diff --git a/CMakeLists.txt b/CMakeLists.txt
index 7bbbf82..52d2c6d 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -5,6 +5,7 @@ set(CMAKE_CXX_STANDARD 17)  # 或更高版本
 set(CMAKE_CXX_STANDARD_REQUIRED ON)
 
 
+
 IF(WIN32)
 	# ======== OpenCV 配置 ========
 	set(OpenCV_DIR "C:/lib/opencv455/build/x64/vc14/lib")
@@ -24,12 +25,22 @@ IF(WIN32)
 							${Ceres_DIR}/include/glog)
 	include_directories(${Ceres_INCLUDE_DIR})
 
+
+
 	set(CERES_LIBRARIES
 	"${Ceres_DIR}/lib/ceres.lib"
 	"${Ceres_DIR}/lib/gflags.lib"
 	"${Ceres_DIR}/lib/glog.lib"
 	)
 
+	if(CMAKE_BUILD_TYPE STREQUAL "Debug")
+		set(CERES_LIBRARIES
+		"${Ceres_DIR}/lib/ceres-debug.lib"
+		"${Ceres_DIR}/lib/gflags_debug.lib"
+		"${Ceres_DIR}/lib/glogd.lib"
+		)
+	endif()
+
 ELSE()
 	# ======== OpenCV 配置 ========
 	find_package(OpenCV REQUIRED)
diff --git a/stitch/src/Arith_BATask.cpp b/stitch/src/Arith_BATask.cpp
index 3e39076..6f28c66 100644
--- a/stitch/src/Arith_BATask.cpp
+++ b/stitch/src/Arith_BATask.cpp
@@ -7,6 +7,8 @@
 using namespace ceres;
 #include "Logger.h"
 
+
+
 #define STABLE_X1 320
 #define STABLE_Y1 256
 
@@ -17,52 +19,42 @@ using namespace ceres;
 #define STABLE_Y3 1080
 
 
-// H投影残差：将左右图全都投影到全景图，最小化同名点全景图上的投影误差。
-// 问题：缺少尺度约束，H矩阵优化后失去正交性  优点：形式简单
+//// H投影残差：将左图投影到右图，最小化同名点全景图上的投影误差。
+//// 问题：缺少尺度约束，H矩阵优化后失去正交性  优点：形式简单
 struct HomographyResidual
 {
 
     HomographyResidual(const cv::KeyPoint& keypoint_i, const cv::KeyPoint& keypoint_j, const cv::Mat H1, const cv::Mat H2)
-        : keypoint_i_(keypoint_i), keypoint_j_(keypoint_j), Hi0_(H1), Hj0_(H2) 
+        : keypoint_i_(keypoint_i), keypoint_j_(keypoint_j),Hi0_(H1), Hj0_(H2)
     {
     }
 
-   
     template <typename T>
     bool operator()(const T* const h_i, const T* const h_j, T* residual) const
     {
-        // 残差计算逻辑
-        T H_i[9] = { h_i[0], h_i[1], h_i[2],
-                    h_i[3], h_i[4], h_i[5],
-                    h_i[6], h_i[7], T(1.0) };
+        typedef Eigen::Matrix<T, 3, 1> EPoint;
+        typedef Eigen::Matrix<T, 3, 3> EMat;
 
-        T H_j[9] = { h_j[0], h_j[1], h_j[2],
-                    h_j[3], h_j[4], h_j[5],
-                    h_j[6], h_j[7], T(1.0) };
+        EMat Mat_H_i;
+        Mat_H_i << T(h_i[0]), T(h_i[1]), T(h_i[2]),
+            T(h_i[3]), T(h_i[4]), T(h_i[5]),
+            T(h_i[6]), T(h_i[7]), T(1.0);
 
-        T p_i[3] = { T(keypoint_i_.pt.x), T(keypoint_i_.pt.y), T(1.0) };
-        T p_j[3] = { T(keypoint_j_.pt.x), T(keypoint_j_.pt.y), T(1.0) };
+        EMat Mat_H_j;
+        Mat_H_j << T(h_j[0]), T(h_j[1]), T(h_j[2]),
+            T(h_j[3]), T(h_j[4]), T(h_j[5]),
+            T(h_j[6]), T(h_j[7]), T(1.0);
 
-        T P_i[3] = { T(0), T(0), T(0) };
-        T P_j[3] = { T(0), T(0), T(0) };
+        EPoint p_i(T(keypoint_i_.pt.x), T(keypoint_i_.pt.y), T(1.0));
+        EPoint p_j(T(keypoint_j_.pt.x), T(keypoint_j_.pt.y), T(1.0));
 
-        for (int row = 0; row < 3; row++)
-        {
-            for (int col = 0; col < 3; col++)
-            {
-                P_i[row] += H_i[row * 3 + col] * p_i[col];
-                P_j[row] += H_j[row * 3 + col] * p_j[col];
-            }
-        }
 
-        P_i[0] /= P_i[2];
-        P_i[1] /= P_i[2];
-        P_j[0] /= P_j[2];
-        P_j[1] /= P_j[2];
+        EPoint warp_i = Mat_H_i * p_i;
+        EPoint img_j = Mat_H_j.inverse() * warp_i;
+        EPoint img_j_1 = img_j / img_j[2];
 
-        // 1.添加重投影误差
-        residual[0] = P_i[0] - P_j[0];
-        residual[1] = P_i[1] - P_j[1];
+        // 计算残差向量
+        residual[0] = (img_j_1 - p_j).squaredNorm();
 
 
         // 2. 不动点位置约束
@@ -70,42 +62,28 @@ struct HomographyResidual
         cv::Point2f pS2 = warpPointWithH(Hi0_, cv::Point2f(STABLE_X2, STABLE_Y2));
         cv::Point2f pS3 = warpPointWithH(Hi0_, cv::Point2f(STABLE_X3, STABLE_Y3));
 
-        T p_1[3] = { T(STABLE_X1), T(STABLE_Y1), T(1.0) };
-        T p_2[3] = { T(STABLE_X2), T(STABLE_Y2), T(1.0) }; 
-        T p_3[3] = { T(STABLE_X3), T(STABLE_Y3), T(1.0) };
-
-        T P_r1[3] = { T(0), T(0), T(0) };
-        T P_r2[3] = { T(0), T(0), T(0) };
-        T P_r3[3] = { T(0), T(0), T(0) };
-
-        for (int row = 0; row < 3; row++)
-        {
-            for (int col = 0; col < 3; col++)
-            {
-                P_r1[row] += H_i[row * 3 + col] * p_1[col];
-                P_r2[row] += H_i[row * 3 + col] * p_2[col];
-                P_r3[row] += H_i[row * 3 + col] * p_3[col];
-            }
-        }
+        EPoint pS1_E{ (T)pS1.x,(T)pS1.y ,T(1.0) };
+        EPoint pS2_E{ (T)pS2.x,(T)pS2.y,T(1.0) };
+        EPoint pS3_E{ (T)pS3.x,(T)pS3.y ,T(1.0) };
 
