Beispiel #1
0
//*****************************************************************************
//  METHOD: ossimRpcProjection::worldToLineSample()
//  
//  Overrides base class implementation. Directly computes line-sample from
//  the polynomials.
//*****************************************************************************
void ossimRpcProjection::worldToLineSample(const ossimGpt& ground_point,
                                      ossimDpt&       imgPt) const
{
   if (traceExec())  ossimNotify(ossimNotifyLevel_DEBUG) << "DEBUG ossimRpcProjection::worldToLineSample(): entering..." << std::endl;

   if(ground_point.isLatNan() ||
      ground_point.isLonNan() )
     {
       imgPt.makeNan();
       return;
     }
         
   //*
   // Normalize the lat, lon, hgt:
   //*
   double nlat = (ground_point.lat - theLatOffset) / theLatScale;
   double nlon = (ground_point.lon - theLonOffset) / theLonScale;
   double nhgt;

   if(ossim::isnan(ground_point.hgt))
   {
      nhgt = (theHgtScale - theHgtOffset) / theHgtScale;
   }
   else
   {
      nhgt = (ground_point.hgt - theHgtOffset) / theHgtScale;
   }

   
   //***
   // Compute the adjusted, normalized line (U) and sample (V):
   //***
   double Pu = polynomial(nlat, nlon, nhgt, theLineNumCoef);
   double Qu = polynomial(nlat, nlon, nhgt, theLineDenCoef);
   double Pv = polynomial(nlat, nlon, nhgt, theSampNumCoef);
   double Qv = polynomial(nlat, nlon, nhgt, theSampDenCoef);
   double U_rot  = Pu / Qu;
   double V_rot  = Pv / Qv;

   //***
   // U, V are normalized quantities. Need now to establish the image file
   // line and sample. First, back out the adjustable parameter effects
   // starting with rotation:
   //***
   double U = U_rot*theCosMapRot + V_rot*theSinMapRot;
   double V = V_rot*theCosMapRot - U_rot*theSinMapRot;

   //***
   // Now back out skew, scale, and offset adjustments:
   //***
   imgPt.line = U*(theLineScale+theIntrackScale) + theLineOffset + theIntrackOffset;
   imgPt.samp = V*(theSampScale+theCrtrackScale) + theSampOffset + theCrtrackOffset;


   if (traceExec())  ossimNotify(ossimNotifyLevel_DEBUG) << "DEBUG ossimRpcProjection::worldToLineSample(): returning..." << std::endl;

   return;
}
Beispiel #2
0
   void ossimTileMapModel::worldToLineSample(const ossimGpt& ground_point,
                                             ossimDpt&       img_pt) const
   {
      // if (traceExec())  ossimNotify(ossimNotifyLevel_DEBUG) << "DEBUG ossimTileMapModel::worldToLineSample(): entering..." << std::endl;

      if(ground_point.isLatNan() || ground_point.isLonNan() )
      {
         img_pt.makeNan();
         return;
      }

      double x = (180.0 + ground_point.lon) / 360.0;
      double y = - ground_point.lat * M_PI / 180; // convert to radians
      y = 0.5 * log((1+sin(y)) / (1 - sin(y)));
      y *= 1.0/(2 * M_PI); // scale factor from radians to normalized
      y += 0.5; // and make y range from 0 - 1

      img_pt.samp = floor(x*pow(2.,static_cast<double>(qDepth))*256);

      img_pt.line = floor(y*pow(2.,static_cast<double>(qDepth))*256);

      return;
   }
Beispiel #3
0
//*****************************************************************************
//  METHOD: ossimRpcModel::worldToLineSample()
//
//  Overrides base class implementation. Directly computes line-sample from
//  the polynomials.
//*****************************************************************************
void ossimRpcModel::worldToLineSample(const ossimGpt& ground_point,
                                      ossimDpt&       img_pt) const
{
    // if (traceExec())  ossimNotify(ossimNotifyLevel_DEBUG) << "DEBUG ossimRpcModel::worldToLineSample(): entering..." << std::endl;

    if(ground_point.isLatNan() || ground_point.isLonNan() )
    {
        img_pt.makeNan();
        return;
    }

