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Loading contentFinding and measuring the individual stars and galaxies in an astronomical image, and separating real sources from noise and artefacts — the first step of nearly every imaging pipeline. Machine-learning methods increasingly complement the classical algorithms, especially in crowded or blended fields.
Facts on this topic will be cited from these primary and reference sources.
Mission data, planetary science, space telescopes, and public-domain imagery.
Most NASA-produced imagery is in the public domain; individual items are checked for usage terms before publication.