Digital Image processing with c++ ( Chapter 6 ) - Image Smoothing (Median filter)

Hi All Today i'm going explain you how to add median filter to image

#include "stdafx.h"
#include <iostream>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/core/core.hpp>

using namespace cv;
using namespace std;


int main()
{
 Mat RGBImage;

 RGBImage =imread("c:/Pictures/noisy.jpg");

 Mat grayScaleImage(RGBImage.size(),CV_8UC1);
 grayScaleImage=Scalar(0);
 Mat FinalImage(RGBImage.size(),CV_8UC1);
 cvtColor(RGBImage,grayScaleImage,CV_RGB2GRAY);
 int kernalWidth=3;
 int kernalHeight=3;
 int kernalSize=kernalHeight*kernalWidth;
 int rows=grayScaleImage.rows;
 int cols=grayScaleImage.cols;
 int pixelArray[9];

 int verticleImageBound=(kernalHeight-1)/2;
 int horizontalImageBound=(kernalWidth-1)/2;

 for(int row=0+verticleImageBound;row<rows-verticleImageBound;row++){

  for(int col=0+horizontalImageBound;col<cols-horizontalImageBound;col++){


   int pixelArrayIndex=0;
   for(int kRow=0;kRow<kernalHeight;kRow++){
    for(int kCol=0;kCol<kernalWidth;kCol++){
     pixelArray[pixelArrayIndex]=grayScaleImage.at<uchar>(kRow+row-verticleImageBound,kCol+col-horizontalImageBound);
     pixelArrayIndex++;
    }
   }


   int elements = sizeof(pixelArray) / sizeof(pixelArray[0]); 
   sort(pixelArray, pixelArray + elements);
   FinalImage.at<uchar>(row, col)=pixelArray[(kernalSize+1)/2];

  }

 }


 namedWindow("Original Image",1);
 imshow("Original Image",grayScaleImage);

 namedWindow("Filtered Image",1);
 imshow("Filtered Image",FinalImage);

 waitKey();
 return 0;
}

When you run this code you see results like this

Digital Image processing with c++ ( Chapter 5 ) - Image Smoothing (Mean filter)

Today i'm going to explain how to add mean filter to noisy image

#include "stdafx.h"
#include <iostream>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/core/core.hpp>

using namespace cv;
using namespace std;


int main()
{
 Mat RGBImage;

 RGBImage =imread("c:/Pictures/8_Color-Noise.png");

 Mat grayScaleImage(RGBImage.size(),CV_8UC1);
 grayScaleImage=Scalar(0);
 Mat FinalImage(RGBImage.size(),CV_8UC1);
 cvtColor(RGBImage,grayScaleImage,CV_RGB2GRAY);
 int kernalWidth=7;
 int kernalHeight=7;
 int kernalSize=kernalHeight*kernalWidth;
 int rows=grayScaleImage.rows;
 int cols=grayScaleImage.cols;

 int verticleImageBound=(kernalHeight-1)/2;
 int horizontalImageBound=(kernalWidth-1)/2;

 for(int row=0+verticleImageBound;row<rows-verticleImageBound;row++){

  for(int col=0+horizontalImageBound;col<cols-horizontalImageBound;col++){

   int ave=0;
   for(int kRow=0;kRow<kernalHeight;kRow++){
    for(int kCol=0;kCol<kernalWidth;kCol++){
     ave+=grayScaleImage.at<uchar>(kRow+row-verticleImageBound,kCol+col-horizontalImageBound);

    }
   }
   FinalImage.at<uchar>(row, col)=ave/kernalSize;

  }

 }


 namedWindow("Gray",0);
 resizeWindow("Gray",512,512);
 imshow("Gray",grayScaleImage);
 namedWindow("smooth",0);
 resizeWindow("smooth",512,512);
 imshow("smooth",FinalImage);

 waitKey();
 return 0;
}

Sample image can download from here


When you run this code you see results like this