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The method described above is recommended because it is quick and usually
efficient. However an alternative method is available which enables you to
process images of lower quality than required by DEFINE/ECHELLE and
generally returns more accurate results. The price to be paid however is a
higher demand for CPU time. The algorithm accepts frame which can be mildly
contaminated by particle hits, bad columns, order gaps due to absorption lines,
as found in FLAT or STD. If the frame is of very low quality for the
order definition, as it may be the case for a science frame, an initial
cleaning is required.
The algorithm assumes that:
- the interorder background is roughly constant over the frame.
- the slope of the orders is in the range ]0.,0.5[
The method is enabled by the parameter:
SET/ECHELLE DEFMTD=HOUGH
The command can run in a fully automatic mode if all three parameters
NBORDI, WIDTHI, THRESI are set to zero. To enforce the detection of
a given number of orders, set the value of NBORDI. If the frame has a low
contrast or if some areas of the interorder background are brighter than faint
orders in the image, it may be useful to set WIDTHI. Given hwthe half width of the orders and io the mean interorder distance, the
optimal value of WIDTHI is in the range ]hw,io - hw[. The threshold
THRESI is normally estimated for each order independently. However
the value can be enforced by giving a non null value to THRESI.
See also the help file of the commands DEFINE/HOUGH and HOUGH/ECHELLE
for more details about the possibilities of this method.
If the image is overscanned, that is includes unsensitive areas in its
lower and upper parts, it is better to avoid this areas by use of the
command SCAN/ECHELLE.
The best way to use this command is to start with null value for
all three parameters NBORDI, WIDTHI, THRESI. For example:
INIT/ECHELLE
SET/ECHELLE DEFMTD=HOUGH ORDREF= ... (order reference frame)
SCAN/ECHELLE ORDREF CURSOR
DEFINE/HOUGH
The successive steps are the following:
- The image ORDREF is smoothed by FILTER/MEDIAN,
a background value is estimated as the minimum of the smoothed
frame in its central part and this value is subtracted from
the frame. The result is stored in middummi.bdf. The frame
middummi is displayed. this image must show a uniformly black
background and a good contrast of the orders against the background.
If this step does not provide a satisfying result, use another
order reference image or clean it using general MIDAS
commands. For a background estimate without previous order definition,
consider the echelle command BACKGROUND/SMOOTH.
- The Hough transform of the middummi is computed and stored in middummh.
A description of this step and of the cluster detection can be found in
Ballester, 1991, Finding Echelle Orders by Hough Transform, Proceedings
of the 3rd ESO/ST-ECF Data Analysis Workshop, pp. 23-28.
The image middummh.bdf must show clear accumulation peaks, roughly
aligned along the columns and with a characteristic ``butterfly''
shape. The number of peaks is equal to the number
of orders. This step is usually straightforward. It may happen
however that bright straight lines in the Hough transform are
generated by uncorrectly removed particle hits.
- The cluster detection is performed on middummh. The slope of detected
orders must be rather constant, as well as the FWHM of the first
bright orders. The FWHM measured on the first order is taken as
reference. The displayed values provide an initial guess for WIDTHI.
A visual check of the cluster detection is available by the low level
command:
HOUGH/ECHELLE middummi P5=NMV
The result of the cluster detection is a table middummr.tbl containing
slope, intercept, fwhm and peak value of the detected orders. To
enforce the behaviour of cluster detection, set the parameter WIDTHI to a value big enough to remove correctly the detected
features.
- The orders are followed individually and a threshold is estimated
for each order. The threshold must vary continuously with the order
number, and the detected positions must be in sufficient number for each
order. The table order.tbl is created by this command. The measured
positions can be visualised on the display window by the commands:
LOAD middummi scale=... cuts=...
SELECT/TABLE order all
LOAD/TAB order :X :Y :ORDER
or
LOAD/TAB order :X :Y
Descriptors START and STEP of middummi must be equal to 1.,1. This
step can be controlled by the parameter THRESI.
- A bivariate polynomial is fitted to the table and outliers are
discarded by a kappa-sigma algorithm. The algorithm should not
discard more than say, 10 percent of the positions and the resulting
fit must be better than 0.3 pixels. The iterative regression and
the kappa-sigma clipping are controlled by the low level command
REGRESSION/ECHELLE.
Next: Wavelength calibration
Up: Reduction using Standard Stars
Previous: Order Definition: Methods STD
Petra Nass
1999-06-15