OpenCV2.4.10之samples_cpp_tutorial-code_learn-----ImgProc(图像处理)

 for( int y = 0; y < image.rows; y++ ){ for( int x = 0; x < image.cols; x++ ){ for( int c = 0; c < 3; c++ ){new_image.at<Vec3b>(y,x)[c] = saturate_cast<uchar>( alpha*( image.at<Vec3b>(y,x)[c] ) + beta );}}}

template<typename _Tp> inline _Tp& Mat::at(int i0, int i1)

typedef Vec<uchar, 3> Vec3b;

template<typename _Tp, int cn> class Vec : public Matx<_Tp, cn, 1>

#include "stdafx.h"    //预编译头文件    /*** @图像膨胀与腐蚀Demo*/#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <stdlib.h>
#include <stdio.h>using namespace cv;///全局变量
Mat src, erosion_dst, dilation_dst;int erosion_elem = 0;
int erosion_size = 0;
int dilation_elem = 0;
int dilation_size = 0;
int const max_elem = 2;
int const max_kernel_size = 21;/** 膨胀腐蚀函数声明 */
void Erosion( int, void* );
void Dilation( int, void* );/**
主函数*/
int main( int, char** argv )
{///加载图片src = imread("D:\\opencv\\lena.png");if( !src.data ){ return -1; }/// 创建窗口namedWindow( "Erosion Demo", WINDOW_AUTOSIZE );namedWindow( "Dilation Demo", WINDOW_AUTOSIZE );moveWindow( "Dilation Demo", src.cols, 0 );/// 创建腐蚀的滑动条createTrackbar( "Element:\n 0: Rect \n 1: Cross \n 2: Ellipse", "Erosion Demo",&erosion_elem, max_elem,Erosion );createTrackbar( "Kernel size:\n 2n +1", "Erosion Demo",&erosion_size, max_kernel_size,Erosion );/// 创建膨胀的滑动条createTrackbar( "Element:\n 0: Rect \n 1: Cross \n 2: Ellipse", "Dilation Demo",&dilation_elem, max_elem,Dilation );createTrackbar( "Kernel size:\n 2n +1", "Dilation Demo",&dilation_size, max_kernel_size,Dilation );/// 开始Erosion( 0, 0 );Dilation( 0, 0 );waitKey(0);return 0;
}/*** @腐蚀函数*/
void Erosion( int, void* )
{int erosion_type = 0;if( erosion_elem == 0 ){ erosion_type = MORPH_RECT; }else if( erosion_elem == 1 ){ erosion_type = MORPH_CROSS; }else if( erosion_elem == 2) { erosion_type = MORPH_ELLIPSE; }Mat element = getStructuringElement( erosion_type,Size( 2*erosion_size + 1, 2*erosion_size+1 ),Point( erosion_size, erosion_size ) );/// 进行腐蚀操作erode( src, erosion_dst, element );imshow( "Erosion Demo", erosion_dst );
}/*** @膨胀函数*/
void Dilation( int, void* )
{int dilation_type = 0;if( dilation_elem == 0 ){ dilation_type = MORPH_RECT; }else if( dilation_elem == 1 ){ dilation_type = MORPH_CROSS; }else if( dilation_elem == 2) { dilation_type = MORPH_ELLIPSE; }Mat element = getStructuringElement( dilation_type,Size( 2*dilation_size + 1, 2*dilation_size+1 ),Point( dilation_size, dilation_size ) );/// 进行膨胀操作dilate( src, dilation_dst, element );imshow( "Dilation Demo", dilation_dst );
}

