Program for spatial correlogram of an image, in C

This program will read an image, convert it to greyscale, crop it to a square, and calculate it's spatial (1D) autocorrelation function (correlogram), printing it to screen.

It uses OpenCV image processing libraries - see here and here

Compilation instructions (in Ubuntu):

 sudo apt-get install libcv-dev libcv1 libcvaux-dev libcvaux1 libhighgui-dev libhighgui1  
 pkg-config --libs opencv; pkg-config --cflags opencv  
 PKG_CONFIG_PATH=/usr/lib/pkgconfig/:${PKG_CONFIG_PATH}  
 export PKG_CONFIG_PATH  
 gcc `pkg-config --cflags --libs opencv` -o Rspat Rspat.c  

Usage in the terminal:

 ./Rspat IMG_0208.JPG   

The program:

	#include <stdio.h>
	#include "cv.h"
	#include "highgui.h"
	int main( int argc, char** argv )
	{
	time_t t1,t2; // initiate timer
	(void) time(&amp;t1);
	// define some variables
	IplImage *im = 0;
	/* check for supplied argument */
	if ( argc <> \n" );
	return 1;
	}
	// load image
	im = cvLoadImage( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
	CvSize sz = cvGetSize(im); // get image dimensions
	int st=(sz.width/2)-(sz.height/2);
	// sets the Region of Interest
	cvSetImageROI(im, cvRect(st, 0, sz.height, sz.height));
	// create destination image
	IplImage *img1 = cvCreateImage(cvGetSize(im),
	im->depth,
	im->nChannels);
	// copy subimage > crop
	cvCopy(im, img1, NULL);
	// reset ROI
	cvResetImageROI(im);
	int M = img1->width; //integer image dimensions
	int N = img1->height;
	int m; // initiate loop counters
	int n;
	CvScalar s1; // initiate temporary storage of scalars
	CvScalar s2;
	CvScalar img1_avg = cvAvg( img1, NULL ); // find average of img1
	int l;
	// initiate main loop
	for( l=1; l<100 img2 =" cvCreateImage(cvGetSize(img1),">depth,
	img1->nChannels);
	// copy subimage > create shifted
	cvCopy(img1, img2, NULL);
	// reset ROI
	cvResetImageROI(img1);
	CvScalar img2_avg = cvAvg( img2, NULL ); // find average of img2
	// reset counters
	double sum_img1_img2 = 0;
	double sum_img1_2 = 0;
	double sum_img2_2 = 0;
	for( m=0; m<M-l ; ++m ){
	for( n=0; n<N-l; ++n ){
	s1=cvGet2D(img1,m,n); // get the (m,n) pixel value of img1
	s2=cvGet2D(img2,m,n); // get the (m,n) pixel value of img2
	sum_img1_img2 = sum_img1_img2 + (s1.val[0]-img1_avg.val[0])*(s2.val[0]-img2_avg.val[0]);
	sum_img1_2 = sum_img1_2 + (s1.val[0]-img1_avg.val[0])*(s1.val[0]-img1_avg.val[0]);
	sum_img2_2 = sum_img2_2 + (s2.val[0]-img2_avg.val[0])*(s2.val[0]-img2_avg.val[0]);
	}
	}
	double corr = sum_img1_img2/sqrt(sum_img1_2*sum_img2_2); // autocorrelation coefficient, lag l
	printf("lag%i,corr=%f\n",l,corr);
	(void) time(&t2);
	return 0;
	}

view raw Rspat.c hosted with ❤ by GitHub