A two-tier scheme for greyscale quantum image watermarking and recovery

Iliyasu, Abdullah M.; Le, Phuc Q.; Yan, Fei; Sun, Bo; Garcia, Jesus A. S.; Dong, Fangyan; Hirota, Kaoru

doi:10.1504/ijica.2013.053179

Cited by 37 publications

(52 citation statements)

References 27 publications

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“…(2) No matter how advanced the QIP protocols we realize are, without physical hardware to tangibly utilize them, they will be less meaningful. Thus far, Iliyasu et al's exploration on the advances in quantum computation to support the realization of QIP application speci¯c hardware 62 remains the only attempt to experimentally validate QIP technologies. It is important that we exploit the interdisciplinary nature of quantum computation for improved synergy between researchers with interests in the physics, optics, computer science and engineering aspects of quantum computation to undertake experimental validations of the QIP protocols that are available.…”

Section: Future Directions For Qipmentioning

confidence: 99%

Quantum image processing: A review of advances in its security technologies

Yan

Iliyasu

Le³

2017

Int. J. Quantum Inform.

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121

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In this review, we present an overview of the advances made in quantum image processing (QIP) comprising of the image representations, the operations realizable on them, and the likely protocols and algorithms for their applications. In particular, we focus on recent progresses on QIP-based security technologies including quantum watermarking, quantum image encryption, and quantum image steganography. This review is aimed at providing readers with a succinct, yet adequate compendium of the progresses made in the QIP sub-area. Hopefully, this e®ort will stimulate further interest aimed at the pursuit of more advanced algorithms and experimental validations for available technologies and extensions to other domains.Keywords: Quantum image; quantum movie; quantum audio; quantum watermarking; quantum image encryption; quantum image steganography.

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Section: Future Directions For Qipmentioning

confidence: 99%

Quantum image processing: A review of advances in its security technologies

Yan

Iliyasu

Le³

2017

Int. J. Quantum Inform.

Self Cite

121

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“…In [30,41], color transformations, C, targeting the single qubit chromatic content of FRQI quantum images (CTQI) were proposed. This transformation was subsequently reviewed and utilized in [31,34] to focus on control condition operations on the color wire of the FRQI image, as shown in Figure 6. In this manner, the colors of every controlled position in the image are changed as defined in Equation (20),…”

Section: Efficient Color Transformations On Frqi Quantum Imagesmentioning

confidence: 99%

“…Interested readers are referred to the available literature, notably [30,32,34,41] for extensive discussions on the CTQI transformation, its review to adapt for use in multi-channel quantum images (MCQI) and some available applications in image watermarking and video encryption.…”

Section: Efficient Color Transformations On Frqi Quantum Imagesmentioning

confidence: 99%

“…They include the pioneering keyless and blind watermarking and authentication strategy (WaQI) [33], its two-tier grayscale version (GQaQI) [34], quantum Fourier transform-based watermark strategy [49] and the duple watermarking strategy for MCQI quantum images [50].…”

Section: Watermarking and Recovery Strategies For Frqi And Mcqi Quantmentioning

confidence: 99%

“…Many image processing strategies exploiting FRQI representation are developed to process transformations that target the geometric information and the color information [29][30][31][32]. In addition, applications based on FRQI representation are presented, such as the watermarking strategies [33][34][35], quantum image data searching [36][37][38] and the framework of producing quantum movies [12,39].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Yan

Iliyasu

Jiang

2014

Entropy

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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.Entropy 2014, 16 5291The 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.

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A Quantum Moving Target Segmentation Algorithm for Grayscale Video

Liu,

Wang,

2023

Adv Quantum Tech

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The moving target segmentation (MTS) aims to segment out moving targets in the video, however, the classical algorithm faces the huge challenge of real‐time processing in the current video era. Some scholars have successfully demonstrated the quantum advantages in some video processing tasks, but not concerning moving target segmentation. In this paper, a quantum moving target segmentation algorithm for grayscale video is proposed, which can use quantum mechanism to simultaneously calculate the difference of all pixels in all adjacent frames and then quickly segment out the moving target. In addition, a feasible quantum comparator is designed to distinguish the grayscale values with the threshold. Then several quantum circuit units are designed in detail to construct the complete quantum circuits for segmenting the moving target. For a quantum video with 2m frames (every frame is a image with q grayscale levels), the complexity of our algorithm can be reduced to O. Compared with the classic counterpart, it is an exponential speedup, while its complexity is also superior to the existing quantum algorithms. Finally, the experiment is conducted on IBM Quantum Experience (IBM Q) to show the feasibility of our algorithm in the noisy intermediate‐scale quantum era.

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A two-tier scheme for greyscale quantum image watermarking and recovery

Cited by 37 publications

References 27 publications

Quantum image processing: A review of advances in its security technologies

Quantum image processing: A review of advances in its security technologies

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

A Quantum Moving Target Segmentation Algorithm for Grayscale Video

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