int performWTP(unsigned char *inputFilename, unsigned char *outputFilename, int image_width, int image_height, int to_extend_image, int extend_by_pixels, int use_FFT, int wavelet_type, int ridge_alg, double starting_scale, double scale_step, double ending_scale, double Morlet_sigma)
{
printf("\nEntering C program...\n");
if (to_extend_image == NO) extend_by_pixels = 0;
int image_width_FFT = 0, order = 0;
if (use_FFT == YES && to_extend_image == YES)
{
//determine log2(image_width)
while (image_width_FFT <= image_width)
{
image_width_FFT = pow(2.0,(double) order);
++order;
}
extend_by_pixels = (image_width_FFT - image_width)/2;
}
//read the fringes image which is BYTE format
printf("Reading %s \n", inputFilename);
unsigned char *fringes = (unsigned char *)calloc(image_width * image_height, sizeof(unsigned char));
FILE *input_file = fopen(inputFilename, "rb");
if(!input_file)
{
printf("\ncan't open file %s\n", inputFilename);
return 1;
}
fread(fringes, sizeof(unsigned char), image_width * image_height, input_file);
fclose(input_file);
//convert fringes to float data type
int i;
float *fringes_float = (float *)malloc(image_width * image_height * sizeof(float));
for (i=0; i<image_width*image_height; ++i)
{
fringes_float[i] = fringes[i];
// printf("\n debug %f\n", fringes_float[i]);
}
//subtract the image from its mathematical mean
remove_DC(fringes_float, image_width, image_height);
if (to_extend_image == YES)
{
printf("Extending the image borders using linear prediction,...\n");
fringes_float = extend_image_linear_prediction(fringes_float, &image_width, &image_height, extend_by_pixels);
}
float *wrapped_phase = (float *)malloc(image_width * image_height * sizeof(float));
//use either the WFA or the WTA function.
if (use_FFT == YES)
{
printf("Performing wavelet transform in Frequency domain, please wait...\n");
WFA(fringes_float, wrapped_phase, image_width, image_height, starting_scale, scale_step, ending_scale, ridge_alg, Morlet_sigma, extend_by_pixels, wavelet_type);
}
else
{
printf("Performing wavelet transform in time domain, please wait...\n");
WTA(fringes_float, wrapped_phase, image_width, image_height, starting_scale, scale_step, ending_scale, ridge_alg, Morlet_sigma, extend_by_pixels, wavelet_type);
}
//crop the image to return it to the original image dimensions
if (to_extend_image == YES)
wrapped_phase = crop_wrapped_phase(wrapped_phase, &image_width, &image_height, extend_by_pixels);
//writing the results to the file
printf("Writing %s \n", outputFilename);
FILE *output_file = fopen(outputFilename, "wb");
fwrite(wrapped_phase, sizeof(float), image_width * image_height, output_file);
fclose(output_file);
//free used memory
free(fringes);
free(fringes_float);
free(wrapped_phase);
printf("Leaving C program...\n \n");
return 0;
}
int main(int argc, char **argv)
{
try {
// parse command line
if (argc != 3)
throw CError(usage, argv[0]);
int argn = 1;
char *dataFileName = argv[argn++];
char *outstem = argv[argn++];
int writeParams = 1;
int writeTimings = 1;
FILE *debugfile = createDebugFile(writeParams, outstem, verbose, argc, argv);
// Load datafile
int width, height, nLabels;
std::vector<int> gt, data, lrPairwise, udPairwise;
MRF::CostVal *dataCostArray, *hCue, *vCue;
if (verbose)
fprintf(stderr, "Loading datafile...\n");
LoadDataFile(dataFileName, width, height, nLabels, dataCostArray, hCue, vCue);
DataCost *dcost = new DataCost(dataCostArray);
SmoothnessCost *scost = new SmoothnessCost(1, 1, 1, hCue, vCue);
EnergyFunction *energy = new EnergyFunction(dcost, scost);
if (verbose)
fprintf(stderr, "Running optimization...\n");
fflush(stderr);
int MRFalg = aRunAll;
int outerIter, innerIter;
MRF *mrf = NULL;
for (int numAlg = aICM; numAlg <= aBPM; numAlg++) {
