Advance image processing

8/14/2019 Advance image processing

1/71

** Image.h** Copyright (C) 2008, Dipak Chirmade* Student, HD SE.* dipak(dot)chirmade(at)gmail(dot)com*

* THE SOFTWARE IS PROVIDED "AS-IS" AND WITHOUT WARRANTY OF ANY KIND,* EXPRESS, IMPLIED OR OTHERWISE, INCLUDING WITHOUT LIMITATION, ANY* WARRANTY OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.* YOU ARE ALLOWED TO USE THIS CODE FOR PERSONAL OR PROFESSIONAL USE* AND IS TOTALLY FREE!** This file defines the functions to deal with image processing.* Few selective snapshots of processed images are also added.**/

ifndef _IMAGE_H_define _IMAGE_H_

*Include files in relevance to image processing functions

/

include "version.h"include "Bmp.h"include include "Randomin.h"include include "noise.h"

*All functions are implemented in generic orderas shown in menu options

/

*Description: Displays the image pixel by pixelArguments : r,g,b attributes of an imageReturns : Nothing

/

oid showImage(image rAttr, image gAttr, image bAttr)

if((r!=NULL)&&(g!=NULL)&&(b!=NULL)){UINT iRow,jCol;for( iRow=0;iRow


2/71

glVertex2i(jCol,screenHeight-iRow-1);glEnd();

}}

*Description: Sets white background and plot black points on itOnly one point at a time can be plotted

Arguments : Image in 'image' struct link listReturns : Nothing

/

oid ShowHistogram(image Gray)

UINT Height,Width;

/*glClear(GL_COLOR_BUFFER_BIT|GL_DEPTH_BUFFER_BIT);

*/

glPointSize(1.0);


3/71

glBegin(GL_POINTS);

for(Width=0;Width


4/71

rs[HHight][HWidth]=(float)rs[HHight][HWidth]+1.0;gs[HHight][HWidth]=(float)gs[HHight][HWidth]+1.0;bs[HHight][HWidth]=(float)bs[HHight][HWidth]+1.0;

}elsefor(int HWidth=0;HWidth


5/71

calculate max histogram counter*/

NormalizationFactor=MaxHistoHeightCount/screenHeight;for(int HWidth=0;HWidth


6/71

*Description: Performs histogram stretchArguments : NothingReturns : Nothing

/

oid DoHistrogramStretch(void)

for(int Height=0;Height


7/71

/

oid DoHistrogramShrink(int MaxWidth,int MinWidth)

/* __Have to go step by step conversion*/float diff0=float(MaxWidth-MinWidth);float diff1=(float)(diff0/(MaxGrayValue-MinGrayValue));



8/71

}return;

*Description: Convert int number to binaryArguments : Int number which need to convert into binary

Returns : Nothing/

tatic int BinaryCounter=0;nt BinaryString[8]={0,0,0,0,0,0,0,0};

oid BinaryConversion(int number) {int remainder=0;if(number > 1);BinaryString[BinaryCounter]=remainder;BinaryCounter++;

return;

*Description: Performs histogram eqalizationArguments : NothingReturns : Nothing

/


9/71

oid DoHistogramEqualization(void)

/*clean array

*/int IsZeroGrayLevel[256+4];for(int CleanConuter=0;CleanConuter


10/71

float CurrentCalculatedProbabilty=(float)tNk/TotalNumberOfPixel;

if(CurrentCalculatedProbabilty==0.0) IsZeroGrayLevel[NormalizationCounter]=1;

ProbabilityThreshold+=CurrentCalculatedProbabilty;

/*

store the calulate probablities to an probdesarray*/ProbDesArray[NormalizationCounter]=CurrentCalculatedProbabilty;

}

/* _debug maessage to check prob density array and calculate sum of probability*/

for(int CleanConuter=0;CleanConuter


11/71

if((int)rs[Height][Width]==NormalizationCounter)rs[Height][Width]=(float)ReplaceableValue;gs[Height][Width]=bs[Height][Width]=rs[Height][Width];

}}

/* _Wrong approch

rawhistogramSrc=CalculateHistrogram(rawhistogramSrc,rs);{int Height;for(int GrayLevel=0;GrayLevel


12/71

*Description: Computers 8 levels of the buffered imageArguments : NothingReturns : Nothing

/

oid ComputeEightLevelbuffers(void)

AllocateSpecificationWinBuffer();



13/71

Description: Colored image to Gray image conversionFormula: 0.5*red+0.3*green+0.2*blue=GrayScaleValueForR=G=B

