ImageFeature fft(const ImageFeature &img) {
ImageFeature result(img.xsize(),img.ysize(),2);
#ifdef HAVE_FFT_LIBRARY
fftw_complex FIMG[img.xsize()][img.ysize()];
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
FIMG[x][y].re=img(x,y,0);
FIMG[x][y].im=0;
}
}
fftwnd_plan plan = fftw2d_create_plan(img.xsize(),img.ysize(), FFTW_FORWARD, FFTW_ESTIMATE | FFTW_IN_PLACE);
fftwnd_one(plan,&FIMG[0][0],NULL);
fftwnd_destroy_plan(plan);
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
result(x,y,0)=FIMG[x][y].re;
result(x,y,1)=FIMG[x][y].im;
}
}
#else
#warning "FFT is used without FFT library enabled."
ERR << "FFT not available, thus returning empty image instead of fourier transformed version. All that comes now is probably bogus." << endl;
#endif
return result;
}
void convolve(ImageFeature &img, const ImageFeature &filter) {
ImageFeature copy=img;
int height2=filter.ysize()/2;
int width2=filter.xsize()/2;
double tmp;
for(uint c=0;c<img.zsize();++c) {
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
tmp=0.0;
for(int i=-width2;i<=width2;++i) {
int xx=x+i;
if(xx<int(img.xsize()) && int(xx) >= 0) {
for(int j=-height2;j<=height2;++j) {
int yy=y+j;
if(int(yy)>=0 && yy < int(img.ysize())) {
tmp+=filter(i+width2,j+height2,0)*copy(xx,yy,c);
}
}
}
}
img(x,y,c)=tmp;
}
}
}
}
void histogramNormalization(ImageFeature &img) {
const uint bins=256;
vector<int> H(bins);
vector<double> T(bins);
for(uint c=0;c<img.zsize();++c) {
//DBG(10) << "c=" << c << endl;
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
++H[int(img(x,y,c)*255)];
}
}
for(uint p=1;p<bins;++p) {
H[p]+=H[p-1];
}
for(uint p=0;p<bins;++p) {
T[p]=(1.0/double(img.size()))*double(H[p]);
}
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
img(x,y,c)=T[int(img(x,y,c)*255)];
}
}
}
}
// default for type is set in imagelib.hpp
// type = 0: maximum (as in HSV)
// type = 1: mean
// type = 2: luminance (use only for RGB images!)
ImageFeature makeGray(const ImageFeature &img, const uint type) {
ImageFeature result(img.xsize(), img.ysize(),1) ;
double value;
if( (type == 2) && (img.zsize() != 3) )
{
ERR << "Image has invalid color resolution!" << endl;
return result;
}
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
value=0.0;
switch(type){
case 0: //max
for(uint c=0;c<img.zsize();++c) {
value=::std::max(value,img(x,y,c));
}
break;
case 1: //mean
for(uint c=0;c<img.zsize();++c) {
value+=img(x,y,c);
}
value/=img.zsize();
break;
case 2: // luminance
value = 0.3 * img(x,y,0) + 0.59 * img(x,y,1) + 0.11 * img(x,y,2);
break;
}
result(x,y,0)=value;
}
}
return result;
}
ImageFeature DifferenceOfGaussian::difference(const ImageFeature& img1, const ImageFeature& img2) {
ImageFeature newImage = ImageFeature(img1.xsize(), img1.ysize(), 1);
for (int x = 0; x < (int) newImage.xsize(); x++) {
for (int y = 0; y < (int) newImage.ysize(); y++) {
newImage(x, y, 0) = img1(x, y, 0) - img2(x, y, 0);
}
}
return newImage;
}
ImageFeature localvariance(const ImageFeature &image, const uint winsize) {
ImageFeature result(image.xsize(),image.ysize(),1);
for(uint x=winsize;x<image.xsize()-winsize;++x) {
for(uint y=winsize;y<image.ysize()-winsize;++y) {