    //***
    // First check if the world point is inside bounding rectangle:
    //***
    //ossimDpt wdp (ground_point);
    //if (!(theBoundGndPolygon.pointWithin(ground_point)))
    // {
    //img_pt = extrapolate(ground_point);
    //if (traceExec())  CLOG << "returning..." << endl;
    //   img_pt.makeNan();
    //    return;
    // }

    //***
    // Normalize the lat, lon, hgt:
    //***
    double nlat = (ground_point.lat - theLatOffset) / theLatScale;
    double nlon = (ground_point.lon - theLonOffset) / theLonScale;
    double nhgt;

    if( ground_point.isHgtNan() )
    {
        // nhgt = (theHgtScale - theHgtOffset) / theHgtScale;
        nhgt = ( - theHgtOffset) / theHgtScale;
    }
    else
    {
        nhgt = (ground_point.hgt - theHgtOffset) / theHgtScale;
    }

    //***
    // Compute the adjusted, normalized line (U) and sample (V):
    //***
    double Pu = polynomial(nlat, nlon, nhgt, theLineNumCoef);
    double Qu = polynomial(nlat, nlon, nhgt, theLineDenCoef);
    double Pv = polynomial(nlat, nlon, nhgt, theSampNumCoef);
    double Qv = polynomial(nlat, nlon, nhgt, theSampDenCoef);
    double U_rot  = Pu / Qu;
    double V_rot  = Pv / Qv;

    //***
    // U, V are normalized quantities. Need now to establish the image file
    // line and sample. First, back out the adjustable parameter effects
    // starting with rotation:
    //***
    double U = U_rot*theCosMapRot + V_rot*theSinMapRot;
    double V = V_rot*theCosMapRot - U_rot*theSinMapRot;

    //***
    // Now back out skew, scale, and offset adjustments:
    //***
    img_pt.line = U*(theLineScale+theIntrackScale) + theLineOffset + theIntrackOffset;

    img_pt.samp = V*(theSampScale+theCrtrackScale) + theSampOffset + theCrtrackOffset;

    // if (traceExec())  ossimNotify(ossimNotifyLevel_DEBUG) << "DEBUG ossimRpcModel::worldToLineSample(): returning..." << std::endl;
    return;
}
//---------------------------------------------------------------------------**
//  METHOD: ossimSensorModel::worldToLineSample()
//  
//  Performs forward projection of ground point to image space.
//  
//---------------------------------------------------------------------------**
void ossimH5GridModel::worldToLineSample(const ossimGpt& worldPoint,
                                         ossimDpt&       ip) const
{
   static const double PIXEL_THRESHOLD    = .1; // acceptable pixel error
   static const int    MAX_NUM_ITERATIONS = 20;

   if(worldPoint.isLatNan() || worldPoint.isLonNan())
   {
      ip.makeNan();
      return;
   }
      
   //---
   // First check if the world point is inside bounding rectangle:
   //---
   int iters = 0;
   ossimDpt wdp (worldPoint);
   if ( m_crossesDateline && (wdp.x < 0.0) )
   {
      // Longitude points stored between 0 and 360.
      wdp.x += 360.0;
   }
   
   if( (m_boundGndPolygon.getNumberOfVertices() > 0) &&
       (!m_boundGndPolygon.hasNans()) )
   {
      if (!(m_boundGndPolygon.pointWithin(wdp)))
      {
         // if(theSeedFunction.valid())
         // {
         //    theSeedFunction->worldToLineSample(worldPoint, ip);
         // }
         // else if(!theExtrapolateGroundFlag) // if I am not already in the extrapolation routine
         // {
         //    ip = extrapolate(worldPoint);
         // }
      ip.makeNan();
         return;
      } 

   }

   //---
   // Substitute zero for null elevation if present:
   //---
   double height = worldPoint.hgt;
   if ( ossim::isnan(height) )
   {
      height = 0.0;
   }

