//像素去震动函数：pixelWithVibrationcorrection()
public void pixelWithVibrationcorrection(OpticMeasureClass opticFlowFunc)
{
int InReferencePictureIndex = 0;//在母板系照片灰度中的索引
Mt = new CSharpAlgorithm.Algorithm.MatrixOfAlgorithm();
//call读识标记点函数，将母板的标记点识取出来
functionFun.ReadMarkPointsFunc();
//将第i张母板标记点存到PictureOpticflowDataResultArray[ReferencePictureDataArray[i].ReferencePictureIndex].PictureMarkpointsArray
opticFlowFunc.PictureOpticflowDataResultArray[opticFlowFunc.ReferencePictureDataArray[InReferencePictureDataArrayIndex].ReferencePictureIndex].PictureMarkpointsArray = functionFun.MarkPointsArray;
CreatArray.creatInReferencePicturePixXYArray(RefPictureWidth * RefPictureHight, ref InReferencePicturePixXYArray);//像素经过旋转平移后在母板坐标系下的坐标数组
//=============待匹配照片循环================
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
CreatArray.creatPixelResultArray(opticFlowFunc, CurPictureIndex, RefPictureHight, RefPictureWidth); //创建像素光流结果数组
//装待匹配照片灰度数组
CurrentPictureBitmap = (Bitmap)Image.FromFile(opticFlowFunc.PictureOpticflowDataResultArray[CurPictureIndex].PictureLujin);
CreatArray.creatPictureGreyArray(CurrentPictureBitmap, ref CurrentPictureGreyArray); //创建待匹配照片灰度数组
functionFun.LoadgrayValuesArrayForMatch(CurrentPictureBitmap, ref CurrentPictureGreyArray); //装载待匹配照片灰度数组
functionFun.ReadMarkPointsFunc(); //call识标记点函数
//将第K张待匹配照片标记点到光流结果数组中
opticFlowFunc.PictureOpticflowDataResultArray[CurPictureIndex].PictureMarkpointsArray = functionFun.MarkPointsArray;
// call 求旋转平移矩阵函数，得到母板照片旋转平移到当前待匹配照片上的旋转平移矩阵函数
functionFun.GetRotationMatrixAndTranslationFunc(ref Mt);
//=============待匹配照片像素循环 像素流计算（去震动像素直接相减）==================
for (int j = 0; j < CurrentPictureGreyArray.Length; j++)
{
// 得到旋转平移后的坐标
functionFun.Get2DzuobiaoInReferencePictureFunc(opticFlowFunc, CurrentPictureBitmap, Mt, T, InReferencePictureDataArrayIndex, j, RefPictureWidth * RefPictureHight, ref InReferencePicturePixXYArray);
//计算编号
functionFun.CalculateIndexOfInReferencePictureFunc(RefPictureHight, RefPictureWidth, j, InReferencePicturePixXYArray, ref InReferencePictureIndex);
//求灰度差 直接相减
Greyvalue = CurrentPictureGreyArray[j].OrigingrayValue - ReferencePictureGreyArray[InReferencePictureIndex].OrigingrayValue;
//将结果存到结果数组中
opticFlowFunc.PictureOpticflowDataResultArray[CurPictureIndex].OpticflowResultFOfPixelArray[j].Greyvalue = Greyvalue;
}
//清空待匹配照片灰度数组
Array.Resize(ref CurrentPictureGreyArray, 0);
}
//销毁对象
functionFun = null;
//清空母版照片灰度数组
Array.Resize(ref ReferencePictureGreyArray, 0);
}
//跳点去震动函数：piontsWithVibrationcorrection()
public void piontsWithVibrationcorrection(OpticMeasureClass opticFlowFunc)
{
int PointArraylength; //第i张母板点坐标数组长度
int InReferencePictureIndex = 0; //在母板系照片灰度中的索引
int s = 0; //点序号
Mt = new CSharpAlgorithm.Algorithm.MatrixOfAlgorithm();
trian = new Triangulation(); // 创建三角剖分对象
CalculateWidthAndHightOfPointImage(); //计算母板点数组的长和宽
//call装顶点表函数，装母板顶点表
trian.GetTrianglerVertexArrayFunc(ReferencePictureBitmap.Height, ReferencePictureBitmap.Width, StepValue);
PointArraylength = trian.TriangleVertexArray.Length; //母板点数组长度
//PointArraylength = RefPicturePointArrayWidth * RefPicturePointArrayHight;//母板点数组长度
packedPiontImageCoorditionArrayFunction(opticFlowFunc, PointArraylength); //装载到母板点数组中
//销毁trian对象
trian = null; //可以这么销毁
functionFun.ReadMarkPointsFunc(); //call读识标记点函数，将母板的标记点识取出来
//将第i张母板标记点存到PictureOpticflowDataResultArray[ReferencePictureDataArray[i].ReferencePictureIndex].PictureMarkpointsArray
opticFlowFunc.PictureOpticflowDataResultArray[opticFlowFunc.ReferencePictureDataArray[InReferencePictureDataArrayIndex].ReferencePictureIndex].PictureMarkpointsArray = functionFun.MarkPointsArray;
CreatArray.creatInReferencePicturePixXYArray(RefPictureHight * RefPictureWidth, ref InReferencePicturePixXYArray); //创建像素经过旋转平移后在母板坐标系下的坐标数组
//=======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
