void GaussianPyramid::ConstructPyramidLevels(const DImage &image, double ratio, int _nLevels)
{
// the ratio cannot be arbitrary numbers
if(ratio>0.98 || ratio<0.4)
ratio=0.75;
nLevels = _nLevels;
if(ImPyramid!=NULL)
delete []ImPyramid;
ImPyramid=new DImage[nLevels];
ImPyramid[0].copyData(image);
double baseSigma=(1/ratio-1);
int n=log(0.25)/log(ratio);
double nSigma=baseSigma*n;
for(int i=1;i<nLevels;i++)
{
DImage foo;
if(i<=n)
{
double sigma=baseSigma*i;
image.GaussianSmoothing(foo,sigma,sigma*3);
foo.imresize(ImPyramid[i],pow(ratio,i));
}
else
{
ImPyramid[i-n].GaussianSmoothing(foo,nSigma,nSigma*3);
double rate=(double)pow(ratio,i)*image.width()/foo.width();
foo.imresize(ImPyramid[i],rate);
}
}
}
//--------------------------------------------------------------------------------------
// function to perfomr coarse to fine optical flow estimation
//--------------------------------------------------------------------------------------
void OpticalFlow::Coarse2FineFlow(DImage &vx, DImage &vy, DImage &warpI2,const DImage &Im1, const DImage &Im2, double alpha, double ratio, int minWidth,
int nOuterFPIterations, int nInnerFPIterations, int nCGIterations)
{
// first build the pyramid of the two images
GaussianPyramid GPyramid1;
GaussianPyramid GPyramid2;
if(IsDisplay)
cout<<"Constructing pyramid...";
GPyramid1.ConstructPyramid(Im1,ratio,minWidth);
GPyramid2.ConstructPyramid(Im2,ratio,minWidth);
if(IsDisplay)
cout<<"done!"<<endl;
// now iterate from the top level to the bottom
DImage Image1,Image2,WarpImage2;
for(int k=GPyramid1.nlevels()-1; k>=0; k--)
{
if(IsDisplay)
cout<<"Pyramid level "<<k;
int width=GPyramid1.Image(k).width();
int height=GPyramid1.Image(k).height();
im2feature(Image1,GPyramid1.Image(k));
im2feature(Image2,GPyramid2.Image(k));
if(k==GPyramid1.nlevels()-1) // if at the top level
{
vx.allocate(width,height);
vy.allocate(width,height);
//warpI2.copyData(Image2);
WarpImage2.copyData(Image2);
}
else
{
vx.imresize(width,height);
vx.Multiplywith(1/ratio);
vy.imresize(width,height);
vy.Multiplywith(1/ratio);
//warpFL(warpI2,GPyramid1.Image(k),GPyramid2.Image(k),vx,vy);
warpFL(WarpImage2,Image1,Image2,vx,vy);
}
//SmoothFlowPDE(GPyramid1.Image(k),GPyramid2.Image(k),warpI2,vx,vy,alpha,nOuterFPIterations,nInnerFPIterations,nCGIterations);
//SmoothFlowPDE(Image1,Image2,WarpImage2,vx,vy,alpha*pow((1/ratio),k),nOuterFPIterations,nInnerFPIterations,nCGIterations);
SmoothFlowPDE(Image1,Image2,WarpImage2,vx,vy,alpha,nOuterFPIterations,nInnerFPIterations,nCGIterations);
if(IsDisplay)
cout<<endl;
}
warpFL(warpI2,Im1,Im2,vx,vy);
}
//--------------------------------------------------------------------------------------
// function to perfomr coarse to fine optical flow estimation
//--------------------------------------------------------------------------------------
void OpticalFlow::Coarse2FineFlow(DImage &vx, DImage &vy, DImage &warpI2,const DImage &Im1, const DImage &Im2, double alpha, double ratio, int minWidth,
int nOuterFPIterations, int nInnerFPIterations, int nCGIterations)