-        P_r1[0] /= P_r1[2];
-        P_r1[1] /= P_r1[2];
+        EPoint p_1{ T(STABLE_X1), T(STABLE_Y1), T(1.0) };
+        EPoint p_2{ T(STABLE_X2), T(STABLE_Y2), T(1.0) };
+        EPoint p_3{ T(STABLE_X3), T(STABLE_Y3), T(1.0) };
 
-        P_r2[0] /= P_r2[2];
-        P_r2[1] /= P_r2[2];
 
-        P_r3[0] /= P_r3[2];
-        P_r3[1] /= P_r3[2];
+        EPoint P_r1 = Mat_H_i * p_1;
+        EPoint P_r2 = Mat_H_i * p_2;
+        EPoint P_r3 = Mat_H_i * p_3;
 
-        // 约束中心点投影位置不变
-        residual[2] =  (P_r1[0] - (T)pS1.x);
-        residual[3] = P_r1[1] - (T)pS1.y;
+        P_r1 /= P_r1[2];
+        P_r2 /= P_r2[2];
+        P_r3 /= P_r3[2];
 
-        residual[4] = (P_r2[0] - (T)pS2.x);
-        residual[5] = P_r2[1] - (T)pS2.y;
 
-        residual[6] = (P_r3[0] - (T)pS3.x);
-        residual[7] = P_r3[1] - (T)pS3.y;
+        // 约束投影位置不变
+        residual[2] = (P_r1 - pS1_E).squaredNorm();
+        residual[3] = (P_r2 - pS2_E).squaredNorm();
+        residual[4] = (P_r3 - pS3_E).squaredNorm();
 
 
         return true;
@@ -121,29 +99,30 @@ private:
 
 };
 
+
+
 // SE3群优化
 // SE3群优化残差：将左图三角化后投影到右图，最小化相对投影误差
 // 问题：不是真正三角化，无深度优化。  优点：有尺度约束，标准做法，可对21个参数优化。
 struct SE3Residual
 {
-    SE3Residual(cv::KeyPoint keypoint_i, cv::KeyPoint keypoint_j,cv::Mat _K, double _fEvHeight)
-        : keypoint_i_(keypoint_i), keypoint_j_(keypoint_j),K(_K),EvHeight(_fEvHeight)
+    SE3Residual(cv::KeyPoint keypoint_i, cv::KeyPoint keypoint_j,cv::Mat _K, double _fEvHeight_i, double _fEvHeight_j)
+        : keypoint_i_(keypoint_i), keypoint_j_(keypoint_j),K(_K),EvHeight_i(_fEvHeight_i), EvHeight_j(_fEvHeight_j)
     {
         
     }
 
     template <typename T>
-    bool operator()(const T* const se3_i, const T* const se3_j,  T* residual) const
+    bool operator()(const T* const se3_i, const T* const se3_j, T* residual) const
     {
         // 左图投影到物方
        // T ptL[3] = {T(keypoint_i_.pt.x), T(keypoint_i_.pt.y)}; // 原始点
 
-
         // 深度矩阵
         Eigen::Matrix<T, 3, 3> M_het_inv;
         M_het_inv << T(1), T(0), T(0),
             T(0), T(1), T(0),
-            T(0), T(0), T(1.0 / EvHeight);
+            T(0), T(0), T(1.0 / EvHeight_i);
 
         // K-1
         Eigen::Matrix<T, 3, 3> K_1;
@@ -176,18 +155,20 @@ struct SE3Residual
         // 恢复尺度
         T GeoX = result[0] / result[2];
         T GeoY = result[1] / result[2];
-
+        T GeoZ = T(EvHeight_i);
         // 平移，获得地理坐标
         GeoX += se3_i[3];
         GeoY += se3_i[4];
+        GeoZ += se3_i[5];
 
         // 正算，投影到右图
         GeoX += -se3_j[3];
         GeoY += -se3_j[4];
+        GeoZ += -se3_j[5];
 
         T rvec_j[3] = { se3_j[0], se3_j[1], se3_j[2] };
 
-        Eigen::Matrix<T, 3, 1> pGeoR(GeoX, GeoY, T(EvHeight));
+        Eigen::Matrix<T, 3, 1> pGeoR(GeoX, GeoY, GeoZ);
         Eigen::Matrix<T, 3, 1> RightRota;
 
         ceres::AngleAxisRotatePoint(rvec_j, pGeoR.data(), RightRota.data());
@@ -200,9 +181,10 @@ struct SE3Residual
         T vR = pUVR[1] / pUVR[2];
 
 
-         // 计算重投影误差
-         residual[0] = uR - T(keypoint_j_.pt.x);
-         residual[1] = vR - T(keypoint_j_.pt.y);
+        // 计算重投影误差
+        residual[0] = uR - T(keypoint_j_.pt.x);
+        residual[1] = vR - T(keypoint_j_.pt.y);
+
 
 
         return true;
@@ -211,20 +193,16 @@ private:
     const cv::KeyPoint keypoint_i_; // 第 i 帧图像中的特征点
     const cv::KeyPoint keypoint_j_; // 第 j 帧图像中的特征点
     cv::Mat_<double> K;  //内参
-    double EvHeight;//高差，用于三角化
+    double EvHeight_i;//高差，用于三角化
+    double EvHeight_j;//高差，用于三角化
 };
 
 
 
-
-
-
-
-
-BA_Task::BA_Task(FileCache<FrameCache>* cache)
+BA_Task::BA_Task(FileCache<FrameCache>* cache, FeatureMatcher* feaProcess)
 {
 	_cache = cache;
-    _FeaMatcher = new FeatureMatcher(DetectorType::SIFT, MatcherType::FLANN);
+    _FeaMatcher = feaProcess;
 
     //google::InitGoogleLogging("ceres");
 }
@@ -253,8 +231,10 @@ void BA_Task::InitTask()
 
 
 
