OTS/OTSIncAMeasureApp/ServiceCenter/CImageHandler.cs

using OTSDataType;
using OTSModelSharp.ImageProcess;
using System;
using System.Collections.Generic;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using static OTSDataType.otsdataconst;

namespace OTSModelSharp.ServiceInterface
{
    using OpenCvSharp;
    using OTSCLRINTERFACE;
    using OTSIMGPROC;
    using OTSModelSharp.DTLBase;
    using System.Drawing.Imaging;
    using System.Runtime.InteropServices;
    using System.Windows;

    public class CImageHandler:IImageProcess
    {
        #region 通过byte数组生成BMP图像文件
        /// <summary>    
        /// 将一个byte的数组转换为8bit灰度位图
        /// </summary>    
        /// <param name="data">数组</param>    
        /// <param name="width">图像宽度</param>    
        /// <param name="height">图像高度</param>    
        /// <returns>位图</returns>    
        public static Bitmap ToGrayBitmap(byte[] data, int width, int height)
        {
            if (width == 0 || height == 0) 
                return null;
            //// 申请目标位图的变量，并将其内存区域锁定    
            Bitmap bmp = new Bitmap(width, height, PixelFormat.Format8bppIndexed);
            //// BitmapData这部分内容  需要 using System.Drawing.Imaging;  
            BitmapData bmpData = bmp.LockBits(new Rectangle(0, 0, width, height),
            ImageLockMode.WriteOnly, PixelFormat.Format8bppIndexed);

            //// 获取图像参数    
            // 扫描线的宽度   
            int stride = bmpData.Stride;
            // 显示宽度与扫描线宽度的间隙  
            int offset = stride - width;
            // 获取bmpData的内存起始位置
            IntPtr iptr = bmpData.Scan0;
            // 用stride宽度，表示这是内存区域的大小
            int scanBytes = stride * height;

            //// 下面把原始的显示大小字节数组转换为内存中实际存放的字节数组    
            int posScan = 0;
            int posReal = 0;// 分别设置两个位置指针，指向源数组和目标数组    
            byte[] pixelValues = new byte[scanBytes];  //为目标数组分配内存    

            //for (int x = height-1;x>=0 ; x--) data[startIndex+ y];//
            for (int x = 0; x < height; x++)
            {
                int startIndex = x * width;
                //// 下面的循环节是模拟行扫描    
                for (int y = 0; y < width; y++)
                {
                    pixelValues[posScan++] = data[posReal++];
                }
                posScan += offset;  //行扫描结束，要将目标位置指针移过那段“间隙”    
            }
            //// 用Marshal的Copy方法，将刚才得到的内存字节数组复制到BitmapData中    
            System.Runtime.InteropServices.Marshal.Copy(pixelValues, 0, iptr, scanBytes);
            bmp.UnlockBits(bmpData);  // 解锁内存区域    

            //// 下面的代码是为了修改生成位图的索引表，从伪彩修改为灰度    
            ColorPalette tempPalette;
            using (Bitmap tempBmp = new Bitmap(1, 1, PixelFormat.Format8bppIndexed))
            {
                tempPalette = tempBmp.Palette;
            }
            for (int i = 0; i < 256; i++)
            {
                tempPalette.Entries[i] = Color.FromArgb(i, i, i);
            }
            bmp.Palette = tempPalette;


            return bmp;
        }
        #endregion

        public static byte[] BitmapToGrayByte(Bitmap bitmap)
        {
            // 申请目标位图的变量，并将其内存区域锁定
            BitmapData bitmapDat = bitmap.LockBits(new Rectangle(0, 0, bitmap.Width, bitmap.Height), ImageLockMode.ReadWrite, bitmap.PixelFormat);
            // 获取bmpData的内存起始位置
            IntPtr intPtr = bitmapDat.Scan0;
            byte[] image = new byte[bitmap.Width * bitmap.Height];//原始数据
            Marshal.Copy(intPtr, image, 0, bitmap.Width * bitmap.Height); // 将数据复制到byte数组中，
            //解锁内存区域  
            bitmap.UnlockBits(bitmapDat);
            return image;
        }

        //获取测量的BSE图
        //COTSSample WSample: 工作样品测量
        //Byte[] BSEImage: 带背景图数据
        //int iHeight:  图像高度
        //int iWidth：  图像宽度
        //Byte[]BSEImageNoBG ： 去背景图数据
        public bool GetBSEImage(COTSImageProcParam ImgProcPrm, double pixelSize, byte[] BSEImage, int iHeight, int iWidth, ref byte[] BSEImageNoBG)
        {
            Rectangle rect = new Rectangle();
            rect.Height = iHeight;
            rect.Width = iWidth;
            CBSEImgClr pBSEImageIn = new CBSEImgClr(rect);
            CBSEImgClr pBSEImageOut = new CBSEImgClr(rect);
            
           
            //pBSEImageIn.SetImageRect(rect);
            pBSEImageIn.SetImageData(BSEImage,iWidth, iHeight );
            //pBSEImageOut.SetImageRect(rect);
            if (null == ImgProcPrm)
            {
                return false;
            }

