mlib_ImageNormCrossCorrel_mediaLib)Library mlib_ImageNormCrossCorrel_Fp(3MLIB)NAMEmlib_ImageNormCrossCorrel_Fp - normalized cross correlation
SYNOPSIS
cc [ flag... ] file... -lmlib [ library... ]
#include <mlib.h>
mlib_status mlib_ImageNormCrossCorrel_Fp(mlib_d64 *correl,
const mlib_image *img1, const mlib_image *img2, const mlib_d64 *mean2,
const mlib_d64 *sdev2);
DESCRIPTION
The mlib_ImageNormCrossCorrel_Fp() function computes the normalized
cross-correlation coefficients between a pair of floating-point images,
on a per-channel basis.
It uses the following equations:
w-1 h-1
SUM SUM (d1[x][y][i] * d2[x][y][i])
x=0 y=0
correl[i] = -------------------------------------
s1[i] * s2[i]
d1[x][y][i] = img1[x][y][i] - m1[i]
d2[x][y][i] = img2[x][y][i] - m2[i]
1 w-1 h-1
m1[i] = ----- * SUM SUM img1[x][y][i]
w*h x=0 y=0
1 w-1 h-1
m2[i] = ----- * SUM SUM img2[x][y][i]
w*h x=0 y=0
w-1 h-1
s1[i] = sqrt{ SUM SUM (img1[x][y][i] - m1[i])**2 }
x=0 y=0
w-1 h-1
s2[i] = sqrt{ SUM SUM (img2[x][y][i] - m2[i])**2 }
x=0 y=0
where w and h are the width and height of the images, respectively; m1
and m2 are the mean arrays of the first and second images, respec‐
tively; s1 and s2 are the un-normalized standard deviation arrays of
the first and second images, respectively.
In usual cases, the normalized cross-correlation coefficient is in the
range of [-1.0, 1.0]. In the case of (s1[i] == 0) or (s2[i] == 0),
where a constant image channel is involved, the normalized cross-corre‐
lation coefficient is defined as follows:
#define signof(x) ((x > 0) ? 1 : ((x < 0) ? -1 : 0))
if ((s1[i] == 0.) || (s2[i] == 0.)) {
if ((s1[i] == 0.) && (s2[i] == 0.)) {
if (signof(m1[i]) == signof(m2[i]) {
correl[i] = 1.0;
} else {
correl[i] = -1.0;
}
} else {
correl[i] = -1.0;
}
}
The two images must have the same type, the same size, and the same
number of channels. They can have 1, 2, 3 or 4 channels. They can be of
type MLIB_FLOAT or MLIB_DOUBLE.
If (mean2 == NULL) or (sdev2 == NULL), then m2 and s2 are calculated in
this function according to the formulas shown above. Otherwise, they
are calculated as follows:
m2[i] = mean2[i];
s2[i] = sdev2[i] * sqrt(w*h);
where mean2 and sdev2 can be the output of mlib_ImageMean() and
mlib_ImageStdDev(), respectively.
In some cases, the resulting coefficients of this function could be
NaN, Inf, or -Inf.
PARAMETERS
The function takes the following arguments:
correl Pointer to normalized cross correlation array on a channel
basis. The array must be the size of channels in the images.
correl[i] contains the cross-correlation of channel i.
img1 Pointer to first image.
img2 Pointer to second image.
mean2 Pointer to the mean array of the second image.
sdev2 Pointer to the standard deviation array of the second image.
RETURN VALUES
The function returns MLIB_SUCCESS if successful. Otherwise it returns
MLIB_FAILURE.
ATTRIBUTES
See attributes(5) for descriptions of the following attributes:
┌─────────────────────────────┬─────────────────────────────┐
│ ATTRIBUTE TYPE │ ATTRIBUTE VALUE │
├─────────────────────────────┼─────────────────────────────┤
│Interface Stability │Committed │
├─────────────────────────────┼─────────────────────────────┤
│MT-Level │MT-Safe │
└─────────────────────────────┴─────────────────────────────┘
SEE ALSOmlib_ImageAutoCorrel(3MLIB), mlib_ImageAutoCorrel_Fp(3MLIB),
mlib_ImageCrossCorrel(3MLIB), mlib_ImageCrossCorrel_Fp(3MLIB),
mlib_ImageNormCrossCorrel(3MLIB), attributes(5)SunOS 5.10 2 Mar 200mlib_ImageNormCrossCorrel_Fp(3MLIB)