Arguments : R,G,B values which one want to convert.Returns : Float value after conversion

/

oid DoHistogramSpecification(void)

/*BinaryConversion((float)123);

*/

float Pr[256+4];for(int NormalizationConuter=0;NormalizationConuter


14/71

int TotalNoOfPix=screenWidth*screenHeight;Pr[NormalizationConuter]=(float)tNk/TotalNoOfPix;

}

float Sk[256+4];for(int NormalizationConuter=0;NormalizationConuter


15/71

if((int)rs[Height][Width]==NormalizationConuter)rs[Height][Width]=(float)ReplaceValue;gs[Height][Width]=bs[Height][Width]=rs[Height][Width];

}}

ComputeEightLevelbuffers();return;

*Description: To get the mean of the imageArguments : voidReturns : mean value

/

loat GetMeanOfTheImage(void)

float Mean=0;int TotalNoOfPix=screenWidth*screenHeight;



16/71

loat GetVarianceOfTheACEWindow(void)

float Mean=GetMeanOfTheACEWindow(),Sigma=0;int TotalNoOfPix=3*3;



17/71

oid DoAdaptiveContrastEnhancement(void)

float MeanOftheWholeImage=(float)GetMeanOfTheImage();for(int Height=1;Height


18/71

{; /*do not do anything*/

}else{float temp1=(float) (MeanOftheWholeImage/GetVarianceOfTheACEWindow());float temp2=(float) ((float)rs[Height][Width]-GetMeanOfTheACEWindow());

temp1=(float)(0.1*temp1*temp2);temp2=(float)0.8*GetMeanOfTheACEWindow();temp1=(float)(temp1+temp2);

temp1=(float)powf(temp1,float(2));gs[Height][Width]=(float)sqrt((float)temp1);

}/*

bd[Height][Width]=gd[Height][Width]=rd[Height][Width];*/

}



19/71

oid AddGaussienNoise(void)

noise_guassian(rori,rs,230,2);



20/71

bs[Height][Width]=gs[Height][Width]=rs[Height][Width];

return;

*Description: Adds Gamma Noise to the image

Arguments : NothingReturns : Nothing/

oid AddGammNoise(void)

noise_Gamma(rori,rs,230,2);



21/71

oid AddExponentialNoise(void)

noise_Exponential(rori,rs,230);for(int Height=0;Height


22/71

*Description: Adds Impluse Noise to the imageArguments : NothingReturns : Nothing

/

oid AddImpluseNoise(void)

noise_imp(rori,rs,0.9,10,100);for(int Height=0;Height


23/71

;/*rs[Height][Width]=(float)210;*/else

rs[Height][Width]=(float)Width;

bs[Height][Width]=gs[Height][Width]=rs[Height][Width];}

return;

*Description: Average filter by window 3x3Arguments : NothingReturns : Nothing

/

oid Average3x3Filter(void)

float _3x3Window[3][3]={{0,0,0},{0,0,0},{0,0,0}};



24/71

_3x3Window[0][2]=(float)rs[Height-1][Width+1];_3x3Window[1][0]=(float)rs[Height][Width-1];_3x3Window[1][1]=(float)rs[Height]

Width];_3x3Window[1][2]=(float)rs[Height][Width+1];_3x3Window[2][0]=(float)rs[Height+1][Width-1];_3x3Window[2][1]=(float)rs[Height+1

Width];_3x3Window[2][2]=(float)rs[Height+1][Width+1];

float TotalGrayValue=0;for(int row=0;row


25/71

_5x5Window[3][3]=(float)rs[Height+1][Width+1];_5x5Window[3][4]=(float)rs[Height+1Width+2];

_5x5Window[4][0]=(float)rs[Height+2][Width-2];_5x5Window[4][1]=(float)rs[Height+2Width-1];

_5x5Window[4][2]=(float)rs[Height+2][Width];_5x5Window[4][3]=(float)rs[Height+2][Width+1];_5x5Window[4][4]=(float)rs[Height+2

Width+2];



26/71

_7x7Window[3][0]=(float)rs[Height][Width-3];_7x7Window[3][1]=(float)rs[Height][Wid];_7x7Window[3][2]=(float)rs[Height][Width-1];

_7x7Window[3][3]=(float)rs[Height][Width]_7x7Window[3][4]=(float)rs[Height][Width+1];_7x7Window[3][5]=(float)rs[Height]

