Mu Jiale, Li Xiaofei, Zhang Xianghua, Wang Pinghe
School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Department of Electrical and Information Engineering, Hunan Institute of Engineering, Xiangtan, 411101, China.
Sci Rep. 2025 Jan 2;15(1):493. doi: 10.1038/s41598-024-84211-8.
Image filtering involves the application of window operations that perform valuable functions, such as noise removal, image enhancement, high dynamic range (HDR) compression, and so on. Guided image filtering is a new type of explicit image filter with multiple advantages. It can effectively remove noise while preserving edge details, and can be used in a variety of scenarios. Here, we report a quantum implementation of guided image filtering algorithm, based on the novel enhanced quantum representation (NEQR) model, and the corresponding quantum circuit has been designed. We find that the speed and quality of filtering are improved significantly due to the quantization, and the time complexity is reduced exponentially from to .
图像滤波涉及执行诸如噪声去除、图像增强、高动态范围(HDR)压缩等有价值功能的窗口操作的应用。引导图像滤波是一种具有多种优势的新型显式图像滤波器。它可以在保留边缘细节的同时有效去除噪声,并且可用于各种场景。在此,我们报告了基于新型增强量子表示(NEQR)模型的引导图像滤波算法的量子实现,并设计了相应的量子电路。我们发现,由于量化,滤波的速度和质量得到了显著提高,时间复杂度从 呈指数级降低到 。