[OpenCV] 线性滤波核心api函数

发布时间 2023-04-12 10:36:25作者: 冷小男

 

 code block:

#include "opencv2/opencv.hpp"  
#include <iostream>
  
using namespace cv;  
using namespace std;  

#define MAX_KERNEL_SIZE 40

Mat g_srcImage, g_dstImage1 ,g_dstImage2, g_dstImage3,g_dstImage4,g_dstImage5;
int g_nBoxfilterValue = 3;
int g_nBlurValue = 3;
int g_nGaussianBlurValue =3 ;
int g_medianBlurValue = 3;
int g_bliateralFilterValue = 3;


string boxFilter_window = "Box Filter";
string blurFilter_window = "Blur Filter";
string GaussianBlur_window = "Gaussian Filter";
string scrollbar_title = "Kernel size";
string medianBlur_window = "Median Blur";
string bilateralFilter_window = "Bialteral Filter" ;


static void callback_boxfilter(int ,void *);
static void callback_blur(int ,void *);
static void callback_GaussianBlur(int ,void *);
static void callback_medianBlur(int,void *);
static void callback_BialteralFilter(int, void *);


int main( )  
{  

    string pic_path = "pathname";
    string src_window = "Source Pic";


    g_srcImage = imread(pic_path,1);
    if(!g_srcImage.data) { cout << "No data in this picture" << endl;return 0;}

    g_dstImage1 = g_srcImage.clone();
    g_dstImage2 = g_srcImage.clone();
    g_dstImage3 = g_srcImage.clone();
    g_dstImage4 = g_srcImage.clone();
    g_dstImage5 = g_srcImage.clone();

    /*show src picture*/
    namedWindow(src_window,1);
    imshow(src_window,g_srcImage);

    //box filter
    namedWindow(boxFilter_window,1);
    createTrackbar(scrollbar_title,boxFilter_window,&g_nBoxfilterValue,MAX_KERNEL_SIZE,callback_boxfilter);
    
    callback_boxfilter(g_nBoxfilterValue,0);
    imshow(boxFilter_window,g_dstImage1);
    //Blur filter
    namedWindow(blurFilter_window,1);
    createTrackbar(scrollbar_title,blurFilter_window,&g_nBlurValue,MAX_KERNEL_SIZE,callback_blur);

    callback_blur(g_nBlurValue,0);
    imshow(blurFilter_window,g_dstImage2);

    //Guassian filter
    namedWindow(GaussianBlur_window,1);
    createTrackbar(scrollbar_title,GaussianBlur_window,&g_nGaussianBlurValue,MAX_KERNEL_SIZE,callback_GaussianBlur);

    callback_GaussianBlur(g_nGaussianBlurValue,0);
    imshow(GaussianBlur_window,g_dstImage3);

    //median blur
    namedWindow(medianBlur_window,1);
    createTrackbar(scrollbar_title,medianBlur_window,&g_medianBlurValue,MAX_KERNEL_SIZE,callback_medianBlur);
    callback_medianBlur(g_medianBlurValue,0);
    imshow(medianBlur_window,g_dstImage4);

    //bilateralFilter
    namedWindow(bilateralFilter_window,1);
    createTrackbar(scrollbar_title,bilateralFilter_window,&g_bliateralFilterValue,MAX_KERNEL_SIZE,callback_BialteralFilter);
    callback_BialteralFilter(g_bliateralFilterValue,0);
    imshow(bilateralFilter_window,g_dstImage5);


    while(char(waitKey(1)) != 'q') {}
    
    return 0;
    

}  

static void callback_boxfilter(int ,void *){

    


    boxFilter(g_srcImage,g_dstImage1,-1,Size(g_nBoxfilterValue+1,g_nBoxfilterValue+1));
    imshow(boxFilter_window,g_dstImage1);

}

static void callback_blur(int ,void *){

     
    blur(g_srcImage,g_dstImage2,Size(g_nBlurValue+1,g_nBlurValue+1));
    imshow(blurFilter_window,g_dstImage2);

}
static void callback_GaussianBlur(int ,void *){

    g_nGaussianBlurValue = g_nGaussianBlurValue &-1 ;
    if(g_nGaussianBlurValue>40) {g_nGaussianBlurValue -=2;}
    //cout << g_nGaussianBlurValue <<endl;
    if(g_nGaussianBlurValue%2 == 1){GaussianBlur(g_srcImage,g_dstImage3,Size(g_nGaussianBlurValue,g_nGaussianBlurValue),0,0);}
    
    imshow(GaussianBlur_window,g_dstImage3);

}

static void callback_medianBlur(int,void *){
    g_medianBlurValue = g_medianBlurValue &-1 ;
    if(g_medianBlurValue>40) {g_medianBlurValue -=2;}
    if(g_medianBlurValue%2 == 1) medianBlur(g_srcImage,g_dstImage4,g_medianBlurValue);
    imshow(medianBlur_window,g_dstImage4);
}


static void callback_BialteralFilter(int , void *){


    bilateralFilter(g_srcImage,g_dstImage5,g_bliateralFilterValue,g_bliateralFilterValue*2,g_bliateralFilterValue/2);
    imshow(bilateralFilter_window,g_dstImage5);
}