Quantum image processing?
Mario Mastriani

TL;DR
This paper critically examines the practical challenges of implementing Quantum Image Processing, highlighting issues with measurement, interfaces, and decoherence, and discusses Quantum Boolean Image Processing as a measurement-friendly alternative.
Contribution
It identifies key practical problems in quantum image processing and discusses Quantum Boolean Image Processing as a solution to measurement-related issues.
Findings
Measurement in quantum image processing is a major practical obstacle.
Quantum Boolean Image Processing avoids measurement problems by using computational basis states.
Classical-to-quantum interfaces are critical but underexplored in the literature.
Abstract
This paper presents a number of problems concerning the practical (real) implementation of the techniques known as Quantum Image Processing. The most serious problem is the recovery of the outcomes after the quantum measurement, which will be demonstrated in this work that is equivalent to a noise measurement, and it is not considered in the literature on the subject. It is noteworthy that this is due to several factors: 1) a classical algorithm that uses Dirac's notation and then it is coded in MATLAB does not constitute a quantum algorithm, 2) the literature emphasizes the internal representation of the image but says nothing about the classical-to-quantum and quantum-to-classical interfaces and how these are affected by decoherence, 3) the literature does not mention how to implement in a practical way (at the laboratory) these proposals internal representations, 4) given that…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Mechanics and Applications · Quantum Information and Cryptography