#include "stdafx.h"    //预编译头文件    /**高级的形态学变换*/#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <stdlib.h>
#include <stdio.h>using namespace cv;/// 全局变量
Mat src, dst;int morph_elem = 0;
int morph_size = 0;
int morph_operator = 0;
int const max_operator = 4;
int const max_elem = 2;
int const max_kernel_size = 21;const char* window_name = "Morphology Transformations Demo";/** 自定义形态学操作函数声明 */
void Morphology_Operations( int, void* );/*** @主函数*/
int main( int, char** argv )
{/// 加载图片src = imread("D:\\opencv\\lena.png");if( !src.data ){ return -1; }/// 创建窗口namedWindow( window_name, WINDOW_AUTOSIZE );/// 创建选择形态学操作类型的滑动条createTrackbar("Operator:\n 0: Opening - 1: Closing  \n 2: Gradient - 3: Top Hat \n 4: Black Hat", window_name, &morph_operator, max_operator, Morphology_Operations );/// 创建形态学元素类型选择的滑动条createTrackbar( "Element:\n 0: Rect - 1: Cross - 2: Ellipse", window_name,&morph_elem, max_elem,Morphology_Operations );/// 创建形态学元素大小选择的滑动条createTrackbar( "Kernel size:\n 2n +1", window_name,&morph_size, max_kernel_size,Morphology_Operations );/// 开始Morphology_Operations( 0, 0 );waitKey(0);return 0;
}/*** @形态学操作函数定义*/
void Morphology_Operations( int, void* )
{// Since MORPH_X : 2,3,4,5 and 6int operation = morph_operator + 2;//创建形态学操作元素Mat element = getStructuringElement( morph_elem, Size( 2*morph_size + 1, 2*morph_size+1 ), Point( morph_size, morph_size ) );/// 形态学操作morphologyEx( src, dst, operation, element );imshow( window_name, dst );
}

• MORPH_OPEN - an opening operation
• MORPH_CLOSE - a closing operation   
• MORPH_GRADIENT - a morphological gradient 
• MORPH_TOPHAT - “top hat”
• MORPH_BLACKHAT - “black hat”

#include "stdafx.h"    //预编译头文件    /**图像的模糊*/
#include <iostream>
#include <vector>#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/features2d/features2d.hpp"using namespace std;
using namespace cv;/// 全局变量
int DELAY_CAPTION = 1500;
int DELAY_BLUR = 100;
int MAX_KERNEL_LENGTH = 31;Mat src; Mat dst;
char window_name[] = "Smoothing Demo";/// 函数声明
int display_caption( const char* caption );
int display_dst( int delay );/*** 主函数*/
int main( void )
{namedWindow( window_name, WINDOW_AUTOSIZE );/// 加载图像src = imread( "D:\\opencv\\lena.png", 1 );if( display_caption( "Original Image" ) != 0 ) { return 0; }dst = src.clone();if( display_dst( DELAY_CAPTION ) != 0 ) { return 0; }/// 均匀线性模糊if( display_caption( "Homogeneous Blur" ) != 0 ) { return 0; }for ( int i = 1; i < MAX_KERNEL_LENGTH; i = i + 2 ){ blur( src, dst, Size( i, i ), Point(-1,-1) );if( display_dst( DELAY_BLUR ) != 0 ) { return 0; } }/// 高斯模糊if( display_caption( "Gaussian Blur" ) != 0 ) { return 0; }for ( int i = 1; i < MAX_KERNEL_LENGTH; i = i + 2 ){ GaussianBlur( src, dst, Size( i, i ), 0, 0 );if( display_dst( DELAY_BLUR ) != 0 ) { return 0; } }/// 中值模糊if( display_caption( "Median Blur" ) != 0 ) { return 0; }for ( int i = 1; i < MAX_KERNEL_LENGTH; i = i + 2 ){ medianBlur ( src, dst, i );if( display_dst( DELAY_BLUR ) != 0 ) { return 0; } }/// 双边模糊if( display_caption( "Bilateral Blur" ) != 0 ) { return 0; }for ( int i = 1; i < MAX_KERNEL_LENGTH; i = i + 2 ){ bilateralFilter ( src, dst, i, i*2, i/2 );if( display_dst( DELAY_BLUR ) != 0 ) { return 0; } }display_caption( "End: Press a key!" );waitKey(0);return 0;
}/*** @显示标题*/
int display_caption( const char* caption )
{dst = Mat::zeros( src.size(), src.type() );putText( dst, caption,Point( src.cols/4, src.rows/2),FONT_HERSHEY_COMPLEX, 1, Scalar(255, 255, 255) );imshow( window_name, dst );int c = waitKey( DELAY_CAPTION );if( c >= 0 ) { return -1; }return 0;
}/*** @显示图像*/
int display_dst( int delay )
{imshow( window_name, dst );int c = waitKey ( delay );if( c >= 0 ) { return -1; }return 0;
}