Width+2];_7x7Window[3][6]=(float)rs[Height][Width+3];_7x7Window[4][0]=(float)rs[Height+1][Width-3];_7x7Window[4][1]=(float)rs[Height+1

Width-2];_7x7Window[4][2]=(float)rs[Height+1][Width-3];

_7x7Window[4][3]=(float)rs[Height+1][Width_7x7Window[4][4]=(float)rs[Height+1][Width+1];_7x7Window[4][5]=(float)rs[Height+1Width+2];_7x7Window[4][6]=(float)rs[Height+1][Width+3];

_7x7Window[5][0]=(float)rs[Height+2][Width-3];_7x7Window[5][1]=(float)rs[Height+2Width-2];_7x7Window[5][2]=(float)rs[Height+2][Width-1];

_7x7Window[5][3]=(float)rs[Height+2][Width_7x7Window[5][4]=(float)rs[Height+2][Width+1];_7x7Window[5][5]=(float)rs[Height+2

Width+2];_7x7Window[5][6]=(float)rs[Height+2][Width+3];_7x7Window[6][0]=(float)rs[Height+3][Width-3];_7x7Window[6][1]=(float)rs[Height+3

Width-2];_7x7Window[6][2]=(float)rs[Height+3][Width-1];_7x7Window[6][3]=(float)rs[Height+3][Width

_7x7Window[6][4]=(float)rs[Height+3][Width+1];_7x7Window[6][5]=(float)rs[Height+3Width+2];_7x7Window[6][6]=(float)rs[Height+3][Width+3];



27/71

oid WeightedAverageFilter(void)

float _3x3Window[3][3]={{0,0,0},{0,0,0},{0,0,0}};



28/71

_3x3Window[2][2]=(float)rs[Height+1][Width+1];



29/71

rs[Height][Width]=bs[Height][Width]=gs[Height][Width];

return;

*Description: Contra Harmonic filter by window 3x3

Arguments : NothingReturns : Nothing/

oid ContraHarmonicFilter(float ValueForQ)

float _3x3Window[3][3]={{0,0,0},{0,0,0},{0,0,0}};



30/71

nt FloatCmp(const void *temp1, const void *temp2){

return (*(int *)temp1 - *(int *)temp2);}

*

Description: Median filter by window 3x3Arguments : NothingReturns : Nothing

/

oid MedianFilter(void)

float _3x3Window[3][3]={{0,34,0},{0,21,0},{0,59,0}};



31/71

_3x3Window[1][2]=(float)rs[Height][Width+1];_3x3Window[2][0]=(float)rs[Height+1][Width-1];_3x3Window[2][1]=(float)rs[Height+1


/*sort the array using quick sort function

*/qsort(_3x3Window, 9, sizeof(int), FloatCmp);

gs[Height][Width]=(float)_3x3Window[1][1];if((float)gs[Height][Width]>(float)255) gs[Height][Width]=(float)255;if((float)gs[Height][Width]


32/71

for(int Width=1;Width


33/71

float _3x3Window[3][3]={{0,0,0},{0,0,0},{0,0,0}};



34/71

_3x3Window[1][2]=(float)rs[Height][Width+1];_3x3Window[2][0]=(float)rs[Height+1][Width-1];_3x3Window[2][1]=(float)rs[Height+1


/*mean calculation

*/float TotalGrayVablue=0;for(int row=0;row


35/71

if((float)rs[Height][Width]


36/71

*Description: Horizontal line detectionArguments : NothingReturns : Nothing

/

oid HorizontalDetection(void)



37/71

if((float)gs[Height][Width]>(float)128){

/*cout


38/71

oid VerticalDetection(void)



39/71

)==(float)gs[Height][Width])*/

if((float)gs[Height][Width]==(float)gs[Height+1][Width])/* ((float)gs[Height][Width]==(float)gs[Height][Width-1]))*/

gs[Height][Width]=255.0;else gs[Height][Width]=0.0;

}}



40/71

return;

*Description: Two or more than horizontal line detectionArguments : Nothing

Returns : Nothing/

oid AnotherHorizontalLineDetection(void)

float _3x3Window[3][3]={{0,0,0},{0,0,0},{0,0,0}};



41/71



42/71

oid Plus45DegreesDetection(void)

float _3x3Window[3][3]={{0,0,0},{0,0,0},{0,0,0}};



43/71

else if(TotalGrayValue>255)gs[Height][Width]=(float)255;else gs[Height][Width]=TotalGrayValue;

