Hybrid Quantum Image Preparation via JPEG Compression

TL;DR

This paper introduces a hybrid classical-quantum image loading method called JQPIE that significantly reduces quantum circuit complexity while maintaining image quality, using JPEG compression techniques.

Contribution

The paper proposes a novel hybrid quantum image preparation scheme that leverages JPEG compression to lower quantum resource requirements, including two variants for efficient quantum image loading.

Findings

Both variants reduce CX gate count and circuit depth significantly.

High image reconstruction quality is preserved, as shown by PSNR and SSIM metrics.

Numerical simulations confirm the effectiveness on benchmark datasets.

Abstract

We present a hybrid classical-quantum image preparation scheme that reduces the quantum implementation cost of image loading for quantum pixel information encoding (QPIE). The proposed method, termed JPEG-assisted QPIE (JQPIE), loads only the quantized JPEG coefficients into a quantum register, leading to substantial reductions in \texttt{CX} gate count and circuit depth while preserving reconstruction quality comparable to classical JPEG compression. We develop two variants of the hybrid strategy. The first realizes the complete JPEG decompression pipeline coherently by implementing inverse quantization via a block-encoded unitary operator. The second, referred to as \emph{quantization-free JQPIE} (QF-JQPIE), omits quantization altogether, thereby avoiding the probabilistic nature of block-encoded quantization. Numerical simulations on standard benchmark image datasets (USC--SIPI and Kodak) demonstrate that both variants achieve significant constant-factor reductions in \texttt{CX} gate count and circuit depth relative to direct QPIE loading, while maintaining high reconstruction quality as measured by PSNR and SSIM.