深圳图派做的网站后台加什么,有口碑的免费网站建设,定制搭建网站,北京网页设计公司兴田德润可信赖文章目录 一、重映射简介二、图像扭曲 一、重映射简介
重映射#xff0c;就是把一幅图像中某位置的像素放置到另一图像指定位置的过程。即#xff1a; 在重映射过程中#xff0c;图像的大小也可以同时发生改变。此时像素与像素之间的关系就不是一一对应关系#xff0c;因… 文章目录 一、重映射简介二、图像扭曲 一、重映射简介
重映射就是把一幅图像中某位置的像素放置到另一图像指定位置的过程。即 在重映射过程中图像的大小也可以同时发生改变。此时像素与像素之间的关系就不是一一对应关系因此在重映射过程中可能会涉及到像素值的插值计算。
Remap(
InputArray src, 输入图像灰度图或真彩图均可
OutputArray dst, 输出图像要求大小和xmap,ymap相同通道数目及数据类型和src相同
InputArray map1, x 映射表 CV_32FC1/CV_32FC2
InputArray map2, y 映射表
int interpolation, 选择的插值方法常见线性插值可选择立方等
int borderMode, BORDER_CONSTANT
const Scalar borderValue color
)头文件 quick_opencv.h声明类与公共函数
#pragma once
#include opencv2\opencv.hpp
using namespace cv;class QuickDemo {
public:...void remap_Demo(Mat image1);void MLS(Mat src, std::vectorPoint p, std::vectorPoint q);void MLS(Mat src, int* p, int* q, int rows, int cols);
};主函数调用该类的公共成员函数
#include opencv2\opencv.hpp
#include quick_opencv.h
#include iostream
using namespace cv;int main(int argc, char** argv) {Mat src imread(D:\\Desktop\\pandas_small22.png);if (src.empty()) {printf(Could not load images...\n);return -1;}QuickDemo qk;qk.remap_Demo(src);vectorPoint p{Point(30, 147), Point(147, 147), Point(268, 147), Point(112, 148),Point(186, 148), Point(98, 316), Point(211, 316)};vectorPoint q{ Point(28, 209), Point(126, 143), Point(282, 26), Point(71, 236), Point(136, 240), Point(79, 313), Point(190, 310)};qk.MLS(src1, p, q);int p_array[7][2] { {30, 147}, {147, 147}, {268, 147}, {112, 148}, {186, 148}, {98, 316}, {211, 316} };int q_array[7][2] { {28, 209}, {126, 143}, {282, 26}, {71, 236}, {136, 240}, {79, 313}, {190, 310} };qk.MLS(src1, (int *)p_array, (int*)q_array, 7, 2);waitKey(0);destroyAllWindows();return 0;
}源文件 quick_demo.cpp实现类与公共函数
void update_map(Mat image, int index, Mat x_map, Mat y_map) {int height image.rows;int width image.cols;double h_41 height * 0.25;double h_43 height * 0.75;double w_41 width * 0.25;double w_43 width * 0.75;for (int h 0; h height; h) {float* x_ptr x_map.ptrfloat(h);float* y_ptr y_map.ptrfloat(h);for (int w 0; w width; w) {switch (index){case 0:if (h h_41 h h_43 ww_41 w w_43) {*x_ptr 2 * (w - w_41 0.5);*y_ptr 2 * (h - h_41 0.5);}else{*x_ptr 0;*y_ptr 0;}break;case 1:*x_ptr width - w - 1;*y_ptr h;break;case 2:*x_ptr w;*y_ptr height - h - 1;break;case 3:*x_ptr width - w - 1;*y_ptr height - h - 1;break;}}}}
void QuickDemo::remap_Demo(Mat image) {Mat dst, x_map, y_map;int index 0;x_map.create(image.size(), CV_32FC1);y_map.create(image.size(), CV_32FC1);int c 0;while (true){c waitKey(400);if ((char)c27){break;}index c % 4;update_map(image,index, x_map, y_map);remap(image, dst, x_map, y_map, INTER_LINEAR, BORDER_CONSTANT, Scalar(255, 0, 0));imshow(remap, dst);}
}
如上两个函数update_map用于更新remap的具体映射方法remap_Demo为调用函数。