-void BA_Task::OptFrame(vector<KeyType> frameInd,cv::Mat H_map)
+void BA_Task::OptFrame(vector<KeyType> frameInd,cv::Mat H_map, std::unordered_map <KeyType, cv::Mat>& global_H)
 {
+    std::lock_guard<std::mutex> lock(mutex_);
+
     // 任务容器初始化
     InitTask();
 
@@ -276,10 +256,10 @@ void BA_Task::OptFrame(vector<KeyType> frameInd,cv::Mat H_map)
 
 
     // 整合为6D参数
-    std::vector<double*> se3_list(_currse3.size());
+    std::vector<double*> se3list(_currse3.size());
     for (int i = 0; i < _currse3.size(); i++)
     {
-        se3_list[i] = (double*)_currse3[i].data;
+        se3list[i] = (double*)_currse3[i].data;
     }
 
     constK = cv::Mat(3, 3, CV_64FC1, ((double*)_origRtK[0].data) + 12);
@@ -287,6 +267,7 @@ void BA_Task::OptFrame(vector<KeyType> frameInd,cv::Mat H_map)
     // 创建 Ceres 问题
     ceres::Problem problemH;
     ceres::Problem problemSE3;
+    ceres::Problem problemH2;
 
     // 添加残差块
     int nParaCnt = 0;//参数组数
@@ -301,6 +282,7 @@ void BA_Task::OptFrame(vector<KeyType> frameInd,cv::Mat H_map)
                 continue;
             }
 
+
             std::vector<cv::DMatch> matches;
             //_FeaMatcher->matchFeatures(_FeaDespVec[i],_FeaDespVec[j],matches);
             _FeaMatcher->matchFeatures_WithH(_FeaPtVec[i], _FeaDespVec[i], _FeaPtVec[j], _FeaDespVec[j], _origMatrix[i], _origMatrix[j], matches);
@@ -319,11 +301,13 @@ void BA_Task::OptFrame(vector<KeyType> frameInd,cv::Mat H_map)
             // 绘制匹配结果
             drawMatch(i, j, matches, H_map);
 #endif
-
+            
             // 添加匹配点对的残差块
             for (int m = 0; m < matches.size(); m++)
             {
                 auto mc = matches[m];
+
+
                 // 注意：这里不对，应该找匹配点！！ todo 节后完成
                 cv::KeyPoint keypoint_i = _FeaPtVec[i][mc.queryIdx];
                 cv::KeyPoint keypoint_j = _FeaPtVec[j][mc.trainIdx];
@@ -339,16 +323,18 @@ void BA_Task::OptFrame(vector<KeyType> frameInd,cv::Mat H_map)
                 cv::Mat Hj0 = _origMatrix[j];
 
 #ifdef OPT_H
+
                 ceres::CostFunction* cost_function =
-                    new ceres::AutoDiffCostFunction<HomographyResidual, 8, 8, 8>(
+                    new ceres::AutoDiffCostFunction<HomographyResidual, 4, 8, 8>(
                         new HomographyResidual(keypoint_i, keypoint_j, Hi0, Hj0));
-                problemH.AddResidualBlock(cost_function, scale_loss, h_list[i], h_list[j]);
+                problemH2.AddResidualBlock(cost_function, scale_loss, h_list[i], h_list[j]);
+#endif
 
-#else
-                ceres::CostFunction* cost_function =
+#ifdef OPT_SE3
+               ceres::CostFunction* cost_function =
                    new ceres::AutoDiffCostFunction<SE3Residual,2,6,6>(
-                       new SE3Residual(keypoint_i, keypoint_j, constK, constHeight));
-                problemSE3.AddResidualBlock(cost_function, scale_loss, se3_list[i],se3_list[j]);
+                       new SE3Residual(keypoint_i, keypoint_j, constK, _depth[i], _depth[j]));
+                problemSE3.AddResidualBlock(cost_function, scale_loss, se3list[i], se3list[j]);
 #endif
 
             }
@@ -361,38 +347,37 @@ void BA_Task::OptFrame(vector<KeyType> frameInd,cv::Mat H_map)
     // 配置求解器
     ceres::Solver::Options options;
     options.max_num_iterations = 10; // 增加最大迭代次数
-    options.function_tolerance = 1e-5; // 设置更严格的函数值容忍度
-    options.gradient_tolerance = 1e-5; // 设置更严格的梯度容忍度
-    options.parameter_tolerance = 1e-5; // 设置更严格的参数容忍度
+    options.function_tolerance = 1e-15; // 设置更严格的函数值容忍度
+    options.gradient_tolerance = 1e-15; // 设置更严格的梯度容忍度
+    options.parameter_tolerance = 1e-15; // 设置更严格的参数容忍度
     options.minimizer_progress_to_stdout = true;
     //options.linear_solver_type = ceres::SPARSE_NORMAL_CHOLESKY; // 使用稀疏求解器
-    options.num_threads = 12; // 使用多线程
+    options.num_threads = 8; // 使用多线程
+
     
     ceres::Solver::Summary summary;
 
     // 求解
 #ifdef OPT_H
-    ceres::Solve(options, &problemH, &summary);
-#else
-    ceres::Solve(options, &problemSE3, &summary);
+    ceres::Solve(options, &problemH2, &summary);
 #endif
 
-    //for (int i = 0; i < _origse3.size(); i++)
-    //{
-    //    std::cout << "------------" << std::endl;
-    //    std::cout << _origse3[i] << std::endl;
-    //    std::cout << _currse3[i] << std::endl;
-    //    std::cout << "------------" << std::endl;
-    //}
-
-
+#ifdef OPT_SE3
+    ceres::Solve(options, &problemSE3, &summary);
+#endif
 
     // 输出结果
-    //std::cout << summary.BriefReport() << std::endl;
+    std::cout << summary.BriefReport() << std::endl;
+    for (int i = 0; i < _currse3.size(); i++)
+    {
+        std::cout << "-----SE3------" << std::endl;
+        std::cout << _origse3[i]- _currse3[i] << std::endl;
+        std::cout << "------------" << std::endl;
+    }
 
-#ifndef OPT_H
+#ifdef OPT_SE3
     // 将优化se3写入H
-    updateSe3();
+    updateSe3toH();
 #endif
 
     //for (int i = 0; i < _origMatrix.size(); i++)
@@ -406,22 +391,35 @@ void BA_Task::OptFrame(vector<KeyType> frameInd,cv::Mat H_map)
     