outerIter = MAXITER;
innerIter = 1;
if (MRFalg < aRunAll && numAlg != MRFalg) continue;
startAlgInitTimer();
switch (numAlg) {
case aICM: mrf = new ICM(width, height, nLabels, energy); innerIter = 5; break;
case aExpansion: mrf = new Expansion(width, height, nLabels, energy); break;
case aSwap: mrf = new Swap(width, height, nLabels, energy); break;
case aTRWS: mrf = new TRWS(width, height, nLabels, energy); break;
case aBPS: mrf = new BPS(width, height, nLabels, energy);
//innerIter = 5;
break;
case aBPM: mrf = new MaxProdBP(width, height, nLabels, energy);
//innerIter = 2;
break;
default: throw new CError("unknown algorithm number");
}
if (debugfile)
fprintf(debugfile, "******* Running %s for up to %d x %d iterations\n",
algs[numAlg], outerIter, innerIter);
mrf->initialize();
mrf->clearAnswer();
bool initializeToWTA = false;
if (initializeToWTA) {
if (debugfile)
fprintf(debugfile, "performing WTA\n");
CByteImage disp;
WTA(dataCostArray, width, height, nLabels, disp);
writeDisparities(disp, 255, "WTA.png", debugfile);
setDisparities(disp, mrf);
} else {
mrf->clearAnswer();
}
float initTime = getAlgInitTime();
FILE *timefile = createTimeFile(writeTimings, outstem, algs[numAlg], debugfile);
runAlg(mrf, numAlg, debugfile, timefile, outerIter, innerIter, initTime);
// save resulting labels as image
CShape sh(width, height, 1);
CByteImage outimg(sh);
int n = 0;
for (int y = 0; y < height; y++) {
for (int x = 0; x < width; x++) {
outimg.Pixel(x, y, 0) = 255* mrf->getLabel(n);
n++;
}
}
char fname[500];
sprintf(fname, "%s-%s.png", outstem, algs[numAlg]);
WriteImageVerb(outimg, fname, 1);
delete mrf;
}
if (writeParams)
fclose(debugfile);
delete energy;
delete scost;
delete dcost;
delete [] dataCostArray;
delete [] hCue;
delete [] vCue;
}
catch (CError &err) {
fprintf(stderr, err.message);
fprintf(stderr, "\n");
return -1;
}
catch (bad_alloc) {
fprintf(stderr, "*** Error: not enough memory\n");
exit(1);
}
return 0;
}
int _tmain(int argc, _TCHAR* argv[])
{
//paragrams
const int rectLeftTopX = 200 ,rectLeftTopY = 200, rectWidth = 1648,rectHeight = 768;
const int toplimit = 1000;
const int hwin = 10,disparity_begin=-15,disparity_range=37;
//variable
int winPixTotal = (hwin+1)*(hwin+1);
int *refer_img = new int[WH]; //存储参考图像
int *target_img = new int[WH]; //存储目标图像
int *refer_I = new int[disparity_range*WH]; //参考图像移位后的每个像素点对应矩形框内像素和
int *refer_MSI = new int[disparity_range*WH]; //参考图像移位后的每个像素点对应矩形框内像素和
int *refer_MSII = new int[disparity_range*WH]; //参考图像移位后的每个像素点对应矩形框内像素平方和
int *target_SI = new int[WH]; //目标图像的每个像素点对应矩形框内像素和
int *target_SII = new int[WH]; //目标图像的的每个像素点对应矩形框内像素平方和
int *DJ = new int[WH]; //参考图像的一阶积分图
int *DJJ = new int[WH]; //参考图像的二阶积分图
int *DIJ = new int[WH*disparity_range];
int *DT = new int[WH]; //目标图像的一阶积分图
int *DTT = new int[WH]; //
int *DM = new int[WH]; //目标图像的一阶积分图
int *DMM = new int[WH]; //目标图像的二阶积分图
int *SIJ = new int[disparity_range*WH]; //参考图像与目标图像的点乘的积分图
float *DI = new float[WH]; //视差深度
// Variables for GPU
float *costmatrix = new float[WH*disparity_range];//匹配代价
float *finalCost = new float[WH*disparity_range]; //匹配代价
String referImgName; //参考图像
String targetImgName;
String SaveImgName;
//指定原始数据的存储位置
referImgName = "TestData\\Reference\\reference.bmp";
targetImgName = "TestData\\Reference\\target\\";
SaveImgName = "TestData\\Reference\\result\\";
//参考图像数据读取
LoadImgFromFilePath(referImgName.c_str(),refer_img, rectLeftTopX,rectLeftTopY,rectWidth,rectHeight);
//像素值阈值截断
PreProcess_Truncation(refer_img,toplimit);
CalculateReferInteg(refer_img,DJ,DJJ,refer_I,refer_MSI,refer_MSII, hwin, disparity_begin, disparity_range);
AdaptiveFilter_refer(refer_img, refer_MSI,winPixTotal);
