X-ray imaging is essential for medical diagnosis, allowing healthcare practitioners to detect and analyze a wide range of illnesses. However, X-ray images often suffer from inherent limitations, including noise and low contrast, which can hide accurate interpretation and diagnosis. To address these challenges, this research paper introduces a novel approach that utilizes frequency domain filters to enhance X-ray image quality. By leveraging the power of frequency analysis, these filters aim to selectively manipulate the frequency components of X-ray images, resulting in improved image clarity, noise reduction, and enhanced diagnostic information. The other part of the paper is structured as follows: Sect. 1 includes: a comprehensive introduction of spatial domain filtering and frequency domain filtering methods. Section 2 provides an introduction of the introduced algorithm. Section 3 presents a review of the existing literature on X-ray image enhancement techniques using frequency domain methods. Section 4 contains the experimental setup, including methodology. Section 5 provides in-depth explanation of frequency domain filters and their applicability to X-ray images. Section 6 contains the dataset used. Section 7 presents and discusses the results of the experiments with the help of graph. Section 8 comprises research gap. Finally, Sect. 9 concludes the paper, highlighting the significance of the findings and suggesting future directions for research in this field.