虚拟视点图像生成004

这几天的成果主要有:

1.由于深度图像本身的缺陷,给原始的深度图像加上预处理,首先是对深度图像进行形态学闭运算,大小为3*3的方形块。然后进行中值滤波,大小为5*5.

cv::Mat element3(3, 3, CV_8U, cv::Scalar(1));

cv::morphologyEx(imageDepth, imageDepth, cv::MORPH_CLOSE, element3);

cv::morphologyEx(imageDepth2, imageDepth2, cv::MORPH_CLOSE, element3);

cv::medianBlur(imageDepth, imageDepth, 5);

cv::medianBlur(imageDepth2, imageDepth2, 5);

2.由于正向映射会出现裂纹现象,所以进行逆向映射,先正向生成深度图像,然后对深度图像进行逆向映射,生成对应的纹理图像,由于生成的深度图像也会有裂纹,所以进行必要的中值滤波。

void wrapingImage_inverse(int ref, int proj, cv::Mat &imageColor, cv::Mat &imageDepth, cv::Mat &imageColorOut, cv::Mat &imageDepthOut)

{

for (int v = 0; v < imageColor.rows; v++)

for (int u = 0; u < imageColor.cols; u++)

{

double d = imageDepthOut.at<cv::Vec3b>(v, u)[0];

if (d == 0)

continue;

if (imageColorOut.at<cv::Vec3b>(v, u)[0] != 0 && imageColorOut.at<cv::Vec3b>(v, u)[1] != 0 && imageColorOut.at<cv::Vec3b>(v, u)[2] != 0)

continue;

pointProject_from_ref_to_otherView(pts, proj, u, v, d);

int u1 = (int)pts[ref][0];

int v1 = (int)pts[ref][1];

int k1 = (int)pts[ref][2];

if (u1 < 0 || u1 >= imageColor.cols - 1 || v1 < 0 || v1 >= imageColor.rows - 1)

continue;

imageColorOut.at<cv::Vec3b>(v, u) = imageColor.at<cv::Vec3b>(v1, u1);

}

}

3.要生成的比较完整的纹理图像,所以用左参考图像生成的纹理图像之后,空洞部分用右参考图像生成的部分进行填补。

wrapingImage(ref, proj, imageColor, imageDepth, imageColorOut, imageDepthOut);

wrapingImage(ref2, proj, imageColor2, imageDepth2, imageColorOut2, imageDepthOut2);

wrapingImage_inverse(ref, proj, imageColor, imageDepth, imageColorOut, imageDepthOut);

wrapingImage_inverse(ref2, proj, imageColor2, imageDepth2, imageColorOut, imageDepthOut2);

4.存在的问题是,由于左右参考图像的关照强度不一样,生成的图像有的较暗,有的较亮,合成之后出现伪影比较严重。如何解决呢??

5.结果.

1.生成的图像

2.原始图像

6.源代码:

#ifndef _wrapingOf3D1
#define _wrapingOf3D1
#include<iostream>
#include<opencv2\opencv.hpp>
#include <math.h>
#include <stdio.h>
#include <cv.h>
#include <highgui.h>
using std::cout;
using std::endl;
double max(double x, double y) {
	return ((x > y) ? x : y);
}
double ssim(char *ref_image, char *obj_image)
{
	// 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(ref_image);
	img2_temp = cvLoadImage(obj_image);

	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)" << std::endl;
	cout << index_scalar.val[2] << endl;
	cout << index_scalar.val[1] << endl;
	cout << index_scalar.val[0] << endl;

	cvReleaseImage(&img1_sq);
	cvReleaseImage(&img2_sq);
	cvReleaseImage(&img1_img2);
	cvReleaseImage(&mu1);
	cvReleaseImage(&mu2);
	cvReleaseImage(&mu1_sq);
	cvReleaseImage(&mu2_sq);
	cvReleaseImage(&mu1_mu2);
	cvReleaseImage(&sigma1_sq);
	cvReleaseImage(&sigma2_sq);
	cvReleaseImage(&sigma12);
	cvReleaseImage(&temp1);
	cvReleaseImage(&temp2);
	cvReleaseImage(&temp3);
	cvReleaseImage(&ssim_map);
	//double ssim=max(max(index_scalar.val[0], index_scalar.val[1]), index_scalar.val[2]);
	double ssim = (index_scalar.val[0] + index_scalar.val[1] + index_scalar.val[2]) / 3;
	return ssim;
}

