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IEEE Transactions on Communications

Complex-Valued Orthogonal Unitary Superposition Encoding-Based Multi-Qubit System for Quantum Image Transmission

Udara Jayasinghe, Thanuj Fernando, Anil Fernando

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.1109/tcomm.2026.3742846

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Complex-valued orthogonal unitary superposition encoding-based multi-qubit system for quantum image transmission

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Reliable high-fidelity image transmission over noisy quantum channels remains a significant challenge, especially under bandwidth constraints, where the use of quantum error correction is often impractical due to its high computational and implementation complexity. Existing encoding schemes, such as Hadamard-based encoding, often exhibit limited noise resilience and low information capacity, reducing their effectiveness for compressed image transmission in high-noise environments. To address these issues, we propose a multi-qubit quantum image transmission framework employing complex-valued orthogonal unitary superposition (COUS) encoding based on the established phase–Hadamard–phase (SHS) unitary transformation, enabling joint amplitude and phase representation for improved robust ness against noise. Input images are first compressed using JPEG or HEIF and channel-encoded using polar codes before being mapped into multi-qubit COUS states for transmission. At the receiver, quantum states are sequentially COUS decoded, channel decoded, and source decoded to reconstruct the images. The system is evaluated through simulations under noisy quantum channel conditions. System performance is analyzed using peak signal-to-noise ratio (PSNR), structural similarity index mea sure (SSIM), and universal quality index (UQI). Simulation re sults demonstrate that COUS encoding consistently outperforms Hadamard-based encoding, achieving up to 4 dB channel SNR gain even with a single-qubit configuration, while higher-qubit configurations further enhance robustness and image quality. These results highlight COUS as a scalable, low-complexity, and noise-resilient approach for high-fidelity quantum image transmission.

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Reliable, high-fidelity image transmission in consumer electronics remains a challenge, particularly over noisy or bandwidth-limited channels. While quantum communication offers potential solutions, conventional single-qubit encoding schemes are limited by low state diversity and noise resilience, reducing their effectiveness for compressed image transmission. To address this, we propose Complex-Valued Orthogonal Unitary Superposition (COUS) encoding, which employs complex-valued superposition to generate highly noise-resilient quantum states within a single-qubit framework. The images are first source encoded using JPEG or HEIF and undergo classical channel coding. The resulting data are quantum encoded via COUS and transmitted over noisy channels. At the receiver, quantum states are sequentially COUS-decoded, channel-decoded, and source-decoded to reconstruct the images. System performance is evaluated using Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Universal Quality Index (UQI). The results show that COUS encoding significantly improves image quality and noise resilience, achieving up to 3 dB channel SNR gain over advanced Quantum Fourier Transform (QFT)-based encodings, 4 dB gain over Hadamard encoding, and 6 dB gain relative to equivalent-bandwidth classical systems, demonstrating its potential for reliable, high-fidelity quantum image transmission regardless of image format.

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Reliable high-fidelity video transmission over noisy quantum channels remains challenging, especially due to temporal dependencies introduced by modern video compression standards. These codecs, such as versatile video coding (VVC), employ inter-frame prediction and group-of-pictures (GOP) structures, which are highly sensitive to channel noise and can lead to error propagation across frames. Conventional quantum encoding schemes, such as Hadamard-based superposition encoding, use fixed real-valued basis transformations that provide limited phase diversity and underutilize the multi-qubit state-space, reducing robustness under noisy quantum channels. To overcome these limitations, this study proposes a multi-qubit complex-valued orthogonal unitary superposition (COUS) encoding framework for quantum video transmission. In the proposed system, VVC-compressed video bitstreams are first protected using classical channel encoding, then segmented and mapped onto multi-qubit COUS quantum states, enabling joint amplitude and phase representation with improved resilience to quantum noise. At the receiver, transmitted quantum states undergo sequential COUS decoding, channel decoding, and VVC bitstream reconstruction to recover the original video frames. The simulation results show that COUS-based multi-qubit system outperforms the Hadamard encoding-based multi-qubit system, achieving peak signal-to-noise ratio (PSNR) up to 47.22 dB, structural similarity index measure (SSIM) up to 0.9905, and video multi-method assessment fusion (VMAF) up to 96.49. Even single-qubit COUS encoding achieves 3–4 dB channel SNR gain, while higher-qubit configurations further enhance robustness and reconstructed video quality. These results confirm that the proposed framework is scalable, noise-resilient, and provides high-fidelity quantum video transmission over noisy channels.

