imop.h File Reference

Image operations. More...

#include "generic.h"

Go to the source code of this file.

Defines

Convolution padding modes
#define VL_CONV_ZERO   0
#define VL_CONV_CIRC   1
#define VL_CONV_CONT   2

Functions

void vl_convtransp_f (vl_single *dst, vl_single const *src, vl_single const *filt, int width, int height, int filt_width, int mode)
 Convolve along columns and take transpose.
void vl_convtransp_d (vl_double *dst, vl_double const *src, vl_double const *filt, int width, int height, int filt_width, int mode)
 Convolve along columns and take transpose.
void vl_imsmooth_f (vl_single *dst, vl_single *temp, vl_single const *src, int width, int height, double sigma)
 Smooth image by Gaussian kernel.
void vl_imsmooth_d (vl_double *dst, vl_double *temp, vl_double const *src, int width, int height, double sigma)
 Smooth image by Gaussian kernel.


Detailed Description

Author:
Andrea Vedaldi

Define Documentation

#define VL_CONV_CIRC   1

Circular convolution

#define VL_CONV_CONT   2

Pad by continuity

#define VL_CONV_ZERO   0

Zero padding


Function Documentation

void vl_convtransp_d ( vl_double dst,
vl_double const *  src,
vl_double const *  filt,
int  width,
int  height,
int  filt_width,
int  mode 
)

The function convolve the columns of the matrix src by the kernel filt of variance s and writes the transpose of the result to the buffer dst.

Remarks:
Here `columns' correspond to the fastest varying index. Often image are stored in row-major order, so the `columns' are actually the `rows' of the image.

To convolve an image by a 2-D separable filter just call this function twice.

The function can be used to process N-dimensional arrays by stacking them properly.

Parameters:
dst output image buffer.
src input image buffer.
filt filter buffer.
width width of the image.
height height of the image.
filt_width filter half width (total width = 2 filt_width + 1).
mode mode flags.

vl_convtransp_f ( vl_single dst,
vl_single const *  src,
vl_single const *  filt,
int  width,
int  height,
int  filt_width,
int  mode 
)

The function convolve the columns of the matrix src by the kernel filt of variance s and writes the transpose of the result to the buffer dst.

Remarks:
Here `columns' correspond to the fastest varying index. Often image are stored in row-major order, so the `columns' are actually the `rows' of the image.

To convolve an image by a 2-D separable filter just call this function twice.

The function can be used to process N-dimensional arrays by stacking them properly.

Parameters:
dst output image buffer.
src input image buffer.
filt filter buffer.
width width of the image.
height height of the image.
filt_width filter half width (total width = 2 filt_width + 1).
mode mode flags.

void vl_imsmooth_d ( vl_double dst,
vl_double temp,
vl_double const *  src,
int  width,
int  height,
double  sigma 
)

The functions convolve the image src by a Gaussian kernel of variance s and write the result to the buffer dst. The functions also need a scratch buffer dst of the same size of the buffers src and dst.

The various functions differ by the data type of the image pixels that they process.

Parameters:
dst output image buffer.
temp scratch image buffer.
src input image buffer.
width width of the buffers.
height height of the buffers.
sigma standard deviation of the Gaussian kernel.

vl_imsmooth_f ( vl_single dst,
vl_single temp,
vl_single const *  src,
int  width,
int  height,
double  sigma 
)

The functions convolve the image src by a Gaussian kernel of variance s and write the result to the buffer dst. The functions also need a scratch buffer dst of the same size of the buffers src and dst.

The various functions differ by the data type of the image pixels that they process.

Parameters:
dst output image buffer.
temp scratch image buffer.
src input image buffer.
width width of the buffers.
height height of the buffers.
sigma standard deviation of the Gaussian kernel.


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