| 要約: | This paper proposes a novel quantum image transmission framework to address the limitations of existing single-qubit time domain systems, which struggle with noise resilience and scalability. The framework integrates frequency domain processing with multi-qubit (1 to 8 qubits) encoding to enhance robustness against quantum noise. Initially, images are source-coded using JPEG and HEIF formats with rate adjustment to ensure consistent bandwidth usage. The resulting bitstreams are channel-encoded and mapped to multi-qubit quantum states. These states are transformed into the frequency domain via the quantum Fourier transform (QFT) for transmission. At the receiver, the inverse QFT recovers the time domain states, followed by multi-qubit decoding, channel decoding, and source decoding to reconstruct the image. Performance is evaluated using bit error rate (BER), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and universal quality index (UQI). Results show that increasing the number of qubits enhances image quality and noise robustness, albeit at the cost of increased system complexity. Compared to time domain processing, the frequency domain approach achieves superior performance across all qubit configurations, with the eight-qubit system delivering up to a 4 dB maximum channel SNR gain for both JPEG and HEIF images. Although single-qubit systems benefit less from frequency domain encoding due to limited representational capacity, the overall framework demonstrates strong potential for scalable and noise-robust quantum image transmission in future quantum communication networks.
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