result(x,y,0)=localvariance(image, winsize, x,y);
}
}
return result;
}
void setPatch(ImageFeature& image, const uint xpos, const uint ypos, const ImageFeature &patch) {
DBG(50) << "set image patch from (" << xpos << "," << ypos << ") to (" << xpos+patch.xsize() << "," << ypos+patch.ysize() << ") " << endl;
for(uint x=0;x<patch.xsize();++x) {
for(uint y=0;y<patch.ysize();++y) {
for(uint z=0;z<patch.zsize();++z) {
if(x+xpos<image.xsize() && y+ypos<image.ysize()) {
image(x+xpos,y+ypos,z)=patch(x,y,z);
}
}
}
}
}
void multiply(ImageFeature &img1, const ImageFeature& img2) {
if ((img1.xsize() != img2.xsize()) ||
(img1.ysize() != img2.ysize()) ||
(img1.zsize() != img2.zsize())) {
DBG(10) << "image features have different sizes, cannot be multiplied.";
}
for (uint z = 0; z < img1.zsize(); z++)
for (uint x = 0; x < img1.xsize(); x++)
for (uint y = 0; y < img1.ysize(); y++) {
img1(x, y, z) = img1(x, y, z) * img2(x, y, z);
}
}
ImageFeature rotate90(const ImageFeature &img) {
uint X=img.xsize();
ImageFeature result(img.ysize(),img.xsize(),img.zsize());
for(uint x=0;x<img.ysize();++x) {
for(uint y=0;y<img.xsize();++y) {
for(uint z=0;z<img.zsize();++z) {
result(x,y,z)=img(y,X-x-1,z);
}
}
}
return result;
}
ImageFeature zeropad(const ImageFeature& image, uint xpad, uint ypad) {
ImageFeature result(image.xsize()+2*xpad, image.ysize()+2*ypad, image.zsize());
for(uint x=xpad;x<image.xsize()+xpad;++x) {
for(uint y=ypad;y<image.ysize()+ypad;++y) {
for(uint c=0;c<image.zsize();++c) {
result(x,y,c)=image(x-xpad,y-ypad,c);
}
}
}
return result;
}
ImageFeature flip(const ImageFeature &img) {
ImageFeature result(img.xsize(),img.ysize(),img.zsize());
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
for(uint z=0;z<img.zsize();++z) {
result(img.xsize()-x-1,y,z)=img(x,y,z);
}
}
}
return result;
}
ImageFeature localEntropy(const ImageFeature &image, const uint winsize) {
ImageFeature result(image.xsize(), image.ysize(), image.zsize());
for(uint x=0;x<image.xsize();++x) {
for(uint y=0;y<image.ysize();++y) {
for(uint z=0; z<image.zsize();++z) {
result(x,y,z)=localEntropy(image, x,y,z,winsize);
}
}
}
return result;
}
void meanandvariance(const ImageFeature &img, double &mean, double &variance, const uint layer) {
mean=0.0; variance=0.0;
for(uint y=0;y<img.ysize();++y) {
for(uint x=0;x<img.xsize();++x) {
mean+=img(x,y,layer);
variance+=img(x,y,layer)*img(x,y,layer);
}
}
uint size=img.xsize()*img.ysize();
mean/=double(size);
variance/=double(size);
variance-=mean*mean;
}
ImageFeature threshold(const ImageFeature &image, const double threshold) {
ImageFeature result(image.xsize(), image.ysize(), image.zsize());
for(uint x=0;x<image.xsize();++x) {
for(uint y=0;y<image.ysize();++y) {
for(uint z=0;z<image.zsize();++z) {
if(image(x,y,z)>=threshold) {
result(x,y,z)=1.0;
} else {
result(x,y,z)=0.0;
}
}
}
}
return result;
}
InterpolatingImage::InterpolatingImage(const ImageFeature& image, uint splinedegree) : sourceImage_(image), splinedegree_(splinedegree) {
#ifdef HAVE_INTERPOL_LIBRARY
coeff_=new float*[image.zsize()];
for(uint i=0; i<image.zsize(); ++i) {
