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details Common Filters VIGRA


Functions

template<...> void convolveImage (SrcIterator supperleft, SrcIterator slowerright, SrcAccessor sa, DestIterator dupperleft, DestAccessor da, Kernel1D< T > const &kx, Kernel1D< T > const &ky)
 Apply two separable filters successively, the first in x-direction, the second in y-direction.

template<...> void simpleSharpening (SrcIterator src_ul, SrcIterator src_lr, SrcAccessor src_acc, DestIterator dest_ul, DestAccessor dest_acc, double sharpening_factor)
 Perform simple sharpening function.

template<...> void gaussianSharpening (SrcIterator src_ul, SrcIterator src_lr, SrcAccessor src_acc, DestIterator dest_ul, DestAccessor dest_acc, double sharpening_factor, double scale)
 Perform sharpening function with gaussian filter.

template<...> void gaussianSmoothing (SrcIterator supperleft, SrcIterator slowerright, SrcAccessor sa, DestIterator dupperleft, DestAccessor da, double scale)
 Perform isotropic Gaussian convolution.

template<...> void gaussianGradient (SrcIterator supperleft, SrcIterator slowerright, SrcAccessor sa, DestIteratorX dupperleftx, DestAccessorX dax, DestIteratorY dupperlefty, DestAccessorY day, double scale)
 Calculate the gradient vector by means of a 1st derivatives of Gaussian filter.

template<...> void laplacianOfGaussian (SrcIterator supperleft, SrcIterator slowerright, SrcAccessor sa, DestIterator dupperleft, DestAccessor da, double scale)
 Filter image with the Laplacian of Gaussian operator at the given scale.

template<...> void hessianMatrixOfGaussian (SrcIterator supperleft, SrcIterator slowerright, SrcAccessor sa, DestIteratorX dupperleftx, DestAccessorX dax, DestIteratorXY dupperleftxy, DestAccessorXY daxy, DestIteratorY dupperlefty, DestAccessorY day, double scale)
 Filter image with the 2nd derivatives of the Gaussian at the given scale to get the Hessian matrix.

template<...> void structureTensor (SrcIterator supperleft, SrcIterator slowerright, SrcAccessor sa, DestIteratorX dupperleftx, DestAccessorX dax, DestIteratorXY dupperleftxy, DestAccessorXY daxy, DestIteratorY dupperlefty, DestAccessorY day, double inner_scale, double outer_scale)
 Calculate the Structure Tensor for each pixel of and image, using Gaussian (derivative) filters.



Detailed Description


These functions calculate common filters by appropriate sequences of calls to separableConvolveX() and separableConvolveY().


Function Documentation


  void convolveImage (...)
 
 

Apply two separable filters successively, the first in x-direction, the second in y-direction.

This function is a shorthand for the concatenation of a call to separableConvolveX() and separableConvolveY() with the given kernels.

Declarations:

pass arguments explicitly:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIterator, class DestAccessor,
                  class T>
        void convolveImage(SrcIterator supperleft,
                           SrcIterator slowerright, SrcAccessor sa,
                           DestIterator dupperleft, DestAccessor da,
                           Kernel1D<T> const & kx, Kernel1D<T> const & ky);
    }

use argument objects in conjuction with Argument Object Factories:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIterator, class DestAccessor,
                  class T>
        inline void
        convolveImage(triple<SrcIterator, SrcIterator, SrcAccessor> src,
                      pair<DestIterator, DestAccessor> dest,
                      Kernel1D<T> const & kx, Kernel1D<T> const & ky);
    }

Usage:

#include "vigra/convolution.hxx"

    vigra::FImage src(w,h), dest(w,h);
    ...

    // implement sobel filter in x-direction
    Kernel1D<double> kx, ky;
    kx.initSymmetricGradient();
    ky.initBinomial(1);
    
    vigra::convolveImage(srcImageRange(src), destImage(dest), kx, ky);


  void gaussianGradient (...)
 
 

Calculate the gradient vector by means of a 1st derivatives of Gaussian filter.

This function is a shorthand for the concatenation of a call to separableConvolveX() and separableConvolveY() with the appropriate kernels at the given scale. Note that this function produces two result images.

Declarations:

pass arguments explicitly:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIteratorX, class DestAccessorX,
                  class DestIteratorY, class DestAccessorY>
        void gaussianGradient(SrcIterator supperleft,
                                SrcIterator slowerright, SrcAccessor sa,
                                DestIteratorX dupperleftx, DestAccessorX dax,
                                DestIteratorY dupperlefty, DestAccessorY day,
                                double scale);
    }

use argument objects in conjuction with Argument Object Factories:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIteratorX, class DestAccessorX,
                  class DestIteratorY, class DestAccessorY>
        inline void
        gaussianGradient(triple<SrcIterator, SrcIterator, SrcAccessor> src,
                          pair<DestIteratorX, DestAccessorX> destx,
                          pair<DestIteratorY, DestAccessorY> desty,
                          double scale);
    }

Usage:

#include "vigra/convolution.hxx"

    vigra::FImage src(w,h), gradx(w,h), grady(w,h);
    ...