}for(int Height=1;Height


44/71

Arguments : NothingReturns : Nothing

/

oid RobertOperatorBasedDetection(void)

float _3x3Window[3][3]={{0,0,0},{0,0,0},{0,0,0}};



45/71

float temp2=(float)_3x3Window[2][1]-(float)_3x3Window[1][2];temp2=(float)powf(temp2,float(2));

temp2=(float)sqrt(temp2);

float TotalGrayValue=(float)(temp1+temp2);if(TotalGrayValue255)gs[Height][Width]=(float)255;else gs[Height][Width]=TotalGrayValue;

/*gs[Height][Width]=(float)(powf((_3x3Window[2][2]-_3x3Window[1][1]),(float)2)+\

(powf((_3x3Window[2][1]-_3x3Window[1][2]),(float)2)));gs[Height][Width]=(float)sqrt((float)gs[Height][Width]);if((float)gs[Height][Width]==(float)1) gs[Height][Width]=(float)255;cout


46/71

TotalXGray+=_2x2windowX[row][col];TotalYGray+=_2x2windowY[row][col];

}

TotalXGray=float(powf(TotalXGray,(float)2));TotalXGray=(float)sqrt(TotalXGray);

TotalYGray=float(powf(TotalYGray,(float)2));TotalYGray=(float)sqrt(TotalYGray);

float TotalGrayValue=float(TotalXGray+TotalYGray);if(TotalGrayValue255)

gs[Height][Width]=(float)255;else gs[Height][Width]=TotalGrayValue;

}



47/71

oid PrewittOperatorBasedDetection(void)

float _3x3Window[3][3]={{0,0,0},{0,0,0},{0,0,0}};



48/71

temp3=float(powf((temp3-temp4),(float)2));temp3=(float)sqrt(temp3);

float TotalGrayValue=(float)(temp1+temp3);if(TotalGrayValue255)

gs[Height][Width]=(float)255;else gs[Height][Width]=TotalGrayValue;/*

cout


49/71

_3x3WindowY[2][2]=(float)rs[Height+1][Width+1]*1;

float TotalXGray=0,TotalYGray=0;for(int row=0;row


50/71

oid SobelOperatorBaseDetection(void)

float _3x3Window[3][3]={{0,0,0},{0,0,0},{0,0,0}};



51/71

temp1=(float)sqrt(temp1);temp3=float(powf((temp3-temp4),(float)2));temp3=(float)sqrt(temp3);

float TotalGrayValue=(float)(temp1+temp3);if(TotalGrayValue255)gs[Height][Width]=(float)255;else gs[Height][Width]=TotalGrayValue;

/*cout


52/71

_3x3WindowX[1][2]=(float)rs[Height][Width+1]*2;_3x3WindowX[2][0]=(float)rs[Height+1][Width-1]*-1;_3x3WindowX[2]

1]=(float)rs[Height+1][Width]*0;_3x3WindowX[2][2]=(float)rs[Height+1][Width+1]*1;

_3x3WindowY[0][0]=(float)rs[Height-1][Width-1]*-1;_3x3WindowY[0][1]=(float)rs[Heigh][Width]*-2;

_3x3WindowY[0][2]=(float)rs[Height-1][Width+1]*-1;_3x3WindowY[1][0]=(float)rs[Height][Width-1]*0;_3x3WindowY[1][1]=(float)rs[Height]Width]*0;

_3x3WindowY[1][2]=(float)rs[Height][Width+1]*0;_3x3WindowY[2][0]=(float)rs[Height+1][Width-1]*1;_3x3WindowY[2][1]=(float)rs[Height

Width]*2;_3x3WindowY[2][2]=(float)rs[Height+1][Width+1]*1;

float TotalXGray=0,TotalYGray=0;for(int row=0;row


53/71

oid LogOperatorBasedDetection(void)

float _5x5Window[5][5]={{0,0,0,0,0},{0,0,0,0,0},{0,0,0,0,0},{0,0,0,0,0},{0,0,0,0,0}};



54/71

_5x5Window[3][2]=(float)rs[Height+1][Width]*-2;_5x5Window[3][3]=(float)rs[Height+1][Width+1]*-1;_5x5Window[3][4]=(float)rs[Height

Width+2]*0;_5x5Window[4][0]=(float)rs[Height+2][Width-2]*0;_5x5Window[4][1]=(float)rs[Height+

Width-1]*0;_5x5Window[4][2]=(float)rs[Height+2][Width]*-1;

_5x5Window[4][3]=(float)rs[Height+2][Width+1]*0;_5x5Window[4][4]=(float)rs[Height+

