NNLSImageSkyModel.h

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//# NNLSImageSkyModel.h: Definition for NNLSImageSkyModel
//# Copyright (C) 1996,1997,1998,2000
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//# $Id$

#ifndef SYNTHESIS_NNLSIMAGESKYMODEL_H
#define SYNTHESIS_NNLSIMAGESKYMODEL_H

#include <synthesis/MeasurementComponents/CleanImageSkyModel.h>
namespace casa { //# NAMESPACE CASA - BEGIN

//forward
class SkyEquation;

// <summary> Briggs' Non-Negative Least Squares deconvolution algorithm </summary>

// <use visibility=export>

// <reviewed reviewer="" date="" tests="" demos="">

// <prerequisite>
//   <li> <linkto class=ImageSkyModel>ImageSkyModel</linkto> module
// </prerequisite>
//
// <etymology>
// NNLSImageSkyModel implements the NNLS deconvolution algorithm.
// It is derived from <linkto class=SkyModel>ImageSkyModel</linkto>.
// </etymology>
//
// <synopsis> 
// NNLS is implemented using the 
// <linkto class=NNLSMatrixSolver>NNLSMatrixSolver</linkto> 
// class. Since the brightness must be non-negative, only the Stokes I
// is solved for. Any other polarizations are not changed.
//
// Two masks are needed: the fluxmask determining the
// free pixels in the output image, and the datamask determining
// the constraint pixels in the dirty image. 
//
// In the solution, a matrix is required having elements connecting
// all free pixels with all constraint pixels. This is constructed
// from the point spread function. The total size of this matrix
// dominates the memory usage. 
// </synopsis> 
//
// <example>
// See the example for <linkto class=SkyModel>SkyModel</linkto>.
// </example>
//
// <motivation>
// </motivation>
//
// <todo asof="97/10/01">
// </todo>

class NNLSImageSkyModel : public CleanImageSkyModel {
public:

  // Solve for this SkyModel
  virtual Bool solve (SkyEquation& me);

private:

  Bool maskedZeroI();

};


} //# NAMESPACE CASA - END

#endif