Histogram Driven Amplitude Embedding for Qubit Efficient Quantum Image Compression
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866915480352063488 |
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| author | Tomar, Sahil Kumar, Sandeep |
| author_facet | Tomar, Sahil Kumar, Sandeep |
| contents | This work introduces a compact and hardware efficient method for compressing color images using near term quantum devices. The approach segments the image into fixed size blocks called bixels, and computes the total intensity within each block. A global histogram with B bins is then constructed from these block intensities, and the normalized square roots of the bin counts are encoded as amplitudes into an n qubit quantum state. Amplitude embedding is performed using PennyLane and executed on real IBM Quantum hardware. The resulting state is measured to reconstruct the histogram, enabling approximate recovery of block intensities and full image reassembly. The method maintains a constant qubit requirement based solely on the number of histogram bins, independent of the resolution of the image. By adjusting B, users can control the trade off between fidelity and resource usage. Empirical results demonstrate high quality reconstructions using as few as 5 to 7 qubits, significantly outperforming conventional pixel level encodings in terms of qubit efficiency and validating the practical application of the method for current NISQ era quantum systems. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2509_04849 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Histogram Driven Amplitude Embedding for Qubit Efficient Quantum Image Compression Tomar, Sahil Kumar, Sandeep Quantum Physics Computer Vision and Pattern Recognition Emerging Technologies Information Theory This work introduces a compact and hardware efficient method for compressing color images using near term quantum devices. The approach segments the image into fixed size blocks called bixels, and computes the total intensity within each block. A global histogram with B bins is then constructed from these block intensities, and the normalized square roots of the bin counts are encoded as amplitudes into an n qubit quantum state. Amplitude embedding is performed using PennyLane and executed on real IBM Quantum hardware. The resulting state is measured to reconstruct the histogram, enabling approximate recovery of block intensities and full image reassembly. The method maintains a constant qubit requirement based solely on the number of histogram bins, independent of the resolution of the image. By adjusting B, users can control the trade off between fidelity and resource usage. Empirical results demonstrate high quality reconstructions using as few as 5 to 7 qubits, significantly outperforming conventional pixel level encodings in terms of qubit efficiency and validating the practical application of the method for current NISQ era quantum systems. |
| title | Histogram Driven Amplitude Embedding for Qubit Efficient Quantum Image Compression |
| topic | Quantum Physics Computer Vision and Pattern Recognition Emerging Technologies Information Theory |
| url | https://arxiv.org/abs/2509.04849 |