Width+2]*0;



55/71

oid ImageSharpeningMaskOne(void)

float _3x3Window[3][3]={{0,0,0},{0,0,0},{0,0,0}};



56/71

gs[Height][Width]=(float)0;else if(TotalGrayValue>255)

gs[Height][Width]=(float)255;else gs[Height][Width]=TotalGrayValue;



57/71

*Description: To sharp image using 3x3 mask, positive laplacianArguments : NothingReturns : Nothing

/

oid PositiveLaplacian(void)

float _3x3Window[3][3]={{0,0,0},{0,0,0},{0,0,0}};



58/71

_3x3Window[0][0]=(float)rs[Height-1][Width-1]*0;_3x3Window[0][1]=(float)rs[Height-Width]*1;

_3x3Window[0][2]=(float)rs[Height-1][Width+1]*0;_3x3Window[1][0]=(float)rs[Height][Width-1]*1;_3x3Window[1][1]=(float)rs[Height]

Width]*-4;_3x3Window[1][2]=(float)rs[Height][Width+1]*1;_3x3Window[2][0]=(float)rs[Height+1][Width-1]*0;_3x3Window[2][1]=(float)rs[Height+

Width]*1;_3x3Window[2][2]=(float)rs[Height+1][Width+1]*0;



59/71



60/71

rs[Height][Width]=(float)0;else rs[Height][Width]=(float)255;



61/71

/*Mg=(float)Mg/TotalPk;

*/

float temp1=float((Mg*Pk)-Mk);temp1=(float)powf(temp1,2.0);

temp1=float(temp1/((Pk)*(1-Pk)));if(temp1


62/71

oid ConnectedComponentBinaryImage(void)

float _5x1Window[4]={0,0,0,0};int TagValue=0,ChangeHight=0;

GlobleThresholding();cout


63/71

if(ChangeHight) {StartHeight=2;StartWidth=2;HLimit=screenHeight-2;WLimit=screenWidth-2;

}else

{StartHeight=1;StartWidth=1;HLimit=screenHeight-1;WLimit=screenWidth-1;

}for(int Height=StartHeight;Height


64/71

for(int Width=StartWidth;Width


65/71

{if(TagNo==(int)gs[Height][Width])

flag=1;}

if(flag==1)TagValue++;

}

cout


66/71

//s componentif(_3x1Buffer[2]>(float)0){float tempBuffer=_3x1Buffer[2]-_3x1Buffer[0];tempBuffer=(tempBuffer/_3x1Buffer[2]);

ss[Height][Width]=(float)tempBuffer*255;}else ss[Height][Width]=(float)0;

//h componentif((float)ss[Height][Width]==(float)0)

{hs[Height][Width]=(float)0;

}else

{float tempBuffer=0;float MaxMin=_3x1Buffer[2]-_3x1Buffer[0];

if(MaxMin!=0){if((float)rs[Height][Width]==(float)_3x1Buffer[2])

{tempBuffer=(float)gs[Height][Width]-(float)bs[Height][Width];tempBuffer=tempBuffer/MaxMin;

}else if((float)gs[Height][Width]==(float)_3x1Buffer[2])

{tempBuffer=(float)bs[Height][Width]-(float)rs[Height][Width];tempBuffer=tempBuffer/MaxMin;tempBuffer+=2.0;

}else if((float)bs[Height][Width]==(float)_3x1Buffer[2])

{tempBuffer=(float)rs[Height][Width]-(float)gs[Height][Width];tempBuffer=tempBuffer/MaxMin;tempBuffer+=4.0;

}}

tempBuffer=tempBuffer*60;if(tempBuffer


67/71

Description: RGB to YIQ conversionArguments : NothingReturns : Nothing

/

oid RGBtoYIQ(void)

AllocateHSVMemory();for(int Height=0;Height


68/71

*/cs[Height][Width]=ss[Height][Width]&hs[Height][Width];

}

return;

*Description: Performs region Growing according to imageArguments : NothingReturns : Nothing

/

oid RegoinGrowing(void)



69/71

/rs[Height][Width]=(float)WhatToSet;



70/71

*Description: Splitting of the image using given size of targeted splitted sectionArguments : Targeted spliting section sizeReturns : Nothing

/

oid Split(int Size=2)

for(int Height=Size;Height


71/71

WhatToSet=200; /*acts as a seed no 9 */else if((float)CurrentGrayLevel>=(float)225&&(float)CurrentGrayLevel

Documents

Advance image processing