 
     // 优化后H写入文件缓存
-    writeFrameInfo();
+    for (size_t i = 0; i < _currMatrix.size(); i++)
+    {
+        auto Key = _frameInd[i];
+
+        // 更新缓存
+        updateCacheH(Key, _currMatrix[i], global_H);
+    }
 
     
 }
 
 
-bool BA_Task::updateCacheH(KeyType Key, cv::Mat H)
+bool BA_Task::updateCacheH(KeyType Key, cv::Mat H, std::unordered_map <KeyType, cv::Mat>& global_H)
 {
 	auto _t_frame_cache = std::make_shared<FrameCache>();
 
 	if (_cache->get(Key, _t_frame_cache))
 	{
+        //cv::Mat old(3, 3, CV_64FC1, _t_frame_cache->H);
+        //std::cout << "before" << old << std::endl;
+        //std::cout << "after" << H << std::endl;
 		// 更新H
 		memcpy(_t_frame_cache->H, H.data, sizeof(double) * 9);
+
 		// 存储
 		_cache->set(Key, _t_frame_cache);
+
+        global_H[Key] = H.clone();
+
 		return true;
 	}
 
@@ -432,7 +430,6 @@ int BA_Task::readFrameInfo(vector<KeyType> frameInd)
 {
     auto _t_frame_cache = std::make_shared<FrameCache>();
     _cache->get(frameInd[0], _t_frame_cache);
-    constHeight = _t_frame_cache->_para.nEvHeight;
 
     for (size_t i = 0; i < frameInd.size(); i++)
     {
@@ -442,6 +439,8 @@ int BA_Task::readFrameInfo(vector<KeyType> frameInd)
             // 记录key
             _frameInd.push_back(key);
 
+            _depth.push_back(_t_frame_cache->_para.nEvHeight);
+
             // 注意Mat 浅拷贝陷阱！！！！！！
 
             // 特征点
@@ -482,27 +481,17 @@ int BA_Task::readFrameInfo(vector<KeyType> frameInd)
     return 0;
 }
 
+
 #include <Arith_GeoSolver.h>
-void BA_Task::updateSe3()
+void BA_Task::updateSe3toH()
 {
     for (size_t i = 0; i < _origse3.size(); i++)
     {
-        _currMatrix[i] = Transe3ToH((double*)_origse3[i].data,  constK, constHeight);
+        _currMatrix[i] = Transe3ToH((double*)_currse3[i].data,  constK, _depth[i]);
     }
 }
 
-int BA_Task::writeFrameInfo()
-{
-    for (size_t i = 0; i < _currMatrix.size(); i++)
-    {
-        auto Key = _frameInd[i];
 
-		// 更新缓存
-		updateCacheH(Key, _currMatrix[i]);
-    }
-
-    return 0;
-}
 
 SINT32 BA_Task::CalMatchMat()
 {
diff --git a/stitch/src/Arith_BATask.h b/stitch/src/Arith_BATask.h
index 1a377c8..f526d94 100644
--- a/stitch/src/Arith_BATask.h
+++ b/stitch/src/Arith_BATask.h
@@ -17,23 +17,24 @@
 
 
 //#define SHOW_MATCH
-//#define OPT_H
 
+//#define OPT_H
+#define OPT_SE3
 
 class  BA_Task
 {
 public:
-	BA_Task(FileCache<FrameCache>* cache);
+	BA_Task(FileCache<FrameCache>* cache, FeatureMatcher* feaProcess);
 	~BA_Task();
 
 	// 初始化BA任务
 	void InitTask();
 
 	// 优化指定帧，并更新H到缓存中,H_map用于优化过程可视化
-	void OptFrame(vector<KeyType> frameInd, cv::Mat H_map);
+	void OptFrame(vector<KeyType> frameInd, cv::Mat H_map, std::unordered_map <KeyType, cv::Mat>& global_H);
+
+
 
-	// 更新缓存中的帧H矩阵，并存储
-	bool updateCacheH(KeyType Key, cv::Mat H);
 
 private:
 
@@ -41,10 +42,11 @@ private:
 	int readFrameInfo(vector<KeyType> frameInd);
 
 	// 更新se3到H
-	void updateSe3();
+	void updateSe3toH();
 
-	// 输出优化结果到cache
-	int writeFrameInfo();
+
+	// 更新缓存中的帧H矩阵，并存储到缓存
+	bool updateCacheH(KeyType Key, cv::Mat H, std::unordered_map <KeyType, cv::Mat>& global_H);
 
 	SINT32 CalMatchMat();//计算匹配性矩阵
 
@@ -67,20 +69,22 @@ private:
 	vector<cv::Mat_<double>> _currMatrix;//当前H矩阵
 
 	// 21维内外参完整参数
-	vector<cv::Mat_<double>> _origRtK;    // 初始RtK参数
+	vector<cv::Mat_<double>> _origRtK;  // 初始RtK参数
 	vector<cv::Mat_<double>> _currRtK;	// 当前RtK参数
 
 	// 提取R->旋转向量 + t
-	vector<cv::Mat_<double>> _origse3;    // 初始旋转向量
+	vector<cv::Mat_<double>> _origse3;  // 初始旋转向量
 	vector<cv::Mat_<double>> _currse3;	// 当前旋转向量
 
 
+	vector<double> _depth;
+
 	vector<vector<cv::Point2f>> _polygon;//帧包围四边形
 	vector<vector<cv::KeyPoint>> _FeaPtVec;//特征点缓存
 	vector<cv::Mat> _FeaDespVec;//特征点描述子
 	vector<FrameInfo> _paraVec;
 
-	double constHeight;
+
 	cv::Mat constK;
 
 private:
@@ -88,6 +92,8 @@ private:
 	// 调试：绘制匹配关系
 	void drawMatch(int i, int j, std::vector<cv::DMatch> match,cv::Mat H_map);
 