#include "stdafx.h"    //预编译头文件    /*** 简单的示例代码显示了如何使用不同的阈值*/#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <stdlib.h>
#include <stdio.h>using namespace cv;/// 全局变量int threshold_value = 0;
int threshold_type = 3;
int const max_value = 255;
int const max_type = 4;
int const max_BINARY_value = 255;Mat src, src_gray, dst;
const char* window_name = "Threshold Demo";const char* trackbar_type = "Type: \n 0: Binary \n 1: Binary Inverted \n 2: Truncate \n 3: To Zero \n 4: To Zero Inverted";
const char* trackbar_value = "Value";/// 函数声明
void Threshold_Demo( int, void* );/*** 主函数*/
int main( int, char** argv )
{/// 加载图片src = imread("D:\\opencv\\lena.png", 1 );///将图像转换为灰度图cvtColor( src, src_gray, COLOR_RGB2GRAY );/// 创建窗口namedWindow( window_name, WINDOW_AUTOSIZE );/// 创建阈值类型选择的滑动块createTrackbar( trackbar_type,window_name, &threshold_type,max_type, Threshold_Demo );createTrackbar( trackbar_value,window_name, &threshold_value,max_value, Threshold_Demo );/// 调用阈值函数Threshold_Demo( 0, 0 );/// Wait until user finishes programfor(;;){int c;c = waitKey( 20 );if( (char)c == 27 ){ break; }}}/***阈值函数定义*/
void Threshold_Demo( int, void* )
{/* 0: Binary1: Binary Inverted2: Threshold Truncated3: Threshold to Zero4: Threshold to Zero Inverted*/threshold( src_gray, dst, threshold_value, max_BINARY_value,threshold_type );imshow( window_name, dst );
}

运行截图:

函数threshold原型为:C++: double threshold(InputArray src, OutputArray dst, double thresh, double maxVal, int thresholdType)¶第一个参数为源图像，第二个参数dst为进行阈值转换后的图像，第三个参数thresh为阈值大小，第五个参数thresholdType为阈值类型。

阈值类型及原理如下图所示:

#include "stdafx.h"    //预编译头文件    /**图像金字塔*/#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <math.h>
#include <stdlib.h>
#include <stdio.h>using namespace cv;/// 全局变量
Mat src, dst, tmp;const char* window_name = "Pyramids Demo";/**主函数*/
int main( void )
{printf( "\n Zoom In-Out demo  \n " );printf( "------------------ \n" );printf( " * [u] -> Zoom in  \n" );printf( " * [d] -> Zoom out \n" );printf( " * [ESC] -> Close program \n \n" );/// Test image - Make sure it s divisible by 2^{n}src = imread( "D:\\opencv\\chicky_512.png" );if( !src.data ){ printf(" No data! -- Exiting the program \n");return -1; }tmp = src;dst = tmp;/// 创建窗口namedWindow( window_name, WINDOW_AUTOSIZE );imshow( window_name, dst );/// Loopfor(;;){int c;c = waitKey(1000);if( (char)c == 27 ){ break; }if( (char)c == 'u' ){ pyrUp( tmp, dst, Size( tmp.cols*2, tmp.rows*2 ) );printf( "** Zoom In: Image x 2 \n" );}else if( (char)c == 'd' ){ pyrDown( tmp, dst, Size( tmp.cols/2, tmp.rows/2 ) );printf( "** Zoom Out: Image / 2 \n" );}imshow( window_name, dst );tmp = dst;}return 0;
}