           


            RemoveBackGround(pBSEImageIn, ImgProcPrm, pixelSize ,ref pBSEImageOut);
         

            BSEImageNoBG = pBSEImageOut.GetImageDataPtr();

            return true;
        }
        /// <summary>
        /// 获取测量的BSE图
        /// </summary>
        /// <param name="BSEImage">BSE原数据</param>
        /// <param name="iHeight">图像高度</param>
        /// <param name="iWidth">图像宽度</param>
        /// <param name="grayStart"></param>
        /// <param name="grayEnd"></param>
        /// <param name="BSEImageNoBG">去背景图数据</param>
        /// <returns></returns>
        public bool GetBSEImage(byte[] BSEImage, int iHeight, int iWidth, int grayStart, int grayEnd, ref byte[] BSEImageNoBG)
        {
            Rectangle rect = new Rectangle();
            rect.Height = iHeight;
            rect.Width = iWidth;
            CBSEImgClr pBSEImageIn = new CBSEImgClr(rect);
            CBSEImgClr pBSEImageOut = new CBSEImgClr(rect);

           
            //pBSEImageIn.SetImageRect(rect);
            pBSEImageIn.SetImageData(BSEImage, iWidth, iHeight );



         
            CIntRangeClr cIntRangeClr = new CIntRangeClr();
            cIntRangeClr.SetStart(grayStart);
            cIntRangeClr.SetEnd(grayEnd);
          
            OTSCLRINTERFACE.ImageProForClr imgpro = new OTSCLRINTERFACE.ImageProForClr();
            int num=0;
            imgpro.GetSpecialGrayRangeImage(pBSEImageIn, cIntRangeClr, pBSEImageOut,ref num);
            for (int i = 0; i < iWidth; i++)
            {
                for (int j = 0; j < iHeight; j++)
                {
                    var bse = pBSEImageOut.GetBSEValue(i, j);
                    if (bse == 255)
                    {
                        var originalBse = pBSEImageIn.GetBSEValue(i, j);
                        pBSEImageOut.SetBSEValue(i, j, originalBse);
                    }
                    else 
                    {
                        pBSEImageOut.SetBSEValue(i, j, 255);
                    }
                  
                
                }
            
            }
            

            BSEImageNoBG = pBSEImageOut.GetImageDataPtr();

            return true;
        }
        // remove background
        public void RemoveBackGround(CBSEImgClr a_pImgIn, COTSImageProcParam a_pImgProcessParam, double a_pixelSize, ref CBSEImgClr a_pImgOut)
        {
       

            List<COTSParticleClr> parts = new List<COTSParticleClr>();
            List<COTSParticleClr> specialGreyparts = new List<COTSParticleClr>();
            if (!RemoveBGAndGetParts(a_pImgIn, a_pImgProcessParam, a_pixelSize, ref parts))
            {
                return;
            }

            if (a_pImgProcessParam.GetSpecialGreyRangeParam().GetIsToRun())
            {
                var param = a_pImgProcessParam.GetSpecialGreyRangeParam();
                var ranges = param.GetSpecialGreyRanges();
              
                
                foreach (var r in ranges)
                {
                    CIntRangeClr r1 = new CIntRangeClr();
                    r1.SetStart(r.range.GetStart());
                    r1.SetEnd(r.range.GetEnd());

                    CDoubleRangeClr r2 = new CDoubleRangeClr();
                    r2.SetStart(r.diameterRange.GetStart());
                    r2.SetEnd(r.diameterRange.GetEnd());

                    GetParticlesBySpecialGray(a_pImgIn, r1, r2, a_pixelSize, ref specialGreyparts);
                }
              
            }


            for (int i = 0; i < a_pImgOut.GetWidth(); i++)
            {
                for (int j = 0; j < a_pImgOut.GetHeight(); j++)
                {
                    a_pImgOut.SetBSEValue(i, j, 255);
                }
            }
            if (specialGreyparts.Count > 0)
            {
                foreach (var p in specialGreyparts)
                {
                    foreach (var s in p.GetFeature().GetSegmentsList())
                    {
                        for (int i = s.GetStart(); i < s.GetStart() + s.GetLength(); i++)
                        {
                            var bseValue = a_pImgIn.GetBSEValue(i, s.GetHeight());
                            a_pImgOut.SetBSEValue(i, s.GetHeight(), bseValue);
                        }
                    }

                }

            }


            foreach (var p in parts)
            {
                foreach (var s in p.GetFeature().GetSegmentsList())
                {
                    for (int i = s.GetStart(); i < s.GetStart() + s.GetLength(); i++)
                    {
                        var bseValue = a_pImgIn.GetBSEValue(i, s.GetHeight());
                        a_pImgOut.SetBSEValue(i, s.GetHeight(), bseValue);
                    }
                }
            
