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Entropy 2014, 16(10), 5290-5338; doi:10.3390/e16105290

Quantum Computation-Based Image Representation, Processing Operations and Their Applications

1
School of Computer Science and Technology, Changchun University of Science and Technology, No. 7089, Weixing Road, Changchun 130022, China
2
Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan
3
College of Engineering, Salman Bin Abdulaziz University, P.O. Box 173, Al-Kharj 11942, Saudi Arabia
*
Author to whom correspondence should be addressed.
Received: 28 June 2014 / Revised: 21 August 2014 / Accepted: 29 August 2014 / Published: 10 October 2014

Abstract

A flexible representation of quantum images (FRQI) was proposed to facilitate the extension of classical (non-quantum)-like image processing applications to the quantum computing domain. The representation encodes a quantum image in the form of a normalized state, which captures information about colors and their corresponding positions in the images. Since its conception, a handful of processing transformations have been formulated, among which are the geometric transformations on quantum images (GTQI) and the CTQI that are focused on the color information of the images. In addition, extensions and applications of FRQI representation, such as multi-channel representation for quantum images (MCQI), quantum image data searching, watermarking strategies for quantum images, a framework to produce movies on quantum computers and a blueprint for quantum video encryption and decryption have also been suggested. These proposals extend classical-like image and video processing applications to the quantum computing domain and offer a significant speed-up with low computational resources in comparison to performing the same tasks on traditional computing devices. Each of the algorithms and the mathematical foundations for their execution were simulated using classical computing resources, and their results were analyzed alongside other classical computing equivalents. The work presented in this review is intended to serve as the epitome of advances made in FRQI quantum image processing over the past five years and to simulate further interest geared towards the realization of some secure and efficient image and video processing applications on quantum computers. View Full-Text
Keywords: quantum computation; quantum information; quantum image; quantum circuit; quantum measurement; quantum watermarking; quantum movie; quantum Fourier transformation (QFT); parallel comparison; probability distribution quantum computation; quantum information; quantum image; quantum circuit; quantum measurement; quantum watermarking; quantum movie; quantum Fourier transformation (QFT); parallel comparison; probability distribution
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Yan, F.; Iliyasu, A.M.; Jiang, Z. Quantum Computation-Based Image Representation, Processing Operations and Their Applications. Entropy 2014, 16, 5290-5338.

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