double psnr(char *ref_image, char *obj_image)
{
	cv::Mat image_ref = cv::imread(ref_image);
	cv::Mat image_obj = cv::imread(obj_image);
	double mse = 0;
	double div_r = 0;
	double div_g = 0;
	double div_b = 0;
	int width = image_ref.cols;
	int height = image_ref.rows;
	double psnr = 0;
	for (int v = 0; v < height; v++)
	{
		for (int u = 0; u < width; u++)
		{
			div_r = image_ref.at<cv::Vec3b>(v, u)[0] - image_obj.at<cv::Vec3b>(v, u)[0];
			div_g = image_ref.at<cv::Vec3b>(v, u)[1] - image_obj.at<cv::Vec3b>(v, u)[1];
			div_b = image_ref.at<cv::Vec3b>(v, u)[2] - image_obj.at<cv::Vec3b>(v, u)[2];
			mse += ((div_r*div_r + div_b*div_b + div_g*div_g) / 3);

		}
	}
	mse = mse / (width*height);
	psnr = 10 * log10(255 * 255 / mse);
	printf("%lf\n", mse);
	printf("%lf\n", psnr);
	return psnr;
}

class Histogram1D{
private:
	int histSize[1];
	float hranges[2];
	const float *ranges[1];
	int channels[1];
public:
	Histogram1D(){
		histSize[0] = 256;
		hranges[0] = 0.0;
		hranges[1] = 255.0;
		ranges[0] = hranges;
		channels[0] = 0;
	}
	cv::MatND getHistogram(const cv::Mat &image){
		cv::MatND hist;
		cv::calcHist(&image, 1, channels, cv::Mat(), hist, 1, histSize, ranges);
		return hist;
	}
	cv::Mat getHistogramImage(const cv::Mat &image){
		cv::MatND hist = getHistogram(image);
		double maxVal = 0;
		double minVal = 0;
		cv::minMaxLoc(hist, &minVal, &maxVal, 0, 0);
		cv::Mat histImg(histSize[0], histSize[0], CV_8U, cv::Scalar(255));
		int hpt = static_cast<int>(0.9*histSize[0]);
		for (int h = 0; h < histSize[0]; h++){
			float binVal = hist.at<float>(h);
			int intensity = static_cast<int>(binVal*hpt / maxVal);
			cv::line(histImg, cv::Point(h, histSize[0]), cv::Point(h, histSize[0] - intensity), cv::Scalar::all(100), 1);
		}
		return histImg;
	}
};

/*
**define a struct included intrinsic and extrinsic args
*/
typedef struct {
	double m_K[3][3]; // 3x3 intrinsic matrix
	double m_RotMatrix[3][3]; // rotation matrix
	double m_Trans[3]; // translation vector

	double m_ProjMatrix[4][4]; // projection matrix
} CalibStruct;
/*
**define globle variables
*/
CalibStruct m_CalibParams[8];
int m_NumCameras = 8;
int m_Width = 1024, m_Height = 768; // camera resolution is 1024x768
double pts[8][3];

/*
**declare function
*/
void InitializeFromFile(char *fileName);
double DepthLevelToZ(unsigned char d);
unsigned char ZToDepthLever(double z);
double projXYZtoUV(double projMatrix[4][4], double x, double y, double z, double *u, double *v);
void projUVZtoXY(double projMatrix[4][4], double u, double v, double z, double *x, double *y, double pt[8][2]);
void wrapingImage(int ref, int proj, cv::Mat &imageColor, cv::Mat &imageDepth, cv::Mat &imageColorOut);
void pointProject_from_ref_to_otherView(double pts[8][2], int ref, int u, int v, unsigned char d);
/*
**define function
*/

/*
** read text file and write args to struct of globle variable
*/
void readCalibrationFile(char *fileName)
{
	int i, j, k;
	FILE *pIn;
	double dIn; // dummy variable
	int camIdx;

	if (pIn = fopen(fileName, "r"))
	{
		for (k = 0; k<m_NumCameras; k++)
		{
			// camera index
			fscanf(pIn, "%d", &camIdx);
			//std::cout << camIdx << std::endl;