coeff_[i]=new float[image.xsize()*image.ysize()];
for(uint x=0; x<image.xsize(); ++x) {
for(uint y=0; y<image.ysize(); ++y) {
coeff_[i][y*image.xsize()+x]=float(image(x,y,i));
}
}
SamplesToCoefficients(coeff_[i],image.xsize(),image.ysize(),splinedegree);
}
#endif
}
double efficientLocalMean(const int x,const int y,const int k,const ImageFeature &laufendeSumme) {
int k2=k/2;
int dimx=laufendeSumme.xsize();
int dimy=laufendeSumme.ysize();
//wanting average over area: (y-k2,x-k2) ... (y+k2-1, x+k2-1)
int starty=y-k2;
int startx=x-k2;
int stopy=y+k2-1;
int stopx=x+k2-1;
if(starty<0) starty=0;
if(startx<0) startx=0;
if(stopx>dimx-1) stopx=dimx-1;
if(stopy>dimy-1) stopy=dimy-1;
double unten, links, oben, obenlinks;
if(startx-1<0) links=0;
else links=laufendeSumme(startx-1,stopy,0);
if(starty-1<0) oben=0;
else oben=laufendeSumme(stopx,starty-1,0);
if((starty-1 < 0) || (startx-1 <0)) obenlinks=0;
else obenlinks=laufendeSumme(startx-1,starty-1,0);
unten=laufendeSumme(stopx,stopy,0);
// cout << "obenlinks=" << obenlinks << " oben=" << oben << " links=" << links << " unten=" <<unten << endl;
int counter=(stopy-starty+1)*(stopx-startx+1);
return (unten-links-oben+obenlinks)/counter;
}
//default values for fact_eq and offset are set in imagelib.hpp.... by paredes
void equalize(ImageFeature &image, uint wndsize, double bnd, uint c, double fact_eq, uint offset) {
double fact_orig=1.0-fact_eq;
int xdim=image.xsize();
int ydim=image.ysize();
int i,j,xini,xend,yini,yend;
ImageFeature acu(xdim,ydim,1);
ImageFeature divisor(xdim,ydim,1);
for(i=0; i < int(ydim-wndsize); i+=offset) {
yini = i;
yend = i+wndsize;
for(j=0; j < int(xdim-wndsize); j+=offset) {
xini = j;
xend = j+wndsize;
eq_histo(xini,xend,yini,yend,image,c,acu,divisor);
}
}
for(j=0; j < ydim; j++) {
for(i=0; i < xdim; i++) {
if ( (image(i,j,c) > bnd) && (divisor(i,j,0) > 0.0) ) {
image(i,j,c)=fact_eq*(acu(i,j,0)/divisor(i,j,0)) + fact_orig*image(i,j,c); // weighted average between original and equalized image
}
}
}
}
void add(ImageFeature &a, const ImageFeature &b, const uint z) {
for(uint x=0;x<a.xsize();++x) {
for(uint y=0;y<a.ysize();++y) {
a(x,y,z)+=b(x,y,0);
}
}
}
void LocalFeatureExtractor::extractPatches(ImageFeature &img, const ::std::vector<FeatureExtractionPosition> &positions, LocalFeatures &lf) {
if(settings_.padding>0) {
img=zeropad(img,settings_.padding, settings_.padding);
}
lf.winsize_=settings_.winsize;
lf.padding_=settings_.padding;
lf.numberOfFeatures_=positions.size();
lf.zsize_=img.zsize();
int windiameter=2*settings_.winsize+1;
lf.dim_=windiameter*windiameter*img.zsize();
lf.imageSizeX_=img.xsize();
lf.imageSizeY_=img.ysize();
lf.filename_=img.filename();
int savesize=settings_.winsize*2+1;
lf.positions_=positions;
lf.data_.resize(positions.size());
for(uint i=0;i<positions.size();++i) {
const FeatureExtractionPosition &pos=positions[i];
ImageFeature p=getPatch(img,pos.x,pos.y,pos.s);
if(uint(pos.s)!=settings_.winsize) {
p=scale(p,savesize,savesize);
}
lf.data_[i]=toVector(p);
}
}
void shift(ImageFeature &img, const double offset) {
for(uint c=0;c<img.zsize();++c) {
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
