Abstract
As the most concerned new model, quantum computing is always a hot topic in the field of information processing. In particular, after the quantum algorithms of Shor large number factor decomposition and Grover search are proposed, people gradually realize that quantum computing is expected to break through the classical computing limit, thus bringing subversive upheaval to the whole information processing field. However, at present, the research on quantum computing theory for image processing is still in its infancy. People still linger on how to use quantum information to characterize images. It is difficult to design a quantum image processing algorithm that can solve practical problems. On the basis of this problem, a quantum image processing system is set up. It is gradually progressive from image storage to image preprocessing, and then to image classification, and then the construction of the whole system is realized, so as to expand the research and analysis. It is found that the processing of computer images by quantum algorithm is accurate and real-time, and it can effectively deal with the problems in traditional image processing. On the one hand, the construction of the quantum image processing system solves the problem of the performance of traditional image processing. On the other hand, the bottom-up research method from the information storage angle can also provide guidance on how to use the online algorithm in other information fields.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Caraiman, S., Manta, V.I.: Image segmentation on a quantum computer. Quantum Inf. Process. 14(5), 1693–1715 (2015)
Jiang, N., Wang, L.: Quantum image scaling using nearest neighbor interpolation. Quantum Inf. Process. 14(5), 1559–1571 (2015)
Jiang, N., Wang, J., Mu, Y.: Quantum image scaling up based on nearest-neighbor interpolation with integer scaling ratio. Quantum Inf. Process. 14(11), 1–26 (2015)
Zhou, R.G., Sun, Y.J.: Quantum multidimensional color images similarity comparison. Quantum Inf. Process. 14(5), 1605–1624 (2015)
Youssry, A., El-Rafei, A., Elramly, S.: A quantum mechanics-based algorithm for vessel segmentation in retinal images. Quantum Inf. Process. 15(6), 1–21 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Chen, S. (2020). Computer Image Processing Technology Based on Quantum Algorithm. In: Liu, Q., Mısır, M., Wang, X., Liu, W. (eds) The 8th International Conference on Computer Engineering and Networks (CENet2018). CENet2018 2018. Advances in Intelligent Systems and Computing, vol 905. Springer, Cham. https://doi.org/10.1007/978-3-030-14680-1_30
Download citation
DOI: https://doi.org/10.1007/978-3-030-14680-1_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-14679-5
Online ISBN: 978-3-030-14680-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)