            }
           
          
          
            return;
        }
        public void BDilate3(string source, string target, int wDegree, int rows, int columns)
        {
            throw new NotImplementedException();
        }

        public void BErode3(string source, string target, int wDegree, int rows, int columns)
        {
            throw new NotImplementedException();
        }

        public bool CalParticleImageProp( COTSParticleClr part, double a_pixelSize)
        {
            OTSCLRINTERFACE.ImageProForClr imgpro = new OTSCLRINTERFACE.ImageProForClr();
            imgpro.CalcuParticleImagePropertes(part,a_pixelSize);
            
            return true;
        }

 

        public bool RemoveBGAndGetParts(CBSEImgClr img, COTSImageProcParam a_pImgProcessParam,double a_pixelSize,ref List<COTSParticleClr> parts)
        {
            
            OTSCLRINTERFACE.ImageProForClr imgpro = new OTSCLRINTERFACE.ImageProForClr();
         
            OTSCLRINTERFACE.COTSImgProcPrmClr prm = GetImageProcPrmClr(a_pImgProcessParam);
            OTSCLRINTERFACE.COTSFieldDataClr flddataclr = new OTSCLRINTERFACE.COTSFieldDataClr();
            if (!imgpro.GetFieldDataFromImage(img, prm, a_pixelSize, flddataclr))
            {
                return false;
            }
            
            parts = flddataclr.GetParticleList();
            return true;

        }
        public bool GetParticlesBySpecialGray(CBSEImgClr img, CIntRangeClr grayrange, CDoubleRangeClr diameterRange,double a_pixelSize, ref List<COTSParticleClr> parts)
        {
            OTSCLRINTERFACE.ImageProForClr imgpro = new OTSCLRINTERFACE.ImageProForClr();

            //OTSCLRINTERFACE.COTSImgProcPrmClr prm = GetImageProcPrmClr(a_pImgProcessParam);
            OTSCLRINTERFACE.COTSFieldDataClr flddataclr = new OTSCLRINTERFACE.COTSFieldDataClr();
            imgpro.GetParticlesBySpecialPartGrayRange(img, grayrange,diameterRange,a_pixelSize, flddataclr);

            parts = flddataclr.GetParticleList();
            return true;

        }
        private COTSImgProcPrmClr GetImageProcPrmClr(COTSImageProcParam a_oSource)
        {

            COTSImgProcPrmClr prmclr = new COTSImgProcPrmClr();
            OTSCLRINTERFACE.CDoubleRangeClr r1 = new OTSCLRINTERFACE.CDoubleRangeClr(a_oSource.GetIncAreaRange().GetStart(), a_oSource.GetIncAreaRange().GetEnd());
            prmclr.SetIncArea(r1);
            OTSCLRINTERFACE.CIntRangeClr r2= new OTSCLRINTERFACE.CIntRangeClr(a_oSource.GetBGGray().GetStart(), a_oSource.GetBGGray().GetEnd());
            prmclr.SetBGGray(r2);
            OTSCLRINTERFACE.CIntRangeClr r3= new OTSCLRINTERFACE.CIntRangeClr(a_oSource.GetParticleGray().GetStart(), a_oSource.GetParticleGray().GetEnd());
            prmclr.SetParticleGray(r3);
            prmclr.SetBGRemoveType((int)a_oSource.GetBGRemoveType());
            prmclr.SetAutoBGRemoveType((int)a_oSource.GetAutoBGRemoveType());
            prmclr.SetErrodDilateParam(a_oSource.GetErrodDilateParam());
            prmclr.SetOverlapParam(a_oSource.GetOverlapParam());

            return prmclr;
        }

        public bool MergeBigBoundaryParticles(List<COTSFieldData> allFields, double pixelSize, int scanFieldSize, System.Drawing.Size ResolutionSize, ref List<COTSParticleClr> mergedParts)
        {
            List<COTSFieldDataClr> fldclrs = new List<COTSFieldDataClr>();
            foreach (var f in allFields)
            {
                COTSFieldDataClr fldclr = new COTSFieldDataClr();
                PointF p1 = f.GetOTSPosition();
                System.Drawing.Point p2 = new System.Drawing.Point((int)p1.X, (int)p1.Y);
                fldclr.SetPosition(p2);
                fldclr.SetImageWidth(f.Width);
                fldclr.SetImageHeight(f.Height);
                var parts = f.GetListAnalysisParticles();
                foreach (var p in parts)
                {
                    fldclr.AddParticle(p);
                }
                fldclrs.Add(fldclr);
            }
            OTSCLRINTERFACE.ImageProForClr imgpro = new OTSCLRINTERFACE.ImageProForClr();

            imgpro.MergeBigBoundaryParticles(fldclrs, pixelSize, scanFieldSize, ResolutionSize, mergedParts);
            return true;