CalculateReferInteg(refer_img,DJ,DJJ,refer_I,refer_MSI,refer_MSII, hwin, disparity_begin, disparity_range);
IplImage* depthShow=cvCreateImage(cvSize(width,height),IPL_DEPTH_8U,1);
cvNamedWindow("depth",1);
//遍历dir文件夹下所有jpg图像，作为目标图像进行三维重建
_finddata_t fileDir;
char* dir="TestData\\Reference\\数据标定\\*.*";
long lfDir;
if((lfDir = _findfirst(dir,&fileDir))==-1l)
printf("No file is found\n");
else{
printf("file list:\n");
do{
printf("%s\n",fileDir.name);
String fn = dir;
fn.erase(fn.length()-3,fn.length());
fn = fn + fileDir.name;
if (fn.find(".bmp") != -1)
{
//从目标图像中取出数据
LoadImgFromFilePath(fn.c_str(),target_img,rectLeftTopX,rectLeftTopY,rectWidth,rectHeight);
clock_t start0, start; //声明两个时间点
//double time,time1,time2,time3,time4,time5,time6,timen; //定义运行时间
start0 = clock(); //获取开始时间
start = clock();
PreProcess_Truncation(target_img,toplimit);
CalculateTargetInteg(target_img,DT,DTT,target_SI,target_SII, hwin);
AdaptiveFilter_target(target_img, target_SI ,winPixTotal);
CalculateTargetInteg(target_img,DM,DMM,target_SI,target_SII, hwin);
printf( "TargetInteg待匹配图像积分图计算时间（CPU）为%.4f 秒\n",(double)(clock() - start) / CLOCKS_PER_SEC);//显示
start = clock(); //获取开始时间
CalculateReferTargetInteg(refer_I,target_img,DIJ,SIJ,hwin,disparity_range);
printf( "Refer*TargetInteg参考图像与目标图像乘积积分图计算时间（CPU）为%.4f 秒\n",(double)(clock() - start) / CLOCKS_PER_SEC);//显示
start = clock();
CalculateAllCostMatrix(refer_MSI,refer_MSII,target_SI,target_SII,SIJ,costmatrix,disparity_range,winPixTotal);
printf( "CalculateAllCostMatrixZNCC算子计算时间（CPU）为%.4f 秒\n",(double)(clock() - start) / CLOCKS_PER_SEC);//显示
start = clock();
blockWTA(costmatrix,finalCost,disparity_range);
printf("blockWTA ZNCC滤波计算时间（CPU）为%.4f 秒\n",(double)(clock() - start) / CLOCKS_PER_SEC);//显示
start = clock();
WTA(finalCost,DI, hwin, disparity_begin, disparity_range);
printf( "WTA 搜索最优ZNCC计算时间（CPU）为%.4f 秒\n",(double)(clock() - start) / CLOCKS_PER_SEC);//显示
start =clock();
TransDepthMap(DI,finalCost, disparity_begin, disparity_range);
printf( "TransDepthMap 三角变换+插值计算时间（CPU）为%.4f 秒\n",(double)(clock() - start) / CLOCKS_PER_SEC); //CLOCKS_PER_SEC，它用来表示一秒钟会有多少个时钟计时单元，进行计算，完成的时间减去开始的时间获得算法运行时间
printf( "Total CPU运行时间为%.4f 秒\n",(double)(clock() - start0) / CLOCKS_PER_SEC);//显示
//对深度图像Resize，从1004x748变成1024x768
ResizeDepthImage(DI);
//利用opencv存储和展示图片
for (int i=0;i<height;i++)
{
uchar *ptr = (uchar *) (depthShow->imageData + i * depthShow->widthStep);
float *ptr1 = (float *) (DI + i*width);
for (int j=0;j<width;j++)
{
ptr[j] = ptr1[width-1-j];
}
}
//解析存储文件名
fn.erase(fn.length()-4,fn.length());
SaveImgName = fn + "_result.jpg";
double blockDepthValue = 0;
for(int i = width/2-hwin;i<width/2+hwin;i++)
{
for(int j = height/2-hwin; j< height/2+hwin;j++)
{
blockDepthValue += DI[i*height + j];
}
}
blockDepthValue /= winPixTotal;
char blockDepthString[10];
sprintf(blockDepthString,"%f",blockDepthValue);
CvFont font;
double hScale=1;
double vScale=1;
int linewidth=2;// 相当于写字的线条
// 初始化字体
cvInitFont(&font,CV_FONT_HERSHEY_SIMPLEX|CV_FONT_ITALIC, hScale,vScale,0,linewidth);//初始化字体，准备写到图片上的
cvSaveImage(SaveImgName.c_str(),depthShow);
cvShowImage("depth",depthShow);
//cvWaitKey(-1);
//把更高精度的深度图存储到txt里面去
String SaveTxtName = fn + ".txt";
SaveDepthMapInTxt(DI,SaveTxtName.c_str());
}
}while( _findnext( lfDir, &fileDir ) == 0 );
}
_findclose(lfDir);
delete refer_img;
delete target_img;
delete refer_I;
delete refer_MSI ;
delete refer_MSII;
delete target_SI ;
delete target_SII ;
delete DJ ;
delete DJJ;
delete DIJ;
delete SIJ;
delete DT;
delete DTT;
delete DM;
delete DMM;
delete costmatrix ; //按层存储
delete finalCost;
delete DI ;
// Comment the following two lines to disable waiting on exit.
cerr << endl << "Press Enter to exit." << endl;
while( cin.get() != '\n');
return 0;
}
