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Image Processing in Quantum Computers

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arxiv 1812.11042 v3 pith:YT3VWEK4 submitted 2018-12-28 cs.CV

classification cs.CV
keywords quantuminformationimageclassicalcomputersimagesprocessingaddition
verification ladder T0 review T1 audit T2 compute T3 formal
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Quantum Image Processing (QIP)is an exciting new field showing a lot of promise as a powerful addition to the arsenal of Image Processing techniques. Representing image pixel by pixel using classical information requires an enormous amount of computational resources. Hence, exploring methods to represent images in a different paradigm of information is important. In this work, we study the representation of images in Quantum Information. The main motivation for this pursuit is the ability of storing N bits of classical information in only log(2N) quantum bits (qubits). The promising first step was the exponentially efficient implementation of the Fourier transform in quantum computers as compared to Fast Fourier Transform in classical computers. In addition, images encoded in quantum information could obey unique quantum properties like superposition or entanglement.

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Cited by 1 Pith paper

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  1. QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks

    quant-ph 2025-07 conditional novelty 5.0 of 10

    QMoE, a quantum mixture-of-experts architecture with a learnable quantum router and multiple parameterized quantum expert circuits, reports consistent accuracy gains over standard quantum neural networks on 8x8 MNIST ...

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