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Most practical users of optical microscopy think in terms of magnification and resolution. Magnification refers to the ratio of the distances between two points in the sample and to those in its image. Resolution refers to the distance between two points in the sample that appear as two distinguishable points in the image. The image itself is an interference phenomenon formed by an optical system, which we usually assess in a plane called the focal plane. In digital microscopy (but also in observation with the human eye), another factor is the size of the sensor element. In the last 15 years, digital cameras with sensors of the size of a 35mm film frame and larger have begun to appear on the market. Extreme sensors with 250 and 410 million optical elements (250 and 410 Mpx) exceed the total number of elements in both human eyes. In addition, there have been significant developments in the design and manufacture of optical systems, particularly influenced by applications in the production of mobile phones and silicon chips. In the latter application, the resulting image is composed of fine structures with a resolution below the theoretical limit of light microscopy and thus appears completely different from the original image template, which was a spot. A separate chapter are the design of the sensors themselves, the quality and distribution of filters, and the like. The aim of developing large-area digital optical microscopy (LADOM) was to extract as much information as possible from the digital image, regardless of the microscope's sensor, lens, or illumination system design. To achieve this, we must first (1) find a focal plane that displays as many distinguished objects as possible. Eventually, we have developed a method for calculating the point divergence gain entropy density [1], a completely new concept for using information entropy to compare large data sets. (2) Another problem is distinguishing between two points. In a grayscale image showing only intensities, the condition for distinguishing between two objects is a combination of the Abbe model (which determines the condition for distinguishing between two adjacent lines on a grid) and the Shannon-Nyquist sampling condition (which determines how many points need to be observed for a given object in order to determine its position). A color image, which is actually a result of the measurement by a color camera (that serves as a spatially resolved colorimeter), contains much more information, especially when combined with knowledge of the incident radiation spectrum, the spectrum of individual filters, and possibly even color errors in the optical system. We showed [2] that it is possible to estimate the absorption/reflection spectrum at each image point. (3) This makes each point a carrier of individual information, with the accuracy limited only by experimental setup. In LADOM microscopy, we have been able to record images of a steel alloy with a 2 × 3 mm2 area at a real resolution of 120 × 120 nm2. The information is currently limited only by the properties of the illumination system. However, the current technical limit is 75 × 75 nm2, which gives us a 1-Gpx image. In this way, we can observe physical and chemical properties of a crystalline assembly of about 480 iron atoms. References: [1] Rychtáriková, R., Korbel, J., Macháček, P., & Štys, D. (2018). Point Divergence Gain and Multidimensional Data Sequences Analysis. Entropy, 20(2), 106. [2] Lonhus, K., Rychtáriková, R., Platonova, G., & Štys, D. (2020). Quasi-spectral Characterization of Intracellular Regions in Bright-field Light Microscopy Images. Sci Rep 10, 18346.
Keywords: large-area high-resolution light microscopy, light microscopy imaging, steel© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.