Документ взят из кэша поисковой машины. Адрес оригинального документа : http://www.arcetri.astro.it/~zibetti/Software/adaptsmooth/README Дата изменения: Fri Dec 3 22:49:28 2010 Дата индексирования: Sun Apr 10 09:08:42 2016 Кодировка: Поисковые слова: http astrokuban.info astrokuban

Adaptsmooth V.2.7.1 15.11.2010 by Stefano Zibetti (MPIA&DARK)
Usage: adaptsmooth -p|b|l|m [-a] [-r RMS_SKY] [-G EFFECTIVE_GAIN]
[-s SN] [-L L] [-c SLCUT] input_image output_image mask
-p : noise mode: poisson+background
-b : noise mode: background-dominated
-l : noise mode: local
-m : switch to input-mask mode
-a : use arithmetic mean instead of median
-r RMS_SKY (requested in poisson+bkg and bkg-dominated noise mode)
-G EFFECTIVE_GAIN : e- per ADU (requested in poisson+bkg mode)
-s SN : minimum S/N requested (defaults to 20.0)
-L L : maximum smoothing radius (defaults to max=27)
-c SLCUT : smoothing level cut
0: no exclusions; 1: exclude first level (1pix scale) from all others;
N<0: exclude up to the (-N)th level below current. Defaults to 0



adaptsmooth adaptively smooths images by replacing each pixel in the
input image with an average (median or mean) of the pixels in a
surrounding region of radius R, a.k.a. "smoothing level" L. L is
varied on a pixel-by-pixel base to allow the smoothed image to reach a
give S/N, or, in alternative, based on a pre-computed mask.

I M P O R T A N T : The input image is assumed to be
*background-subtracted*.

For general information about the algorithms and the code please refer
to the "paper". Here you can find a quick manual.

-- Getting and installing the code

You can get the code package adaptsmooth.tgz from this "URL" or by
requesting it directly to the author zibetti@mpia.de.

Before installing the code check that you have the CFITSIO library
installed (http://heasarc.nasa.gov/fitsio/).

To install the code follow these steps:
cd to your preferred installation directory
tar -zxf adaptsmooth.tgz
cd adaptsmooth_current_distr
edit the Makefile to specify:
BINDIR directory where the adaptsmooth executable will be
CFITSIO_LFLAG directory where the libcfitsio.a is located
CFITSIO_IFLAG directory where the fitsio*.h files are located
run "make adaptsmooth"
done!
Make sure that $BINDIR is in your executable PATH

-- Note on fits file i/o
adaptsmooth assumes images are in the primary HDU of the fits files.
adaptsmooth takes as input image any numeric format (integer or float,
single or double precision) and internally converts it to
single-precision floating point. The output image is always a
single-precision float. The output mask is short-integer type. When
the mask is input, only integer types are accepted.

All header information in the input image is propagated to the output
image (and mask if the case), with the addition of the history and all
relevant parameters of adapthsmooth-ing.

Overwriting of output file is not allowed in the current version.

-- Running the code
adaptsmooth runs from command line.

Just issuing "adaptsmooth" returns a summary of the usage (reported at
the beginning of this document).

Here is a more in-depth explanation of the usage and available
options.

adaptsmooth always requires a mode option (p|b|l|m), an input fits
image, a name for the output image and one for the smoothing mask,
which contains the smoothing level at each position.

Mode options p|b|l specify that the program determines the smoothing
to be applied based on different noise estimates in the input image
itself: in p mode poisson+background noise is assumed, in b
background-dominated noise, in l mode noise is given by the local
rms. At each pixel, the smoothing is iteratively increased until the
requested S/N or the maximum smoothing level is reached. In this
second case, the underflow value -1e10 is output into the image and
100 is written in the smoothing mask.

Mode option m tells adaptsmooth to smooth according the smoothing
mask, given as input.

p mode requires background rms noise (-r parameter) and the effective
gain, i.e. the number of photoelectrons per ADU (-G parameter) to be
specified.

b mode requires background rms noise (-r parameter)

l mode does not require any further option, as well as m mode

Images are meant to be standard fits images. Pixels are always assumed
to be in the primary extension. The input image can be any numeric
type, although internal conversion to single precision float is
applied. The output image is single precision float. As for the mask,
in input-mask mode it must be any integer type, in output is
short-integer.

--Optional parameters

-s : specifies the minimum S/N to reach at each pixel (default is 20).
-L : specifies the maximum smoothing level that can be reached
(default is the maximum allowed by the code, i.e. 27)
-a : specifies to use the arithmetic mean instead of the median
(default) as average
-c : specifies the smoothing level cut (default is 0, i.e. no cuts)

"Smoothing level cuts" can be useful to avoid bright localized sources
to contaminate the surroundings. See the "paper" for more details.
-c 0 (default) means no exclusions
-c 1 excludes all pixels that are individually above the S/N
threshold, that therefore do not contribute to smoothed levels
-c N (N<0) exclude all pixels that are up to -N levels below the
current.



--Examples:

a) smooth an image with background-dominated noise rms=2.4, to a
minimum S/N of 10.0, up to a max smoothing level of 10 (no pixel
exclusion):

adaptsmooth -b -r 2.4 -s 10.0 -L 10 image.fits image_smooth.fits image_mask.fits

b) smooth an image assuming poisson+background noise, rms=2.4 and
effective gain=5.2 e-/ADU, to a minimum S/N of 10.0, up to a max
smoothing level of 10 (no pixel exclusion):

adaptsmooth -p -r 2.4 -G 5.2 -s 10.0 -L 10 image.fits image_smooth.fits image_mask.fits

c) smooth an image with rms noise determined locally, to a minimum S/N of
10.0, up to a max smoothing level of 10 (no pixel exclusion):

adaptsmooth -l -s 10.0 -L 10 image.fits image_smooth.fits image_mask.fits

d) smooth an image according to a pre-computed mask (no pixel exclusion):

adaptsmooth -m image.fits image_smooth.fits image_mask.fits

e) smooth an image with rms noise determined locally, to a minimum S/N
of 10.0, up to a max smoothing level of 10, excluding pixels whose
smoothing level is lower by 2 wrt the current level:

adaptsmooth -l -s 10.0 -L 10 -c 2 image.fits image_smooth.fits
image_mask.fits

f) as a) but using average instead of median:

adaptsmooth -b -a -r 2.4 -s 10.0 -L 10 image.fits image_smooth.fits image_mask.fits