## 1 Introduction  
Classical optical microscopy is one of the foundations of medical and biological research [1, 2]. The classic solution is based on the human eye and many methods have been used to improve the image quality in order to highlight the desired features. Various physical methods are used, such as microstructure illumination methods, work with the handling of filters, including the use of multispectral and hyperspectral methods, as well as biochemical methods, where image segmentation is performed using dedicated staining [3].  
An extremely important element in the development of microscopy, although often overlooked, is the change in the method of image analysis. The introduction of computer image analysis methods combined with knowledge-based methods, in particular machine learning methods [4], allows one to extend the possibilities of microstructure analysis. Improving image quality or extracting essential features is not only essential for systems that perform automatic analysis, but also for human specialists using CADx (computer aided diagnosis) systems [5; 6]. This possibly essential part of the important information in a digital image is available but is not visible to the human eye, or its microstructure is too complex for the human brain, even a trained specialist, to analyze.  
A typical solution used in classical microscopy is the use of dedicated staining and a bright field microscope [7]. In this configuration, an ordinary lamp (halogen or LED) is the light source that passes through the slide, and then, when magnified by an optical system, is visible to the eye or the camera sensor. This solution is cheap and does not quickly degrade the microstructure in the slide.  
The development of the image acquisition technique has led to the expansion of microstructure acquisition methods not only in the visible light spectrum. One of the known methods of image acquisition is fluorescence microscopy [8; 9]. This method uses a lamp with a UV light which excites the sample when it hits the sample. As a result of this excitation, light is emitted of a different wavelength, which is observed by the optical system of the microscope. This technique can be used when the observer is a human if the wavelength is within the sensitivity of the human eye. The use of a digital camera enables the analysis of wavelengths outside the sensitivity range of the human eye's light spectrum.  
The most important disadvantages of fluorescence microscopy [7] are photobleaching and photo damage of observed tissue [10; 11; 12]. These processes are not fully understood and manifest themselves by burning off the observed material. This means that a longer observation of the same section of a slide results in a gradual irreversible destruction of the microstructures. It depends on the wavelength--the shorter the wavelength, the faster the process is. This is especially troublesome in research where the same structures are often required for analyses. The use of digital microscopy with the use of a slide scanner reduces this problem because the acquisition is done once and the analysis is performed on the computer screen. Unfortunately, both fluorescent microscopes and fluorescent slide scanners are much more expensive than typical microscopes. An exemplary reason is the cost of dedicated lenses.