void BasicSonar::createAccumulatedShadowAndNoise(int horizontal_scans, int vertical_scans, int pixels_per_line,
std::vector<double> noise_percentage, std::vector<double>* result)
{
for (int i=0; i < horizontal_scans; i++)
{
int accumulated_num_of_rays = 0;
for (int j=0; j < pixels_per_line; j++)
{
if (noise_percentage.at(i*pixels_per_line + j) > 0)
{
accumulated_num_of_rays += noise_percentage.at(i*pixels_per_line + j);
result->at(i*pixels_per_line + j) += gaussianNoise(0,gaussian_kernel);
}
else if (result->at(i*pixels_per_line + j) == 0)
{
result->at(i*pixels_per_line + j) = ( 1 - (accumulated_num_of_rays/ (double) vertical_scans)) * base_water_noise + gaussianNoise(0,gaussian_kernel);
}
else
{
result->at(i*pixels_per_line + j) += gaussianNoise(0,gaussian_kernel);
}
}
}
}
void convertImages(Arguments* args){
char** mask = NULL;
TwoPoints source, dest;
FILE* eyeList;
char line[ FILE_LINE_LENGTH ];
char filename[MAX_FILENAME_LENGTH];
char imagename[MAX_FILENAME_LENGTH];
char suffix[MAX_FILENAME_LENGTH];
int i;
scaleArgs(args, args->scale);
dest.x1 = args->eyeLx;
dest.y1 = args->eyeLy;
dest.x2 = args->eyeRx;
dest.y2 = args->eyeRy;
/* Prepare file suffix encoding preprocessing settings, blank if not requested */
if (args->configSuffix) {
sprintf(suffix,"_%s", imageSuffix(args)); }
else {
suffix[0] = '\0'; }
if(args->maskType == CL_YES){
MESSAGE("Creating Mask.");
mask = generateMask(args->sizeWidth, args->sizeHeight, args->ellipseX, args->ellipseY, args->ellipseA, args->ellipseB);
}
eyeList = fopen(args->eyeFile,"r");
DEBUG_CHECK(eyeList,"Error opening eye coordinates file");
for(i = 1;;i++){
Image pgm;
Image geo;
Matrix transform;
fgets(line, FILE_LINE_LENGTH, eyeList);
if(feof(eyeList)) break;
if(sscanf(line,"%s %lf %lf %lf %lf",filename, &(source.x1), &(source.y1), &(source.x2), &(source.y2)) != 5){
printf("Error parsing line %d of eye coordinate file. Exiting...",i);
exit(1);
}
/* shift the eye coordinates if neccessary */
source.x1 += args->shiftX;
source.y1 += args->shiftY;
source.x2 += args->shiftX;
source.y2 += args->shiftY;
sprintf(imagename,"%s\\%s.pgm",args->inputDir,filename);
MESSAGE1ARG("Processing image: %s",filename);
pgm = readPGMImage(imagename);
if(args->histType == HIST_PRE){
DEBUG(1," Performing Pre Histogram Equalization.");
histEqual(pgm,256);
}
if(args->preNormType == CL_YES){
DEBUG(1," Performing Pre Pixel Normalization.");
ZeroMeanOneStdDev(pgm);
}
if(args->preEdge){
smoothImageEdge(pgm, args->preEdge);
}
if(args->geoType == CL_YES){
DEBUG(1," Performing Geometric Normalization.");
transform = generateTransform(&source,&dest,args->reflect);
geo = transformImage(pgm,args->sizeWidth,args->sizeHeight,transform);
}
else{
transform = makeIdentityMatrix(3);
geo = transformImage(pgm,args->sizeWidth,args->sizeHeight,transform);
}
if(args->noise != 0.0){
DEBUG(1," Adding Gausian Noise.");
gaussianNoise(geo,args->noise);
}
if(args->histType == HIST_POST){
DEBUG(1," Performing Post Histogram Equalization.");
histEqualMask(geo,256, (const char**) mask);
}
if(args->nrmType == CL_YES){
DEBUG(1," Performing final value normalization and Applying Mask.");
ZeroMeanOneStdDevMasked(geo, (const char **) mask);
}
else{
DEBUG(1," No Value Normalization. Just Applying Mask.");
