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
Topic revision: r1 - 29 Aug 2009, AnitaRichards
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