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/*************************************************************************************
Author : Yash S. Bhalgat
***************************************************************************************
---------- Performs Contrast Limited Adaptive Histogram Equalisation -------------
Usage :
1) output_img = adapthisteq(input_img);
In this usage, the image itself is used as the guidance image.
2) output_img = adapthisteq(input_img, clip_limit);
Example :
img = imread("lena.jpg");
imshow(img);
output_img = adapthisteq(img, img, 9);
imshow(output_img);
***********************************************************************/
#include <numeric>
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/opencv.hpp"
#include <iostream>
#include <algorithm> // std::max
using namespace cv;
using namespace std;
extern "C"
{
#include "api_scilab.h"
#include "Scierror.h"
#include "BOOL.h"
#include <localization.h>
#include <sciprint.h>
#include "../common.h"
int opencv_adapthisteq(char *fname, unsigned long fname_len)
{
SciErr sciErr;
int intErr = 0;
int iRows=0,iCols=0;
int *piAddr2 = NULL;
int i,j,k;
double clip_limit;
//Default clip limit
clip_limit = 0.001;
//checking input argument
CheckInputArgument(pvApiCtx, 1, 2);
CheckOutputArgument(pvApiCtx, 1, 1);
int inputarg = *getNbInputArgument(pvApiCtx);
Mat input_img;
retrieveImage(input_img,1);
if(inputarg == 2){
//for value of clip_limit
sciErr = getVarAddressFromPosition(pvApiCtx,2,&piAddr2);
if (sciErr.iErr)
{
printError(&sciErr, 0);
return 0;
}
intErr = getScalarDouble(pvApiCtx, piAddr2, &clip_limit);
if(intErr)
return intErr;
}
//Main function
//cvtColor(input_img, input_img, CV_RGB2GRAY);
float C[256];
int row = input_img.rows;
int col = input_img.cols;
int window_x = 90;
int window_y = 90;
int min_x, min_y, max_x, max_y;
Mat window_matrix;
//float clip_limit = 0.001;
int histSize = 256; //from 0 to 255
float range[] = { 0, 256 } ;
const float* histRange = { range };
Mat H;
Mat output_img = Mat::zeros(input_img.size(), input_img.type());
if(input_img.channels()==1){
for(int i=0; i<row; i++){
for(int j=0; j<col; j++){
min_x = max(0,i-window_x);
min_y = max(0,j-window_y);
max_x = min(row-1,i+window_x);
max_y = min(col-1,j+window_y);
window_matrix = input_img(Range(min_x, max_x), Range(min_y, max_y));
//window_matrix = inputImage(min_x:max_x,min_y:max_y);
if(input_img.at<uchar>(i,j)==0) output_img.at<uchar>(i,j) =0;
else{
calcHist(&window_matrix, 1, 0, Mat(), H, 1, &histSize, &histRange);
int N = window_matrix.rows;
int M = window_matrix.cols;
H=H/(N*M);
// cout<<H<<endl;
for(int z=0; z<256; z++){
if(H.at<float>(0,z) > clip_limit) H.at<float>(0,z) = clip_limit;
}
float contrastArea = 1.0 - cv::sum(H).val[0];
float height = contrastArea / 256.00;
H = H + height;
//cout<<cv::sum(H).val[0]<<endl;
C[0] = H.at<float>(0,0)*255;
for(int k=1; k<256; k++){
C[k]= C[k-1] + H.at<float>(0,k)*255;
}
//cout<<C[255]<<endl;
output_img.at<uchar>(i,j) = C[input_img.at<uchar>(i,j)];
}
}
}
}
else if(input_img.channels()==3){
vector<cv::Mat> Ichannels;
split(input_img, Ichannels);
for(int d=0; d<3; d++){
for(int i=0; i<row; i++){
for(int j=0; j<col; j++){
min_x = max(0,i-window_x);
min_y = max(0,j-window_y);
max_x = min(row-1,i+window_x);
max_y = min(col-1,j+window_y);
window_matrix = Ichannels[d](Range(min_x, max_x), Range(min_y, max_y));
if(Ichannels[d].at<uchar>(i,j)==0) output_img.at<Vec3b>(i,j)[d] =0;
else{
calcHist(&window_matrix, 1, 0, Mat(), H, 1, &histSize, &histRange);
int N = window_matrix.rows;
int M = window_matrix.cols;
H=H/(N*M);
// cout<<H<<endl;
for(int z=0; z<256; z++){
if(H.at<float>(0,z) > clip_limit) H.at<float>(0,z) = clip_limit;
}
float contrastArea = 1.0 - cv::sum(H).val[0];
float height = contrastArea / 256.00;
H = H + height;
//cout<<cv::sum(H).val[0]<<endl;
C[0] = H.at<float>(0,0)*255;
for(int k=1; k<256; k++){
C[k]= C[k-1] + H.at<float>(0,k)*255;
}
//cout<<C[255]<<endl;
output_img.at<Vec3b>(i,j)[d] = C[Ichannels[d].at<uchar>(i,j)];
}
}
}
}
}
//returning image
string tempstring = type2str(output_img.type());
char *checker;
checker = (char *)malloc(tempstring.size() + 1);
memcpy(checker, tempstring.c_str(), tempstring.size() + 1);
returnImage(checker,output_img,1);
free(checker);
//Assigning the list as the Output Variable
AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1;
//Returning the Output Variables as arguments to the Scilab environment
ReturnArguments(pvApiCtx);
return 0;
}
/* ==================================================================== */
}
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