标题： 基于泰勒展开的快速量子图像压缩算法 显示英文标题

标题： A Fast Quantum Image Compression Algorithm based on Taylor Expansion

摘要： 随着存储图像需求的增加，传统图像压缩方法在平衡压缩大小和图像质量方面面临挑战。 然而，混合量子-经典模型可以通过利用量子位的优势来弥补这一弱点。 在本研究中，我们在参数化量子电路中升级了一种量子图像压缩算法。 我们的方法将图像数据编码为单位运算符参数，并应用量子编译算法来模拟加密过程。 通过利用一阶泰勒展开，我们显著降低了计算成本和损失，优于之前的版本。 在基准图像（包括Lenna和Cameraman）上的实验结果表明，我们的方法在保持较低压缩损失的同时，将迭代次数减少了高达86%，这对于高分辨率图像更为有利。 结果证实，所提出的算法提供了一种高效且可扩展的图像压缩机制，使其成为未来图像处理应用的有前景的候选方案。 显示英文摘要

摘要： With the increasing demand for storing images, traditional image compression methods face challenges in balancing the compressed size and image quality. However, the hybrid quantum-classical model can recover this weakness by using the advantage of qubits. In this study, we upgrade a quantum image compression algorithm within parameterized quantum circuits. Our approach encodes image data as unitary operator parameters and applies the quantum compilation algorithm to emulate the encryption process. By utilizing first-order Taylor expansion, we significantly reduce both the computational cost and loss, better than the previous version. Experimental results on benchmark images, including Lenna and Cameraman, show that our method achieves up to 86\% reduction in the number of iterations while maintaining a lower compression loss, better for high-resolution images. The results confirm that the proposed algorithm provides an efficient and scalable image compression mechanism, making it a promising candidate for future image processing applications.