ANALYSE = _LOGICAL (Read)
ANALYSE should be given
a
TRUE value if an analysis of a previously generated deconvolution is to be performed,
instead of a whole new deconvolution being started. An analysis returns the integrated
flux in some area of the deconvolved image you specify, together with the standard
deviation on the integrated flux value. The area to be integrated over is specified by
an image associated with Parameter MASK. This facility can, for instance, be
used to assess the significance of structure seen in the deconvolution. An
analysis can only be performed if the input NDF (see Parameter IN) contains a
MEM2D
extension (see Parameter EXTEND). If the input does contain such an
extension, and if the extension shows that the deconvolution was completed,
then ANALYSE is defaulted to
TRUE, otherwise it is defaulted to
FALSE.
[]
DEF = _REAL (Read)
This is the value to which the output image will default
in areas for which there is no valid data in the input. The ‘zero entropy’
image is defined to be a flat surface with value given by Parameter DEF. Any
deviation of the output image away from this image will cause its entropy to become
negative. Thus a maximum-entropy criterion causes the output image to be as similar
as possible to a flat surface with value DEF (within the constraints of the
data). DEF is defaulted to the mean data value in the input image and must
always be strictly positive. []
EXTEND = _LOGICAL (Read)
If EXTEND has a
TRUE value, then the output NDF will contain an extension called MEM2D which
will contain all the information required to either restart or analyse the
deconvolution. Note, including this extension makes the output file much bigger (by
about a factor of seven). [TRUE]
FWHMICF = _REAL (Read)
This is the Full
Width at Half Maximum (in pixels) of a Gaussian Intrinsic Correlation Function
(ICF) to be used in the deconvolution. The ICF can be used to encode prior
knowledge of pixel-to-pixel correlations in the output image. A value of 0 for
FWHMICF causes no ICF to be used, and so no correlations are expected in the
output. Larger values encourage smoothness in the output on the scale of the ICF.
If a non-zero ICF is used, the image entropy which is maximised is not the
output image, but a ‘hidden’ image. This hidden image is the deconvolution
of the output image with the ICF, and is assumed to have no pixel-to-pixel
correlations. [2]
FWHMPSF = _REAL (Read)
This is the Full Width at Half Maximum
(in pixels) of a Gaussian Point Spread Function (PSF). This PSF is used to
deconvolve the input only if Parameter PSFTYPE has the value "Gaussian".
ILEVEL = _INTEGER (Read)
ILEVEL controls the amount of information displayed
as MEM2D runs. If set to 0 then no information is displayed. Larger values
up to a maximum of 3, give larger amounts of information. A value of 3 gives
full MEMSYS3 diagnostics after each iteration. [1]
IN = NDF (Read)
The
input
NDF . This can either contain an image to be deconvolved, or the output
from a previous run of MEM2D. The NDF is considered to be an output from MEM2D
if it contains an extension called MEM2D (see Parameter EXTEND). If such an
extension is found, a check is made to see if the NDF contains a completed
deconvolution or a partial deconvolution. If the deconvolution is complete, the
ANALYSE parameter is defaulted to
TRUE, and unless you override this default,
an analysis of the deconvolution contained in the input NDF is performed. If
the input deconvolution is not complete, then the deconvolution process is
restarted from where it left off. If no MEM2D extension is found, then a new
deconvolution is started from scratch.
MASK = NDF (Read)
An image to use as a
mask to define the areas to be integrated when performing an analysis (see
Parameter ANALYSE). The integrated-flux value calculated by the analysis is
actually the total data sum in the product of the mask and the deconvolved
image. Mask pixel values can be positive or negative (or zero) and so, for
instance, masks can be arranged which subtract off a background brightness from a
source before returning the integrated source flux.
MODEL = NDF (Read)
An
image to use as the default model for the reconstruction. If a null value is
given, then a constant value given by the Parameter DEF is used to define a
flat default model. The section of the given image which matches the bounds of
the input image is used. Any bad pixels in the image cause the corresponding
pixels in the input image to be ignored. Such pixels are set bad in the output.
The model image should contain no pixels with a value of zero or less. The
default model is defined to have zero entropy. The hidden image will tend to
the default model in the absence of data. It should be noted that this model
applies to the ‘hidden’ image, not the actually required reconstructed image. The
reconstructed image is obtained from the hidden image by blurring the hidden image with
the ICF. [!]
MODELOUT = NDF (Write)
An image which can be used for the
default model in a further run of MEM2D. Each pixel value in the created image
is a linear combination of the model value at the corresponding pixel in the
current reconstruction, and the hidden image pixel value. Pixels for which the
hidden image is well away from the current model, tend towards the value of
the hidden image; pixels for which the hidden image is close to the current
model tend towards the model. Running MEM2D several times, using the new model
created on the previous run as the model for the current run, can reduce the
‘mottling’ often seen in MEM2D reconstructions. [!]
