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Everything about Hexagonal sampling

A multidimensional signal is a function of M independent variables where. Real world signals, which are generally continuous time signals, have to be discretized (sampled) in order to ensure that digital systems can be used to process the signals. It is during this process of discretization where sampling comes into picture. Although there are many ways of obtaining a discrete representation of a continuous time signal, periodic sampling is by far the simplest scheme. Theoretically, sampling can be performed with respect to any set of points. But practically, sampling is carried out with respect to a set of points that have a certain algebraic structure. Such structures are called lattices. Mathematically, the process of sampling an -dimensional signal can be written as: Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Hexagonal samplingA 5-minute orientation
  2. Skim a recent paper: A Hexagonal Grid-Sampling Scheme for Improving X-Ray Diffraction-Retained Austenite Measurements of Sheet SteelsInfluential work since 2022
  3. Pick up a classic book: Quantitative graph theoryThe most-reprinted book on the subject
  4. Read the landmark paper: The design of hexagonal sampling structures for image digitization and their use with local operatorsCited 50 times
  5. Go sideways: Multidimensional samplingA closely related topic
  6. Go sideways: Multidimensional transformA closely related topic

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