   //---
   // Utilize iterative scheme for arriving at image point. Begin with guess
   // at image center:
   //---
   if(theSeedFunction.valid())
   {
      theSeedFunction->worldToLineSample(worldPoint, ip);
   }
   else
   {
      ip.u = theRefImgPt.u;
      ip.v = theRefImgPt.v;
   }
   
   ossimDpt ip_du;
   ossimDpt ip_dv;

   ossimGpt gp, gp_du, gp_dv;
   double dlat_du, dlat_dv, dlon_du, dlon_dv;
   double delta_lat, delta_lon, delta_u, delta_v;
   double inverse_norm;
   bool done = false;
   //---
   // Begin iterations:
   //---
   do
   {
      //---
      // establish perturbed image points about the guessed point:
      //---
      ip_du.u = ip.u + 1.0;
      ip_du.v = ip.v;
      ip_dv.u = ip.u;
      ip_dv.v = ip.v + 1.0;
      
      //---
      // Compute numerical partials at current guessed point:
      //---
      lineSampleHeightToWorld(ip,    height, gp);
      lineSampleHeightToWorld(ip_du, height, gp_du);
      lineSampleHeightToWorld(ip_dv, height, gp_dv);
      
      if(gp.isLatNan() || gp.isLonNan())
      {
         gp = ossimCoarseGridModel::extrapolate(ip);
      }
      if(gp_du.isLatNan() || gp_du.isLonNan())
      {
         gp_du = ossimCoarseGridModel::extrapolate(ip_du);
      }
      if(gp_dv.isLatNan() || gp_dv.isLonNan())
      {
         gp_dv = ossimCoarseGridModel::extrapolate(ip_dv);
         
      }

      if ( m_crossesDateline )
      {
         // Longitude set to between 0 and 360.
         if ( gp.lon < 0.0 )    gp.lon    += 360.0;
         if ( gp_du.lon < 0.0 ) gp_du.lon += 360.0;
         if ( gp_dv.lon < 0.0 ) gp_dv.lon += 360.0;
      }
      
      dlat_du = gp_du.lat - gp.lat; //e
      dlon_du = gp_du.lon - gp.lon; //g
      dlat_dv = gp_dv.lat - gp.lat; //f
      dlon_dv = gp_dv.lon - gp.lon; //h
      
      //---
      // Test for convergence:
      // Use the wdp as it was corrected if there was a date line cross.
      //
      delta_lat = wdp.lat - gp.lat;
      delta_lon = wdp.lon - gp.lon;

      // Compute linearized estimate of image point given gp delta:
      inverse_norm = dlat_dv*dlon_du - dlat_du*dlon_dv; // fg-eh
      
      if (!ossim::almostEqual(inverse_norm, 0.0, DBL_EPSILON))
      {
         delta_u = (-dlon_dv*delta_lat + dlat_dv*delta_lon)/inverse_norm;
         delta_v = ( dlon_du*delta_lat - dlat_du*delta_lon)/inverse_norm;
         ip.u += delta_u;
         ip.v += delta_v;
      }
      else
      {
         delta_u = 0;
         delta_v = 0;
      }

#if 0
      cout << "gp:    " << gp
           << "\ngp_du: " << gp_du
           << "\ngp_dv: " << gp_dv
           << "\ndelta_lat: " << delta_lat
           << "\ndelta_lon: " << delta_lon     
           << "\ndelta_u: " << delta_u
           << "\ndelta_v: " << delta_v
           << endl;
#endif      
      
      done = ((fabs(delta_u) < PIXEL_THRESHOLD)&&
              (fabs(delta_v) < PIXEL_THRESHOLD));
      ++iters;

   } while ( (!done) && (iters < MAX_NUM_ITERATIONS));

   //---
   // Note that this error mesage appears only if max count was reached while
   // iterating. A linear (no iteration) solution would finish with iters =
   // MAX_NUM_ITERATIONS + 1:
   //---
#if 0 /* please leave for debug: */
   if (iters >= MAX_NUM_ITERATIONS)
   {
      std::cout << "MAX ITERATION!!!" << std::endl;
      std::cout << "delta_u = "   << delta_u
                << "\ndelta_v = " << delta_v << "\n";
   }
   else
   {
      std::cout << "ITERS === " << iters << std::endl;
   }
   std::cout << "iters = " << iters << "\n";
#endif   

