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Дата изменения: Wed Jul 2 05:49:36 2008
Дата индексирования: Tue Oct 2 10:29:22 2012
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Поисковые слова: holographic principle
XMM-Newton Science Analysis System Page: 1
emosaic
July 2, 2008
Abstract
Mosaic EPIC images.
1 Instruments/Modes
Instrument Mode
EPIC MOS+pn Imaging
2 Use
pipeline processing yes
interactive analysis yes
3 Description
This task accepts an arbitrary number (maximum 999 in practice) of input images and combines them
to produce a single mosaiced image. Exposure images may optionally be supplied in parallel with the
raw event images, in which case the output image will be exposure corrected.
The task will only handle images which are a tangent plane projection of the sky, for example those
created from the X and Y columns of EPIC event lists using evselect. Images from the optical monitor,
which in their raw form contain a signi cant amount of distortion, could in principle be mosaiced after
reprojection to the tangent plane projection.
The output image is the additive mosaic of the input images, in other words no average is performed.
If the input image list is matched with a corresponding list of exposure maps, these exposure maps are
additively mosaiced in parallel, then the output image is divided by the mosaiced exposure map. This
approach is preferable to mosaicing exposure corrected images, as it helps avoid problems of poor counting
statistics in areas of low exposure. Binary masks can be simulated by providing exposure images which
have a pixel values of zero or one.
The output pixel size (in degrees) and world-coordinate system (WCS) reference coordinate for the output
image are set to those of the rst input image.
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The task can read images in any of the DAL-supported numeric data types. If all the input images have
the same data type (and if --withexposure is not set), the output image also has that type; otherwise
the output is written in real64. If --withexposure is set, this task also looks up the input exposuresets
as well, then the datatype with a larger bytesize one (e.g., FLOAT rather than INTEGER) between input
images and exposuresets is used for the type for the output image, providing that all the input sets
have the same data type; otherwise the output is written in real64.
4 Parameters
This section documents the parameters recognized by this task (if any).
Parameter Mand Type Default Constraints
imagesets yes dataset
list
List of input image datasets to be mosaiced
mosaicedset yes dataset
Name of output mosaiced image dataset
withexposure no boolean no
Handle exposure images in parallel
exposuresets no dataset
list
List of exposure image datasets.
sampling no string point point|bilinear
Sampling method
forceuniformkwds no boolean no point|bilinear
Whether to use the same keyword forms in the case of 1 input image as are used when there is more than
1.
5 Errors
This section documents warnings and errors generated by this task (if any). Note that warnings and
errors can also be generated in the SAS infrastructure libraries, in which case they would not be docu-
mented here. Refer to the index of all errors and warnings available in the HTML version of the SAS
documentation.
wrongNumberOfImages (error)
Number of images and exposure images di ers
badDims (error)
Only 2-D images are supported
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sizesDi er (error)
Image and corresponding exposure image di er in size
badType (error)
Image is of unsupported data type
tooMany (error)
More than 999 input images were supplied
6 Input Files
1. List of image les (image in primary header)
2. List of exposure images (image in primary header)
7 Output Files
1. Output image
8 Algorithm
Read parameters
Read each input image
Read corresponding exposure image (if required)
Set output projection (reference coordinate, pixel size) from the
first input image
Project corners of each input image into output frame to find the
bounds of the output image
Calculate size of output image in pixels from bounds and pixel size
Create output image
Loop over input images
Loop over pixels in output image
Project coordinate of output pixel into frame of input image
Sample input pixel, add sample to output image
Sample input exposure image pixel, add to output exposure
image (if required)
End loop
End loop
Divide output image by output exposure image (if required)
Write output image
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9 Comments
 Should we allow the reference coordinate and pixel size of output image to be de ned by
input parameters?
 Current implementation of the re-projection is a little ineфcient.
 Current implementation loads all image data into memory simultaneously. This could cause
problems if mosaicing a large number of images.
 The task currently assumes that exposure images are listed in the same order as their raw
photon twin, and the WCS keywords of exposure images are taken from the raw image.
 Task should be capable of writing output image as any (sensible) data type, chosen by input
parameter.
 Currently only point-sampling is supported.
 Limits should be placed on the size of the output image.
References
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