AIPS HELP file for MEDI in 31DEC22
As of Sat May 21 13:25:47 2022
MEDI: Task to combine four overlapping images
INNAME First image name
INCLASS First image class
INSEQ 0.0 9999.0 First image seq. #
INDISK 0.0 9.0 First image disk drive #
IN2NAME Second image name
IN2CLASS Second image class
IN2SEQ 0.0 9999.0 Second image seq. #
IN2DISK 0.0 9.0 Second image disk drive #
IN3NAME Third image name
IN3CLASS Third image class
IN3SEQ 0.0 9999.0 Third image seq. #
IN3DISK 0.0 9.0 Third image disk #
IN4NAME Fourth image name
IN4CLASS Fourth image class
IN4SEQ 0.0 9999.0 Fourth image seq. #
IN4DISK 0.0 9.0 Fourth image disk #
DOALIGN -2.0 1.0 Should images be coincident?
OUTNAME Output image name
OUTCLASS Output image class
OUTSEQ -1.0 9999.0 Output image seq. #
OUTDISK 0.0 9.0 Output image disk drive #
BLC 0.0 4096.0 Bottom left corner
TRC 0.0 4096.0 Top right corner
APARM Parameters for algorithm:
(1) - (4) scale and offset
(8) > 0 => blank with 0.0
(9) Map1 clip level
(10) Map2 clip level
see HELP COMB
BPARM Noise/control parameters:
(1) Map noise level
0 ignore noise
(3) > 0 => output
(4) < 0.5 => clip w inputs
> 1.5 => clip w S/N
else => clip w noise
(5) minimum ok S/N or
maximum ok noise
(6) max output noise
0 -> any
see HELP MEDI
MEDI is a task in which four input images are combined on
a pixel by pixel level to produce an output image and an
optional deviation image. The MEDIan, like the AVERAGE,
is used to estimate the most likely (true) value of an
observable. The average is a more efficient estimator of a
value when the noise of the measurement is gaussian
distributed with zero mean. However in the presence of
out-lying data (noise), the MEDIAN is a more efficient
INNAME......First image name. Standard defaults.
INCLASS.....First image class. Standard defaults.
INSEQ.......First image seq. #. 0 => highest.
INDISK......Disk drive # for the first image. 0 => any.
IN2NAME.....Second image name. Standard defaults.
IN2CLASS....Second image class. Standard defaults.
IN2SEQ......Second image seq. #. 0 => highest.
IN2DISK.....Disk drive # for the second image. 0 => any.
IN3NAME.....Third image name. Standard defaults.
IN3CLASS....Third image class. Standard defaults.
IN3SEQ......Third image seq. #. 0 => highest.
IN3DISK.....Disk # for Third image. 0 => any.
IN4NAME.....Fourth image name. Standard defaults.
IN4CLASS....Fourth image class. Standard defaults.
IN4SEQ......Fourth image seq. #. 0 => highest.
IN4DISK.....Disk # for Fourth image. 0 => any.
DOALIGN.....Controls how the four images are to be aligned (see HELP
DOALIGN). True (>.1) means that the images must agree in
their coordinates, though not necessarily in the reference
pixel position. Alignment is by coordinate values (if
DOALIGN > -0.1) or by offsets from the reference pixel
positions (if DOALIGN <= -0.1). NOTE: all real axes (>1
point) are aligned. If DOALIGN = -2, the headers are
ignored and the images are aligned at pixel (1,1,...).
OUTNAME.....Output image name. Standard defaults.
OUTCLASS....Output image class. Standard behavior with default =
either the output STOKES in string form or the MEDI if
the output STOKES is the same as the first input image.
The noise image has the 6th character of class set to N.
OUTSEQ......Output image seq. #. 0 => highest unique.
OUTDISK.....Output disk number. 0 => highest with space.
BLC.........Bottom left corner of the 1st input image. The other
images are aligned by coordinates (see DOALIGN) on all
axes having > 1 point. The other images may have fewer
real axes than the 1st. The 4 windows must have the same
dimension on the first 2 axes, but the task will select a
smaller window than was specified if needed to overlap the
TRC.........Top right corner of input images. (See BLC.)
APARM.......Parameters needed for algorithm:
APARM(1), APARM(2), APARM(3), APARM(4) used as above.
APARM(8) > 0 => Use 0.0 for clipped & illegal values
<= 0 => Use blanking for clipped & illegal values
APARM(9) = Clip if Abs (MAP(1)) < APARM(9) - image units.
APARM(10) = Clip if Abs(MAP(2)) < APARM(10) - image units.
There are no defaults for APARM(9) and (10) and a zero
value means no clipping. Used only if BPARM(4) <= 0.5
BPARM.......Parameters needed noise calculation and control:
BPARM(1) = 1-sigma level on 1st input map.
BPARM(3) = false (<= 0) => output normal image
= true (> 0) => output normal and sigma image
Blanking is the same for both settings of B(3).
BPARM(4) <= 0.5 => Blank output map using input map values
else => Blank output map using output map sigma
>= 1.5 => Blank output map using output map S/N.
BPARM(5) = Error on output map value above which output
pixel is blanked (if BPARM(4) = 1) 0 -> ignore
= S/N ratio of output map value below which output
pixel is blanked (if BPARM(4) = 2) 0 -> ignore
BPARM(6) = Maximum value of sigma to be output (used if > 0 and
BPARM(3) > 0 only).
NOTE: certain combinations of BPARM(3), BPARM(4) do not
make much sense but all are allowed. Output images
which are constant will be written and a warning message will
Task MATHS is used to do mathematical operations on single images.
MEDIAN Details: In the case of one or two un-blanked pixel
values, the MEDIAN is the average of the un-blanked values.
The deviation image pixel is blanked. In the case of 3
un-blanked pixel values, the middle of the three values is
the median, and the deviation image contains the average of
the high and low pixels, minus the middle pixel. In the
case of 4 un-blanked input values, the median is the average
of the middle two values and the deviation image is the
average of the high and low values, minus the average of the
middle two values.
MEDI.FOR is a modified verison of COMB.FOR
Created by Glen Langston in 99 December