SSIM.cpp

/*
 * The equivalent of Zhou Wang's SSIM matlab code using OpenCV.
 * from http://www.cns.nyu.edu/~zwang/files/research/ssim/index.html
 * The measure is described in :
 * "Image quality assessment: From error measurement to structural similarity"
 * C++ code by Rabah Mehdi. http://mehdi.rabah.free.fr/SSIM
 *
 * This implementation is under the public domain.
 * @see http://creativecommons.org/licenses/publicdomain/
 * The original work may be under copyrights. 
 */

#include <cv.h>	
#include <highgui.h>
#include <iostream.h>

/*
 * Parameters : complete path to the two image to be compared
 * The file format must be supported by your OpenCV build
 */
int main(int argc, char** argv)
{
	if(argc!=3)
		return -1;
	
	// default settings
	double C1 = 6.5025, C2 = 58.5225;

	IplImage
		*img1=NULL, *img2=NULL, *img1_img2=NULL,
		*img1_temp=NULL, *img2_temp=NULL,
		*img1_sq=NULL, *img2_sq=NULL,
		*mu1=NULL, *mu2=NULL,
		*mu1_sq=NULL, *mu2_sq=NULL, *mu1_mu2=NULL,
		*sigma1_sq=NULL, *sigma2_sq=NULL, *sigma12=NULL,
		*ssim_map=NULL, *temp1=NULL, *temp2=NULL, *temp3=NULL;
	

	/***************************** INITS **********************************/
	img1_temp = cvLoadImage(argv[1]);
	img2_temp = cvLoadImage(argv[2]);

	if(img1_temp==NULL || img2_temp==NULL)
		return -1;

	int x=img1_temp->width, y=img1_temp->height;
	int nChan=img1_temp->nChannels, d=IPL_DEPTH_32F;
	CvSize size = cvSize(x, y);

	img1 = cvCreateImage( size, d, nChan);
	img2 = cvCreateImage( size, d, nChan);

	cvConvert(img1_temp, img1);
	cvConvert(img2_temp, img2);
	cvReleaseImage(&img1_temp);
	cvReleaseImage(&img2_temp);

	
	img1_sq = cvCreateImage( size, d, nChan);
	img2_sq = cvCreateImage( size, d, nChan);
	img1_img2 = cvCreateImage( size, d, nChan);
	
	cvPow( img1, img1_sq, 2 );
	cvPow( img2, img2_sq, 2 );
	cvMul( img1, img2, img1_img2, 1 );

	mu1 = cvCreateImage( size, d, nChan);
	mu2 = cvCreateImage( size, d, nChan);

	mu1_sq = cvCreateImage( size, d, nChan);
	mu2_sq = cvCreateImage( size, d, nChan);
	mu1_mu2 = cvCreateImage( size, d, nChan);
	

	sigma1_sq = cvCreateImage( size, d, nChan);
	sigma2_sq = cvCreateImage( size, d, nChan);
	sigma12 = cvCreateImage( size, d, nChan);

	temp1 = cvCreateImage( size, d, nChan);
	temp2 = cvCreateImage( size, d, nChan);
	temp3 = cvCreateImage( size, d, nChan);

	ssim_map = cvCreateImage( size, d, nChan);
	/*************************** END INITS **********************************/


	//////////////////////////////////////////////////////////////////////////
	// PRELIMINARY COMPUTING
	cvSmooth( img1, mu1, CV_GAUSSIAN, 11, 11, 1.5 );
	cvSmooth( img2, mu2, CV_GAUSSIAN, 11, 11, 1.5 );
	
	cvPow( mu1, mu1_sq, 2 );
	cvPow( mu2, mu2_sq, 2 );
	cvMul( mu1, mu2, mu1_mu2, 1 );


	cvSmooth( img1_sq, sigma1_sq, CV_GAUSSIAN, 11, 11, 1.5 );
	cvAddWeighted( sigma1_sq, 1, mu1_sq, -1, 0, sigma1_sq );
	
	cvSmooth( img2_sq, sigma2_sq, CV_GAUSSIAN, 11, 11, 1.5 );
	cvAddWeighted( sigma2_sq, 1, mu2_sq, -1, 0, sigma2_sq );

	cvSmooth( img1_img2, sigma12, CV_GAUSSIAN, 11, 11, 1.5 );
	cvAddWeighted( sigma12, 1, mu1_mu2, -1, 0, sigma12 );
	

	//////////////////////////////////////////////////////////////////////////
	// FORMULA

	// (2*mu1_mu2 + C1)
	cvScale( mu1_mu2, temp1, 2 );
	cvAddS( temp1, cvScalarAll(C1), temp1 );

	// (2*sigma12 + C2)
	cvScale( sigma12, temp2, 2 );
	cvAddS( temp2, cvScalarAll(C2), temp2 );

	// ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
	cvMul( temp1, temp2, temp3, 1 );

	// (mu1_sq + mu2_sq + C1)
	cvAdd( mu1_sq, mu2_sq, temp1 );
	cvAddS( temp1, cvScalarAll(C1), temp1 );

	// (sigma1_sq + sigma2_sq + C2)
	cvAdd( sigma1_sq, sigma2_sq, temp2 );
	cvAddS( temp2, cvScalarAll(C2), temp2 );

	// ((mu1_sq + mu2_sq + C1).*(sigma1_sq + sigma2_sq + C2))
	cvMul( temp1, temp2, temp1, 1 );

	// ((2*mu1_mu2 + C1).*(2*sigma12 + C2))./((mu1_sq + mu2_sq + C1).*(sigma1_sq + sigma2_sq + C2))
	cvDiv( temp3, temp1, ssim_map, 1 );


	CvScalar index_scalar = cvAvg( ssim_map );
	
	// through observation, there is approximately 
	// 1% error max with the original matlab program

	cout << "(R, G & B SSIM index)" << endl ;
	cout << index_scalar.val[2] * 100 << "%" << endl ;
	cout << index_scalar.val[1] * 100 << "%" << endl ;
	cout << index_scalar.val[0] * 100 << "%" << endl ;

	// if you use this code within a program
	// don't forget to release the IplImages
	return 0;
}