenterDiff);
FP.SetProgress1("最大中心变化率：", CenterDiff, tmpCenterChangeMax, "");
}
else
{
FP.Output("第" + tmpItera.ToString() + "次迭代出现聚类中心的合并或分裂，不计算中心变化率...");
}
//将新的中心变为旧的中心，准备开始新一轮迭代
for (int i = 0; i < ICenter.Count; i++)
{
for (int band = 0; band < bandNum; band++)
{
ICenter[i].OldCenter[band] = ICenter[i].NewCenter[band];
}
}
//将临时新建的聚类中心添加到全局聚类中心的末尾，并清空临时聚类中心
ICenter.AddRange(tmpChangeCenter);
tmpChangeCenter.Clear();
tmpItera++;
//判断是否继续循环。
if (tmpItera % 2 == 0)
{
if (((MaxItera > 1) && (tmpItera > MaxItera)) || (!tmpCenterModified && tmpCenterChangeMax < CenterDiff) || (tmpItera > 10000))
{
tmpContinue = false;
}
}
}
FP.Finish();
DS.Dispose();
return(true);
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
return(false);
}
}
/// <summary>
/// K-Means算法。
/// </summary>
/// <param name="InputDS">输入的数据集。</param>
/// <param name="Kind">分类数。</param>
/// <param name="MaxItera">最大迭代次数。</param>
/// <param name="CenterDiff">聚类中心变化率阈值。</param>
/// <param name="OutPath">输出路径。</param>
/// <returns>操作成功或失败。</returns>
public static bool KMeans(OSGeo.GDAL.Dataset InputDS, int Kind, int MaxItera, double CenterDiff, string OutPath)
{
try
{
if (InputDS == null)
{
throw new ArgumentNullException("输入数据集为空。");
}
if (String.IsNullOrWhiteSpace(OutPath.Trim()))
{
throw new ArgumentNullException("输出路径为空或非法。");
}
OSGeo.GDAL.Driver Dri = OSGeo.GDAL.Gdal.GetDriverByName("Gtiff");
if (Dri == null)
{
throw new Exception("无法获取GDAL Driver。");
}
int bandNum = InputDS.RasterCount;
int xSize = InputDS.RasterXSize;
int ySize = InputDS.RasterYSize;
FrmProgress FP = new FrmProgress()
{
Text = "正在进行K-Means分类...",
};
Thread t = new Thread(() =>
{
FP.ShowDialog();
});
t.SetApartmentState(ApartmentState.STA);
t.Start();
OSGeo.GDAL.Dataset DS = Dri.Create(OutPath, xSize, ySize, 1, OSGeo.GDAL.DataType.GDT_Byte, null);
FP.Output("已创建输出数据集\"" + OutPath + "\"，数据类型为GDT_Byte。");
Tools.Common.CopyMetadata(InputDS, DS);
int tmpItera = 0;
bool tmpContinue = true;
double[] min = new double[bandNum];
double[] max = new double[bandNum];
double[] mean = new double[bandNum];
double[] stddev = new double[bandNum];
ClusterCenter[] KCenter = new ClusterCenter[Kind];
//计算数据集各波段统计数据
for (int i = 0; i < bandNum; i++)
{
Tools.Common.GetStatistics(InputDS.GetRasterBand(i + 1), out min[i], out max[i], out mean[i], out stddev[i]);
}
//初始化聚类中心
for (int i = 0; i < Kind; i++)
{
KCenter[i] = new ClusterCenter(bandNum);
for (int band = 0; band < bandNum; band++)
{
KCenter[i].NewCenter[band] = KCenter[i].OldCenter[band] = mean[band] + stddev[band] - 2 * i * stddev[band] / Kind;
}
}
//循环体
while (tmpContinue)
{
FP.Output("正在迭代第" + (tmpItera + 1).ToString() + "次...");
FP.SetProgress2("正在迭代：", tmpItera + 1, MaxItera, "次");
//重置所有类的像元计数为1
for (int i = 0; i < Kind; i++)
{
KCenter[i].PixelCount = 1;
}
for (int i = 0; i < Kind; i++)
{
string tmpCenter = "第" + (i + 1).ToString() + "类中心：\r\n";
for (int band = 0; band < bandNum; band++)
{