			// camera intrinsics
			for (i = 0; i < 3; i++){
				fscanf(pIn, "%lf\t%lf\t%lf", &(m_CalibParams[camIdx].m_K[i][0]), &(m_CalibParams[camIdx].m_K[i][1]), &(m_CalibParams[camIdx].m_K[i][2]));
				//std::cout << (m_CalibParams[camIdx].m_K[i][0])<<"\t"<<(m_CalibParams[camIdx].m_K[i][1]) <<"\t"<< (m_CalibParams[camIdx].m_K[i][2]) << std::endl;
			}

			// read barrel distortion params (assume 0)
			fscanf(pIn, "%lf", &dIn);
			fscanf(pIn, "%lf", &dIn);

			// read extrinsics
			for (i = 0; i<3; i++)
			{
				for (j = 0; j<3; j++)
				{
					fscanf(pIn, "%lf", &dIn);
					m_CalibParams[camIdx].m_RotMatrix[i][j] = dIn;
					//std::cout << m_CalibParams[camIdx].m_RotMatrix[i][j] << std::endl;
				}

				fscanf(pIn, "%lf", &dIn);
				m_CalibParams[camIdx].m_Trans[i] = dIn;
			}

		}

		fclose(pIn);
	}
}// readCalibrationFile

/*
**calcular all projectionMatrices depended on struct variables
*/
void computeProjectionMatrices()
{
	int i, j, k, camIdx;
	double(*inMat)[3];
	double exMat[3][4];

	for (camIdx = 0; camIdx<m_NumCameras; camIdx++)
	{
		// The intrinsic matrix
		inMat = m_CalibParams[camIdx].m_K;

		// The extrinsic matrix
		for (i = 0; i<3; i++)
		{
			for (j = 0; j<3; j++)
			{
				exMat[i][j] = m_CalibParams[camIdx].m_RotMatrix[i][j];
			}
		}

		for (i = 0; i<3; i++)
		{
			exMat[i][3] = m_CalibParams[camIdx].m_Trans[i];
		}

		// Multiply the intrinsic matrix by the extrinsic matrix to find our projection matrix
		for (i = 0; i<3; i++)
		{
			for (j = 0; j<4; j++)
			{
				m_CalibParams[camIdx].m_ProjMatrix[i][j] = 0.0;

				for (k = 0; k<3; k++)
				{
					m_CalibParams[camIdx].m_ProjMatrix[i][j] += inMat[i][k] * exMat[k][j];
				}
			}
		}

		m_CalibParams[camIdx].m_ProjMatrix[3][0] = 0.0;
		m_CalibParams[camIdx].m_ProjMatrix[3][1] = 0.0;
		m_CalibParams[camIdx].m_ProjMatrix[3][2] = 0.0;
		m_CalibParams[camIdx].m_ProjMatrix[3][3] = 1.0;
	}
}

/**
**init projection matrix
*/
void InitializeFromFile(char *fileName)
{
	readCalibrationFile(fileName);
	computeProjectionMatrices();
}
/**
**calcular z depended on d of depth image
*/
double DepthLevelToZ(unsigned char d)
{
	double z;
	double MinZ = 44.0, MaxZ = 120.0;

	z = 1.0 / ((d / 255.0)*(1.0 / MinZ - 1.0 / MaxZ) + 1.0 / MaxZ);
	return z;
}

/**
**calcular d of depth image depended on z
*/
unsigned char ZToDepthLever(double z)
{
	double MinZ = 44.0, MaxZ = 120.0;
	unsigned char d;
	d = (unsigned char)(255.0*(1 / (double)z - 1 / MaxZ) / (1 / MinZ - 1 / MaxZ));
	return d;
}

/**
**calcular x,y depended on u,v,z and projection Matrix
**for example,projection Matrix is m_CalibParams[i].m_ProjMatrix which is index of camera
*/
void projUVZtoXY(double projMatrix[4][4], double u, double v, double z, double *x, double *y)
{
	double c0, c1, c2;

	// image (0,0) is bottom lefthand corner
	v = (double)m_Height - v - 1.0;

	c0 = z*projMatrix[0][2] + projMatrix[0][3];
	c1 = z*projMatrix[1][2] + projMatrix[1][3];
	c2 = z*projMatrix[2][2] + projMatrix[2][3];

	*y = u*(c1*projMatrix[2][0] - projMatrix[1][0] * c2) +
		v*(c2*projMatrix[0][0] - projMatrix[2][0] * c0) +
		projMatrix[1][0] * c0 - c1*projMatrix[0][0];