{
// first build the pyramid of the two images
GaussianPyramid GPyramid1;
GaussianPyramid GPyramid2;
if(IsDisplay)
cout<<"Constructing pyramid...";
GPyramid1.ConstructPyramid(Im1,ratio,minWidth);
GPyramid2.ConstructPyramid(Im2,ratio,minWidth);
if(IsDisplay)
cout<<"done!"<<endl;
// now iterate from the top level to the bottom
DImage Image1,Image2,WarpImage2;
// initialize noise
// cout << GPyramid1.nlevels() << " pyramid levels\n";
for(int k=GPyramid1.nlevels()-1;k>=0;k--)
{
if(IsDisplay)
cout<<"Pyramid level "<<k+1;
int width=GPyramid1.Image(k).width();
int height=GPyramid1.Image(k).height();
im2feature(Image1,GPyramid1.Image(k));
im2feature(Image2,GPyramid2.Image(k));
// cout << "\t- level " << k+1 << " size " << width <<"x" << height <<endl;
if(k==GPyramid1.nlevels()-1) // if at the top level
{
vx.allocate(width,height);
vy.allocate(width,height);
WarpImage2.copyData(Image2);
}
else
{
vx.imresize(width,height);
vx.Multiplywith(1/ratio);
vy.imresize(width,height);
vy.Multiplywith(1/ratio);
if(interpolation == Bilinear)
warpFL(WarpImage2,Image1,Image2,vx,vy);
else
Image2.warpImageBicubicRef(Image1,WarpImage2,vx,vy);
}
SmoothFlowSOR(Image1,Image2,WarpImage2,vx,vy,alpha,nOuterFPIterations+k,nInnerFPIterations,nCGIterations+k*3);
//GMPara.display();
if(IsDisplay)
cout<<endl;
}
//warpFL(warpI2,Im1,Im2,vx,vy);
Im2.warpImageBicubicRef(Im1,warpI2,vx,vy);
warpI2.threshold();
}
//------------------------------------------------------------------------------------------------
// multi-grid belie propagation
//------------------------------------------------------------------------------------------------
void BPFlow::generateCoarserLevel(BPFlow &bp)
{
//------------------------------------------------------------------------------------------------
// set the dimensions and parameters
//------------------------------------------------------------------------------------------------
bp.Width=Width/2;
if(Width%2==1)
bp.Width++;
bp.Height=Height/2;
if(Height%2==1)
bp.Height++;
bp.Area=bp.Width*bp.Height;
bp.s=s;
bp.d=d;
DImage foo;
Im_s.smoothing(foo);
foo.imresize(bp.Im_s,bp.Width,bp.Height);
Im_d.smoothing(foo);
foo.imresize(bp.Im_d,bp.Width,bp.Height);
bp.IsDisplay=IsDisplay;
bp.nNeighbors=nNeighbors;
//------------------------------------------------------------------------------------------------
// allocate buffers
//------------------------------------------------------------------------------------------------
for(int i=0;i<2;i++)
{
bp.pOffset[i]=new int[bp.Area];
bp.pWinSize[i]=new int[bp.Area];
ReduceImage(bp.pOffset[i],Width,Height,pOffset[i]);
ReduceImage(bp.pWinSize[i],Width,Height,pWinSize[i]);
for(int j = 0;j<bp.Area;j++)
bp.pWinSize[i][j] = __max(bp.pWinSize[i][j],1);
}
//------------------------------------------------------------------------------------------------
// generate data term
//------------------------------------------------------------------------------------------------
bp.nTotalMatches=bp.AllocateBuffer(bp.pDataTerm,bp.ptrDataTerm,bp.pWinSize[0],bp.pWinSize[1]);
