Vips.Image.stdif

### Method

# Vips Imagestdif

#### Declaration [src]

    int
    vips_stdif (
      VipsImage* in,
      VipsImage** out,
      int width,
      int height,
      ...
    )

#### Description [src]

`vips_stdif()` performs 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 equation:

    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 `width`, `height` 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:

    vips stdif $VIPSHOME/pics/huysum.v fred.v 0.5 128 0.5 50 11 11

The operation 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.

Optional arguments

- `a`: `gdouble`, weight of new mean
- `m0`: `gdouble`, target mean
- `b`: `gdouble`, weight of new deviation
- `s0`: `gdouble`, target deviation

See also

`vips_hist_local()`.

This method is not directly available to language bindings.

#### Parameters

`out`

  Type: `VipsImage`

  Output image.

  The argument will be set by the function.
  The caller of the method takes ownership of the returned data, and is responsible for freeing it.

`width`

  Type: `int`

  Width of region.

`height`

  Type: `int`

  Height of region.

`...`

  Type: ``

  `NULL`-terminated list of optional named arguments.

#### Return value

Type: `int`

0 on success, -1 on error.