	*y /= v*(projMatrix[2][0] * projMatrix[0][1] - projMatrix[2][1] * projMatrix[0][0]) +
		u*(projMatrix[1][0] * projMatrix[2][1] - projMatrix[1][1] * projMatrix[2][0]) +
		projMatrix[0][0] * projMatrix[1][1] - projMatrix[1][0] * projMatrix[0][1];

	*x = (*y)*(projMatrix[0][1] - projMatrix[2][1] * u) + c0 - c2*u;
	*x /= projMatrix[2][0] * u - projMatrix[0][0];
} // projUVZtoXY

/**
**calcular u,v,z1 depended on x,y,z
**z1 is after projection and z is before projection.z1 is return value
**/

double projXYZtoUV(double projMatrix[4][4], double x, double y, double z, double *u, double *v)
{
	double w;

	*u = projMatrix[0][0] * x +
		projMatrix[0][1] * y +
		projMatrix[0][2] * z +
		projMatrix[0][3];

	*v = projMatrix[1][0] * x +
		projMatrix[1][1] * y +
		projMatrix[1][2] * z +
		projMatrix[1][3];

	w = projMatrix[2][0] * x +
		projMatrix[2][1] * y +
		projMatrix[2][2] * z +
		projMatrix[2][3];

	*u /= w;
	*v /= w;

	// image (0,0) is bottom lefthand corner
	*v = (double)m_Height - *v - 1.0;

	return w;

} // projXYZtoUV

/**

**/

void pointProject_from_ref_to_otherView(double pts[8][3], int ref, int u, int v, unsigned char d)
{
	double x, y, z = DepthLevelToZ(d);

	//printf("Testing projection of pt (%d,%d) in camera 0 with d = %d (z = %f) to other cameras\n", u, v, d, z);

	projUVZtoXY(m_CalibParams[ref].m_ProjMatrix, (double)u, (double)v, z, &x, &y);
	//printf("3D pt = (%f, %f, %f) [coordinates wrt reference camera]\n", x, y, z);
	for (int cam = 0; cam<8; cam++)
	{
		double *pt = pts[cam];
		pt[0] = 0;
		pt[1] = 0;
		pt[2] = 0;
	}
	for (int cam = 0; cam<8; cam++)
	{
		double *pt = pts[cam];

		pt[2] = projXYZtoUV(m_CalibParams[cam].m_ProjMatrix, x, y, z, &pt[0], &pt[1]);
		//printf("Camera %d: (%f, %f)\n", cam, pt[0], pt[1]);
		pt[2] = ZToDepthLever(pt[2]);
	}
}

/**
**wraping image,ref represent reference cam,proj represent projection cam
**the kernal code
**/
void wrapingImage(int ref, int proj, cv::Mat &imageColor, cv::Mat &imageDepth, cv::Mat &imageColorOut, cv::Mat &imageDepthOut)
{
	for (int v = 0; v < imageColor.rows; v++)
		for (int u = 0; u < imageColor.cols; u++)
		{
			double d = imageDepth.at<cv::Vec3b>(v, u)[0];
			pointProject_from_ref_to_otherView(pts, ref, u, v, d);
			int u1 = (int)pts[proj][0];
			int v1 = (int)pts[proj][1];
			int k1 = (int)pts[proj][2];
			if (u1 < 0 || u1 >= imageColor.cols - 1 || v1 < 0 || v1 >= imageColor.rows - 1)
				continue;
			if (k1 < imageDepthOut.at<cv::Vec3b>(v1, u1)[0])
				continue;
			imageColorOut.at<cv::Vec3b>(v1, u1) = imageColor.at<cv::Vec3b>(v, u);
			imageDepthOut.at<cv::Vec3b>(v1, u1)[0] = k1;
			imageDepthOut.at<cv::Vec3b>(v1, u1)[1] = k1;
			imageDepthOut.at<cv::Vec3b>(v1, u1)[2] = k1;
		}
}
void wrapingImage_inverse(int ref, int proj, cv::Mat &imageColor, cv::Mat &imageDepth, cv::Mat &imageColorOut, cv::Mat &imageDepthOut)
{
	for (int v = 0; v < imageColor.rows; v++)
		for (int u = 0; u < imageColor.cols; u++)
		{

