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In image processing, the amount of data to be processed grows rapidly, inparticular when imaging methods yield images of more than two dimensions ortime series of images. Thus, efficient processing is a challenge, as data sizesmay push even supercomputers to their limits. Quantum image processing promisesto encode images with logarithmically less qubits than classical pixels in theimage. In theory, this is a huge progress, but so far not many experiments havebeen conducted in practice, in particular on real backends. Often, the preciseconversion of classical data to quantum states, the exact implementation, andthe interpretation of the measurements in the classical context arechallenging. We investigate these practical questions in this paper. Inparticular, we study the feasibility of the Flexible Representation of QuantumImages (FRQI). Furthermore, we check experimentally what is the limit in thecurrent noisy intermediate-scale quantum era, i.e. up to which image size animage can be encoded, both on simulators and on real backends. Finally, wepropose a method for simplifying the circuits needed for the FRQI. With ouralteration, the number of gates needed, especially of the error-pronecontrolled-NOT gates, can be reduced. As a consequence, the size of manageableimages increases.

Improved FRQI on superconducting processors and its restrictions in the NISQ era