Quantum Fourier Transform for Image Processing

Fuente: arXiv
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Autori principali: Zhang, Ze Yu, Gao, Weibo
Natura: Preprint
Pubblicazione: 2023
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author Zhang, Ze Yu
Gao, Weibo
author_facet Zhang, Ze Yu
Gao, Weibo
contents Quantum information processing and its subfield, quantum image processing, are rapidly growing fields as a result of advancements in the practicality of quantum mechanics. In this paper, we propose a quantum algorithm for processing information, such as one-dimensional time series and two-dimensional images, in the frequency domain. The information of interest is encoded into the magnitude of probability amplitude or the coefficient of each basis state. The oracle for filtering operates based on postselection results, and its explicit circuit design is presented. This oracle is versatile enough to perform all basic filtering, including high pass, low pass, band pass, band stop, and many other processing techniques. Finally, we present two novel schemes for transposing matrices in this paper. They use similar encoding rules but with deliberate choices in terms of selecting basis states. These schemes could potentially be useful for other quantum information processing tasks, such as edge detection. The proposed techniques are implemented on the IBM Qiskit quantum simulator. Some results are compared with traditional information processing results to verify their correctness and are presented in this paper.
format Preprint
id arxiv_https___arxiv_org_abs_2305_05953
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Quantum Fourier Transform for Image Processing
Zhang, Ze Yu
Gao, Weibo
Quantum Physics
Data Structures and Algorithms
Emerging Technologies
Quantum information processing and its subfield, quantum image processing, are rapidly growing fields as a result of advancements in the practicality of quantum mechanics. In this paper, we propose a quantum algorithm for processing information, such as one-dimensional time series and two-dimensional images, in the frequency domain. The information of interest is encoded into the magnitude of probability amplitude or the coefficient of each basis state. The oracle for filtering operates based on postselection results, and its explicit circuit design is presented. This oracle is versatile enough to perform all basic filtering, including high pass, low pass, band pass, band stop, and many other processing techniques. Finally, we present two novel schemes for transposing matrices in this paper. They use similar encoding rules but with deliberate choices in terms of selecting basis states. These schemes could potentially be useful for other quantum information processing tasks, such as edge detection. The proposed techniques are implemented on the IBM Qiskit quantum simulator. Some results are compared with traditional information processing results to verify their correctness and are presented in this paper.
title Quantum Fourier Transform for Image Processing
topic Quantum Physics
Data Structures and Algorithms
Emerging Technologies
url https://arxiv.org/abs/2305.05953