for(int i=0;i<bp.Height;i++)
for(int j=0;j<bp.Width;j++)
{
int offset=i*bp.Width+j;
for(int ii=0;ii<2;ii++)
for(int jj=0;jj<2;jj++)
{
int y=i*2+ii;
int x=j*2+jj;
if(y<Height && x<Width)
{
int nStates=(bp.pWinSize[0][offset]*2+1)*(bp.pWinSize[1][offset]*2+1);
for(int k=0;k<nStates;k++)
bp.pDataTerm[offset].data()[k]+=pDataTerm[y*Width+x].data()[k];
}
}
}
//------------------------------------------------------------------------------------------------
// generate range term
//------------------------------------------------------------------------------------------------
bp.ComputeRangeTerm(gamma/2);
}
//--------------------------------------------------------------------------------------
// function to perfomr coarse to fine optical flow estimation
//--------------------------------------------------------------------------------------
void OpticalFlow::Coarse2FineFlow(DImage &vx, DImage &vy, DImage &warpI2,const DImage &Im1, const DImage &Im2, double alpha, double ratio, int minWidth,
int nOuterFPIterations, int nInnerFPIterations, int nCGIterations)
{
// first build the pyramid of the two images
GaussianPyramid GPyramid1;
GaussianPyramid GPyramid2;
if(IsDisplay)
cout<<"Constructing pyramid...";
GPyramid1.ConstructPyramid(Im1,ratio,minWidth);
GPyramid2.ConstructPyramid(Im2,ratio,minWidth);
if(IsDisplay)
cout<<"done!"<<endl;
// now iterate from the top level to the bottom
DImage Image1,Image2,WarpImage2;
//GaussianMixture GMPara(Im1.nchannels()+2);
// initialize noise
switch(noiseModel){
case GMixture:
GMPara.reset(Im1.nchannels()+2);
break;
case Lap:
LapPara.allocate(Im1.nchannels()+2);
for(int i = 0;i<LapPara.dim();i++)
LapPara[i] = 0.02;
break;
}
for(int k=GPyramid1.nlevels()-1;k>=0;k--)
{
if(IsDisplay)
cout<<"Pyramid level "<<k;
int width=GPyramid1.Image(k).width();
int height=GPyramid1.Image(k).height();
im2feature(Image1,GPyramid1.Image(k));
im2feature(Image2,GPyramid2.Image(k));
if(k==GPyramid1.nlevels()-1) // if at the top level
{
vx.allocate(width,height);
vy.allocate(width,height);
//warpI2.copyData(Image2);
WarpImage2.copyData(Image2);
}
else
{
vx.imresize(width,height);
vx.Multiplywith(1/ratio);
vy.imresize(width,height);
vy.Multiplywith(1/ratio);
//warpFL(warpI2,GPyramid1.Image(k),GPyramid2.Image(k),vx,vy);
if(interpolation == Bilinear)
warpFL(WarpImage2,Image1,Image2,vx,vy);
else
Image2.warpImageBicubicRef(Image1,WarpImage2,vx,vy);
}
//SmoothFlowPDE(GPyramid1.Image(k),GPyramid2.Image(k),warpI2,vx,vy,alpha,nOuterFPIterations,nInnerFPIterations,nCGIterations);
//SmoothFlowPDE(Image1,Image2,WarpImage2,vx,vy,alpha*pow((1/ratio),k),nOuterFPIterations,nInnerFPIterations,nCGIterations,GMPara);
//SmoothFlowPDE(Image1,Image2,WarpImage2,vx,vy,alpha,nOuterFPIterations,nInnerFPIterations,nCGIterations);
SmoothFlowSOR(Image1,Image2,WarpImage2,vx,vy,alpha,nOuterFPIterations+k,nInnerFPIterations,nCGIterations+k*3);
//GMPara.display();
if(IsDisplay)
cout<<endl;
}
//warpFL(warpI2,Im1,Im2,vx,vy);
Im2.warpImageBicubicRef(Im1,warpI2,vx,vy);
warpI2.threshold();
}