Felbontásnövelésre

Felbontásnövelésre, often translated as resolution enhancement, refers to techniques used to improve the effective resolution of an image or signal. This is particularly relevant in fields like microscopy, imaging, and digital signal processing where the inherent limitations of the capturing or sampling equipment may restrict the level of detail discernible. While a system might have a physical resolution limit, felbontásnövelésre aims to overcome this by inferring finer details that are not directly sampled.

Common methods for felbontásnövelésre involve computational algorithms. These can include deconvolution techniques, which attempt to reverse the blurring effect caused by the imaging system's point spread function. Super-resolution algorithms, a more advanced form of felbontásnövelésre, reconstruct a high-resolution image from multiple lower-resolution inputs, often by exploiting sub-pixel shifts or combining information from different measurements. These techniques are widely applied in scientific research, such as in optical microscopy to visualize cellular structures with greater clarity, and in consumer electronics to enhance the quality of photographs and videos. The goal is always to extract more information than would be apparent at the native resolution.