			double d = imageDepthOut.at<cv::Vec3b>(v, u)[0];
			if (d == 0)
				continue;
			if (imageColorOut.at<cv::Vec3b>(v, u)[0] != 0 && imageColorOut.at<cv::Vec3b>(v, u)[1] != 0 && imageColorOut.at<cv::Vec3b>(v, u)[2] != 0)
				continue;
			pointProject_from_ref_to_otherView(pts, proj, u, v, d);
			int u1 = (int)pts[ref][0];
			int v1 = (int)pts[ref][1];
			int k1 = (int)pts[ref][2];
			if (u1 < 0 || u1 >= imageColor.cols - 1 || v1 < 0 || v1 >= imageColor.rows - 1)
				continue;
			imageColorOut.at<cv::Vec3b>(v, u) = imageColor.at<cv::Vec3b>(v1, u1);
		}
}

void dipslay(char *calibParam, char *refColor, char *refDepth, char *refColor2, char *refDepth2, char *actColor)
{
	//initialize projection_Matrix
	InitializeFromFile(calibParam);
	//display projection_Matrix
	for (int i = 0; i < m_NumCameras; i++){
		for (int j = 0; j < 3; j++){
			for (int k = 0; k < 3; k++)
				std::cout << m_CalibParams[i].m_K[j][k] << "\t";
			std::cout << std::endl;
		}

		for (int j = 0; j < 3; j++){
			for (int k = 0; k < 3; k++)
				std::cout << m_CalibParams[i].m_RotMatrix[j][k] << "\t";
			std::cout << std::endl;
		}
		for (int k = 0; k < 3; k++)
			std::cout << m_CalibParams[i].m_Trans[k] << "\t";
		std::cout << std::endl;
		std::cout << std::endl;
		std::cout << std::endl;
		std::cout << std::endl;
	}
	//suspend and users enter a digit
	int aa;
	//std::cin >> aa;
	//read color image and depth image of refrence
	cv::Mat imageColor = cv::imread(refColor);
	cv::Mat imageDepth = cv::imread(refDepth);
	cv::Mat imageColor2 = cv::imread(refColor2);
	cv::Mat imageDepth2 = cv::imread(refDepth2);
	//read true image used to compare
	cv::Mat imageColor_actual = cv::imread(actColor);
	//set reference cam
	int ref = 5;
	int ref2 = 7;
	//set projection cam
	int proj = 6;
	//test code
	pointProject_from_ref_to_otherView(pts, ref, 700, 700, imageDepth.at<cv::Vec3b>(700, 700)[0]);
	for (int i = 0; i < 8; i++)
	{
		std::cout << pts[i][0] << "\t" << pts[i][1] << std::endl;
	}
	//std::cin >> aa;
	//define two variable of output
	cv::Mat imageColorOut;
	cv::Mat imageColorOut2;
	cv::Mat imageDepthOut;
	cv::Mat imageDepthOut2;
	imageColorOut.create(imageColor.rows, imageColor.cols, imageColor.type());
	imageColorOut2.create(imageColor.rows, imageColor.cols, imageColor.type());
	imageDepthOut.create(imageColor.rows, imageColor.cols, imageColor.type());
	imageDepthOut2.create(imageColor.rows, imageColor.cols, imageColor.type());
	for (int v = 0; v < imageColor.rows; v++)
	{
		for (int u = 0; u < imageColor.cols; u++)
		{
			imageColorOut.at<cv::Vec3b>(v, u)[0] = 0;
			imageColorOut.at<cv::Vec3b>(v, u)[1] = 0;
			imageColorOut.at<cv::Vec3b>(v, u)[2] = 0;
			imageColorOut2.at<cv::Vec3b>(v, u)[0] = 0;
			imageColorOut2.at<cv::Vec3b>(v, u)[1] = 0;
			imageColorOut2.at<cv::Vec3b>(v, u)[2] = 0;
			imageDepthOut.at<cv::Vec3b>(v, u)[0] = 0;
			imageDepthOut.at<cv::Vec3b>(v, u)[1] = 0;
			imageDepthOut.at<cv::Vec3b>(v, u)[2] = 0;
			imageDepthOut2.at<cv::Vec3b>(v, u)[0] = 0;
			imageDepthOut2.at<cv::Vec3b>(v, u)[1] = 0;
			imageDepthOut2.at<cv::Vec3b>(v, u)[2] = 0;

