Aztec curve: proposal for a new space-filling curve
This is an incremental contribution for researchers in data storage, indexing, and compressed sensing, offering a new alternative for space-filling curve applications.
The paper tackles the problem of space-filling curves by proposing the Aztec curve, which enables bi-dimensional clustering not available in Hilbert or Peano curves, and shows similar performance to Hilbert curve in a compressed sensing application.
Different space-filling curves (SFCs) are briefly reviewed in this paper, and a new one is proposed. A century has passed between the inception of this kind of curves, since then they have been found useful in computer science, particularly in data storage and indexing due to their clustering properties, being Hilbert curve the most well-known member of the family of fractals. The proposed Aztec curve, with similar characteristics to the Hilbert's curve, is introduced in this paper, accompanied by a grammatical description for its construction. It yields the possibility of creating bi-dimensional clusters, not available for Hilbert nor Peano curves. Additional to this, a case of application on the scope of Compressed Sensing is implemented, in which the use of Hilbert curve is contrasted with Aztec curve, having a similar performance, and positioning the Aztec curve as viable and a new alternative for future exploitation on applications that make use of SFC's.