CreatArray.creatPointsResultArray(opticFlowFunc, CurPictureIndex, RefPicturePointArrayHight, RefPicturePointArrayWidth); //创建点光流结果数组
CurrentPictureBitmap = (Bitmap)Image.FromFile(opticFlowFunc.PictureOpticflowDataResultArray[CurPictureIndex].PictureLujin);
CreatArray.creatPictureGreyArray(CurrentPictureBitmap, ref CurrentPictureGreyArray); //创建 匹配照片灰度数组
functionFun.LoadgrayValuesArrayForMatch(CurrentPictureBitmap, ref CurrentPictureGreyArray); //装待匹配照片灰度数组
CreatArray.creatPictureDlateGreyArray(CurrentPictureBitmap, ref PictureDlateGreyArray); //创建灰度差数组
CreatArray.creatHomologousPointsDisplacementsArray(PointArraylength, ref HomologousPointsDisplacementsArray); //创建位移场数组
functionFun.ReadMarkPointsFunc(); //call识标记点函数
opticFlowFunc.PictureOpticflowDataResultArray[CurPictureIndex].PictureMarkpointsArray = functionFun.MarkPointsArray; //将第K张待匹配照片标记点到光流结果数组中
// call 求旋转平移矩阵函数，得到母板照片旋转平移到当前待匹配照片上的旋转平移矩阵函数
functionFun.GetRotationMatrixAndTranslationFunc(ref Mt);
// 求母板照片和待匹配照片灰度差
for (int j = 0; j < CurrentPictureGreyArray.Length; j++)
{
// 得到旋转平移后的坐标
functionFun.Get2DzuobiaoInReferencePictureFunc(opticFlowFunc, CurrentPictureBitmap, Mt, T, InReferencePictureDataArrayIndex, j, CurrentPictureGreyArray.Length, ref InReferencePicturePixXYArray);
//计算编号
functionFun.CalculateIndexOfInReferencePictureFunc(RefPictureHight, RefPictureWidth, j, InReferencePicturePixXYArray, ref InReferencePictureIndex);
//求灰度差 直接相减
PictureDlateGreyArray[j] = CurrentPictureGreyArray[j].OrigingrayValue - ReferencePictureGreyArray[InReferencePictureIndex].OrigingrayValue;
}
//清数组
Array.Resize(ref CurrentPictureGreyArray, 0);
//=============待匹配照片 点循环 计算（去震动）==================
//for (int j = 0; j < PointArraylength; j++)
//{
// //将点坐标存起
// opticFlowFunc.PictureOpticflowDataResultArray[CurPictureIndex].OpticflowResultFOfPointsArray[j].pointCoordinate.X = opticFlowFunc.ReferencePictureDataArray[i].PiontImageCoorditionArray[j].X;
// opticFlowFunc.PictureOpticflowDataResultArray[CurPictureIndex].OpticflowResultFOfPointsArray[j].pointCoordinate.Y = opticFlowFunc.ReferencePictureDataArray[i].PiontImageCoorditionArray[j].Y;
// // call求灰度差函数
// functionFun.racepossibleEdgePointIndexFunc(RefPicturePointArrayHight, RefPicturePointArrayWidth, opticFlowFunc.ReferencePictureDataArray[i].IndexArray[j], ref CurrentPixtNeighbourArray);
// //判断 八邻域数组长度是否为8，不为8的话 梯度赋0
// if (CurrentPixtNeighbourArray.Count == 8)
// {
// //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]];
// }
// else
// {
// Grad.X = 0;
// Grad.Y = 0;
// }
// //将灰度差存到结果数组里面
// opticFlowFunc.PictureOpticflowDataResultArray[CurPictureIndex].OpticflowResultFOfPointsArray[j].Grad = Grad;
//}
//=====存到赵涛数组里===========
//装载显示点的坐标
for (int j = 0; j < PointArraylength; j++)
{
HomologousPointsDisplacementsArray[j].pointCoordinate.X = opticFlowFunc.ReferencePictureDataArray[InReferencePictureDataArrayIndex].PiontImageCoorditionArray[j].X;
HomologousPointsDisplacementsArray[j].pointCoordinate.Y = opticFlowFunc.ReferencePictureDataArray[InReferencePictureDataArrayIndex].PiontImageCoorditionArray[j].Y;
}
//====母板点数组循环计算=========
for (int j = 0; j < PointArraylength; j++)
{
//装八邻域数组
functionFun.racepossibleEdgePointIndexFunc(ReferencePictureBitmap.Height, ReferencePictureBitmap.Width, opticFlowFunc.ReferencePictureDataArray[InReferencePictureDataArrayIndex].IndexArray[j], ref CurrentPixtNeighbourArray);
//判断 八邻域数组长度是否为8，不为8的话 梯度赋0
if (CurrentPixtNeighbourArray.Count == 8)
{
//soble算子
HomologousPointsDisplacementsArray[s].deltaX = 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]];
HomologousPointsDisplacementsArray[s].deltaY = -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]];
}
else
{
HomologousPointsDisplacementsArray[s].deltaX = 0;
HomologousPointsDisplacementsArray[s].deltaY = 0;
}
s++;
}
//销毁对象
functionFun = null;
// 清除数组
Array.Resize(ref PictureDlateGreyArray, 0);
CurrentPixtNeighbourArray.Clear();
}
// 清除数组
Array.Resize(ref ReferencePictureGreyArray, 0);
}
