The contemporary trends in professional education within higher education institutions necessitate the utilization of contemporary computer technologies. The effective application of computational resources for the resolution of mathematical and applied problems facilitates the acceleration of results and the expansion of the range of investigated problems. This paper presents an analysis of the applied study of Fourier series in the context of their use for image processing. Mathematical methods based on the theory of continuous and discrete Fourier transforms have a variety of applications, including in the fields of acoustics, optics, electrical engineering, and signal and image processing. The authors investigate a methodology for executing the two-dimensional Fourier transform through the utilization of the Python programming language. Additionally, they elucidate and delineate algorithms and instruments for enhancing image quality through the implementation of diverse filtering techniques. The objective of this study is to cultivate proficiency in mathematical and computer modelling techniques for the resolution of practical issues, such as those pertaining to signal and image processing. Specific focus is dedicated to the enhancement and scaling of images through the utilization of two-dimensional Fourier transform, employing the Python programming language and dedicated mathematical operations, image processing and data visualization libraries.