NAME
wiener - performs wiener filtering
SYNOPSIS
#include "CVIPimage.h"
#include "CVIPtransform.h"
#include "CVIPxformfilter.h"
#include "CVIPdef.h"
#include "CVIParithlogic.h"
Image *wiener(Image *degr, Image *degr_fn, Image *p_noise,
Image *p_orig, int choice, int cutoff)
<degr> - pointer to the degraded image
<degr_fn> - pointer to the degradation function
<p_noise> - pointer to the noise power spectral density
<p_orig> - pointer to the original image power spectral
density
<choice> - 1 to let R(u,v) = 1, or 2 to let R(u,v) = 0
(R(u,v) = restoration filter, this is used
when the denominator = 0)
<cutoff> - cutoff frequency for filtering
PATH
$CVIPHOME/XFORMFILTER/InverseFilter.c
DESCRIPTION
This function performs a wiener filter, (a frequency domain
filter). See any image processing textbook for info on
Wiener Filters. The function does its own memory manage-
ment, freeing everything passed to it, so if you need your
images intact, make a copy of them before calling this func-
tion.
The function tries to determine whether an FFT has been per-
formed on the passed images. If not, the function will per-
form the FFT. This is especially important to note for the
power images. If the power images are in the spatial
domain, they will have an FFT performed on them, before the
squared magnitude is calculated. If an FFT is detected in
the history of any of the power images, that image is
assumed to be representing a power image, and no squared
magnitude is calculated.
The function will also extend the sizes of the passed images
as best it can when they are of unequal size.
Also note that the passed images must have the same number
of (color) bands.
TYPES AND CONSTANTS
None
RETURN VALUES
A pointer to the restored (filtered) image
HISTORY
History information recorded:
parameter #1 = filter cutoff.
parameter #2 = method 1: F(u,v)=G(u,v) when H(u,v)=0
method 2: F(u,v)=0 when H(u,v)=0
EXAMPLE
#include <CVIPtoolkit.h>
#include <CVIPimage.h>
#include <CVIPdef.h>
#include <CVIPconvert.h>
#include <CVIPview.h>
#include "CVIPxformfilter.h"
#define VIEWER "picture"
#define VIDEO_APP "SunVideo &"
void main()
{
Image *cvipImage,*cvipImage1;
Image *cvipImage2,*cvipImage3;
IMAGE_FORMAT format;
char *inputfile,*outputfile;
char *inputfile1,*inputfile2;
(void) setDisplay_Image(VIEWER,"default");
print_CVIP("\n\t\tEnter the File Name of the degraded
image: ");
inputfile =(char *) getString_CVIP();
format = getFormat_CVIP(inputfile);
cvipImage = read_Image(inputfile,1);
view_Image(cvipImage, inputfile);
free(inputfile);
/* the following call creates a gaussian mask of size
3 * 3 */
cvipImage1 = (Image *)h_image(3,3,3);
print_CVIP("\n\t\tEnter the File Name of the original
power spectrum image: ");
inputfile1 =(char *) getString_CVIP();
format = getFormat_CVIP(inputfile1);
cvipImage2 = read_Image(inputfile1,1);
view_Image(cvipImage2, inputfile1);
free(inputfile1);
print_CVIP("\n\t\tEnter the File Name of the noise power
spectrum image: ");
inputfile2 =(char *) getString_CVIP();
format = getFormat_CVIP(inputfile2);
cvipImage3 = read_Image(inputfile2,1);
view_Image(cvipImage3, inputfile2);
free(inputfile2);
/* the following call performs the wiener filter on the
input image with the gaussian mask and the cut off
frequency equal to 32 */
cvipImage3=(Image *)wiener(cvipImage,cvipImage1,cvipImage2,
cvipImage3,1,32);
cvipImage=(Image *)ifft_transform(cvipImage3,256);
print_CVIP("\n\t\tEnter the Output File Name: ");
outputfile = getString_CVIP();
view_Image(cvipImage,outputfile);
write_Image(cvipImage,outputfile,CVIP_NO,CVIP_NO,format,1);
free(outputfile);
}
SEE ALSO
libxformfilter
AUTHOR
Copyright (C) 1996 SIUE - by Scott E. Umbaugh and Arve
Kjoelen.