		}
	}
	//save_dir
	char *save_dir = "C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\";
	//wraping from reference view to virtruel view
	//cv::medianBlur(imageDepth, imageDepth, 7);
	//cv::medianBlur(imageDepth2, imageDepth2, 7);
	cv::Mat element3(3, 3, CV_8U, cv::Scalar(1));
	cv::morphologyEx(imageDepth, imageDepth, cv::MORPH_CLOSE, element3);
	cv::morphologyEx(imageDepth2, imageDepth2, cv::MORPH_CLOSE, element3);
	cv::medianBlur(imageDepth, imageDepth, 5);
	cv::medianBlur(imageDepth2, imageDepth2, 5);
	//cv::GaussianBlur(imageDepth, imageDepth, cv::Size(5, 5), 1.5);    // 高斯平滑 模糊  线性滤波器
	//cv::GaussianBlur(imageDepth2, imageDepth2, cv::Size(5, 5), 1.5);    // 高斯平滑 模糊  线性滤波器
	//cv::blur(imageDepth, imageDepth, cv::Size(5, 5));
	//cv::blur(imageDepth2, imageDepth2, cv::Size(5, 5));
	//wrapingImage(ref2, proj, imageColor2, imageDepth2, imageColorOut2, imageDepthOut2);
	wrapingImage(ref, proj, imageColor, imageDepth, imageColorOut, imageDepthOut);
	wrapingImage(ref2, proj, imageColor2, imageDepth2, imageColorOut2, imageDepthOut2);
	cv::medianBlur(imageDepthOut, imageDepthOut, 5);
	cv::medianBlur(imageDepthOut2, imageDepthOut2, 5);
	cv::imshow("virtruel_Depth_image", imageDepthOut);
	cv::imwrite("C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\virtruel_Depth_image01.jpg", imageDepthOut);
	cv::imshow("virtruel_Depth_image2", imageDepthOut2);
	cv::imwrite("C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\virtruel_Depth_image21.jpg", imageDepthOut2);
	for (int v = 0; v < imageColor.rows; v++)
	{
	for (int u = 0; u < imageColor.cols; u++)
	{
	imageColorOut.at<cv::Vec3b>(v, u)[0] = 0;
	imageColorOut.at<cv::Vec3b>(v, u)[1] = 0;
	imageColorOut.at<cv::Vec3b>(v, u)[2] = 0;
	imageColorOut2.at<cv::Vec3b>(v, u)[0] = 0;
	imageColorOut2.at<cv::Vec3b>(v, u)[1] = 0;
	imageColorOut2.at<cv::Vec3b>(v, u)[2] = 0;

