Quantum image processing: challenges and future research issues

Chakraborty, Sanjay; Mandal, Sudhindu Bikash; Shaikh, Soharab Hossain

doi:10.1007/s41870-018-0227-8

Cited by 22 publications

(6 citation statements)

References 39 publications

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“…The entanglement of qubits results in an exponential growth of memory. A one-dimensional sequence requires only ([log 2 n]) qubits and N bits in a classical system 19 , 27 , 43 . The memory consumption is ([log 2 n + log 2 m]) qubits for comparing two sequences.…”

Section: Discussionmentioning

confidence: 99%

A biological sequence comparison algorithm using quantum computers

Kösoglu-Kind,

Loredo,

Grossi

et al. 2023

Sci Rep

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Genetic information is encoded as linear sequences of nucleotides, represented by letters ranging from thousands to billions. Differences between sequences are identified through comparative approaches like sequence analysis, where variations can occur at the individual nucleotide level or collectively due to various phenomena such as recombination or deletion. Detecting these sequence differences is vital for understanding biology and medicine, but the complexity and size of genomic data require substantial classical computing power. Inspired by human visual perception and pixel representation on quantum computers, we leverage these techniques to implement pairwise sequence analysis. Our method utilizes the Flexible Representation of Quantum Images (FRQI) framework, enabling comparisons at a fine granularity to single letters or amino acids within gene sequences. This novel approach enhances accuracy and resolution, surpassing traditional methods by capturing subtle genetic variations with precision. In summary, our approach offers algorithmic advantages, including reduced time complexity, improved space efficiency, and accurate sequence comparisons. The novelty lies in applying the FRQI algorithm to compare quantum images in genome sequencing, allowing for examination at the individual letter or amino acid level. This breakthrough holds promise for advancing biological data analysis and enables a more comprehensive understanding of genetic information.

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Section: Discussionmentioning

confidence: 99%

A biological sequence comparison algorithm using quantum computers

Kösoglu-Kind,

Loredo,

Grossi

et al. 2023

Sci Rep

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“…In their work [16], the authors compared different methods of image storage, image representations and image retrievals in a quantum system. They have also presented and discussed the advancement in quantum image processing.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Other Quantum interests Paper [10] ✓ Paper [11] ✓ Paper [12] ✓ Paper [13] ✓ Paper [14] ✓ Paper [15] ✓ Paper [16] ✓ Paper [17] ✓ Paper [18] ✓ Paper [19] ✓ Paper [20] ✓ Paper [21] ✓ Present paper ✓ ✓ ✓ In computer science, all useful information is represented using a succession of bits of 0's and 1's in low-level codes that can be decoded using low-level to high-level transcription programs for different purposes, such as displaying, reading and writing or even other useful purposes, each bit has to be 0 or 1 but not both.…”

Section: Quantum Image Processingmentioning

confidence: 99%

The Security of Information Systems and Image Processing Supported by the Quantum Computer: A review

Nouioua¹,

Belbachir²

2022

Adv. sci. technol. eng. syst. j.

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The knowledge and understanding of the technology of quantum computers and their superiority over classical computers are still insufficient or uncertain for many communities of researchers, manufacturers, investors and the general public. For this reason, we try in this article to present and explain some of the basic concepts of quantum computers. We explain how the quantum phenomena may be employed to conceive a quantum computer by defining the qubit that will represent the data entity corresponding to the bit in the classical computer and how this computer can effectively be powerful. We address the issue of strengthening the information system security through a simulation of a spy hunter and the importance of image processing security using the quantum computer, which will minimize the data processing time regardless of the amount of data to be processed. The security of the images will lead us to introduce the new prospects of using multilevel systems instead of binary systems, which will exponentially increase the gain in the size of the memory used.

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“…Besides, with checking and starting the process, the quantum storage capacity will increase exponentially. In the meantime by comparing the Quantum image representation for an image with a 2 2n pixel , in other words in an image of 2 n × 2 n , we can use fewer qubits than other representation, Among can mention normal arbitrary superposition state (NASS), multi-channel of quantum images (MCQI), flexible representation of quantum images (FRQI), novel enhanced quantum representation (NEQR), Quantum Multi-Channel Representation (QMCR) and generalized model of NEQR (GNEQR).It is also being more difficult to recover encrypted images in these representations due to the encryption of pixels based on their probability amplitude [14][15][16][17][18][19][20][21][22][23][24][25][26]. among the superior features of image quantum processing compared to its classical example, we can mention more efficiency in quantum Fourier transform and quantum discrete cosine transform.…”

Section: Introductionmentioning

confidence: 99%

Quantum RGB Image Encryption based on Bit-planes and Logistic Map

Basiri,

Matin,

Naseri

2024

Preprint

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Data encryption is one of the main factors in their transmission. In this paper, we have described an algorithm for color image encryption, some quantum encryption and image scrambling operations will be performed based on bitplane representation of quantum images (BRQI). Next, the image created using the logistic map (key image) is blended with the output of the first step, which was possible with the help of a quantum comparator circuit. Finally we create a secure image as the output of the encryption algorithm. Experiments with simulation and analysis of parameters such as entropy and correlation coefficient of adjacent pixels in three main positions show that the proposed algorithm has been very efficient and effective in securing and encrypting color images.

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Quantum image processing: challenges and future research issues

Cited by 22 publications

References 39 publications

A biological sequence comparison algorithm using quantum computers

A biological sequence comparison algorithm using quantum computers

The Security of Information Systems and Image Processing Supported by the Quantum Computer: A review

Quantum RGB Image Encryption based on Bit-planes and Logistic Map

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