Go to the source code of this file.
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typedef unsigned int | uint |
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template<uint dim> |
void | CTL::imgproc::filter (Chunk2D< float > &image, FiltMethod m) |
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template<uint dim> |
void | CTL::imgproc::filter (Chunk2D< double > &image, FiltMethod m) |
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template<uint dim> |
void | CTL::imgproc::filter (VoxelVolume< float > &volume, FiltMethod m) |
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template<uint dim> |
void | CTL::imgproc::filter (VoxelVolume< double > &volume, FiltMethod m) |
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void | CTL::imgproc::median3 (VoxelVolume< float > &volume) |
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void | CTL::imgproc::median3NN (VoxelVolume< float > &volume) |
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template void | CTL::imgproc::filter< 0u > (VoxelVolume< float > &volume, FiltMethod m) |
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template void | CTL::imgproc::filter< 1u > (VoxelVolume< float > &volume, FiltMethod m) |
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template void | CTL::imgproc::filter< 2u > (VoxelVolume< float > &volume, FiltMethod m) |
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template void | CTL::imgproc::filter< 0u > (VoxelVolume< double > &volume, FiltMethod m) |
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template void | CTL::imgproc::filter< 1u > (VoxelVolume< double > &volume, FiltMethod m) |
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template void | CTL::imgproc::filter< 2u > (VoxelVolume< double > &volume, FiltMethod m) |
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template void | CTL::imgproc::filter< 0u > (Chunk2D< float > &image, FiltMethod m) |
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template void | CTL::imgproc::filter< 1u > (Chunk2D< float > &image, FiltMethod m) |
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template void | CTL::imgproc::filter< 0u > (Chunk2D< double > &image, FiltMethod m) |
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template void | CTL::imgproc::filter< 1u > (Chunk2D< double > &image, FiltMethod m) |
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◆ FiltMethod
Enumeration for filter methods that can be used.
To incorporate a new filter method, add a value to this enumeration (in filter.h) and provide the corresponding implementation of the method (see filter.cpp file for more information).
In general, values on the borders will be computed by extrapolating with zeros outside, where no valid values are available for the filtering, i.e. within the half filter size.
Enumerator |
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None | Does not perform any modification to the image.
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Gauss3 | This computes a Gaussian smoothing based on bionomial coefficients. The filter size N is three. For this, the standard deviation is \( \sigma=\frac{\sqrt{N-1}}{2}=\frac{1}{\sqrt{2}}\approx0.7071 \) and the elements are \( \frac{1}{4}\left[\begin{array}{ccc} 1 & 2 & 1\end{array}\right]\;. \)
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Gauss5 | This computes a Gaussian smoothing based on bionomial coefficients. The filter size N is five. For this, the standard deviation is \( \sigma=\frac{\sqrt{N-1}}{2}=1 \) and the elements are \( \frac{1}{16}\left[\begin{array}{ccccc} 1 & 4 & 6 & 4 & 1\end{array}\right]\;. \)
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Gauss7 | This computes a Gaussian smoothing based on bionomial coefficients. The filter size N is seven. For this, the standard deviation is \( \sigma=\frac{\sqrt{N-1}}{2}=\frac{\sqrt{6}}{2}\approx1.225 \) and the elements are \( \frac{1}{64}\left[\begin{array}{ccccccc} 1 & 6 & 15 & 20 & 15 & 6 & 1\end{array}\right]\;. \)
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Average3 | This computes the arithmetic mean over three adjacent image values, i.e. the filter elements are \( \frac{1}{3}\left[\begin{array}{ccc} 1 & 1 & 1\end{array}\right]\;. \)
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Median3 | This computes the median of three adjacent image values.
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MedianAbs3 | This computes the median element wrt. the absolute value of three adjacent image values and returns the orignial (signed) image value.
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MaxAbs3 | This computes the maximum element wrt. the absolute value of three adjacent image values and returns the orignial (signed) image value.
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◆ filter() [1/4]
Filters the data in image along the dimension dim using the filter method m.
◆ filter() [2/4]
Filters the data in image along the dimension dim using the filter method m.
◆ filter() [3/4]
Filters the data in volume along the dimension dim using the filter method m.
◆ filter() [4/4]
Filters the data in volume along the dimension dim using the filter method m.
◆ median3()
void CTL::imgproc::median3 |
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VoxelVolume< float > & |
volume | ) |
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Performs median filtering of the data in volume within a 3x3x3 voxel neighborhood. At the borders, the volume is mirrored for filtering.
◆ median3NN()
void CTL::imgproc::median3NN |
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VoxelVolume< float > & |
volume | ) |
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Performs median filtering of the data in volume in its immediate voxel neighborhood (ie. 6 neighbors in total). At the borders, the volume is mirrored for filtering.