How can one sample images with sampling rates close to the theoretical minimum?

This addresses the problem of efficient image sampling for applications in digital imaging and signal processing, though it appears incremental as it builds on existing sampling theory.

The paper tackles the problem of minimizing the number of measurements required for digital image acquisition and reconstruction with a given accuracy, proposing a sampling theory-based method that approaches the minimal sampling rate defined by sampling theory, with experimental verification and applicability extensions discussed.