	}
	}
	cv::Mat element4(5, 5, CV_8U, cv::Scalar(1));
	cv::morphologyEx(imageDepthOut, imageDepthOut, cv::MORPH_CLOSE, element4);
	cv::Mat element5(5, 5, CV_8U, cv::Scalar(1));
	cv::morphologyEx(imageDepthOut2, imageDepthOut2, cv::MORPH_CLOSE, element5);
	//wrapingImage_inverse(ref2, proj, imageColor2, imageDepth2, imageColorOut2, imageDepthOut2);
	wrapingImage_inverse(ref, proj, imageColor, imageDepth, imageColorOut, imageDepthOut);
	wrapingImage_inverse(ref2, proj, imageColor2, imageDepth2, imageColorOut, imageDepthOut2);
	//display reference_image
	/*cv::imshow("reference_image", imageColor);
	cv::imwrite("C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\reference_image.jpg", imageColor);*/
	//display virtruel_image
	//cv::medianBlur(imageColorOut, imageColorOut, 3);
	//cv::cvtColor(imageColorOut, imageColorOut, CV_BGR2GRAY);
	/*cv::equalizeHist(imageDepthOut, imageDepthOut);
	cv::equalizeHist(imageDepthOut2, imageDepthOut2);*/
	cv::imshow("virtruel_Color_image01", imageColorOut);
	cv::imwrite("C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\virtruel_Color_image01.jpg", imageColorOut);
	cv::imshow("virtruel_Color_image21", imageColorOut2);
	cv::imwrite("C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\virtruel_Color_image21.jpg", imageColorOut2);
	////display virtruel_image
	//cv::imshow("virtruel_Color_image21", imageColorOut2);
	//cv::imwrite("C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\virtruel_Color_image21.jpg", imageColorOut2);
	//display virtruel_image
	//cv::medianBlur(imageDepthOut, imageDepthOut, 3);
	/*cv::medianBlur(imageDepthOut, imageDepthOut, 5);
	cv::medianBlur(imageDepthOut2, imageDepthOut2, 5);*/
	/*cv::imshow("virtruel_Depth_image", imageDepthOut);
	cv::imwrite("C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\virtruel_Depth_image01.jpg", imageDepthOut);
	cv::imshow("virtruel_Depth_image2", imageDepthOut2);
	cv::imwrite("C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\virtruel_Depth_image21.jpg", imageDepthOut2);*/
	//display actruel_image
	//cv::cvtColor(imageColor_actual, imageColor_actual, CV_BGR2GRAY);
	cv::imshow("actruel_image", imageColor_actual);
	cv::imwrite("C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\actruel_image.jpg", imageColor_actual);
	////mix reference and virtruel and check changes
	cv::Mat imageColorRefVSProj;
	cv::addWeighted(imageColorOut, 0.5, imageColorOut2, 0.5, 0.0, imageColorRefVSProj);
	cv::imshow("imageColorRefVSProj", imageColorRefVSProj);
	cv::imwrite("C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\imageColorRefVSProj.jpg", imageColorRefVSProj);
	////mix actual and virtruel and check changes
	/*cv::Mat imageColorActVSProj;
	cv::addWeighted(imageColor_actual, 0.5, imageColorOut2, 0.5, 0.0, imageColorActVSProj);
	cv::imshow("imageColorActVSProj", imageColorActVSProj);
	cv::imwrite("C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\imageColorActVSProj.jpg", imageColorActVSProj);*/
	cv::waitKey();

}

void main()
{
	/*char *refColor = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Breakdancers\\cam2\\color-cam2-f060.jpg";
	char *refDepth = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Breakdancers\\cam2\\depth-cam2-f060.png";
	char *refColor2 = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Breakdancers\\cam4\\color-cam4-f060.jpg";
	char *refDepth2 = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Breakdancers\\cam4\\depth-cam4-f060.png";
	char *calibParam = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Breakdancers\\calibParams-breakdancers.txt";
	char *actColor = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Breakdancers\\cam3\\color-cam3-f060.jpg";*/
	char *refColor = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Ballet\\cam5\\color-cam5-f000.jpg";
	char *refDepth = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Ballet\\cam5\\depth-cam5-f000.png";
	char *refColor2 = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Ballet\\cam7\\color-cam7-f000.jpg";
	char *refDepth2 = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Ballet\\cam7\\depth-cam7-f000.png";
	char *calibParam = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Ballet\\calibParams-ballet.txt";
	char *actColor = "C:\\Users\\jiang\\Desktop\\experientdata\\3DVideos-distrib\\MSR3DVideo-Ballet\\cam6\\color-cam6-f000.jpg";
	char *ref_img = "C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\virtruel_Color_image01.jpg";
	char *act_img = "C:\\Users\\jiang\\Desktop\\experientdata\\experiencePictrue\\actruel_image.jpg";
	dipslay(calibParam, refColor, refDepth, refColor2, refDepth2, actColor);
	double value_psnr = psnr(ref_img, act_img);
	printf("psnr=%lf\n", value_psnr);
	double value_ssim = ssim(ref_img, act_img);
	printf("ssim=%lf\n", value_ssim);
	getchar();
	int aa;
	std::cin >> aa;
}
#endif
时间: 2024-07-31 19:46:37

虚拟视点图像生成004的相关文章

虚拟视点图像生成007

今天来总结一下这几日的研究成果: (1)要对生成的虚拟视点图像去除伪影,需要进行大空洞区域的空洞扩张,直接应用opencv的形态学膨胀和腐蚀操作发现整体对图像进行了模糊,不是本实验要求的结果,所以提出了大边缘腐蚀操作算子,仅对大空洞周围的像素进行腐蚀. void dealXjlk(cv::Mat &imageColor) { cv::Mat imageColor2; imageColor2.create(imageColor.rows, imageColor.cols, imageColor.t

