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Histogram Driven Amplitude Embedding for Qubit Efficient Quantum Image Compression

Published: September 5, 2025 | arXiv ID: 2509.04849v1

By: Sahil Tomar, Sandeep Kumar

Potential Business Impact:

Shrinks color pictures using quantum computers.

Business Areas:
Quantum Computing Science and Engineering

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.

Page Count
7 pages

Category
Physics:
Quantum Physics