img(x,y,c)+=offset;
}}}
}
void ImageFeature::append(const ImageFeature& img) {
if(img.xsize()==xsize_ && img.ysize() == ysize_) {
uint oldsize=data_.size();
data_.resize(data_.size()+img.zsize(),vector<double>(xsize()*ysize()));
for(uint c=0;c<img.zsize();++c) {
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
(*this)(x,y,oldsize+c)=img(x,y,c);
}
}
}
zsize_=data_.size();
} else {
ERR << "Images not compatible for appending" << endl;
}
}
void iDCT(ImageFeature &src, ImageFeature &dest) {
dest.resize(src.xsize(),src.ysize(),src.zsize()); //NB Not efficient
for(uint c=0;c<src.zsize();++c) {
uint i,j,k;
double sum;
// Transform in x direction
ImageFeature horizontal(src.xsize(), src.ysize(),1);
for (j = 0; j < src.ysize(); j++) {
for (i = 0; i < src.xsize(); i++) {
sum = 0.0;
for (k = 0; k < src.xsize(); k++) {
sum += alpha(k,src.xsize())*src(k,j,0)* cos(double(2*i+1)*M_PI*double(k)/(double(2*src.xsize())));
}
horizontal(i,j,0) = sum;
}
}
// Transform in y direction
for (i = 0; i < src.xsize(); i++) {
for (j = 0; j < src.ysize(); j++) {
sum = 0.0;
for (k = 0; k < src.ysize(); k++) {
sum += alpha(k, src.xsize())*horizontal(i,k,0)* cos(double(2*j+1)*M_PI*double(k)/(double(2*src.ysize())));
}
dest(i,j,c) = sum;
}
}
}
}
double maximum(const ImageFeature &img, uint c) {
double max=-1.0;
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
max=::std::max(max,img(x,y,c));
}
}
return max;
}
void multiply(ImageFeature &img, const double s) {
for(uint z=0;z<img.zsize();++z) {
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
img(x,y,z)*=s;
}
}
}
}
void absolute(ImageFeature &img1) {
for (uint z = 0; z < img1.zsize(); z++)
for (uint x = 0; x < img1.xsize(); x++)
for (uint y = 0; y < img1.ysize(); y++) {
if (img1(x, y, z) < 0.0) {
img1(x, y, z) = -img1(x, y, z);
}
}
}
void gammaCorrection(ImageFeature &img, double gamma) {
for(uint c=0;c<img.zsize();++c) {
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
img(x,y,c)=exp(gamma*log(img(x,y,c)));
}
}
}
}
double minimum(const ImageFeature &img, uint c) {
double min=numeric_limits<double>::max();
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
min=::std::min(min,img(x,y,c));
}
}
return min;
}
void divide(ImageFeature &a, const double &d) {
for(uint x=0;x<a.xsize();++x) {
for(uint y=0;y<a.ysize();++y) {
for(uint z=0;z<a.zsize();++z) {
a(x,y,z)/=d;
}
}
}
}
void appendHorizontally(ImageFeature &imga, const ImageFeature &imgb) {
if(imga.ysize()!=imgb.ysize() || imga.zsize() != imgb.zsize()) {
ERR << "Images have to have same width and depth" << endl;
} else {
ImageFeature tmp(imga);
imga.resize(imga.xsize()+imgb.xsize(),imga.ysize(),imga.zsize());
for(uint y=0;y<tmp.ysize();++y) {
for(uint z=0;z<tmp.zsize();++z) {
for(uint x=0;x<tmp.xsize();++x) {
imga(x,y,z)=tmp(x,y,z);
}
for(uint x=tmp.xsize();x<tmp.xsize()+imgb.xsize();++x) {
imga(x,y,z)=imgb(x-tmp.xsize(),y,z);
}
}
}
}
}
void contrast(ImageFeature &img,const double min, const double max) {
double m=max-min;
for(uint x=0;x<img.xsize();++x) {
for(uint y=0;y<img.ysize();++y) {
for(uint z=0;z<img.zsize();++z) {
img(x,y,z)=img(x,y,z)*m+min;
}
}
}
}