虚拟视点图像生成006

这一段时间的研究成果有: (1)对于映射到虚拟视点后直接取整这个问题,对他进行了改进. 方法:首先开辟存储空间进行存储映射后的深度信息,而不是存储量化后的深度值: 其次开辟存储空间存储四舍五入后的整数像素点到映射后的精确位置的欧拉值: 再后对于映射后的像素点不是简单地取整,而是四舍五入进行取整: 最后,对于映射到同一位置的像素点,比较深度信息,深度值大的进行显示,深度值相同的,比较欧拉值,欧拉值小的进行显示. 结果:psnr值和ssim都有一定程度的提高,成功!!!!! (2)对于映射后两张图片

虚拟视点图像生成008

昨天在小海同学的帮助下,终于配置好了vsrs软件,在此非常感谢.遇到的一些问题,我想都是大家在配置过程中都会遇到的,所以记录一下,以便大家配置过程中参考: 1.首先得下载vsrs软件3.5版本,还有一个软件是计算深度图像的在此一并分享,下载地址是: http://download.csdn.net/detail/u012361418/8714777 http://download.csdn.net/download/putong2006/3452765 2.配置opencv2.4.9(我用的2.

虚拟视点图像的生成009

psnr值在30db左右,ssim在0.85左右. 源代码: #ifndef _wrapingOf3D1 #define _wrapingOf3D1 #include<iostream> #include<opencv2\opencv.hpp> #include "opencv2/imgproc/imgproc.hpp" #include "opencv2/highgui/highgui.hpp" #include <math.h>

OpenGL ES学习笔记(二)&mdash;&mdash;平滑着色、自适应宽高及三维图像生成

首先申明下,本文为笔者学习<OpenGL ES应用开发实践指南(Android卷)>的笔记,涉及的代码均出自原书,如有需要,请到原书指定源码地址下载. <Android学习笔记--OpenGL ES的基本用法.绘制流程与着色器编译>中实现了OpenGL ES的Android版HelloWorld,并且阐明了OpenGL ES的绘制流程,以及编译着色器的流程及注意事项.本文将从现实世界中图形显示的角度,说明OpenGL ES如何使得图像在移动设备上显示的更加真实.首先,物体有各种颜色

php基础之gd图像生成、缩放、logo水印和简单验证码实现

php基础之gd图像生成.缩放.logo水印和简单验证码实现 阅读目录 图像生成 缩略图 水印生成 验证码 gd 库是php最常用的图片处理库之一(另外一个是imagemagick),可以生成图片.验证码.水印.缩略图等等.要使用gd库首先需要开启gd库扩 展,windows系统下需要在php.ini中将extension=php_gd2.dll 前边的分号去掉然后重启web服务器,linux系统下一般在编译php时已经开启gd库扩展,要是没有开启gd库扩展则需要先编译安装freetype ,j

文档生成工具doxygen+图像生成工具GraphViz

文档生成工具doxygen+图像生成工具GraphViz 虽然jdk自带的javadoc也很好用,不过使用doxygen+GraphViz 的组合可以生成许多强大的图(类图.协作图.文件包含/被包含图.函数调用/被调用图.类继承体系图等),另外,doxygen支持直接生成chm文档,支持LaTeX公式,如果你有一个支持php的服务器,生成的html还可以加入一个搜索框. doxygen是开源的C语言软体,可以在它的官方网站上下载到软体和源码:http://www.stack.nl/~dimitr

virtualBox复制以前的虚拟硬盘文件生成新的虚拟机启动后找不到网卡

VirtualBox复制以前的虚拟硬盘文件生成新的虚拟机时重启后一般网卡不能正常使用 使用ifup eth0或service network restart时会报错(CentOS6.X) 原因: 新虚拟的硬件配置与旧虚拟硬盘文件中记录的硬件配置有一定差异,即使所有的硬件选择与之前一样也会出现配置信息不一致(如网卡的MAC地址)的问题 解决方法: 进入 /etc/udev/rules.d目录 修改70-persistent-net.rules文件即可 文件中记录有两个网卡,如果现有只有一个的话可以

最简单的分形图像生成算法

本文将提供一段完整地生成一幅分形图像文件的C语言代码,并且极为简单.我相信这应该是最简单的分形图像生成算法.大部分的分形图像代码也都很短,但一有递归迭代就难以理解了.而这段代码则很好懂,并且其生成的图像会使人意想不到. #include <iostream> #include <cmath> #include <cstdlib> #define DIM 1000 void pixel_write(int,int); FILE *fp; int main() { fp =