        }
       
        /// <summary>
        /// 根据Segment寻找边缘坐标点
        /// </summary>
        /// <param name="width"></param>
        /// <param name="height"></param>
        /// <param name="segmentClrs"></param>
        /// <returns></returns>
        public static List<System.Drawing.Point> FindContoursBySegment(int width, int height, List<COTSSegmentClr> segmentClrs)
        {
            List<System.Drawing.Point> points = new List<System.Drawing.Point>(); 
            using (Mat mat = new Mat(height, width, MatType.CV_8UC1, new Scalar(0)))
            {
                for (int i = 0; i < segmentClrs.Count; i++)
                {
                    Cv2.Line(mat, new OpenCvSharp.Point(segmentClrs[i].GetStart(), segmentClrs[i].GetHeight()), new OpenCvSharp.Point(segmentClrs[i].GetStart() + segmentClrs[i].GetLength(), segmentClrs[i].GetHeight()), Scalar.White, 1, LineTypes.AntiAlias);
                }
                Point[][] contours;
                HierarchyIndex[] hierarchy;
                Cv2.FindContours(mat, out contours, out hierarchy, RetrievalModes.External, ContourApproximationModes.ApproxSimple, null);
                for (int i = 0; i < contours.ToList().Count(); i++)
                {
                    for (int j = 0; j < contours[i].Count(); j++)
                    {
                        System.Drawing.Point point = new System.Drawing.Point(contours[i][j].X, contours[i][j].Y);
                        if (!points.Contains(point))
                        {
                            points.Add(point);
                        }
                    }
                }
            }
            return points;
        }

        public bool RepeatedParticleTreatment(List<COTSFieldData> allFields, COTSSample theSample, string stdPath)
        {
            int maxPartCount = theSample.GetMsrParams().GetXRayParam().GetXrayLimit();
            int overlap = theSample.GetMsrParams().GetImageProcessParam().GetOverlapParam();
            double pixelSize = theSample.CalculatePixelSize();
            System.Drawing.Size resolutionSize = theSample.GetResolutionSize();
            int scanFieldSizeX = theSample.GetSEMDataMsr().GetScanFieldSize();
            int scanFieldSizeY = scanFieldSizeX * resolutionSize.Height / resolutionSize.Width;
            int offsetX = scanFieldSizeX - (int)(overlap * pixelSize);
            int offsetY = scanFieldSizeY - (int)(overlap * pixelSize);
            List<COTSParticleClr> deletePartList = new List<COTSParticleClr>();

            foreach (var item in allFields)
            {
                if (!item.GetIsMeasureComplete())
                {
                    break;
                }
                //找到上下左右四帧图
                List<COTSFieldData> leftField = allFields.Where(a => a.OTSPos == new System.Drawing.PointF(item.OTSPos.X - offsetX, item.OTSPos.Y)).ToList();
                List<COTSFieldData> rightField = allFields.Where(a => a.OTSPos == new System.Drawing.PointF(item.OTSPos.X + offsetX, item.OTSPos.Y)).ToList();
                List<COTSFieldData> upField = allFields.Where(a => a.OTSPos == new System.Drawing.PointF(item.OTSPos.X, item.OTSPos.Y + offsetY)).ToList();
                List<COTSFieldData> downField = allFields.Where(a => a.OTSPos == new System.Drawing.PointF(item.OTSPos.X, item.OTSPos.Y - offsetY)).ToList();
                //判断是否有效
                if (leftField.Count() == 1)//包含左帧图
                {
                    if (leftField[0].GetIsMeasureComplete() == true)//存在测量帧图
                    {
                        //寻找重叠颗粒
                        deletePartList.AddRange(FieldFun(leftField[0], item, "left_right", resolutionSize, overlap));
                    }
                }
                if (rightField.Count() == 1)//包含右帧图
                {
                    if (rightField[0].GetIsMeasureComplete() == true)//存在测量帧图
                    {
                        //寻找重叠颗粒
                        deletePartList.AddRange(FieldFun(item, rightField[0], "left_right", resolutionSize, overlap));
                    }
                }
                if (upField.Count() == 1)//包含上帧图
                {
                    if (upField[0].GetIsMeasureComplete() == true)//存在测量帧图
                    {
                        //寻找重叠颗粒
                        deletePartList.AddRange(FieldFun(upField[0], item, "up_down", resolutionSize, overlap));
                    }
                }
                if (downField.Count() == 1)//包含下帧图
                {
                    if (downField[0].GetIsMeasureComplete() == true)//存在测量帧图
                    {
                        //寻找重叠颗粒
                        deletePartList.AddRange(FieldFun(item, downField[0], "up_down", resolutionSize, overlap));
                    }
                }
            }

            //数据库操作
            SQLiteHelper sQLiteHelper = new SQLiteHelper(stdPath);
            sQLiteHelper.GetDBConnection();
            sQLiteHelper.BeginTransaction();

            deletePartList = deletePartList.Distinct().ToList();//去重

            if (!sQLiteHelper.DeletePartForTransaction(deletePartList))
            {
                return false;
            }

            sQLiteHelper.CommitTransaction();

            return true;
        }

        private List<COTSParticleClr> FieldFun(COTSFieldData left_upField, COTSFieldData right_downField, string style, System.Drawing.Size resolutionSize, int overlap)
        {
            List<COTSParticleClr> particleClrs = new List<COTSParticleClr>();
            if (style == "left_right")
            {
                //寻找左帧图的右侧区域颗粒
                foreach (var leftParticles in left_upField.GetListAnalysisParticles())
                {
                    Rectangle leftRectangle = (Rectangle)leftParticles.GetParticleRect();
                    if (leftRectangle.Left > resolutionSize.Width - overlap)//未跨界
                    {
                        if (leftRectangle.Right == resolutionSize.Width)//颗粒右侧在边界处截断
                        {

