private void 八邻域函数ToolStripMenuItem_Click(object sender, EventArgs e)
{
Apicturegrayinformation[] ApicturegrayinformationArray;
ArrayList neighbourhood = new ArrayList();
//ApicturegrayinformationArray = new Apicturegrayinformation[0];
//StreamReader rd = File.OpenText("data.txt");
//string s = rd.ReadLine();
//string[] ss = s.Split(',');
//int row = int.Parse(ss[0]); //行数
//int col = int.Parse(ss[1]); //每行数据的个数
//double[,] p1 = new double[row, col]; //数组
//for (int i = 0; i < row; i++) //读入数据并赋予数组
//{
// string line = rd.ReadLine();
// string[] data = line.Split(',');
// for (int j = 0; j < col; j++)
// {
// Array.Resize(ref ApicturegrayinformationArray, ApicturegrayinformationArray.Length + 1);
// ApicturegrayinformationArray[i].currentgrayValue = byte.Parse(data[j]);
// }
//}
functionFun.racepossibleEdgePointIndexFunc(5120, 5120, 11884921, ref neighbourhood);
}
// 跳点不去震动函数：piontsNoVibrationcorrection()
public void piontsNoVibrationcorrection(OpticMeasureClass opticFlowFunc)
{
int PointArraylength; //第i张母板点坐标数组长度
CalculateWidthAndHightOfPointImage(); //计算母板点数组的长和宽
trian = new Triangulation(); // 创建三角剖分对象
//call装顶点表函数，装母板顶点表
trian.GetTrianglerVertexArrayFunc(ReferencePictureBitmap.Height, ReferencePictureBitmap.Width, StepValue);
PointArraylength = trian.TriangleVertexArray.Length;
packedPiontImageCoorditionArrayFunction(opticFlowFunc, PointArraylength);//装母板点数组
//销毁trian对象
trian.Destroy();
GC.Collect();
//=============待匹配照片循环 计算==================
for (int k = 0; k < length; k++)
{
CurPictureIndex = opticFlowFunc.ReferencePictureDataArray[InReferencePictureDataArrayIndex].IndexOfPictureForMachArray[k];//待匹配照片在结果数组中的索引
CurrentPictureBitmap = (Bitmap)Image.FromFile(opticFlowFunc.PictureOpticflowDataResultArray[opticFlowFunc.ReferencePictureDataArray[InReferencePictureDataArrayIndex].IndexOfPictureForMachArray[k]].PictureLujin);
CreatArray.creatPictureGreyArray(CurrentPictureBitmap, ref CurrentPictureGreyArray); //创建 匹配照片灰度数组
CreatArray.creatPictureDlateGreyArray(CurrentPictureBitmap, ref PictureDlateGreyArray); //创建灰度差值数组
functionFun.LoadgrayValuesArrayForMatch(CurrentPictureBitmap, ref CurrentPictureGreyArray); //装载 匹配照片灰度数组
//CreatArray.creatHomologousPointsDisplacementsArray(PointArraylength,ref HomologousPointsDisplacementsArray);//创建位移场数组
CreatArray.creatPointsResultArray(opticFlowFunc, CurPictureIndex, RefPicturePointArrayHight, RefPicturePointArrayWidth);//创建结果数组
// 求母板照片和待匹配照片灰度差
for (int j = 0; j < CurrentPictureGreyArray.Length; j++)
{
PictureDlateGreyArray[j] = CurrentPictureGreyArray[j].OrigingrayValue - ReferencePictureGreyArray[j].OrigingrayValue;
}
//清数组
Array.Resize(ref CurrentPictureGreyArray, 0);
//====母板点数组循环计算=========
for (int j = 0; j < PointArraylength; j++)
{
//装载点坐标数组
opticFlowFunc.PictureOpticflowDataResultArray[CurPictureIndex].OpticflowResultFOfPointsArray[j].pointCoordinate.X = opticFlowFunc.ReferencePictureDataArray[InReferencePictureDataArrayIndex].PiontImageCoorditionArray[j].X;
opticFlowFunc.PictureOpticflowDataResultArray[CurPictureIndex].OpticflowResultFOfPointsArray[j].pointCoordinate.Y = opticFlowFunc.ReferencePictureDataArray[InReferencePictureDataArrayIndex].PiontImageCoorditionArray[j].Y;
//装八邻域数组
functionFun.racepossibleEdgePointIndexFunc(ReferencePictureBitmap.Height, ReferencePictureBitmap.Width, opticFlowFunc.ReferencePictureDataArray[InReferencePictureDataArrayIndex].IndexArray[j], ref CurrentPixtNeighbourArray);
//soble算子
Grad.X = 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[1]] + 2 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[2]] + 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[3]] - 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[5]] - 2 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[6]] - 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[7]];
Grad.Y = -2 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[0]] - 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[1]] + 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[3]] + 2 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[4]] + 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[5]] - 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[7]];
//Prewitt算子
//Grad.X = 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[1]] + 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[2]] + 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[3]] - 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[5]] - 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[6]] - 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[7]];
//Grad.Y = -1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[0]] - 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[1]] + 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[3]] +1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[4]] + 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[5]] - 1 * PictureDlateGreyArray[(int)CurrentPixtNeighbourArray[7]];
opticFlowFunc.PictureOpticflowDataResultArray[CurPictureIndex].OpticflowResultFOfPointsArray[j].Grad = Grad;
}
// 清除数组
Array.Resize(ref PictureDlateGreyArray, 0);
CurrentPixtNeighbourArray.Clear();
}
// 清除数组
Array.Resize(ref ReferencePictureGreyArray, 0);
}