Zhang Wei, Li Siwei, Yang Zhigang, Yu Bin, Lin Danying, Xiong Jia, Qu Junle
Center for Biomedical Photonics & College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China.
Biomed Opt Express. 2020 Jun 9;11(7):3648-3658. doi: 10.1364/BOE.396336. eCollection 2020 Jul 1.
Deconvolution technique has been widely used in fluorescence microscopy to restore fine structures of biological samples. However, conventional deconvolution methods usually achieve little contrast enhancement in dense structures that have the intervals close to the Rayleigh criterion. Herein, we developed a novel deconvolution method, termed virtual single-pixel imaging (-SPI). Differing from existing deconvolution methods, -SPI aims to retrieve the less blurred image directly, not the sample distribution which cannot be actually obtained. And the result can be retrieved simply by solving a linear matrix in spatial domain. In addition, the proposed method has no requirement of calibrating parameters of microscope system. Simulation and experimental results demonstrated that the proposed -SPI method can enhance the contrast of dense structures significantly and acquire a 24% increase in resolution.
反卷积技术已在荧光显微镜中广泛应用，用于恢复生物样本的精细结构。然而，传统的反卷积方法在间隔接近瑞利判据的密集结构中通常几乎无法实现对比度增强。在此，我们开发了一种新型反卷积方法，称为虚拟单像素成像（-SPI）。与现有的反卷积方法不同，-SPI旨在直接检索模糊程度较低的图像，而非实际上无法获得的样本分布。并且通过在空间域求解一个线性矩阵即可简单地检索出结果。此外，该方法无需校准显微镜系统的参数。模拟和实验结果表明，所提出的 -SPI方法能够显著增强密集结构的对比度，并使分辨率提高24%。