NITER = _INTEGER (Read)
The
maximum number of maximum-entropy iterations to perform. MEM2D continues the
deconvolution until either MEMSYS3 indicates that the termination criterion
() has
been reached, or the maximum number of iterations is reached. If a deconvolution
requires more iterations than was allowed by NITER, then you can choose to continue the
deconvolution by giving the prematurely terminated output from MEM2D as the
input to another run of MEM2D, specifying a larger value for NITER. [50]
NOISE = LITERAL (Read)
NOISE defines the noise statistics within the input
image. It can take the value
"Gaussian" or
"Poisson". If Gaussian noise is
selected, the data variances are set initially to the values stored in the
VARIANCE component of the input NDF. If no such component exists, then the
data variances are set to a constant value equal to the RMS difference between
adjacent pixels in the
x direction. MEMSYS3 scales these initial noise estimates to
maximise the data ‘evidence’. The evidence is displayed as
"LOG(PROB)" and
the noise scaling factor as
"SIGMA", if Parameter ILEVEL is set to
2 or more.
If Poisson statistics are selected the uncertainty in each data value is, as
usual, of the order of the square root of the data value. When using Poisson
statistics, there is no equivalent to the noise scaling performed when using
Gaussian statistics. Any input VARIANCE component is ignored.
["Gaussian"]
OUT = NDF (Write)
The output image in a ‘primitive’ NDF. The output is the
same size as the input. Any pixels which were flagged as bad in the input will
also be bad in the output. If Parameter EXTEND is TRUE, then the output NDF
contains an extension called MEM2D containing information which allows the
deconvolution to be either continued or analysed. There is no VARIANCE component in the
output, but any QUALITY values are propagated from the input to the output. If
Parameter UPDATE is TRUE, then the output NDF is created after the first iteration
and is updated after each subsequent iteration.
PSF = NDF (Read)
An NDF
holding an estimate of the Point Spread Function (PSF) of the input image. This
PSF is used to deconvolve the input only if Parameter PSFTYPE has the value
"NDF". The PSF can be centred anywhere within the image, the location of the
centre is specified using Parameters XCENTRE and YCENTRE. The extent of the PSF
actually used is controlled by Parameter THRESH.
PSFTYPE = LITERAL (Read)
PSFTYPE determines if the Point Spread Function used in the deconvolution
is to be Gaussian (if PSFTYPE="Gaussian"), or is to be defined by an image
you supply (if PSFTYPE="NDF"). ["NDF"]
RATE = _REAL (Read)
This is the
value to use for the MEMSYS3 RATE parameter. It determines the rate at which
the convergence is allowed to proceed. If RATE is high, each maximum-entropy
iteration is allowed to make a big change to the current reconstruction. This
can cause numeric problems within MEMSYS3 resulting in MEM2D crashing with a
"floating overflow" error. If this happens, try reducing RATE. Useful values
will normally be of the order of unity, and must lie in the interval 0.0001 to
100. [0.5]
THRESH = _REAL (Read)
The fraction of the PSF peak amplitude
at which the extents of the NDF PSF are determined. It must be positive and
less than 0.5. This parameter is only used when PSFTYPE="NDF". An error will
result if the input PSF is truncated above this threshold. [0.0625]
TITLE =
LITERAL (Read)
A
title for the output NDF. A null (
!) value means using the
title of the input NDF.
[!] UPDATE = _LOGICAL (Read)
If UPDATE is given a
TRUE value, then the output NDF will be created after the first iteration,
and will then be updated after each subsequent iteration. This means that the
current reconstruction can be examined without aborting the application. Also, if
Parameter EXTEND is TRUE, then if the job aborts for any reason, it can be
restarted from the last completed iteration (see Parameter IN). [TRUE]
XCENTRE =
_INTEGER (Read)
The x pixel index of the centre of the PSF within the supplied
PSF image. This is only required if PSFTYPE is "NDF". XCENTRE is defaulted
to the middle pixel (rounded down if there are an even number of pixels per
line). []
YCENTRE = _INTEGER (Read)
The y pixel index (line number) of
the centre of the PSF within the supplied PSF image. This is only required if
PSFTYPE is "NDF". YCENTRE is defaulted to the middle line (rounded down if
there are an even number of lines). []
MEM deconvolution is extremely CPU intensive.
The total CPU time taken depends partly on the size of the image, and partly
on the complexity of the structure within the image. As a typical example, a
100100
image containing 20 Gaussians on a flat background took about 34 minutes of elapsed
time on an unloaded DEC Alpha 2000. Deconvolution jobs should therefore always be done
in batch. To perform an analysis on a deconvolution takes about the same length of time
as a single deconvolution iteration.