How to Reduce Noise using the Average Filter of Image Processing?
How To Reduce Noise Using The Average Filter Of Image Processing?¶
Introduction
The photograph has many noises. We can reduce the noise using the average filter. There are a 3 by 3 matrix matching the photograph. We are amount of the pixels of the 3 by 3 matrix. Then, we divide by 9. The result is the center pixel value of the 3 by 3 matrix. We will rewrite the result into the photograph.
Equipment
Operation System: Microsoft Windows 7 (64 bit)
Development Utility: Microsoft Visual Studio 2010
Usage
// The loop of the average filter.
for ( int iI = 0; iI < 6; iI++)
{
// The height of the image.
for ( int iY = 1; iY < imageA->DibInfo->bmiHeader.biHeight - 1; iY++ )
{
// The width of the image.
for ( int iX = 1; iX < imageA->DibInfo->bmiHeader.biWidth - 1; iX++ )
{
// RGB variable
dobFilterResultR = 0;
dobFilterResultG = 0;
dobFilterResultB = 0;
// The height is 3 by 3 matrix. [-1,1]
for ( intFWY = -1; intFWY <= 1; intFWY++ )
{
// The width is 3 by 3 matrix. [-1.1]
for ( intFWX = -1; intFWX <= 1; intFWX++ )
{
// The index with 3 by 3 matrix. The bit depth is three. Because the bit depth is 24 bits.
// So we multiplied by three.
lIDXA = ( (iX+intFWX) * 3 ) + ( (iY+intFWY) * imageA->DibInfo->bmiHeader.biWidth * 3 );
// Get the pixel of the blue channel.
byteRGB_BA = imageA->DibArry[lIDXA+0];
// Get the pixel of the green channel.
byteRGB_GA = imageA->DibArry[lIDXA+1];
// Get the pixel of the red channel.
byteRGB_RA = imageA->DibArry[lIDXA+2];
// The amount of the red pixel.
dobFilterResultR += byteRGB_RA;
// The amount of the green pixel.
dobFilterResultG += byteRGB_GA;
// The amount of the blue pixel.
dobFilterResultB += byteRGB_BA;
} // The closing "The width is 3 by 3 matrices [-1,1]".
} // The closing "The height is 3 by 3 matrices [-1,1]".
// The sum of red pixel divide by 9.
dobFilterResultR /= 9;
// The sum of green pixel divide by 9.
dobFilterResultG /= 9;
// The sum of blue pixel divide by 9.
dobFilterResultB /= 9;
// The index of the image.
lIDXB = ( iX * 3 ) + ( iY * imageB->DibInfo->bmiHeader.biWidth * 3 );
// Write the result of blue into image B.
imageB->DibArry[lIDXB+0] = dobFilterResultB;
// Write the result of green into image B.
imageB->DibArry[lIDXB+1] = dobFilterResultG;
// Write the result of red into image B.
imageB->DibArry[lIDXB+2] = dobFilterResultR;
// Write the result of blue into image A.
imageA->DibArry[lIDXB+0] = dobFilterResultB;
// Write the result of green into image A.
imageA->DibArry[lIDXB+1] = dobFilterResultG;
// Write the result of red into image A.
imageA->DibArry[lIDXB+2] = dobFilterResultR;
} // The closing "The width of the image".
} // The closing "The height of the image".
} // The closing "The loop of the average filter".
You can download source code and binary code as below:
https://drive.google.com/file/d/0BzHb_OyLyVZlSnh3YTFQUEZZTHc/view?usp=sharing
Exception
There is a notice, if your bit depth of bitmap file are not 24 bits, you should change your bitmap files to adapt this program, or you could rewrite this source code to fit your bitmap format.
You have to install Microsoft SDK v7.1, because I include windowscodes.lib.
#pragma comment(lib, "windowscodecs.lib")
Reference
[1] Gary Bradski and Adrian Kaehler, “Learning OpenCV: Computer Vision with the OpenCV Library,” O’REILLY, September 2008, ISBN:978-0-596-51613-0
Acknowledge
Thank you (Microsoft Visual Studio 2010, Lenna Sjööblom) very much for this great development utility and beautiful photo.
