Image restoration model for microscopic defocused images based on blurring kernel guidance.

Defocus blurring imaging seriously affects the observation accuracy and application range of optical microscopes, and the blurring kernel function is a key parameter for high-resolution image restoration. However, its solving process is complicated and high in computational cost. Image restoration based on most neural networks has high requirements on data sets and the image resolution after restoration is limited because of the lack of quantitative estimation of blurring kernels.

Evaluating the resolution of conventional optical microscopes through point spread function measurement.

In the imaging process of conventional optical microscopy, the primary factor hindering microscope resolution is the energy diffusion of incident light, most directly described by the point spread function (PSF). Therefore, accurate calculation and measurement of PSF are essential for evaluating and enhancing imaging resolution. Currently, there are various methods to obtain PSFs, each with different advantages and disadvantages suitable for different scenarios.

Three-dimensional modelling of blur property for conventional optical microscopes.

Intensity diffusion caused by optical diffraction limits the imaging resolution of conventional optical microscopes, therefore modelling and measuring the intensity transmission and distribution property of the light sources is a significant research topic in system development and pattern recognition. However, the complicated wave propagation process in optical imaging makes it difficult to provide a direct, analytical and simple mathematical model to measure the relationship between the blur degree and various camera parameters. In this study, an improved intensity transmission and distribution calculation method for conventional optical microscopes was proposed; furthermore, a simple mathematical relation between the blur degree and camera parameters was achieved based on the proposed method.