    // calculate gradient vector at scale = 3.0
    vigra::gaussianGradient(srcImageRange(src),
                             destImage(gradx), destImage(grady), 3.0);


  void gaussianSharpening (...)
 
 

Perform sharpening function with gaussian filter.

This function use the gaussianSmoothing() at first and scale the source image (

src 
) with the
scale 
factor in an temporary image (
tmp 
). At second the new pixel in the destination image will be with following formel calculate:
    dest = (1 + sharpening_factor)*src - sharpening_factor*tmp

Preconditions:

    1. sharpening_factor >= 0
    2. scale >= 0

Declarations:

pass arguments explicitly:

    namespace vigra {
      template <class SrcIterator, class SrcAccessor,
            class DestIterator, class DestAccessor>
      void gaussianSharpening(SrcIterator src_ul, SrcIterator src_lr, SrcAccessor src_acc,
                  DestIterator dest_ul, DestAccessor dest_acc, double sharpening_factor, 
                  double scale)
    }

use argument objects in conjuction with Argument Object Factories:

    namespace vigra {
      template <class SrcIterator, class SrcAccessor,
            class DestIterator, class DestAccessor>
      void gaussianSharpening(triple<SrcIterator, SrcIterator, SrcAccessor> src,
                  pair<DestIterator, DestAccessor> dest, double sharpening_factor, 
                  double scale)
    }

Usage:

#include "vigra/convolution.hxx"

    vigra::FImage src(w,h), dest(w,h);
    ...

    // sharpening with sharpening_factor = 3.0
    // smoothing with scale = 0.5
    vigra::gaussianSmoothing(srcImageRange(src), destImage(dest), 3.0, 0.5);


  void gaussianSmoothing (...)
 
 

Perform isotropic Gaussian convolution.

This function is a shorthand for the concatenation of a call to separableConvolveX() and separableConvolveY() with a Gaussian kernel of the given scale. The function uses BORDER_TREATMENT_REFLECT.

Declarations:

pass arguments explicitly:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIterator, class DestAccessor>
        void gaussianSmoothing(SrcIterator supperleft,
                                SrcIterator slowerright, SrcAccessor sa,
                                DestIterator dupperleft, DestAccessor da,
                                double scale);
    }

use argument objects in conjuction with Argument Object Factories:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIterator, class DestAccessor>
        inline void
        gaussianSmoothing(triple<SrcIterator, SrcIterator, SrcAccessor> src,
                          pair<DestIterator, DestAccessor> dest,
                          double scale);
    }

Usage:

#include "vigra/convolution.hxx"

    vigra::FImage src(w,h), dest(w,h);
    ...

    // smooth with scale = 3.0
    vigra::gaussianSmoothing(srcImageRange(src), destImage(dest), 3.0);


  void hessianMatrixOfGaussian (...)
 
 

Filter image with the 2nd derivatives of the Gaussian at the given scale to get the Hessian matrix.

The Hessian matrix is a symmetric matrix defined as:

where denote 2nd derivatives of Gaussians at the given scale, and is the convolution symbol. This function calls separableConvolveX() and separableConvolveY() with the appropriate 2nd derivative of Gaussian kernels and puts the results in the three destination images. The first destination image will contain the second derivative in x-direction, the second one the mixed derivative, and the third one holds the derivative in y-direction.

Declarations:

pass arguments explicitly:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIteratorX, class DestAccessorX,
                  class DestIteratorXY, class DestAccessorXY,
                  class DestIteratorY, class DestAccessorY>
        void hessianMatrixOfGaussian(SrcIterator supperleft,
                                SrcIterator slowerright, SrcAccessor sa,
                                DestIteratorX dupperleftx, DestAccessorX dax,
                                DestIteratorXY dupperleftxy, DestAccessorXY daxy,
                                DestIteratorY dupperlefty, DestAccessorY day,
                                double scale);
    }

use argument objects in conjuction with Argument Object Factories:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIteratorX, class DestAccessorX,
                  class DestIteratorXY, class DestAccessorXY,
                  class DestIteratorY, class DestAccessorY>
        inline void
        hessianMatrixOfGaussian(triple<SrcIterator, SrcIterator, SrcAccessor> src,
                          pair<DestIteratorX, DestAccessorX> destx,
                          pair<DestIteratorXY, DestAccessorXY> destxy,
                          pair<DestIteratorY, DestAccessorY> desty,
                          double scale);
    }

Usage:

#include "vigra/convolution.hxx"

    vigra::FImage src(w,h), hxx(w,h), hxy(w,h), hyy(w,h);
    ...

    // calculate Hessian of Gaussian at scale = 3.0
    vigra::hessianMatrixOfGaussian(srcImageRange(src),
        destImage(hxx), destImage(hxy), destImage(hyy), 3.0);


  void laplacianOfGaussian (...)
 
 

Filter image with the Laplacian of Gaussian operator at the given scale.

