BUGS · SEE_ALSO

## NAME

mkgauss -- Generate a 2-D image having an object of Gaussian type.

## USAGE

`mkgauss outim n1 n2 pos1 pos2 amp sigma1 sigma2 fwhm1 fwhm2 rms`

## DESCRIPTION

This is a task for generating a 2-D image having an object of Gaussian type (Gaussian function). Zero-mean Gaussian white noise may be added.

For the Gaussian function, if `sigma1` is zero, then `fwhm1` will be used and `sigma1` will be ignored. Otherwise `sigma1` will be used and `fwhm1` will be ignored. They are related by `sigma1` = `fwhm1` / sqrt(8ln2). Enter a small value, say 1.0E-4, for `sigma1` to virtually set it to zero, but `sigma1` is used. This rule is also applicable to `sigma2` and `fwhm2`.

This task can be used in conjunction with other tasks to make images having simple patterns.

## PARAMETERS

- outim [file name]
- Output image name.

- n1, n[integer]
- Image sizes in the first (x) and second (y) dimensions.

- pos1, pos[real]
- Gaussian function's central positions in the first and second dimensions.

- amp [real]
- Peak amplitude of the Gaussian function.

- sigma1, sigma[real]
- Gaussian function's sigmas in the first and second dimensions.

- fwhm1, fwhm[real]
- Gaussian function's full widths at half maximum in the first and second dimensions.

- rms [real]
- Rms value of Gaussian noise.

- seed=[integer]
- Seed for generating the noise.

## EXAMPLES

We do not recommend that you enter parameters on the command line,
as shown in the example below---use `epar` instead.

1. Generate a 128x128 noise-free point spread function of Gaussian type, which is centrally located (at (65,65)) and normalized so that its maximum is one, and has sigmas equal to 2 in the both dimensions. (x: don't care about the value.) Use any file name you like for outim.

im> mkgauss outim 128 128 65 65 1 2 2 x x 0

2. Generate a point spread function same as in 1., but has FWHMs equal to 2 in the both dimensions.

me>mkgauss outim 128 128 65 65 1 0 0 2 2 0

3. Generate a delta function at the center.

me>mkgauss outim 128 128 65 65 1 0 0 0 0 0

4. Generate a noise-free function with zero values everywhere except along a line segment parallel to the x-axis (centrally located 1-D Gaussian function with peak=1, sigma=3).

me>mkgauss outim 128 128 65 65 1 3 0 x 0 0

5. Same as in 4., but the line segment is now parallel to the y-axis.

me>mkgauss outim 128 128 65 65 1 1e-4 3 x x 0

6. Generate a noise-only image with rms=2, seed=919191 (zero-mean Gaussian white noise).

me>mkgauss outim 128 128 x x 0 x x x x 2 seed=919191

## TIME REQUIREMENTS

## BUGS

## SEE ALSO