                        }
                        else
                        {
                            particleClrs.Add(leftParticles);
                        }
                    }
                }
            }
            else
            {
                //寻找上帧图的下侧区域颗粒
                foreach (var upParticles in left_upField.GetListAnalysisParticles())
                {
                    Rectangle upRectangle = (Rectangle)upParticles.GetParticleRect();
                    if (upRectangle.Top > resolutionSize.Height - overlap / 2)//未跨界
                    {
                        if (upRectangle.Bottom == resolutionSize.Height)//颗粒下方在边界处截断
                        {

                        }
                        else
                        {
                            particleClrs.Add(upParticles);
                        }
                    }
                }
            }

            return particleClrs;
        }

        public Mat CombinImageX(Mat[] list_mats, int OverlapParam, int type)
        {
            List<Mat> matStitch = new List<Mat>();//拼接
            List<Mat> matCombin = new List<Mat>();//合并
            for (int i = 0; i < list_mats.Count(); i++)
            {
                if (i == 0)//首张
                {
                    matCombin.Add(new Mat(list_mats[i], new Rect(0, 0, list_mats[i].Width - OverlapParam - 100, list_mats[i].Height)));
                    matStitch.Add(new Mat(list_mats[i], new Rect(list_mats[i].Width - OverlapParam - 100, 0, OverlapParam + 100, list_mats[i].Height)));
                }
                else if(i == list_mats.Count() - 1)//末张
                {
                    matStitch.Add(new Mat(list_mats[i], new Rect(0, 0, OverlapParam + 100, list_mats[i].Height)));
                    matCombin.Add(new Mat(list_mats[i], new Rect(OverlapParam + 100, 0, list_mats[i].Width - OverlapParam - 100, list_mats[i].Height)));
                }
                else
                {
                    matStitch.Add(new Mat(list_mats[i], new Rect(0, 0, OverlapParam + 100, list_mats[i].Height)));
                    matCombin.Add(new Mat(list_mats[i], new Rect(OverlapParam + 100, 0, list_mats[i].Width - (OverlapParam + 100) * 2, list_mats[i].Height)));
                    matStitch.Add(new Mat(list_mats[i], new Rect(list_mats[i].Width - OverlapParam - 100, 0, OverlapParam + 100, list_mats[i].Height)));
                }
            }

            for (int i = 0; i < matStitch.Count; i += 2)
            {
                if (matStitch.Count == 1)
                {
                    matCombin.Insert(i + 1, matStitch[i]);
                }
                else
                {
                    matCombin.Insert(i + 1, StitchImageX((int)(OverlapParam / 2 * 1.2), type, matStitch[i], matStitch[i + 1]));
                }
            }

            Mat pano = new OpenCvSharp.Mat();
            Cv2.HConcat(matCombin.ToArray(), pano);

            return pano;
        }

        public Mat CombinImageY(Mat[] list_mats, int OverlapParam, int type)
        {
            List<Mat> matStitch = new List<Mat>();//拼接
            List<Mat> matCombin = new List<Mat>();//合并
            for (int i = 0; i < list_mats.Count(); i++)
            {
                if (i == 0)//首张
                {
                    matCombin.Add(new Mat(list_mats[i], new Rect(0, 0, list_mats[i].Width, list_mats[i].Height - OverlapParam - 100)));
                    matStitch.Add(new Mat(list_mats[i], new Rect(0, list_mats[i].Height - OverlapParam - 100, list_mats[i].Width, OverlapParam + 100)));
                }
                else if (i == list_mats.Count() - 1)//末张
                {
                    matStitch.Add(new Mat(list_mats[i], new Rect(0, 0, list_mats[i].Width, OverlapParam + 100)));
                    matCombin.Add(new Mat(list_mats[i], new Rect(0, OverlapParam + 100, list_mats[i].Width, list_mats[i].Height - OverlapParam - 100)));
                }
                else
                {
                    matStitch.Add(new Mat(list_mats[i], new Rect(0, 0, list_mats[i].Width, OverlapParam + 100)));
                    matCombin.Add(new Mat(list_mats[i], new Rect(0, OverlapParam + 100, list_mats[i].Width, list_mats[i].Height - (OverlapParam + 100) * 2)));
                    matStitch.Add(new Mat(list_mats[i], new Rect(0, list_mats[i].Height - OverlapParam - 100, list_mats[i].Width, OverlapParam + 100)));
                }
            }

            for (int i = 0; i < matStitch.Count; i += 2)
            {
                if (matStitch.Count == 1)
                {
                    matCombin.Insert(i + 1, matStitch[i]);
                }
                else
                {
                    matCombin.Insert(i + 1, StitchImageY(OverlapParam, type, matStitch[i], matStitch[i + 1]));
                }
            }

