Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Quantum Information Processing

The quantum Fourier transform based on quantum vision representation

Hai-Sheng Li, Ping Fan, Haiying Xia, Shuxiang Song, Xiangjian He

Published Oct 25, 2018• 24 citations
Publisher
DOI
10.1007/s11128-018-2096-2

Related papers

Quantum vision representations and multi-dimensional quantum transforms

Hai-Sheng Li, Shuxiang Song, Ping Fan +3 more

Information Sciences•Jun 13, 2019•27 citations

New look on quantum representation of images: Fourier transform representation

Artyom M. Grigoryan, Sos S. Agaian

Quantum Information Processing•Mar 21, 2020•52 citations

Representation-theoretical properties of the approximate quantum Fourier transform

Martin Rötteler, Thomas Beth

Applicable Algebra in Engineering Communication and Computing•Mar 7, 2008•4 citations

Quantum Fourier Transform Neural Network with image blockwise representation for image classification

Desheng Kong, Kangning An, Kairan Zhang +5 more

Knowledge-Based Systems•Apr 11, 2026•0 citations

Quantum Fourier Transform in Image Processing

Д.Т. Мухамедиева, Р.А. Собиров, N. M. Turgunova +1 more

Communications in computer and information science•Jan 1, 2024•11 citations

Quantum Fourier Transforms

Quantum Fourier transform (QFT) plays a key role in many quantum algorithms, but the existing circuits of QFT are incomplete and lacking the proof of correctness. Furthermore, it is difficult to apply QFT to the concrete field of information processing. Thus, this chapter firstly investigates quantum vision representation (QVR) and develops a model of QVR (MQVR). Then, four complete circuits of QFT and inverse QFT (IQFT) are designed. Meanwhile, this chapter proves the correctness of the four complete circuits using formula derivation. Next, 2D QFT and 3D QFT based on QVR are proposed. Experimental results with simulation show the proposed QFTs are valid and useful in processing quantum images and videos. In conclusion, this chapter develops a complete framework of QFT based on QVR and provides a feasible scheme for QFT to be applied in quantum vision information processing.

Advances in computer and electrical engineering book series•Aug 26, 2020•0 citations
Quantum Fourier transform (QFT) plays a key role in many quantum algorithms, but the existing circuits of QFT are incomplete and lacking the proof of correctness. Furthermore, it is difficult to apply QFT to the concrete field of information processing. Thus, this chapter firstly investigates quantum vision representation (QVR) and develops a model of QVR (MQVR). Then, four complete circuits of QFT and inverse QFT (IQFT) are designed. Meanwhile, this chapter proves the correctness of the four complete circuits using formula derivation. Next, 2D QFT and 3D QFT based on QVR are proposed. Experimental results with simulation show the proposed QFTs are valid and useful in processing quantum images and videos. In conclusion, this chapter develops a complete framework of QFT based on QVR and provides a feasible scheme for QFT to be applied in quantum vision information processing.