Image segmentation on a quantum computer

Image segmentation on a quantum computer In this paper, we address the field of quantum information processing and analyze the prospects of applying quantum computation concepts to image processing tasks. Specifically, we discuss the development of a quantum version for the image segmentation operation. This is an important technique that comes up in many image processing applications. We consider the threshold-based segmentation and show that a quantum circuit to achieve this operation can be built using a quantum oracle that implements the thresholding function. We discuss the circuit implementation of the oracle operator and provide examples of segmenting synthetic and real images. The main advantage of the quantum version for image segmentation over the classical approach is its speedup and is provided by the special properties of quantum information processing: superposition of states and inherent parallelism. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quantum Information Processing Springer Journals

Image segmentation on a quantum computer

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Publisher
Springer US
Copyright
Copyright © 2015 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/s11128-015-0932-1
Publisher site
See Article on Publisher Site

Abstract

In this paper, we address the field of quantum information processing and analyze the prospects of applying quantum computation concepts to image processing tasks. Specifically, we discuss the development of a quantum version for the image segmentation operation. This is an important technique that comes up in many image processing applications. We consider the threshold-based segmentation and show that a quantum circuit to achieve this operation can be built using a quantum oracle that implements the thresholding function. We discuss the circuit implementation of the oracle operator and provide examples of segmenting synthetic and real images. The main advantage of the quantum version for image segmentation over the classical approach is its speedup and is provided by the special properties of quantum information processing: superposition of states and inherent parallelism.

Journal

Quantum Information ProcessingSpringer Journals

Published: Jan 30, 2015

References

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