예제 #1
0
NEWMAT::ColumnVector
ossimRpcProjection::getResidue(const ossimTieGptSet& tieSet)
{
   //init
   NEWMAT::ColumnVector residue;
   int dimObs;

   bool useImageObs = useForward(); //caching
   if (useImageObs)
   {
      dimObs = 2; //image observation
   } else {
      dimObs = 3; //ground observations
   }
   int no = dimObs * tieSet.size(); //number of observations

   residue.ReSize(no);

   const vector<ossimRefPtr<ossimTieGpt> >& theTPV = tieSet.getTiePoints();
   vector<ossimRefPtr<ossimTieGpt> >::const_iterator tit;
   unsigned long c=1;

   if (useImageObs)
   { 
     //image observations 
     ossimDpt resIm;
     // loop on tie points
      for (tit = theTPV.begin() ; tit != theTPV.end() ; ++tit)
      {
         //compute residue
         resIm = (*tit)->tie - forward(**tit);
         residue(c++) = resIm.x;
         residue(c++) = resIm.y;
      }
   } else {
      // ground observations
      ossimGpt gd;
      // loop on tie points
      for (tit = theTPV.begin() ; tit != theTPV.end() ; ++tit)
      {
         //compute residue
         gd = inverse((*tit)->tie);
         residue(c++) = ((*tit)->lon - gd.lon) * 100000.0; //approx meters //TBC TBD
         residue(c++) = ((*tit)->lat - gd.lat) * 100000.0 * cos(gd.lat / 180.0 * M_PI);
         residue(c++) = (*tit)->hgt - gd.hgt; //meters
      }
   } //end of if (useImageObs)

   return residue;
}
예제 #2
0
void
ossimRpcProjection::buildNormalEquation(const ossimTieGptSet& tieSet,
                                      NEWMAT::SymmetricMatrix& A,
                                      NEWMAT::ColumnVector& residue,
                                      NEWMAT::ColumnVector& projResidue,
                                      double pstep_scale)
{
   //goal:       build Least Squares system
   //constraint: never store full Jacobian matrix in memory (can be huge)
   //            so we build the matrices incrementally
   // the system can be built using forward() or inverse() depending on the projection capabilities : useForward()
   //
   //TBD : add covariance matrix for each tie point

   //init
   int np = getNumberOfAdjustableParameters();
   int dimObs;
   bool useImageObs = useForward(); //caching
   if (useImageObs)
   {
      dimObs = 2; //image observation
   } else {
      dimObs = 3; //ground observations
   }
   int no = dimObs * tieSet.size(); //number of observations

   A.ReSize(np);
   residue.ReSize(no);
   projResidue.ReSize(np);
   //Zeroify matrices that will be accumulated
   A           = 0.0;
   projResidue = 0.0;

   const vector<ossimRefPtr<ossimTieGpt> >& theTPV = tieSet.getTiePoints();
   vector<ossimRefPtr<ossimTieGpt> >::const_iterator tit;
   unsigned long c=1;

   if (useImageObs)
   { 
     //image observations 
     ossimDpt* imDerp = new ossimDpt[np];
     ossimDpt resIm;
     // loop on tie points
      for (tit = theTPV.begin() ; tit != theTPV.end() ; ++tit)
      {
         //compute residue
         resIm = (*tit)->tie - forward(*(*tit));
         residue(c++) = resIm.x;
         residue(c++) = resIm.y;

         //compute all image derivatives regarding parametres for the tie point position
         for(int p=0;p<np;++p)
         {
            imDerp[p] = getForwardDeriv( p , *(*tit) , pstep_scale);
         }

         //compute influence of tie point on all sytem elements
         for(int p1=0;p1<np;++p1)
         {        
            //proj residue: J * residue
            projResidue.element(p1) += imDerp[p1].x * resIm.x + imDerp[p1].y * resIm.y;

            //normal matrix A = transpose(J)*J
            for(int p2=p1;p2<np;++p2)
            {
               A.element(p1,p2) += imDerp[p1].x * imDerp[p2].x + imDerp[p1].y * imDerp[p2].y;
            }
         }
      }
      delete []imDerp;
   }
   else
   {
      // ground observations
      std::vector<ossimGpt> gdDerp(np);
      ossimGpt gd, resGd;
      // loop on tie points
      for (tit = theTPV.begin() ; tit != theTPV.end() ; ++tit)
      {
         //compute residue
         gd = inverse((*tit)->tie);
         residue(c++) = resGd.lon = ((*tit)->lon - gd.lon) * 100000.0;
         residue(c++) = resGd.lat = ((*tit)->lat - gd.lat) * 100000.0 * cos(gd.lat / 180.0 * M_PI);
         residue(c++) = resGd.hgt = (*tit)->hgt - gd.hgt; //TBD : normalize to meters?

         //compute all image derivatives regarding parametres for the tie point position
         for(int p=0;p<np;++p)
         {
            gdDerp[p] = getInverseDeriv( p , (*tit)->tie, pstep_scale);
         }

         //compute influence of tie point on all sytem elements
         for(int p1=0;p1<np;++p1)
         {        
            //proj residue: J * residue
            projResidue.element(p1) += gdDerp[p1].lon * resGd.lon + gdDerp[p1].lat * resGd.lat + gdDerp[p1].hgt * resGd.hgt; //TBC

            //normal matrix A = transpose(J)*J
            for(int p2=p1;p2<np;++p2)
            {
               A.element(p1,p2) += gdDerp[p1].lon * gdDerp[p2].lon + gdDerp[p1].lat * gdDerp[p2].lat + gdDerp[p1].hgt * gdDerp[p2].hgt;
            }
         }
      }
   } //end of if (useImageObs)
}