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Reliable high-fidelity image transmission over noisy quantum channels remains a significant challenge, especially under bandwidth constraints, where the use of quantum error correction is often impractical due to its high computational and implementation complexity. Existing encoding schemes, such as Hadamard-based encoding, often exhibit limited noise resilience and low information capacity, reducing their effectiveness for compressed image transmission in high-noise environments. To address these issues, we propose a multi-qubit quantum image transmission framework employing complex-valued orthogonal unitary superposition (COUS) encoding based on the established phase–Hadamard–phase (SHS) unitary transformation, enabling joint amplitude and phase representation for improved robust ness against noise. Input images are first compressed using JPEG or HEIF and channel-encoded using polar codes before being mapped into multi-qubit COUS states for transmission. At the receiver, quantum states are sequentially COUS decoded, channel decoded, and source decoded to reconstruct the images. The system is evaluated through simulations under noisy quantum channel conditions. System performance is analyzed using peak signal-to-noise ratio (PSNR), structural similarity index mea sure (SSIM), and universal quality index (UQI). Simulation re sults demonstrate that COUS encoding consistently outperforms Hadamard-based encoding, achieving up to 4 dB channel SNR gain even with a single-qubit configuration, while higher-qubit configurations further enhance robustness and image quality. These results highlight COUS as a scalable, low-complexity, and noise-resilient approach for high-fidelity quantum image transmission.
Reliable, high-fidelity image transmission in consumer electronics remains a challenge, particularly over noisy or bandwidth-limited channels. While quantum communication offers potential solutions, conventional single-qubit encoding schemes are limited by low state diversity and noise resilience, reducing their effectiveness for compressed image transmission. To address this, we propose Complex-Valued Orthogonal Unitary Superposition (COUS) encoding, which employs complex-valued superposition to generate highly noise-resilient quantum states within a single-qubit framework. The images are first source encoded using JPEG or HEIF and undergo classical channel coding. The resulting data are quantum encoded via COUS and transmitted over noisy channels. At the receiver, quantum states are sequentially COUS-decoded, channel-decoded, and source-decoded to reconstruct the images. System performance is evaluated using Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Universal Quality Index (UQI). The results show that COUS encoding significantly improves image quality and noise resilience, achieving up to 3 dB channel SNR gain over advanced Quantum Fourier Transform (QFT)-based encodings, 4 dB gain over Hadamard encoding, and 6 dB gain relative to equivalent-bandwidth classical systems, demonstrating its potential for reliable, high-fidelity quantum image transmission regardless of image format.
Reliable high-fidelity video transmission over noisy quantum channels remains challenging, especially due to temporal dependencies introduced by modern video compression standards. These codecs, such as versatile video coding (VVC), employ inter-frame prediction and group-of-pictures (GOP) structures, which are highly sensitive to channel noise and can lead to error propagation across frames. Conventional quantum encoding schemes, such as Hadamard-based superposition encoding, use fixed real-valued basis transformations that provide limited phase diversity and underutilize the multi-qubit state-space, reducing robustness under noisy quantum channels. To overcome these limitations, this study proposes a multi-qubit complex-valued orthogonal unitary superposition (COUS) encoding framework for quantum video transmission. In the proposed system, VVC-compressed video bitstreams are first protected using classical channel encoding, then segmented and mapped onto multi-qubit COUS quantum states, enabling joint amplitude and phase representation with improved resilience to quantum noise. At the receiver, transmitted quantum states undergo sequential COUS decoding, channel decoding, and VVC bitstream reconstruction to recover the original video frames. The simulation results show that COUS-based multi-qubit system outperforms the Hadamard encoding-based multi-qubit system, achieving peak signal-to-noise ratio (PSNR) up to 47.22 dB, structural similarity index measure (SSIM) up to 0.9905, and video multi-method assessment fusion (VMAF) up to 96.49. Even single-qubit COUS encoding achieves 3–4 dB channel SNR gain, while higher-qubit configurations further enhance robustness and reconstructed video quality. These results confirm that the proposed framework is scalable, noise-resilient, and provides high-fidelity quantum video transmission over noisy channels.