电镜图像的量子衍生增强算法

在量子信息处理框架下,从像素灰度归一化、像素量子态表示、量子测量、测量结果映射等方面,总结了现有量子衍生图像增强算法的处理流程。以 SARS-CoV-2 新冠病毒电镜图像增强为样本,结合实验分析,改进了量子衍生增强算子的加权方式,提出了灰度变换可调参数优化值的非迭代式确定算子。实验结果表明,量子衍生增强算法综合考虑了电镜图像的全局与局部信息,兼顾了对电镜图像对比度与亮度的调节,图像细节清晰、明暗适宜。

Quantum-inspired Enhancement Algorithms of Electron Microscope Images

Under the framework of quantum information processing, the processing procedures of existing quantum-derived image enhancement algorithms are summarized from the aspects of pixel grayscale normalization, pixel quantum state representation, quantum measurement, and measurement result mapping. Taking the SARS-CoV-2 new coronavirus electron microscope image enhancement as a sample, combined with experimental analysis, the weighting method of the quantum derived enhancement operator is improved, and a non-iterative determination operator for the optimized value of the adjustable parameter of the gray scale transformation is proposed. The experimental results show that the quantum-derived enhancement algorithm comprehensively considers the global and local information of the electron microscope image, takes into account the adjustment of the contrast and brightness of the electron microscope image, and enhances the image with clear details and appropriate brightness.