二、图像扭曲
MLS算法 图像扭曲 Image Deformation Using Moving Least Squares 论文。 最小二乘法MLS对图像进行变形 python 实现
Point NewPoint(Point V, vectorPoint p, vectorPoint q){vectorfloatW;Point p_star, q_star Point(0, 0);for (int i 0; i p.size() - 1; i){float temp;if (p[i] V){temp INT_MAX;}else{temp 1.0 / (((p[i].x - V.x) * (p[i].x - V.x)) ((p[i].y - V.y) * (p[i].y - V.y)));}W.push_back(temp);}float px 0, py 0, qx 0, qy 0, W_sum 0;for (int i 0; i W.size() - 1; i){px W[i] * p[i].x;py W[i] * p[i].y;qx W[i] * q[i].x;qy W[i] * q[i].y;W_sum W[i];}p_star.x px / W_sum;p_star.y py / W_sum;q_star.x qx / W_sum;q_star.y qy / W_sum;vectorPoint p_hat, q_hat;for (int i 0; i p.size() - 1; i){p_hat.push_back(p[i] - p_star);q_hat.push_back(q[i] - q_star);}Mat pi_hat_t_ Mat::zeros(2, 1, CV_32FC1);Mat_float pi_hat_t pi_hat_t_;Mat pi_hat_ Mat::zeros(1, 2, CV_32FC1);Mat_float pi_hat pi_hat_;Mat M_1_ Mat::zeros(2, 2, CV_32FC1);Mat_float M_1 M_1_;for (int i 0; i p_hat.size() - 1; i){pi_hat_t.atfloat(0, 0) p_hat[i].x;pi_hat_t.atfloat(1, 0) p_hat[i].y;pi_hat.atfloat(0, 0) p_hat[i].x;pi_hat.atfloat(0, 1) p_hat[i].y;M_1 pi_hat_t * W[i] * pi_hat;}Mat_float M_1_inv M_1.inv();M_1 M_1_inv;Mat pj_hat_t_ Mat::zeros(2, 1, CV_32FC1);Mat_float pj_hat_t pj_hat_t_;Mat qj_hat_ Mat::zeros(1, 2, CV_32FC1);Mat_float qj_hat qj_hat_;Mat M_2_ Mat::zeros(2, 2, CV_32FC1);Mat_float M_2 M_2_;for (int j 0; j q.size() - 1; j){pj_hat_t.atfloat(0, 0) p_hat[j].x;pj_hat_t.atfloat(1, 0) p_hat[j].y;qj_hat.atfloat(0, 0) q_hat[j].x;qj_hat.atfloat(0, 1) q_hat[j].y;M_2 W[j] * pj_hat_t * qj_hat;}Mat_float M M_1 * M_2;//ok//cout M M endl;Point x_p_star V - p_star;Mat M_x_p_star_ Mat::zeros(1, 2, CV_32FC1);Mat_float M_x_p_star M_x_p_star_;M_x_p_star.atfloat(0, 0) x_p_star.x;M_x_p_star.atfloat(0, 1) x_p_star.y;Mat M_q_star_ Mat::zeros(1, 2, CV_32FC1);Mat_float M_q_star M_q_star_;M_q_star.atfloat(0, 0) q_star.x;M_q_star.atfloat(0, 1) q_star.y;Mat_float Lv M_x_p_star * M M_q_star;return Point(Lv.atfloat(0, 0), Lv.atfloat(0, 1));
}void QuickDemo::MLS(Mat src, std::vectorPoint p, std::vectorPoint q){double time0 static_castdouble(getTickCount());Mat dst Mat::zeros(src.rows, src.cols, CV_8UC3);for (int i 0; i src.rows; i){for (int j 0; j src.cols; j){Point old Point(j, i);Point new_point NewPoint(old, p, q);//cout old old \tnew new_point endl;dst.atVec3b(i, j) src.atVec3b(abs(new_point.y), abs(new_point.x));}}double time1 static_castdouble(getTickCount());cout Total cost time is ((time1 - time0) / getTickFrequency()) seconds endl;imshow(dst_msl, dst);
}重载函数