            Mat pano = new OpenCvSharp.Mat();
            Cv2.VConcat(matCombin.ToArray(), pano);

            return pano;
        }

        public struct MStitch
        {
            public int Pwidth;//单幅图像的宽度
            public int Pheight;//单幅图像的高度
            public int W_min;//最小的重叠区域宽度
            public int W_max;//最大的重叠区域宽度
            public int H_min;//最小的重叠区域高度
            public double minval;//块过滤阈值
            public Mat im;//图像信息
        }
        public struct ImageParam
        {
            public int W_box;//宽度信息
            public int H_box;//高度信息
            public int bdown;//上下信息
            public MStitch mStitch; //参数结构
            public Mat im;//图像信息
        }

        /// <summary>
        /// 横向拼图
        /// </summary>
        public Mat StitchImageX(int min_w, int type, Mat newImg1, Mat newImg2)
        {
            MStitch mStitch = new MStitch();
            mStitch.Pwidth = newImg1.Width;
            mStitch.Pheight = newImg1.Height;
            mStitch.W_min = min_w;
            mStitch.W_max = min_w;
            mStitch.H_min = newImg1.Height;
            mStitch.minval = 255;
            mStitch.im = newImg1;

            ImageParam imageParam = Fun_Match(newImg2, mStitch);
            imageParam.im = newImg2;

            if (type == 2)
            {
                return Fun_Stitch(imageParam);
            }
            else
            {
                return Fun_StitchRGB(imageParam);
            }
        }

        /// <summary>
        /// 纵向拼图
        /// </summary>
        public Mat StitchImageY(int min_w, int type, Mat newImg1, Mat newImg2)
        {
            Cv2.Transpose(newImg1, newImg1);
            Cv2.Flip(newImg1, newImg1, FlipMode.X);

            Cv2.Transpose(newImg2, newImg2);
            Cv2.Flip(newImg2, newImg2, FlipMode.X);

            MStitch mStitch = new MStitch();
            mStitch.Pwidth = newImg1.Width;
            mStitch.Pheight = newImg1.Height;
            mStitch.W_min = min_w - 100;
            mStitch.W_max = min_w + 100;
            mStitch.H_min = newImg1.Height;
            mStitch.minval = 255;
            mStitch.im = newImg1;

            ImageParam imageParam = Fun_Match(newImg2, mStitch);
            imageParam.im = newImg2;

            Mat result = type == 2 ? Fun_Stitch(imageParam) : Fun_StitchRGB(imageParam);

            Cv2.Transpose(result, result);
            Cv2.Flip(result, result, FlipMode.Y);

            return result;
        }

        public static ImageParam Fun_Match(Mat im2, MStitch mStitch)
        {
            ImageParam imageParam = new ImageParam();
            double imsum = 0;
            int x1 = 0;
            int y1 = 0;
            int x2 = 0;
            int y2 = 0;
            int w_ind = 0;
            int h_ind = 0;

            //在上窗口所有匹配块内进行搜索
            for (int w = mStitch.W_min; w <= mStitch.W_max; w++)
            {
                for (int h = mStitch.H_min; h <= mStitch.Pheight; h++)
                {
                    imsum = 0;//块差分集初始化
                    x2 = 1;
                    for (x1 = mStitch.Pwidth - w; x1 <= mStitch.Pwidth; x1 += 5)
                    {
                        y2 = 1;
                        for (y1 = mStitch.Pheight - h + 1; y1 <= mStitch.Pheight; y1 += 5)
                        {
                            //块差分集计算
                            CheckRC(ref x1, ref y1, mStitch.im);
                            CheckRC(ref x2, ref y2, im2);
                            imsum = imsum + Math.Abs(mStitch.im.At<Vec3b>(y1, x1).Item0 - im2.At<Vec3b>(y2, x2).Item0);
                            y2 = y2 + 5;
                        }
                        x2 = x2 + 5;
                    }
                    //阈值更新
                    if (imsum * 5 * 5 <= mStitch.minval * w * h)
                    {
                        mStitch.minval = imsum * 5 * 5 / (w * h);
                        w_ind = w;
                        h_ind = h;
                    }
                }
            }

            imageParam.W_box = w_ind;
            imageParam.H_box = h_ind;
            imageParam.bdown = 1;