+	std::mutex mutex_;
+
 };
 
 
diff --git a/stitch/src/Arith_BlendMap.cpp b/stitch/src/Arith_BlendMap.cpp
index 7627735..460f8f9 100644
--- a/stitch/src/Arith_BlendMap.cpp
+++ b/stitch/src/Arith_BlendMap.cpp
@@ -35,6 +35,7 @@ cv::Mat MapBlend::getPanMaskMat()
 
 void MapBlend::ClearPan()
 {
+	std::lock_guard<std::mutex> lock(mutex_);
 	_panImage.setTo(0);
 	_panMask.setTo(0);
 }
@@ -245,7 +246,7 @@ void MapBlend::FrameMap_1(cv::Mat src, cv::Mat H_Geo, cv::Mat mapH)
 
 void MapBlend::BatchMapWithH(const vector<KeyType> frameInd, const cv::Mat mapH, std::unordered_map <KeyType, cv::Mat>allH, BLEND_TYPE blendType)
 {
-
+	std::lock_guard<std::mutex> lock(mutex_);
 	if (frameInd.empty())
 	{
 		return;
@@ -324,6 +325,7 @@ void MapBlend::BatchMapWithH(const vector<KeyType> frameInd, const cv::Mat mapH,
 
 void MapBlend::BatchMap(const vector<KeyType> frameInd, const cv::Mat mapH, BLEND_TYPE blendType)
 {
+	std::lock_guard<std::mutex> lock(mutex_);
 	// 从文件缓存获取帧
 	auto _t_frame_cache = std::make_shared<FrameCache>();
 
diff --git a/stitch/src/Arith_BlendMap.h b/stitch/src/Arith_BlendMap.h
index 34a19eb..f81c3aa 100644
--- a/stitch/src/Arith_BlendMap.h
+++ b/stitch/src/Arith_BlendMap.h
@@ -69,6 +69,8 @@ private:
 
 	cv::Mat _panMask; //覆盖区域遮罩
 
+	std::mutex mutex_;
+
 };
 
 
diff --git a/stitch/src/Arith_GeoSolver.cpp b/stitch/src/Arith_GeoSolver.cpp
index 03264e2..8c5c4a6 100644
--- a/stitch/src/Arith_GeoSolver.cpp
+++ b/stitch/src/Arith_GeoSolver.cpp
@@ -133,7 +133,6 @@ Mat GeoSolver::Mat_TransENG2uv(FrameInfo info)
 	//[u,v,1]'=Z*M*[X,Y,DH]' = Z*M*[1,0,0;0,1,0;0,0,DH]'*[X,Y,1]'
 	//[u,v,1]'=Z*M(内参)*M(alaph)*M(beta)*M(roll)*M(pitch)*M(yaw)*[X,Y,DH]
 
-
 	// 深度矩阵
 	Mat M_het = (Mat_<double>(3, 3) << 1, 0, 0,
 		0, 1, 0,
@@ -246,17 +245,25 @@ cv::Mat TransRtKToH(RtK rtk, double Depth)
 		(R[3] + T[1] * R[6]), (R[4] + T[1] * R[7]), (R[5] + T[1] * R[8]),
 		R[6], R[7], R[8]);
 
-
 	// 归一化
 	H = H / H.at<double>(2, 2);
 
-	return H;
+	return H.clone();
 }
 
 cv::Mat Transe3ToH(double* se3, cv::Mat K, double Depth)
 {
 	RtK rtk;
 	cv::Rodrigues(cv::Mat(3, 1, CV_64FC1, se3), rtk.R);
+
+
+	//cv::Mat w, u, vt;
+	//cv::SVD::compute(rtk.R, w, u, vt);
+
+	//// 核心：确保 u * vt 是精确的正交矩阵
+	//// 而不是直接对R进行尺度归一化
+	//rtk.R = u * vt;
+
 	rtk.T = cv::Mat(3, 1, CV_64FC1, se3 + 3);
 
 	rtk.K = K;
@@ -304,8 +311,6 @@ cv::Mat GeoSolver::findHomography(FrameInfo info)
 	tf_p2g.R = Mat_TransENG2uv(info).inv();
 	tf_p2g.T = Mat_TransENGMove(info);
 
-
-
 	double R[9] = { 0 };
 	double T[3] = { 0 };
 
diff --git a/stitch/src/Arith_GeoSolver.h b/stitch/src/Arith_GeoSolver.h
index f5fa420..2d133c4 100644
--- a/stitch/src/Arith_GeoSolver.h
+++ b/stitch/src/Arith_GeoSolver.h
@@ -68,8 +68,6 @@ private:
     // 计算当前帧李群（SE3）和投影K
     RtK AnlayseRtK(FrameInfo info);
 
-
-
     // 帧像方-地理坐标
     cv::Point2f Trans_uv2Geo(cv::Point2f pos_frame, TForm form);
 
diff --git a/stitch/src/Arith_UnderStitch.cpp b/stitch/src/Arith_UnderStitch.cpp
index e854e5a..d3a11de 100644
--- a/stitch/src/Arith_UnderStitch.cpp
+++ b/stitch/src/Arith_UnderStitch.cpp
@@ -55,11 +55,9 @@ UnderStitch::UnderStitch(std::string cachedir)
 
 	_GeoSolver = new GeoSolver();
 
-	_FeaMatcher = new FeatureMatcher(DetectorType::ORB, MatcherType::FLANN);
+	_FeaMatcher = new FeatureMatcher(DetectorType::ORB, MatcherType::BF);
 
-	_BATask = new BA_Task(_cache);
-
-	/*_BlendTask = new MapBlend(_cache);*/
+	_BATask = new BA_Task(_cache, _FeaMatcher);
 
 	_panPara = { 0 };
 
@@ -125,7 +123,7 @@ UPanInfo UnderStitch::InitMap(FrameInfo para)
 	auto geo_pro_rect = warpRectWithH_2Rect(H0,cv::Size(para.nWidth, para.nHeight));
 	
 	// 计算目标比例（单帧投影后占全景图的0.25）
-	float target_ratio = 0.08;
+	float target_ratio = 0.25;
 	float current_ratio = MAX(geo_pro_rect.width / (target_ratio*panPara.m_pan_width), geo_pro_rect.height / (target_ratio*panPara.m_pan_height));
 
 	// 调整scale参数
@@ -348,6 +346,31 @@ UPanInfo UnderStitch::ShiftMap(FrameInfo para,int& shift_x,int& shift_y)
 }
 
 
+
+void UnderStitch::run_test(FrameInfo para)
+{
+	cv::Mat H1 = _GeoSolver->findHomography(para);
+
+	RtK rtk;
+	cv::Mat H2 = _GeoSolver->findHomography(para, rtk);
+
+
+
+	cv::Vec3d rvec;
+	cv::Rodrigues(rtk.R, rvec);
+
+
+	double se3[6] = { 0 };
+	memcpy(se3, rvec.val, sizeof(double) * 3);
+	memcpy(se3 + 3, rtk.T.data, sizeof(double) * 3);
+
+	auto H3 = Transe3ToH(se3,rtk.K, para.nEvHeight);
+
+
+	int a = 0;
+}
+
+
 UPanInfo UnderStitch::Init(FrameInfo info)
 {
 	// 以向下零位初始化
@@ -425,6 +448,8 @@ SINT32 UnderStitch::Run(GD_VIDEO_FRAME_S frame, FrameInfo para)
 	LOG_INFO("Run Frame {}", para.nFrmID);
 	TransPitch(para);
 
