Bespoke Fractal Sampling Patterns for Discrete Fourier Space via the
Kaleidoscope Transform
- URL: http://arxiv.org/abs/2108.00639v1
- Date: Mon, 2 Aug 2021 05:16:58 GMT
- Title: Bespoke Fractal Sampling Patterns for Discrete Fourier Space via the
Kaleidoscope Transform
- Authors: Jacob M. White, Stuart Crozier, and Shekhar S. Chandra
- Abstract summary: Chaotic sensing employs deterministic, fractal sampling in conjunction with finite, iterative reconstruction schemes.
Chaotic sensing was found to outperform traditional compressed sensing for magnetic resonance imaging.
The ability to design tailor-made fractal sampling patterns expands the utility of the DFT in chaotic imaging.
- Score: 1.6274397329511197
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Sampling strategies are important for sparse imaging methodologies,
especially those employing the discrete Fourier transform (DFT). Chaotic
sensing is one such methodology that employs deterministic, fractal sampling in
conjunction with finite, iterative reconstruction schemes to form an image from
limited samples. Using a sampling pattern constructed entirely from periodic
lines in DFT space, chaotic sensing was found to outperform traditional
compressed sensing for magnetic resonance imaging; however, only one such
sampling pattern was presented and the reason for its fractal nature was not
proven. Through the introduction of a novel image transform known as the
kaleidoscope transform, which formalises and extends upon the concept of
downsampling and concatenating an image with itself, this paper: (1)
demonstrates a fundamental relationship between multiplication in modular
arithmetic and downsampling; (2) provides a rigorous mathematical explanation
for the fractal nature of the sampling pattern in the DFT; and (3) leverages
this understanding to develop a collection of novel fractal sampling patterns
for the 2D DFT with customisable properties. The ability to design tailor-made
fractal sampling patterns expands the utility of the DFT in chaotic imaging and
may form the basis for a bespoke chaotic sensing methodology, in which the
fractal sampling matches the imaging task for improved reconstruction.
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