Point NewPoint(Point V, float* W, int* p, int* q , float* p_hat, float* q_hat, int rows, int cols) {Point p_star, q_star Point(0, 0);float temp 0;float px 0, py 0, qx 0, qy 0, W_sum 0;for (int i 0; i rows; i) {int p_0 *(p i * cols);int p_1 *(p i * cols 1);if (!(p_0 V.x p_1 V.y)) {temp 1.0 / (((p_0 - V.x) * (p_0 - V.x)) ((p_1 - V.y) * (p_1 - V.y)));}else {temp INT_MAX;}W[i] temp;px temp * p_0;py temp * p_1;qx temp * (*(q i * cols));qy temp * (*(q i * cols 1));W_sum temp;}p_star.x px / W_sum;p_star.y py / W_sum;q_star.x qx / W_sum;q_star.y qy / W_sum;for (int i 0; i rows; i) {*(p_hat i * cols) *(p i * cols) - p_star.x;*(p_hat i * cols 1) *(p i * cols 1) - p_star.y;*(q_hat i * cols) *(q i * cols) - p_star.x;*(q_hat i * cols 1) *(q i * cols 1) - p_star.y;}// Mat pi_hat_t_ Mat::zeros(2, 1, CV_32FC1);Mat_float pi_hat_t pi_hat_t_;Mat pi_hat_ Mat::zeros(1, 2, CV_32FC1);Mat_float pi_hat pi_hat_;Mat M_1_ Mat::zeros(2, 2, CV_32FC1);Mat_float M_1 M_1_;// Mat pj_hat_t_ Mat::zeros(2, 1, CV_32FC1);Mat_float pj_hat_t pj_hat_t_;Mat qj_hat_ Mat::zeros(1, 2, CV_32FC1);Mat_float qj_hat qj_hat_;Mat M_2_ Mat::zeros(2, 2, CV_32FC1);Mat_float M_2 M_2_;// for (int i 0; i rows; i) {float p_hat_x *(p_hat i * cols);float p_hat_y *(p_hat i * cols 1);pi_hat_t.atfloat(0, 0) p_hat_x;pi_hat_t.atfloat(1, 0) p_hat_y;pi_hat.atfloat(0, 0) p_hat_x;pi_hat.atfloat(0, 1) p_hat_y;M_1 pi_hat_t * W[i] * pi_hat;pj_hat_t.atfloat(0, 0) p_hat_x;pj_hat_t.atfloat(1, 0) p_hat_y;qj_hat.atfloat(0, 0) *(q_hat i * cols);qj_hat.atfloat(0, 1) *(q_hat i * cols 1);M_2 pj_hat_t * W[i] * qj_hat;}Mat_float M_1_inv M_1.inv();M_1 M_1_inv;Mat_float M M_1 * M_2;////// 如下为总公式计算////Point x_p_star V - p_star;Mat M_x_p_star_ Mat::zeros(1, 2, CV_32FC1);Mat_float M_x_p_star M_x_p_star_;M_x_p_star.atfloat(0, 0) x_p_star.x;M_x_p_star.atfloat(0, 1) x_p_star.y;Mat M_q_star_ Mat::zeros(1, 2, CV_32FC1);Mat_float M_q_star M_q_star_;M_q_star.atfloat(0, 0) q_star.x;M_q_star.atfloat(0, 1) q_star.y;Mat_float Lv M_x_p_star * M M_q_star;return Point(Lv.atfloat(0, 0), Lv.atfloat(0, 1));}void QuickDemo::MLS(Mat src, int* p, int* q, int rows, int cols) {double time0 static_castdouble(getTickCount());Mat dst Mat::zeros(src.rows, src.cols, CV_8UC3);assert(7 rows); // 若断言失败请修改如下三个数组的长度为rowsfloat W[7] { 0 }; // 权重长度为p数组长度rows7float p_hat[7][2] { 0 }; // p_hat长度为p数组长度rows7float q_hat[7][2] { 0 }; // q_hat长度为p数组长度rows7for (int i 0; i src.rows; i) {for (int j 0; j src.cols; j) {Point new_point NewPoint(Point(j, i), W, p, q, (float*)p_hat, (float*)p_hat, rows, cols);//cout old old \tnew new_point endl;dst.atVec3b(i, j) src.atVec3b(abs(new_point.y), abs(new_point.x));//cout src.atuchar src.atVec3b(new_point.y,new_point.x) endl;}}double time1 static_castdouble(getTickCount());cout Total cost time is ((time1 - time0) / getTickFrequency()) seconds endl;imshow(dst_msl, dst);
}
————鸣谢与拓展阅读 使用范例 记录四图像处理之瘦脸 MLS算法 C实现 OpenCV局部变形算法探究添加链接描述 基于移动最小二乘MLS的图像扭曲刚性变形python实现 使用重映射实现图像的局部扭曲 来实现 图像增强。