This function calls separableConvolveX() and separableConvolveY() with the appropriate 2nd derivative of Gaussian kernels in x- and y-direction and then sums the results to get the Laplacian.

Declarations:

pass arguments explicitly:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIterator, class DestAccessor>
        void laplacianOfGaussian(SrcIterator supperleft,
                                SrcIterator slowerright, SrcAccessor sa,
                                DestIterator dupperleft, DestAccessor da,
                                double scale);
    }

use argument objects in conjuction with Argument Object Factories:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIterator, class DestAccessor>
        inline void
        laplacianOfGaussian(triple<SrcIterator, SrcIterator, SrcAccessor> src,
                          pair<DestIterator, DestAccessor> dest,
                          double scale);
    }

Usage:

#include "vigra/convolution.hxx"

    vigra::FImage src(w,h), dest(w,h);
    ...

    // calculate Laplacian of Gaussian at scale = 3.0
    vigra::laplacianOfGaussian(srcImageRange(src), destImage(dest), 3.0);


  void simpleSharpening (...)
 
 

Perform simple sharpening function.

This function use convolveImage( ) with following filter:

    -sharpening_factor/16.0,    -sharpening_factor/8.0,    -sharpening_factor/16.0,
    -sharpening_factor/8.0,   1.0+sharpening_factor*0.75,  -sharpening_factor/8.0,
    -sharpening_factor/16.0,    -sharpening_factor/8.0,    -sharpening_factor/16.0;    

and use BORDER_TREATMENT_REFLECT as border treatment mode.

Preconditions:

    1. sharpening_factor >= 0
    2. scale >= 0

Declarations:

Declarations:

pass arguments explicitly:

    namespace vigra {
      template <class SrcIterator, class SrcAccessor,
                class DestIterator, class DestAccessor>
      void simpleSharpening(SrcIterator src_ul, SrcIterator src_lr, SrcAccessor src_acc,
                            DestIterator dest_ul, DestAccessor dest_acc, double sharpening_factor)

    }

use argument objects in conjuction with Argument Object Factories:

    namespace vigra {
      template <class SrcIterator, class SrcAccessor, 
            class DestIterator, class DestAccessor>
      inline
      void simpleSharpening(triple<SrcIterator, SrcIterator, SrcAccessor> src,
                        pair<DestIterator, DestAccessor> dest, double sharpening_factor)
      {
      simpleSharpening(src.first, src.second, src.third,
               dest.first, dest.second, sharpening_factor);
      }

    }

Usage:

#include "vigra/convolution.hxx"

    vigra::FImage src(w,h), dest(w,h);
    ...

    // sharpening with sharpening_factor = 0.1
    vigra::simpleSharpening(srcImageRange(src), destImage(dest), 0.1);


  void structureTensor (...)
 
 

Calculate the Structure Tensor for each pixel of and image, using Gaussian (derivative) filters.

The Structure Tensor is is a smoothed version of the Euclidean product of the gradient vector with itself. I.e. it's a symmetric matrix defined as:

where denotes Gaussian smoothing at the outer scale, are the gradient components taken at the inner scale, is the convolution symbol, and etc. are pixelwise products of the 1st derivative images. This function calls separableConvolveX() and separableConvolveY() with the appropriate Gaussian kernels and puts the results in the three destination images. The first destination image will contain , the second one , and the third one holds .

Declarations:

pass arguments explicitly:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIteratorX, class DestAccessorX,
                  class DestIteratorXY, class DestAccessorXY,
                  class DestIteratorY, class DestAccessorY>
        void structureTensor(SrcIterator supperleft,
                                SrcIterator slowerright, SrcAccessor sa,
                                DestIteratorX dupperleftx, DestAccessorX dax,
                                DestIteratorXY dupperleftxy, DestAccessorXY daxy,
                                DestIteratorY dupperlefty, DestAccessorY day,
                                double inner_scale, double outer_scale);
    }

use argument objects in conjuction with Argument Object Factories:

    namespace vigra {
        template <class SrcIterator, class SrcAccessor,
                  class DestIteratorX, class DestAccessorX,
                  class DestIteratorXY, class DestAccessorXY,
                  class DestIteratorY, class DestAccessorY>
        inline void
        structureTensor(triple<SrcIterator, SrcIterator, SrcAccessor> src,
                          pair<DestIteratorX, DestAccessorX> destx,
                          pair<DestIteratorXY, DestAccessorXY> destxy,
                          pair<DestIteratorY, DestAccessorY> desty,
                          double nner_scale, double outer_scale);
    }

Usage:

#include "vigra/convolution.hxx"

    vigra::FImage src(w,h), stxx(w,h), stxy(w,h), styy(w,h);
    ...

    // calculate Structure Tensor at inner scale = 1.0 and outer scale = 3.0
    vigra::structureTensor(srcImageRange(src),
        destImage(stxx), destImage(stxy), destImage(styy), 1.0, 3.0);

© Ullrich Köthe (koethe@informatik.uni-hamburg.de)
Cognitive Systems Group, University of Hamburg, Germany

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VIGRA 1.2.0 (7 Aug 2003)