Image storage, retrieval, compression and segmentation in a quantum system

Image storage, retrieval, compression and segmentation in a quantum system A set of quantum states for $$M$$ colors and another set of quantum states for $$N$$ coordinates are proposed in this paper to represent $$M$$ colors and coordinates of the $$N$$ pixels in an image respectively. We design an algorithm by which an image of $$N$$ pixels and $$m$$ different colors is stored in a quantum system just using $$2N+m$$ qubits. An algorithm for quantum image compression is proposed. Simulation result on the Lena image shows that compression ratio of lossless is 2.058. Moreover, an image segmentation algorithm based on quantum search quantum search which can find all solutions in the expected times in $$O(t\sqrt{N} )$$ is proposed, where $$N$$ is the number of pixels and $$t$$ is the number of targets to be segmented. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quantum Information Processing Springer Journals

Image storage, retrieval, compression and segmentation in a quantum system

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Publisher
Springer US
Copyright
Copyright © 2013 by Springer Science+Business Media New York
Subject
Physics; Quantum Information Technology, Spintronics; Quantum Computing; Data Structures, Cryptology and Information Theory; Quantum Physics; Mathematical Physics
ISSN
1570-0755
eISSN
1573-1332
D.O.I.
10.1007/s11128-012-0521-5
Publisher site
See Article on Publisher Site

Abstract

A set of quantum states for $$M$$ colors and another set of quantum states for $$N$$ coordinates are proposed in this paper to represent $$M$$ colors and coordinates of the $$N$$ pixels in an image respectively. We design an algorithm by which an image of $$N$$ pixels and $$m$$ different colors is stored in a quantum system just using $$2N+m$$ qubits. An algorithm for quantum image compression is proposed. Simulation result on the Lena image shows that compression ratio of lossless is 2.058. Moreover, an image segmentation algorithm based on quantum search quantum search which can find all solutions in the expected times in $$O(t\sqrt{N} )$$ is proposed, where $$N$$ is the number of pixels and $$t$$ is the number of targets to be segmented.

Journal

Quantum Information ProcessingSpringer Journals

Published: Jan 9, 2013

References

  • Processing images in entangled quantum systems
    Venegas-Andraca, SE; Ball, JL
  • A flexible representation of quantum images for polynomial preparation, image compression, and processing operations
    Le, PQ; Dong, F; Hirota, K

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