+	run_test(para);
+
     //// 视频帧筛选
     if (!FilterFrame(para))
     {
@@ -447,6 +472,7 @@ SINT32 UnderStitch::Run(GD_VIDEO_FRAME_S frame, FrameInfo para)
 	if (!isFrameInPanView(cv::Size(para.nWidth, para.nHeight), _H_pan * H_geo,
 		cv::Size(_panPara.m_pan_width, _panPara.m_pan_height)))
 	{
+
 		LOG_INFO("Frame {} is out of pan view, reinitializing projection parameters", para.nFrmID);
 
 		// 输出当前所有瓦片，再不输出就会丢失当前全景中的瓦片
@@ -472,6 +498,9 @@ SINT32 UnderStitch::Run(GD_VIDEO_FRAME_S frame, FrameInfo para)
 		// 清空全景视场
 		_MapBlender->ClearPan();
 
+		// 清空视场内帧
+		_baCurrViewKey.clear();
+
 		// 将BatchMap操作放入线程池中后台处理
 		_threadPool.commit([this, recvFrameKeys=_recvFrameKey, h_pan=_H_pan, Hgeos = _frameGeoHAll]() {
 			_MapBlender->BatchMapWithH(recvFrameKeys, h_pan, Hgeos);
@@ -499,7 +528,6 @@ SINT32 UnderStitch::Run(GD_VIDEO_FRAME_S frame, FrameInfo para)
 	// 投影帧到全景
 	_MapBlender->FrameMap(src, H_geo, _H_pan);
 
-
 	// 预处理+缓存
 	ReceiveFrame(frame, para);
 
@@ -509,10 +537,11 @@ SINT32 UnderStitch::Run(GD_VIDEO_FRAME_S frame, FrameInfo para)
 		// 异步执行BA优化
 		_threadPool.commit(
 			[this]() {
-				OptAndOutCurrPan();
+				OptAndOutCurrPan(_baWindowKey);
 			},
 			"BA_Optimization"
 		);
+
 	}
 
 	return 0;
@@ -520,33 +549,50 @@ SINT32 UnderStitch::Run(GD_VIDEO_FRAME_S frame, FrameInfo para)
 }
 
 
-
 void UnderStitch::Stop()
 {
 	_recvFrameKey.clear();
-	_baWindowKey.clear();
+	_baWindowKey.clear(); 
+	_baCurrViewKey.clear();
 	_cache->clear();
 }
 
+
 SINT32 UnderStitch::OptAndOutCurrPan()
 {
-	LOG_INFO("BA_Optimization start{}-{}",_baWindowKey[0],_baWindowKey[_baWindowKey.size()-1]);
+	return 0;
+}
+
+SINT32 UnderStitch::OptAndOutCurrPan(vector<KeyType> workFrame)
+{
+	LOG_INFO("BA_Optimization start{}-{}", workFrame[0], workFrame[workFrame.size()-1]);
 	if (_config.bUseBA)
 	{
+		//BA_Task* task = new BA_Task(_cache, _FeaMatcher);
 		// 优化滑动窗口内的帧
-		_BATask->OptFrame(_baWindowKey, _H_pan);
+		_BATask->OptFrame(workFrame, _H_pan, _frameGeoHAll);
 		LOG_INFO("BA_Optimization finish");
 	}
 
 	// 重投影所有帧到全景，这里以文件缓存H为准，因为优化结果直接更新到cache中
-	_MapBlender->BatchMap(_baWindowKey, _H_pan);
+	_MapBlender->BatchMap(workFrame, _H_pan);
 
 	// 输出当前所有瓦片
 	LOG_INFO("ExportTileSet");
 	_googleProduct.ExportTileSet(_MapBlender->getPanImageMat(), _MapBlender->getPanMaskMat(), 
 		_taskTilesVec, _outDir, _filename + std::to_string(_lastFrameKey));
 
-	return _baWindowKey.size();
+	return workFrame.size();
+}
+
+SINT32 UnderStitch::BatchAdjust(vector<KeyType> ids)
+{
+
+	// 优化滑动窗口内的帧
+	_BATask->OptFrame(ids, _H_pan, _frameGeoHAll);
+	LOG_INFO("BA_Optimization finish");
+
+	return ids.size();
 }
 
 
@@ -603,7 +649,7 @@ bool UnderStitch::FilterFrame(FrameInfo para)
 bool UnderStitch::TriggerBA(FrameInfo para)
 {
     // 1. 固定帧间隔触发
-    const int FIXED_FRAME_INTERVAL = 10;
+    const int FIXED_FRAME_INTERVAL = 30;
     if (_totalFrameCnt % FIXED_FRAME_INTERVAL == 0)
     {
         LOG_INFO("TriggerBA: Fixed frame interval {} reached",FIXED_FRAME_INTERVAL);
@@ -771,7 +817,7 @@ SINT32 UnderStitch::ReceiveFrame(GD_VIDEO_FRAME_S img, FrameInfo para)
 	// 深拷贝图像数据
 	memcpy(_t_frame_cache->_data,img.u64VirAddr[0],imgSize);
 
-
+	_t_frame_cache->nHeight = para.nEvHeight;
 
 	// 开启BA才提取特征
 	if (_config.bUseBA)
@@ -842,6 +888,8 @@ SINT32 UnderStitch::ReceiveFrame(GD_VIDEO_FRAME_S img, FrameInfo para)
 
 	_recvFrameKey.push_back(para.nFrmID);
 	_baWindowKey.push_back(para.nFrmID);
+	_baCurrViewKey.push_back(para.nFrmID);
+
 
 	// 保持滑动窗口大小
 	const size_t WINDOW_SIZE = 30;  // 滑动窗口大小
@@ -853,7 +901,7 @@ SINT32 UnderStitch::ReceiveFrame(GD_VIDEO_FRAME_S img, FrameInfo para)
 	// 优化表初始化
 	_recvFrameOptFlag[para.nFrmID] = 0;
 
-
+	
 
 
 
diff --git a/stitch/src/Arith_UnderStitch.h b/stitch/src/Arith_UnderStitch.h
index 781bf96..4526262 100644
--- a/stitch/src/Arith_UnderStitch.h
+++ b/stitch/src/Arith_UnderStitch.h
@@ -43,6 +43,10 @@ public:
 