            //在下窗口所有匹配块内进行搜索
            Parallel.For(mStitch.W_min, mStitch.W_max, w =>
            {
                Parallel.For(mStitch.H_min, mStitch.Pheight, h =>
                {
                    imsum = 0;//块差分集初始化
                    x2 = 1;
                    for (x1 = mStitch.Pwidth - w; x1 <= mStitch.Pwidth; x1 += 5)
                    {
                        y1 = 1;
                        for (y2 = mStitch.Pheight - h + 1; y2 <= mStitch.Pheight; y2 += 5)
                        {
                            //块差分集计算
                            CheckRC(ref x1, ref y1, mStitch.im);
                            CheckRC(ref x2, ref y2, im2);
                            imsum = imsum + Math.Abs(mStitch.im.At<Vec3b>(y1, x1).Item0 - im2.At<Vec3b>(y2, x2).Item0);
                            y1 = y1 + 5;
                        }
                        x2 = x2 + 5;
                    }
                    //阈值更新
                    if (imsum * 5 * 5 <= mStitch.minval * w * h)
                    {
                        mStitch.minval = imsum * 5 * 5 / (w * h);
                        w_ind = w;
                        h_ind = h;
                        imageParam.bdown = 0;
                    }
                });
            });

            imageParam.mStitch = mStitch;

            return imageParam;
        }

        public static void CheckRC(ref int x, ref int y, Mat im)
        {
            //图像矩阵访问有效性检测
            // 输入参数：
            // x——列
            // y——行
            // im——图像矩阵
            // 输出参数：
            // x——列
            // y——行
            y = Math.Max(y, 1);
            y = Math.Min(y, im.Height - 1);
            x = Math.Max(x, 1);
            x = Math.Min(x, im.Width - 1);
        }

        public Mat Fun_Stitch(ImageParam imageParam)
        {
            //图像融合
            //输入参数：
            //im2——待融合图像
            //W_box——宽度信息
            //H_box——高度信息
            //bdown——上下信息
            //MStitch——参数结构
            //输出参数：
            //MStitch——参数结构
            //im——融合图像

            Mat img = imageParam.im;
            int x1 = 0;
            int y1 = 0;
            int x2 = 0;
            int y2 = 0;
            double w = 0.5; //融合权值

            if (imageParam.bdown == 1)
            {
                //下区域重叠
                x2 = 1;
                //融合重叠区域
                for (x1 = imageParam.mStitch.Pwidth - imageParam.W_box; x1 < imageParam.mStitch.Pwidth; x1++)
                {
                    y2 = 1;
                    for (y1 = imageParam.mStitch.Pheight - imageParam.H_box + 1; y1 < imageParam.mStitch.Pheight; y1++)
                    {
                        //安全性检测
                        CheckRC(ref x1, ref y1, imageParam.mStitch.im);
                        CheckRC(ref x2, ref y2, imageParam.im);
                        //融合权值
                        w = (double)x2 / (double)imageParam.W_box;
                        //加权融合
                        double ColorRGB = imageParam.mStitch.im.At<Vec3b>(y1, x1).Item0 * (1.0 - w) + imageParam.im.At<Vec3b>(y2, x2).Item0 * w;
                        imageParam.mStitch.im.Set<Vec3b>(y1, x1, new Vec3b((byte)ColorRGB, (byte)ColorRGB, (byte)ColorRGB));
                        y2 = y2 + 1;
                    }
                    x2 = x2 + 1;
                }
            }
            else
            {
                //上区域重叠
                x2 = 1;
                //融合重叠区域
                for (x1 = imageParam.mStitch.Pwidth - imageParam.W_box; x1 < imageParam.mStitch.Pwidth; x1++)
                {
                    y2 = 1;
                    for (y1 = imageParam.mStitch.Pheight - imageParam.H_box + 1; y1 < imageParam.mStitch.Pheight; y1++)
                    {
                        //安全性检测
                        CheckRC(ref x1, ref y1, imageParam.mStitch.im);
                        CheckRC(ref x2, ref y2, imageParam.im);
                        //融合权值
                        w = (double)x2 / (double)imageParam.W_box;
                        //加权融合
                        double ColorRGB = imageParam.mStitch.im.At<Vec3b>(y1, x1).Item0 * (1.0 - w) + imageParam.im.At<Vec3b>(y2, x2).Item0 * w;
                        imageParam.mStitch.im.Set<Vec3b>(y1, x1, new Vec3b((byte)ColorRGB, (byte)ColorRGB, (byte)ColorRGB));

                        y2 = y2 + 1;
                    }
                    x2 = x2 + 1;
                }
            }

            //最终图
            img = new Mat(imageParam.mStitch.Pheight, imageParam.mStitch.Pwidth + imageParam.im.Width - x2 + 1, MatType.CV_8UC3);

            //分离出重叠区域
            Rect m_select = new Rect(x2 - 1, 0, imageParam.im.Width - x2 + 1, imageParam.mStitch.Pheight);
            Mat imgSwitch = new Mat(imageParam.im, m_select);
            Cv2.HConcat(imageParam.mStitch.im, imgSwitch, img);

            return img;
        }

        public Mat Fun_StitchRGB(ImageParam imageParam)
        {
            //图像融合
            //输入参数：
            //im2——待融合图像
            //W_box——宽度信息
            //H_box——高度信息
            //bdown——上下信息
            //MStitch——参数结构
            //输出参数：
            //MStitch——参数结构
            //im——融合图像

