An Optimized Quantum Representation for Color Digital Images

Li, Kai; Zhang, Yi; Lü, Kai; Wang, Xiaoping; Wang, Xin

doi:10.1007/s10773-018-3813-4

Cited by 24 publications

(9 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(26), a color image can be written in three parts, as shown below:             . (28) Compared with NEQR and NCQI, THE storage capacity of BRQI is increased by 16 times and 218 times respectively, so it has a lower quantum cost. Besides, it can operate on color images.…”

Section: Brqimentioning

confidence: 99%

“…Liu et al proposed the OCQR based on the NCQI, which uses the 3D quantum sequence to store color quantum images, one representing the channel value, another representing channel index, and another introducing position information [28]. The OCQR can be expressed as The OCQR takes full advantage of quantum superposition to store the RGB value of each pixel.…”

Section: P Ocqrmentioning

confidence: 99%

“…Inspired by the three representations, a series of new quantum image representations have appeared. At present, quantum image representations mainly include NAQSS (Normal Arbitrary Quantum Superposition State) [14], QSMC&QSNC (Quantum States for M Colors and N Coordinates of An Image) [15], SQR (Simple Quantum Representation of Infrared Images) [16], QUALPI (Quantum Log-Polar Images) [17], NEQR (Novel Enhanced Quantum Representation) [18], CQIR (Caraiman's Quantum Image Representation) [19], MCQI (Multi-Channel Quantum Images) [20], INEQR(Improved NEQR) [21], GNEQR(A Generalized Model of NEQR) [22], NCQI(A Novel Quantum Representation of Color Digital Images) [23], BRQI (A Bitplane Representation of Quantum Images) [24], QRCI(A New Quantum Representation Model of Color Digital Images) [25], QRMMI (A Quantum Representation Model for Multiple Images) [26], QRMW (Quantum Representation of Multi Wavelength Images) [27], OCQR (An Optimized Quantum Representation for Color Digital Images) [28], FRQCI (An Improved FRQI Model) [29], QMCR (A Digital RGB Multi-Channel Representation for Quantum Colored Images) [30], IFRQI (Improved Flexible Representation of Quantum Images) [31], QBIR (A Quantum Block Image Representation) [32], OQIM (Order-encoded Quantum Image Model) [33], QIIR (Quantum Indexed Image Representation) [8], and DRQCI (A Double Quantum Color Images Representation Model) [34].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A New Trend of Quantum Image Representations

Guo

Liu

et al. 2020

IEEE Access

View full text Add to dashboard Cite

Quantum image processing will be an important issue in the age of quantum computers. Quantum image processing generally includes quantum image representations, quantum image processing algorithms, and quantum image measurement. Among them, quantum image representation is a very important part of quantum image processing. Therefore, it is of great significance for quantum image processing to study the representation of quantum images. First, we elaborate on the main quantum image representations and analyze, compare and summarize them. This paper focuses on the definition of these quantum image representations the preparation of quantum images and the number of quantum bits required as well as the computational complexity. Then, this paper analyzes, compares and summarizes the similarities and differences between these quantum image representations. Finally, the challenges and future development in the field of quantum image processing are summarized and forecasted. This work will help researchers to understand the advances related to quantum image representations in the field of quantum image processing and is therefore of some reference value.

show abstract

Section: Brqimentioning

confidence: 99%

Section: P Ocqrmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A New Trend of Quantum Image Representations

Guo

Liu

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The first step of an image processing algorithm is to encode the classical image as a quantum state. A number of different forms of quantum encoding methods have been proposed [26][27][28][29][30][31][32]. They differ in their applicability for binary, greyscale or color images, the amount of resources consumed, and the efficiency of the image retrieval process.…”

Section: Introductionmentioning

confidence: 99%

A hybrid-qudit representation of digital RGB images

Das¹,

Caruso²

2022

Preprint

View full text Add to dashboard Cite

Quantum image processing is an emerging topic in the field of quantum information and technology. In this paper, we propose a new quantum image representation of RGB images, which is an improvement to all the existing representations in terms of using minimum resource. We use two entangled quantum registers constituting of total 7 qutrits to encode the color channels and their intensities. Additionally, we generalize the existing encoding methods by using both qubits and qutrits to encode the pixel positions of a rectangular image. This hybrid-qudit approach aligns well with the current progress of NISQ devices in incorporating higher dimensional quantum systems than qubits. We then describe the image encoding method using higherorder qubit-qutrit gates, and demonstrate the decomposition of these gates in terms of simpler elementary gates. We use the Google Cirq's quantum simulator to verify the image retrieval. We show that the complexity of the image encoding process is linear in the number of pixels. Lastly, we discuss the image compression and some basic RGB image processing protocols using our representation.

show abstract

“…The quantum image representation model plays an important role as the basis of quantum image processing. There have been many research results on quantum image representation models, such as Qubit Lattice 14 , Entangled Image 15 , Real Ket 16 , a flexible representation for quantum images (FRQI) 17 , a novel enhanced quantum representation (NEQR) 18 , a normal arbitrary quantum superposition state (NASS) 19 , multi-channel representation of quantum image (MCRQI) 20 ,quantum states for M colors and N coordinates of an image (QSMC&QSNC) 21 , simple quantum representation of infrared images (SQR) 22 , quantum log-polar images (QUALPI) 23 , Caraiman’s quantum Image representation (CQIR) 24 , multi-channel quantum images (MCQI) 25 , Improved NEQR (INEQR) 26 , a generalized model of NEQR (GNEQR) 27 , a novel quantum representation of color digital images (NCQI) 28 , a bitplane representation of quantum images (BRQI) 29 , a new quantum representation model of color digital images (QRCI) 30 , a quantum representation model for multiple images (QRMMI) 31 , quantum representation of multi wavelength images (QRMW) 32 , an optimized quantum representation for color digital images (OCQR) 33 , an improved FRQI model (FRQCI) 34 , a digital RGB multi-channel representation for quantum colored images (QMCR) 35 , an improved flexible representation of quantum images (IFRQI) 36 , a quantum block image representation (QBIR) 37 , order-encoded quantum image model (OQIM) 38 , quantum indexed image representation (QIIR) 39 , and a double quantum color images representation model (DRQCI) 40 and so on. These quantum image representations encode color pixels as well as positions in different ways, making them somewhat different in terms of image processing applications and algorithmic complexity.…”

Section: Introductionmentioning

confidence: 99%

An improved novel quantum image representation and its experimental test on IBM quantum experience

Guo

Liu

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Quantum image representation (QIR) is a necessary part of quantum image processing (QIP) and plays an important role in quantum information processing. To address the problems that NCQI cannot handle images with inconsistent horizontal and vertical position sizes and multi-channel image processing, an improved color digital image quantum representation (INCQI) model based on NCQI is proposed in this paper. The INCQI model can process color images and facilitate multi-channel quantum image transformations and transparency information processing of images using auxiliary quantum bits. In addition, the quantum image control circuit was designed based on INCQI. And quantum image preparation experiments were conducted on IBM Quantum Experience (IBMQ) to verify the feasibility and effectiveness of INCQI quantum image preparation. The prepared image information was obtained by quantum measurement in the experiment, and the visualization of quantum information was successfully realized. The research in this paper has some reference value for the research related to QIP.

show abstract

An Optimized Quantum Representation for Color Digital Images

Cited by 24 publications

References 20 publications

A New Trend of Quantum Image Representations

A New Trend of Quantum Image Representations

A hybrid-qudit representation of digital RGB images

An improved novel quantum image representation and its experimental test on IBM quantum experience

Contact Info

Product

Resources

About