     SINT32 OptAndOutCurrPan();
 
+    SINT32 OptAndOutCurrPan(vector<KeyType> workFrame);
+
+    SINT32 BatchAdjust(vector<KeyType> ids);
+
     GD_VIDEO_FRAME_S     ExportPanAddr();
 
     cv::Mat ExportPanMat();
@@ -56,7 +60,6 @@ private:
     // 俯仰零位转换
     void TransPitch(FrameInfo& para);
      
-    
     // 判断帧是否在全景图视场内
     bool isFrameInPanView(const cv::Size& frameSize, const cv::Mat& H, const cv::Size& panSize);
 
@@ -95,10 +98,14 @@ private:
     // 重新定位全景图配置，用于帧超出全景图视场时平移调整
     UPanInfo     ShiftMap(FrameInfo para,int& shift_x,int& shift_y);
 
+
+    void run_test(FrameInfo para);
+
 private:
 
     vector<KeyType> _recvFrameKey;// 接收帧总表
     vector<KeyType> _baWindowKey;// BA滑动窗口
+    vector<KeyType> _baCurrViewKey;//当前视口内帧
     std::map<KeyType, int> _recvFrameOptFlag;//接收帧的优化标记
 
     // 邻接关系表
diff --git a/stitch/src/FrontStitch/Arith_FrontStitch.cpp b/stitch/src/FrontStitch/Arith_FrontStitch.cpp
index bd9b067..9e1e39c 100644
--- a/stitch/src/FrontStitch/Arith_FrontStitch.cpp
+++ b/stitch/src/FrontStitch/Arith_FrontStitch.cpp
@@ -36,7 +36,7 @@ FrontStitch::FrontStitch(std::string cachedir)
 
     _FeaMatcher = new FeatureMatcher(DetectorType::SIFT, MatcherType::FLANN);
 
-    _BATask = new BA_Task(_cache);
+    _BATask = new BA_Task(_cache, _FeaMatcher);
 
     _FBlendTask = new FrontMapBlend(_cache);
 }
@@ -380,18 +380,6 @@ SINT32 FrontStitch::ReceiveFrame(GD_VIDEO_FRAME_S img, FrameInfo para)
     return _totalFrameCnt;
 }
 
-SINT32 FrontStitch::ProcessFrame(vector<KeyType> keys)
-{
-    if (keys.size() == 0)
-    {
-        return -1;
-    }
-
-    // 优化所有帧
-    _BATask->OptFrame(keys, cv::Mat::zeros(cv::Size(3,3),CV_8UC1));
-
-    return 0;
-}
 
 
 
diff --git a/stitch/src/FrontStitch/Arith_FrontStitch.h b/stitch/src/FrontStitch/Arith_FrontStitch.h
index f7d7d8f..7c92b8b 100644
--- a/stitch/src/FrontStitch/Arith_FrontStitch.h
+++ b/stitch/src/FrontStitch/Arith_FrontStitch.h
@@ -133,8 +133,6 @@ private:
     // 缓存接收帧
     SINT32 ReceiveFrame(GD_VIDEO_FRAME_S img, FrameInfo para);
 
-    // 处理帧
-    SINT32 ProcessFrame(vector<KeyType> keys);
 
 
 private:
diff --git a/stitch/src/StitchStruct.h b/stitch/src/StitchStruct.h
index 9b54bd8..9ea4098 100644
--- a/stitch/src/StitchStruct.h
+++ b/stitch/src/StitchStruct.h
@@ -76,6 +76,8 @@ struct FrameCache
     // SE3
     DOUBLE64 RtK[21];  //R(9)+T(3)+K(9)
     DOUBLE64 se3[6];     //旋转向量+平移向量，李代数（优化项）
+
+    DOUBLE64 nHeight;
 };
 
 
diff --git a/stitch/src/Version.h b/stitch/src/Version.h
index 46c777c..0007ede 100644
--- a/stitch/src/Version.h
+++ b/stitch/src/Version.h
@@ -2,5 +2,5 @@
 
 #pragma once
 #include <string>
-std::string BUILD_TIME = "BUILD_TIME 2025_11_11-09.47.45";
+std::string BUILD_TIME = "BUILD_TIME 2025_11_14-15.38.58";
 std::string VERSION = "BUILD_VERSION 1.0.1";
diff --git a/tests/ProcDJ.cpp b/tests/ProcDJ.cpp
index f271da7..da4f5e4 100644
--- a/tests/ProcDJ.cpp
+++ b/tests/ProcDJ.cpp
@@ -156,9 +156,9 @@ std::vector<FrameData> parseDJISRT(const std::string& filename) {
 
 void ProcDJVideo(vector<std::string> videoPathList, vector<std::string> srtPathList)
 {
-    auto stitcher = API_UnderStitch::Create();
+    auto stitcher = API_UnderStitch::Create("F:/cache");
 
-    stitcher->SetOutput("DJI", "D:/google_tiles");
+    stitcher->SetOutput("DJI", "F:/google_tiles");
 
     GD_VIDEO_FRAME_S frame = { 0 };//输入帧
     GD_VIDEO_FRAME_S pan = { 0 };//输出全景
@@ -187,7 +187,7 @@ void ProcDJVideo(vector<std::string> videoPathList, vector<std::string> srtPathL
 
     std::vector<FrameData> srt_init = parseDJISRT(srtPathList[0]);
 
-    int nStart = 3550;
+    int nStart = 2000;
 
     FrameInfo info = { 0 };
     info.nFrmID = nStart;
@@ -195,7 +195,7 @@ void ProcDJVideo(vector<std::string> videoPathList, vector<std::string> srtPathL
     info.camInfo.fPixelSize = srt_init[nStart].pixel_size_um * nDownSample;
 
     info.craft.stAtt.fYaw = srt_init[nStart].gb_yaw;
-    info.craft.stAtt.fPitch = srt_init[nStart].gb_pitch;
+    info.craft.stAtt.fPitch = 0;
     info.craft.stAtt.fRoll = srt_init[nStart].gb_roll;
 
     info.craft.stPos.B = srt_init[nStart].latitude;
@@ -206,7 +206,7 @@ void ProcDJVideo(vector<std::string> videoPathList, vector<std::string> srtPathL
     info.nEvHeight = srt_init[nStart].rel_alt;
 
     info.servoInfo.fServoAz = 0;
-    info.servoInfo.fServoPt = 0;
+    info.servoInfo.fServoPt = srt_init[nStart].gb_pitch;
 
     info.nWidth = width / nDownSample;
     info.nHeight = height / nDownSample;
@@ -217,7 +217,7 @@ void ProcDJVideo(vector<std::string> videoPathList, vector<std::string> srtPathL
     UPanConfig cfg = { 0 };
     cfg.bOutFrameTile = 0;
     cfg.bOutGoogleTile = 1;
-    cfg.bUseBA = 0;
+    cfg.bUseBA = 1;
     stitcher->SetConfig(cfg);
 
     mat_pan = stitcher->ExportPanMat();
@@ -266,15 +266,13 @@ void ProcDJVideo(vector<std::string> videoPathList, vector<std::string> srtPathL
 
             cv::resize(mat, mat_ds2, cv::Size(width / nDownSample, height / nDownSample));
 
