This class implements convolutions with fixed kernel sizes. More...
#include <mlConvolutionFilter.h>
Public Types | |
| enum | ConvKernelTypes { AVERAGE_33_KERNEL = 0, AVERAGE_55_KERNEL, AVERAGE_77_KERNEL, AVERAGE_1010_KERNEL, AVERAGE_2525_KERNEL, GAUSS_33_KERNEL, GAUSS_55_KERNEL, LAPLACE_KERNEL, LAPLACE_2_KERNEL, SOBEL_1_KERNEL, SOBEL_2_KERNEL, SOBEL_3_KERNEL, SOBEL_4_KERNEL, ID_KERNEL, FROM_EXTERNAL_KERNEL, NUM_CONV_KERNEL_TYPES } |
The ConvKernelTypes decide which kernel is used to filter the input image. More... | |
Public Member Functions | |
| ConvolutionFilter () | |
| Constructor. | |
| EnumField * | getConvKernelFld () const |
Access to parameter field(s) See documentation of _convKernelFld. | |
Static Public Attributes | |
| static const char *const | ConvKernelNames [] |
| Strings for ConvKernelNames. | |
Protected Member Functions | |
| virtual void | handleNotification (Field *field) |
| Called when a parameter field is changed. | |
| virtual void | _userKernelPostUpdate () |
| Update the kernel to the selected kernel state if no external kernel is connected. | |
| virtual void | calculateOutputImageProperties (int outIndex) |
Computes the output image properties from the input image properties and the _convKernelFld. | |
| CALC_ROW_H () | |
The implementation of the calculateOutputSubImage() method overloaded from Module is done in this macro. | |
| template<typename DATATYPE > | |
| void | calcRow (MLsoffset *indexTab, size_t indexTabSize, MLsoffset srcVoxelOffset, size_t numVox, DATATYPE *inCursor, DATATYPE *outCursor, const ImageVector &) |
| In this virtual template method the filtering of one row needs to be implemented. | |
Detailed Description
This class implements convolutions with fixed kernel sizes.
For related code and more information see mlKernelExample.h, mlKernel.h, mlKernelBaseModule.h, mlKernelModule.h, mlKernelEditor.h, mlRankFilter.h, mlExtConvolutionFilter.h, mlKernelMacros, mlKernelTools.h and mlConvolutionFilter.h.
Definition at line 37 of file mlConvolutionFilter.h.
Member Enumeration Documentation
The ConvKernelTypes decide which kernel is used to filter the input image.
AVERAGE_33_KERNEL
3 x 3 Kernel. All Elements of this kernel have normalized and equal coefficents:
1/9 1/9 1/9 1/9 1/9 1/9 1/9 1/9 1/9
AVERAGE_55_KERNEL
5 x 5 Kernel. All Elements are normalized and have equal coefficents.
AVERAGE_77_KERNEL
7 x 7 Kernel. All Elements are normalized and have equal coefficents.
AVERAGE_1010_KERNEL
10 x 10 Kernel. All Elements are normalized and have equal coefficents.
AVERAGE_2525_KERNEL
25 x 25 Kernel. All Elements are normalized and have equal coefficents.
GAUSS_33_KERNEL
Apply a 3x3 - Gausskernel. Smooth image and emphasizes the inner voxels.
1/16 2/16 1/16 2/16 4/16 2/16 1/16 2/16 1/16
GAUSS_55_KERNEL
Apply a 5 x 5 Gausskernel.
LAPLACE_KERNEL
Apply a 3 x 3 Laplacekernel. Used for detection edges by taking the 2nd derivation into account.
0 1 0 1 -4 1 0 1 0
LAPLACE_2_KERNEL
Apply a 3 x 3 Laplace2kernel.
1 2 1 2 -12 2 1 2 1
SOBEL_1_KERNEL
Apply a 3 x 3 Sobel1kernel. Used for detecting edges in vertical direction and smoothing in horizontal direction.
1 0 -1 2 0 -2 1 0 -1
SOBEL_2_KERNEL
Apply a 3 x 3 Sobel2kernel. Used for detecting edges in horizontal direction and smoothing in vertical direction.
1 2 1 0 0 0 -1 -2 -1
SOBEL_3_KERNEL
Apply a 3 x 3 Sobel3kernel. Used for detecting edges in diagonal direction and smoothing in contrary direction.
0 -1 -2 1 0 -1 2 1 0
SOBEL_4_KERNEL
Apply a 3 x 3 Sobel4kernel. Used for detecting edges in diagonal direction and smoothing in contrary direction.
-2 -1 0 -1 0 1 0 1 2
ID_KERNEL
Do nothing.
FROM_EXTERNAL_KERNEL
Kernel defined elsewhere and set via field connections in the _kernelInputFld.
- Enumerator:
Definition at line 128 of file mlConvolutionFilter.h.
Constructor & Destructor Documentation
| ml::ConvolutionFilter::ConvolutionFilter | ( | ) |
Constructor.
Initializes the fields, the members and the field connections with the field container.
Note that with the following method calls an additional field interface is created as described in KernelModule and KernelBaseModule:
_createImageIntervalFields(0, 1024, true, false);_createExternalKernelFields(false, false);_createKernelInfoField();_createKernelOutputField();
Also available are the fields access methods from KernelBaseModule:
Member Function Documentation
| virtual void ml::ConvolutionFilter::_userKernelPostUpdate | ( | ) | [protected, virtual] |
Update the kernel to the selected kernel state if no external kernel is connected.
Reimplemented from ml::KernelModule.
| ml::ConvolutionFilter::CALC_ROW_H | ( | ) | [protected] |
The implementation of the calculateOutputSubImage() method overloaded from Module is done in this macro.
It implements page border handling and a dispatcher to call the correct template version of calcRow() with the correct parameters. Note that CALC_ROW_CPP() also needs to be added in the .cpp file.
| void ml::ConvolutionFilter::calcRow | ( | MLsoffset * | indexTab, |
| size_t | indexTabSize, | ||
| MLsoffset | srcVoxelOffset, | ||
| size_t | numVox, | ||
| DATATYPE * | inCursor, | ||
| DATATYPE * | outCursor, | ||
| const ImageVector & | |||
| ) | [protected] |
In this virtual template method the filtering of one row needs to be implemented.
It will be called by the CALC_ROW_H() / CALC_ROW_CPP() macro.
| virtual void ml::ConvolutionFilter::calculateOutputImageProperties | ( | int | outIndex | ) | [protected, virtual] |
Computes the output image properties from the input image properties and the _convKernelFld.
Reimplemented from ml::KernelModule.
| EnumField* ml::ConvolutionFilter::getConvKernelFld | ( | ) | const [inline] |
Access to parameter field(s) See documentation of _convKernelFld.
Definition at line 171 of file mlConvolutionFilter.h.
| virtual void ml::ConvolutionFilter::handleNotification | ( | Field * | field | ) | [protected, virtual] |
Called when a parameter field is changed.
Reimplemented from ml::KernelModule.
Member Data Documentation
const char* const ml::ConvolutionFilter::ConvKernelNames[] [static] |
Strings for ConvKernelNames.
Definition at line 149 of file mlConvolutionFilter.h.
The documentation for this class was generated from the following file:
- MeVisLab/Standard/Sources/ML/MLKernel/mlConvolutionFilter.h