            Mat img = imageParam.im;
            int x1 = 0;
            int y1 = 0;
            int x2 = 0;
            int y2 = 0;
            double w = 0.5; //融合权值

            if (imageParam.bdown == 1)
            {
                //下区域重叠
                x2 = 1;
                //融合重叠区域
                for (x1 = imageParam.mStitch.Pwidth - imageParam.W_box; x1 < imageParam.mStitch.Pwidth; x1++)
                {
                    y2 = 1;
                    for (y1 = imageParam.mStitch.Pheight - imageParam.H_box + 1; y1 < imageParam.mStitch.Pheight; y1++)
                    {
                        //安全性检测
                        CheckRC(ref x1, ref y1, imageParam.mStitch.im);
                        CheckRC(ref x2, ref y2, imageParam.im);
                        //融合权值
                        w = (double)x2 / (double)imageParam.W_box;
                        //加权融合
                        double ColorR = imageParam.mStitch.im.At<Vec3b>(y1, x1).Item0 * (1.0 - w) + imageParam.im.At<Vec3b>(y2, x2).Item0 * w;
                        double ColorG = imageParam.mStitch.im.At<Vec3b>(y1, x1).Item1 * (1.0 - w) + imageParam.im.At<Vec3b>(y2, x2).Item1 * w;
                        double ColorB = imageParam.mStitch.im.At<Vec3b>(y1, x1).Item2 * (1.0 - w) + imageParam.im.At<Vec3b>(y2, x2).Item2 * w;
                        if (imageParam.mStitch.im.At<Vec3b>(y1, x1).Item0 == imageParam.mStitch.im.At<Vec3b>(y1, x1).Item1 &&
                            imageParam.mStitch.im.At<Vec3b>(y1, x1).Item1 == imageParam.mStitch.im.At<Vec3b>(y1, x1).Item2 &&
                            imageParam.im.At<Vec3b>(y2, x2).Item0 == imageParam.im.At<Vec3b>(y2, x2).Item1 &&
                            imageParam.im.At<Vec3b>(y2, x2).Item1 == imageParam.im.At<Vec3b>(y2, x2).Item2)
                        {
                            imageParam.mStitch.im.Set<Vec3b>(y1, x1, new Vec3b((byte)ColorR, (byte)ColorG, (byte)ColorB));
                        }
                        else
                        {

                        }

                        y2 = y2 + 1;
                    }
                    x2 = x2 + 1;
                }
            }
            else
            {
                //上区域重叠
                x2 = 1;
                //融合重叠区域
                for (x1 = imageParam.mStitch.Pwidth - imageParam.W_box; x1 < imageParam.mStitch.Pwidth; x1++)
                {
                    y2 = 1;
                    for (y1 = imageParam.mStitch.Pheight - imageParam.H_box + 1; y1 < imageParam.mStitch.Pheight; y1++)
                    {
                        //安全性检测
                        CheckRC(ref x1, ref y1, imageParam.mStitch.im);
                        CheckRC(ref x2, ref y2, imageParam.im);
                        //融合权值
                        w = (double)x2 / (double)imageParam.W_box;
                        //加权融合
                        double ColorR = imageParam.mStitch.im.At<Vec3b>(y1, x1).Item0 * (1.0 - w) + imageParam.im.At<Vec3b>(y2, x2).Item0 * w;
                        double ColorG = imageParam.mStitch.im.At<Vec3b>(y1, x1).Item1 * (1.0 - w) + imageParam.im.At<Vec3b>(y2, x2).Item1 * w;
                        double ColorB = imageParam.mStitch.im.At<Vec3b>(y1, x1).Item2 * (1.0 - w) + imageParam.im.At<Vec3b>(y2, x2).Item2 * w;
                        if (imageParam.mStitch.im.At<Vec3b>(y1, x1).Item0 == imageParam.mStitch.im.At<Vec3b>(y1, x1).Item1 &&
                            imageParam.mStitch.im.At<Vec3b>(y1, x1).Item1 == imageParam.mStitch.im.At<Vec3b>(y1, x1).Item2 &&
                            imageParam.im.At<Vec3b>(y2, x2).Item0 == imageParam.im.At<Vec3b>(y2, x2).Item1 &&
                            imageParam.im.At<Vec3b>(y2, x2).Item1 == imageParam.im.At<Vec3b>(y2, x2).Item2)
                        {
                            imageParam.mStitch.im.Set<Vec3b>(y1, x1, new Vec3b((byte)ColorR, (byte)ColorG, (byte)ColorB));
                        }
                        else
                        {

                        }

                        y2 = y2 + 1;
                    }
                    x2 = x2 + 1;
                }
            }

            //最终图
            img = new Mat(imageParam.mStitch.Pheight, imageParam.mStitch.Pwidth + imageParam.im.Width - x2 + 1, MatType.CV_8UC3);

            //分离出重叠区域
            Rect m_select = new Rect(x2 - 1, 0, imageParam.im.Width - x2 + 1, imageParam.mStitch.Pheight);
            Mat imgSwitch = new Mat(imageParam.im, m_select);
            Cv2.HConcat(imageParam.mStitch.im, imgSwitch, img);

            return img;
        }
    }
}