-
-
             FrameInfo info = { 0 };
             info.nFrmID = frmID;
             info.camInfo.nFocus = srt[frmID].real_focal_mm;
             info.camInfo.fPixelSize = srt[frmID].pixel_size_um * nDownSample;
 
             info.craft.stAtt.fYaw = srt[frmID].gb_yaw;
-            info.craft.stAtt.fPitch = srt[frmID].gb_pitch;
+            info.craft.stAtt.fPitch = 0;
             info.craft.stAtt.fRoll = srt[frmID].gb_roll;
 
             info.craft.stPos.B = srt[frmID].latitude;
@@ -285,7 +283,7 @@ void ProcDJVideo(vector<std::string> videoPathList, vector<std::string> srtPathL
             info.nEvHeight = srt[frmID].abs_alt;
 
             info.servoInfo.fServoAz = 0;
-            info.servoInfo.fServoPt = 0;
+            info.servoInfo.fServoPt = srt[frmID].gb_pitch;
 
             info.nWidth = mat_ds2.cols;
             info.nHeight = mat_ds2.rows;
@@ -372,18 +370,11 @@ int main()
     vector<std::string> videoPathList;
     vector<std::string> srtPathList;
 
-    string folder = "F:/DJI_202504181507_016/";
+    string folder = "F:/K2D_data/";
 
-    folder = "D:/H30T云台/DJI_202504181507_016/";
-    //string folder = "/media/wang/data/DJI_202504181507_016/";
-    //
-    //videoPathList.push_back(folder + "DJI_20250418152649_0005_W.MP4");
-	//srtPathList.push_back(folder + "DJI_20250418152649_0005_W.srt");
 
-  // videoPathList.push_back(folder + "DJI_20250418153043_0006_W.MP4");
-   //srtPathList.push_back(folder + "DJI_20250418153043_0006_W.srt");
-    videoPathList.push_back(folder + "DJI_20250418152649_0005_W.MP4");
-    srtPathList.push_back(folder + "DJI_20250418152649_0005_W.srt");
+    videoPathList.push_back(folder + "DJI_20250418153043_0006_W.MP4");
+    srtPathList.push_back(folder + "DJI_20250418153043_0006_W.srt");
 
    //videoPathList.push_back(folder + "DJI_20250418153043_0006_W.MP4");
    //srtPathList.push_back(folder + "DJI_20250418153043_0006_W.srt");
diff --git a/tests/stitch_S732.cpp b/tests/stitch_S732.cpp
index 837b24b..b627ebe 100644
--- a/tests/stitch_S732.cpp
+++ b/tests/stitch_S732.cpp
@@ -13,7 +13,7 @@ using namespace std;
 
 void ProcessVL(string filePath)
 {
-    auto stitcher = API_UnderStitch::Create("F:/cache");
+    auto stitcher = API_UnderStitch::Create("D:/cache");
     stitcher->SetOutput("BT", "google_tiles");
 
 
@@ -125,7 +125,7 @@ void ProcessVL(string filePath)
             UPanConfig cfg = { 0 };
             cfg.bOutGoogleTile = 1;
             cfg.bOutFrameTile = 0;
-            cfg.bUseBA = 0;
+            cfg.bUseBA = 1;
             stitcher->SetConfig(cfg);
 
             stitcher->SetOutput("baotou","F:/google_tiles");
@@ -135,7 +135,7 @@ void ProcessVL(string filePath)
 
             mat_pan = cv::Mat(pan.u32Height, pan.u32Width, CV_8UC4, pan.u64VirAddr[0]);
 
-            output.open("output.mp4", VideoWriter::fourcc('M', 'P', '4', 'V'), 50, Size(pan.u32Width / 16, pan.u32Height / 16), true);
+            output.open("output.mp4", VideoWriter::fourcc('M', 'P', '4', 'V'), 50, Size(pan.u32Width / 8, pan.u32Height / 8), true);
             if (!output.isOpened())
             {
                 cout << "打开视频失败" << endl;
@@ -144,7 +144,7 @@ void ProcessVL(string filePath)
         }
         else
         {
-            std::cout << info.craft.stPos.B << " " << info.craft.stPos.L << " " << info.craft.stPos.H << " "
+            std::cout << info.nFrmID << "   " <<info.craft.stPos.B << " " << info.craft.stPos.L << " " << info.craft.stPos.H << " "
                 << info.craft.stAtt.fYaw << " " << info.craft.stAtt.fPitch << " " << info.craft.stAtt.fRoll << " "
                 << info.servoInfo.fServoAz << " " << info.servoInfo.fServoPt + 90
                 << std::endl;
@@ -160,8 +160,8 @@ void ProcessVL(string filePath)
         }
 
         Mat pan_ds; 
-        Mat pan_rgb_ds(cv::Size(mat_pan.cols / 16, mat_pan.rows / 16),CV_8UC3);
-        cv::resize(mat_pan, pan_ds, cv::Size(mat_pan.cols / 16, mat_pan.rows / 16));
+        Mat pan_rgb_ds(cv::Size(mat_pan.cols / 8, mat_pan.rows / 8),CV_8UC3);
+        cv::resize(mat_pan, pan_ds, cv::Size(mat_pan.cols / 8, mat_pan.rows / 8));
 
         cv::cvtColor(pan_ds, pan_rgb_ds, cv::COLOR_BGRA2BGR);
 
@@ -169,6 +169,7 @@ void ProcessVL(string filePath)
 
         output.write(pan_rgb_ds);
 
+        cv::namedWindow("pan_opt",0);
         imshow("pan_opt", pan_rgb_ds);