**NAME**

im_stdif, im_stdif_raw - statistical differentiation of an image

**SYNOPSIS**

**#include** **<vips/vips.h>**
int im_stdif(in, out, a, m0, b, s0, xw, yw)
IMAGE *in, *out;
double a, m0, b, s0;
int xw, yw;
int im_stdif_raw(in, out, a, m0, b, s0, xw, yw)
IMAGE *in, *out;
double a, m0, b, s0;
int xw, yw;

**DESCRIPTION**

im_stdif() preforms statistical differencing according to the formula
given in page 45 of the book "An Introduction to Digital Image
Processing" by Wayne Niblack. This transformation emphasises the way in
which a pel differs statistically from its neighbours. It is useful for
enhancing low-contrast images with lots of detail, such as X-ray
plates.
At point (i,j) the output is given by the eqn:
vout(i,j) = a*m0 + (1-a)*meanv +
(vin(i,j) - meanv) * (b*s0) / (s0+b*stdv)
Values a, m0, b and s0 are entered, while meanv and stdv are the values
calculated over a moving window of size xw, yw centred on pixel (i,j).
m0 is the new mean, a is the weight given to it. s0 is the new standard
deviation, b is the weight given to it. Try:
im_stdif $VIPSHOME/pics/huysum.v fred.v 0.5 128 0.5 50 11 11
The opreation works on one-band UCHAR images only, and writes a one-
band UCHAR image as its result. The output image has the same size as
the input - a black border is added to mark uncomputable pixels.
im_stdif_raw() behaves exactly as im_stdif(), but does not add the
border of black pixels.

**RETURN** **VALUE**

All functions returns 0 on success and -1 on error.

**SEE ALSO**

im_lhisteq(3), im_histgr(3), im_hsp(3), im_heq(3).

**COPYRIGHT**

1991-1996, The National Gallery and Birkbeck College
10 May 1991