tmpCenter += "\t第" + (band + 1).ToString() + "波段中心：" + KCenter[i].OldCenter[band] + "\r\n";
}
FP.Output(tmpCenter);
}
//遍历数据集每一行
for (int row = 0; row < ySize; row++)
{
FP.SetProgress1("正在处理：", row + 1, ySize, "行");
double[][] tmpInput = new double[bandNum][]; //用于存储输入像元的交错数组
//将一行的所有波段像元值读取入交错数组
for (int band = 0; band < bandNum; band++)
{
tmpInput[band] = new double[xSize];
InputDS.GetRasterBand(band + 1).ReadRaster(0, row, xSize, 1, tmpInput[band], xSize, 1, 0, 0);
}
byte[] tmpOut = new byte[xSize]; //用于存储输出像元的数组
//遍历一行的每一列，对像元分类
for (int col = 0; col < xSize; col++)
{
double[] tmpPix = new double[bandNum]; //临时存储单个像元所有波段的数组
//将指定行列的所有波段像元转储到数组
for (int band = 0; band < bandNum; band++)
{
tmpPix[band] = tmpInput[band][col];
}
double[] tmpDis = new double[Kind]; //单个像元到不同聚类中心的距离数组
//计算像元到不同聚类中心的距离
for (int i = 0; i < Kind; i++)
{
tmpDis[i] = Distance(tmpPix, KCenter[i].OldCenter);
}
double tmpMinDis = tmpDis[0]; //最小距离
int tmpClass = 0; //分类
//计算最小值及分类
for (int i = 1; i < Kind; i++)
{
if (tmpDis[i] < tmpMinDis)
{
tmpMinDis = tmpDis[i];
tmpClass = i;
}
}
//更新聚类中心
for (int band = 0; band < bandNum; band++)
{
KCenter[tmpClass].NewCenter[band] = (KCenter[tmpClass].NewCenter[band] * KCenter[tmpClass].PixelCount + tmpPix[band]) / (KCenter[tmpClass].PixelCount + 1);
}
//写入分类并增加对应类的像元计数
tmpOut[col] = (byte)(tmpClass + 1);
KCenter[tmpClass].PixelCount += 1;
}
DS.GetRasterBand(1).WriteRaster(0, row, xSize, 1, tmpOut, xSize, 1, 0, 0);
DS.FlushCache();
Thread.Sleep(1);
if (FP.Canceled)
{
Thread.Sleep(500);
FP.Finish();
throw new OperationCanceledException("操作被用户取消。");
}
}
for (int i = 0; i < Kind; i++)
{
string tmpCenter = "聚类后第" + (i + 1).ToString() + "类：\r\n\t新中心：";
for (int band = 0; band < bandNum; band++)
{
tmpCenter += KCenter[i].NewCenter[band] + ", ";
}
FP.Output(tmpCenter);
}
double[] tmpCenterChange = new double[Kind];
//计算聚类中心变化率
for (int i = 0; i < Kind; i++)
{
for (int band = 0; band < bandNum; band++)
{
if (Math.Abs(KCenter[i].OldCenter[band]) <= 1e-7) //分母为0
{
tmpCenterChange[i] += Math.Abs(KCenter[i].NewCenter[band] - KCenter[i].OldCenter[band]) / 0.0001;
}
else
{
tmpCenterChange[i] += Math.Abs(KCenter[i].NewCenter[band] - KCenter[i].OldCenter[band]) / KCenter[i].OldCenter[band];
}
}
tmpCenterChange[i] /= bandNum;
}
//计算最大变化率
double tmpCenterChangeMax = tmpCenterChange[0];
for (int i = 1; i < Kind; i++)
{
if (tmpCenterChange[i] > tmpCenterChangeMax)
{
tmpCenterChangeMax = tmpCenterChange[i];
}
}
FP.Output("中心变化率：" + tmpCenterChangeMax + "，阈值：" + CenterDiff);
FP.SetProgress1("最大中心变化率：", CenterDiff, tmpCenterChangeMax, "");
//将新的中心变为旧的中心，准备开始新一轮迭代
for (int i = 0; i < Kind; i++)
{
for (int band = 0; band < bandNum; band++)
{
KCenter[i].OldCenter[band] = KCenter[i].NewCenter[band];
}
}
tmpItera++;
//判断是否继续循环
if (((MaxItera > 1) && (tmpItera > MaxItera)) || (tmpCenterChangeMax < CenterDiff) || (tmpItera > 10000))
{
tmpContinue = false;
}
}
FP.Finish();
DS.Dispose();
return(true);
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
return(false);
}
}