.help unwrap May87 noao.imred.vtel
.ih
NAME
unwrap -- Filter an IRAF image; remove binary wrap-around.
.ih
USAGE
unwrap listin listout
.ih
PARAMETERS
.ls listin
List of images to unwrap, this is an IRAF template.
.le
.ls listout
List of output images, this is an IRAF template.  If the output list
is the same as the input list, the unwrapping is done in-place.
.le
.ls threshold1 = 128
Data jump threshold for first unwrap pass.
.le
.ls wrapval1 = 256
Factor to multiply wrap value by for first unwrap pass.
.le
.ls threshold2 = 128
Data jump threshold for second unwrap pass.
.le
.ls wrapval2 = 256
Factor to multiply wrap value by for second unwrap pass.
.le
.ls cstart = 2
Column of image to start unwrapping.  Columns are numbered from left to right.
.le
.ls step = 5
Number of steps (1-5) to perform on image (unwrap1, difference, unwrap2,
reconstruct, fixlines).
.le
.ls verbose = yes
If set, program produces progress reports, etc.
.le
.ih
DESCRIPTION
Unwrap checks for binary wraparound in IRAF images.
The algorithm consists of reading the image line by line, unwrapping
each line, and writing the line out to another image.  The procedure
for unwraping is a five step process.
.ls Step one: unwrap1
Unwrapping is accomplished by scanning the data line and looking for
large jumps in the data values.  Large negative jumps are interpreted
as data wrapping and large positive jumps are interpreted as data unwrapping.
The program keeps track of the number of wraps, each data element in the
array has wrapval1 * wrapnumber added.  This effectively unwraps an image
in which the point to point variation in the data values is small compared
to the variation caused by a binary wrap.
.le
.ls Step two: difference
A difference image is produced from the above step one image by calculating
the pixel to pixel difference between all of the pixels in the line.  The
first column of the image is generally left intact so that the image can
be reconstructed in a later step.  Step one often produces streaks in the
image due to data variation large enough to mimic wrapping.  This step
two difference image eliminates most of these streaks except for their
point of origin, where the confusion occured.
.le
.ls Step three: unwrap2
This is the second unwrapping step.  The image is unwrapped as in step
one using the second set of unwrap values (threshold2, wrapval2).
.le
.ls Step four: reconstruct
The original image is reconstructed from the step three image by
adding pixel values successively to line pixels.
.le
.ls Step five: fixlines
If bad lines (streaks) still can be found in the image, they are
eliminated by replacing the line by the average of the lines above
and below bad line.
.le
.ih
EXAMPLES
1. To unwrap an image called "continuum" and store the resulting image in
"unwrapped", and use the default parameters, the command might be:

.nf
	vt> unwrap continuum unwrapped
.fi

2. To unwrap all the images in the directory starting with s1492 and store
the unwrapped images in s1492*u, to start in column 31, to do four steps,
and to see verbose output, the command might be:

.nf
	vt> unwrap s1494* s1492*//u cstart=31 step=4 v+
.fi

.ih
SEE ALSO
.endhelp