   //---
   // The image point computed this way corresponds to full image space.
   // Apply image offset in the case this is a sub-image rectangle:
   //---
   ip -= theSubImageOffset;
   
} // End: worldToLineSample( ... )
void ossimEquDistCylProjection::worldToLineSample(const ossimGpt &worldPoint,
                                                  ossimDpt&       lineSample)const
{
   if(theModelTransformUnitType != OSSIM_UNIT_UNKNOWN)
   {
      ossimMapProjection::worldToLineSample(worldPoint, lineSample);
      
      return;
   }
   else
   {
      // make sure our tie point is good and world point
      // is good.
      //
      if(theUlEastingNorthing.isNan()||
         worldPoint.isLatNan() || worldPoint.isLonNan())
      {
         lineSample.makeNan();
         return;
      }
      // initialize line sample
      //   lineSample = ossimDpt(0,0);
      
      // I am commenting this code out because I am going to
      // move it to the ossimImageViewProjectionTransform.
      //
      // see if we have a datum set and if so
      // shift the world to our datum.  If not then
      // find the easting northing value for the world
      // point.
      if(theDatum)
      {
         ossimGpt gpt = worldPoint;
         
         gpt.changeDatum(theDatum);
         
         // lineSample is currently in easting northing
         // and will need to be converted to line sample.
         lineSample = forward(gpt);
      }
      else
      {
         // lineSample is currently in easting northing
         // and will need to be converted to line sample.
         lineSample = forward(worldPoint);
      }
      
      // check the final result to make sure there were no
      // problems.
      //
      if(!lineSample.isNan())
      {
         //       if(!isIdentityMatrix())
         //       {
         //          ossimDpt temp = lineSample;
         
         //          lineSample.x = theInverseTrans[0][0]*temp.x+
         //                         theInverseTrans[0][1]*temp.y+
         //                         theInverseTrans[0][2];
         
         //          lineSample.y = theInverseTrans[1][0]*temp.x+
         //                         theInverseTrans[1][1]*temp.y+
         //                         theInverseTrans[1][2];
         //       }
         //       else
         {
            lineSample.x = ((lineSample.x  - theUlEastingNorthing.x)/theMetersPerPixel.x);
            
            // We must remember that the Northing is negative since the positive
            // axis for an image is assumed to go down since it's image space.
            lineSample.y = (-(lineSample.y - theUlEastingNorthing.y)/theMetersPerPixel.y);
         }
      }
   }
}
void ossimEquDistCylProjection::lineSampleHeightToWorld(const ossimDpt &lineSample,
                                                        const double&  hgtEllipsoid,
                                                        ossimGpt&      gpt)const
{
   //
   // make sure that the passed in lineSample is good and
   // check to make sure our easting northing is good so
   // we can compute the line sample.
   //
   //
   if(lineSample.hasNans())
   {
      gpt.makeNan();
      return;
   }
   if(theModelTransformUnitType != OSSIM_UNIT_UNKNOWN)
   {
      ossimMapProjection::lineSampleHeightToWorld(lineSample, hgtEllipsoid, gpt);
      return;
   }
   else
   {
      if(theUlEastingNorthing.hasNans())
      {
         gpt.makeNan();
         return;
      }
      ossimDpt eastingNorthing;
      
      eastingNorthing = (theUlEastingNorthing);
      
      eastingNorthing.x += (lineSample.x*theMetersPerPixel.x);
      
      //
      // Note:  the Northing is positive up.  In image space
      // the positive axis is down so we must multiply by
      // -1
      //
      eastingNorthing.y += (-lineSample.y*theMetersPerPixel.y);
      
      //
      // now invert the meters into a ground point.
      //
      gpt = inverse(eastingNorthing);
      gpt.datum(theDatum);
      
      if(gpt.isLatNan() && gpt.isLonNan())
      {
         gpt.makeNan();
      }
      else
      {
         // Finally assign the specified height:
         gpt.hgt = hgtEllipsoid;
      }
   }
   if(theElevationLookupFlag)
   {
      gpt.hgt = ossimElevManager::instance()->getHeightAboveEllipsoid(gpt);
   }
}