applyMask(geo, (const char **) mask);
}
if(args->postEdge){
smoothImageEdge(geo, args->postEdge);
}
if(args->nrmDir){
sprintf(imagename,"%s\\%s%s.nrm", args->nrmDir, filename, suffix);
DEBUG_STRING(1," Saving nrm: %s",imagename);
writeFeretImage(geo,imagename);
}
if(args->pgmDir){
sprintf(imagename,"%s\\%s%s.pgm", args->pgmDir, filename, suffix);
DEBUG_STRING(1," Saving pgm: %s",imagename);
writePGMImage(geo,imagename,0);
}
if(args->sfiDir){
sprintf(imagename,"%s\\%s%s.sfi", args->sfiDir, filename, suffix);
DEBUG_STRING(1," Saving sfi: %s",imagename);
writeRawImage(geo,imagename);
}
freeImage(geo);
freeImage(pgm);
freeMatrix(transform);
}
fclose(eyeList);
}
int main(void)
{
// 讀圖
cv::Mat mImg = cv::imread("lena.bmp", cv::IMREAD_GRAYSCALE);
// 防止找不到圖
if (mImg.empty())
{
std::cout << "Not Found!" << std::endl;
exit(EXIT_FAILURE);
}
// 宣告空間
cv::Mat oriImg = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat gauImg = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat Gaussian = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat GaussianNoise = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat SP = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat SPNoise = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat Uniform = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat UniformNoise = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat AFilter = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat Adaptive = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat SAdaptive = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat UAdaptive = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
cv::Mat Gdaptive = cv::Mat::zeros(mImg.rows, mImg.cols, CV_8UC1);
int histogram[256] = { 0 };
int hisGaussian[256] = { 0 };
int hisSP[256] = { 0 };
int hisUniform[256] = { 0 };
int hisA[256] = { 0 };
int hisB[256] = { 0 };
int hisC[256] = { 0 };
char windowname[] = { 0 };
// gaussianNoise(oriImg, gauImg, amp);
// gaussianNoise(mImg, GaussianNoise);
spNoise(mImg, SPNoise, hisSP);
uniformNoise(mImg, UniformNoise, hisUniform);
gaussianNoise(mImg, GaussianNoise, hisGaussian);
//AdaptivefFilter(mImg, Adaptive, hisA);
AdaptivefFilter(SPNoise, SAdaptive, hisB);
AdaptivefFilter(UniformNoise, UAdaptive, hisC);
AdaptivefFilter(GaussianNoise, Gdaptive, hisA);
// 叫圖
histDisplay(hisUniform, "hisUniform");
histDisplay(hisSP, "hisSP");
histDisplay(hisGaussian, "hisGaussian");
//histDisplay(histogram, "histogram");
histDisplay(hisA, "hisA");
cv::namedWindow("LenaOutputOne", cv::WINDOW_AUTOSIZE);
cv::imshow("LenaOutputOne", mImg);
cv::namedWindow("GaussianOut", cv::WINDOW_AUTOSIZE);
cv::imshow("GaussianOut", GaussianNoise);
cv::namedWindow("SPOut", cv::WINDOW_AUTOSIZE);
cv::imshow("SPOut", SPNoise);
cv::namedWindow("UniformOut", cv::WINDOW_AUTOSIZE);
cv::imshow("UniformOut", UniformNoise);
cv::namedWindow("UniformOut", cv::WINDOW_AUTOSIZE);
cv::imshow("UniformOut", UniformNoise);
cv::namedWindow("SAdaptiveOut", cv::WINDOW_AUTOSIZE);
cv::imshow("SAdaptiveOut", SAdaptive);
cv::namedWindow("UAdaptiveOut", cv::WINDOW_AUTOSIZE);
cv::imshow("UAdaptiveOut", UAdaptive);
cv::namedWindow("GAdaptiveOut", cv::WINDOW_AUTOSIZE);
cv::imshow("GAdaptiveOut", Gdaptive);
cv::waitKey(0);
return 0;
}