Abstract
Image coding in quantum computing primarily focuses on encoding position and color information. This study introduces an enhanced quantum image representation by employing entanglement state encoding within the HSI color model. The proposed model employs a 2-qubit entanglement state to encode the H (hue) and S (saturation) channels. This approach significantly improves the efficiency of quantum image processing, including quantum image retrieval, in comparison with the QIRHSI representation model based on two superposition states. EQIRHSI, the enhanced model, paves the way for new avenues of research in quantum image processing, while retaining the advantages of the QIRHSI model. These advantages include superior intensity channel processing when compared to the MCQI model, as well as lower storage space requirements in contrast to the NCQI model. The paper delves into the polynomial preparation and complexity analysis for constructing EQIRHSI states, quantum image processing, and quantum image compression. Additionally, the study evaluates EQIRHSI’s performance by analyzing six images. The results demonstrate that EQIRHSI achieves an average compression rate of 83.91%, surpassing the MCQI model by 1.2 times.
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Acknowledgements
This work is supported by the Heilongjiang Provincial Natural Science Foundation (CN) (LH2022F032) and the Shandong Provincial Natural Science Foundation (CN) (ZR2022LLZ003). This work also was supported by the EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia. Also, Ahmed A. Abd El-Latif acknowledges the Talented Young Scientist Program: TYSP for their support.
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Li, M., Song, X. & El-Latif, A.A.A. EQIRHSI: enhanced quantum image representation using entanglement state encoding in the HSI color model. Quantum Inf Process 22, 334 (2023). https://doi.org/10.1007/s11128-023-04092-0
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DOI: https://doi.org/10.1007/s11128-023-04092-0