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A multi-scale approach to automated feature extraction from HI data cubes

Kemper, P. (2005) A multi-scale approach to automated feature extraction from HI data cubes. Master's Thesis / Essay, Astronomy.

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Abstract

Due to the increasing sizes of datasets (three-dimensional spectral datasets from a radio interferometer) produced by modern astronomical observatories, feature extraction in a highly automated fashion becomes more and more a necessity. Therefore a multi-scale approach to automated feature extraction based on the wavelet transform and morphological operators, has been implemented. The discrete wavelet transform is performed by the 'a trous' algorithm. A multi-scale approach allows for object extraction independent of size and shape (adaptive filtering). The model has been tested successfully on astronomical datasets, in both the spatial as well as in the visibility domain.

Item Type: Thesis (Master's Thesis / Essay)
Degree programme: Astronomy
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 07:28
Last Modified: 15 Feb 2018 07:28
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/8311

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