Image Analysis
Robert Laing
Recognising errors in the image plane
Expectations: how to decide whether an image is as good as it needs to be/can be.
Predicting the off-source noise level.
Signatures of phase and amplitude errors:
additive and multiplicative errors;
long and short timescales;
subtracting a model
Examples:
bad antennas, baselines, data-points,spectral channels;
interference;
confusion;
deconvolution problems (polarization errors in other lecture)
Remedial action
Image Analysis
The importance of matched resolution and spatial frequency coverage
Image manipulation and combination; error propagation (1, 2 and many images)
Interpolation
Convolution
Deriving parameters from images:
(Gaussian) fitting and error estimation
Automated source-finding algorithms
Integrated flux densities; resolution, short-spacing and zero-level issues; summing clean components, integrating images, ....
Time variability; component-fitting and cross-correlation techniques for measuring motion
More sophisticated model-fitting (jet models as an example)
Getting data out of the standard packages and into your own code
This topic: ERIS2009
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Topic revision:
29 Aug 2009,
AnitaRichards
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