
IMAGE QUALITY ENHANCEMENT USING FILTERING METHODS
Bakhromov Khasan , Lecturer at Tashkent University of Applied SciencesAbstract
In my research, I explore methods for improving image quality using frequency-domain analysis and the Fourier transform. The study focuses on the application of frequency filtering techniques for noise suppression, distortion reduction, and enhancement of image sharpness. The article examines the operation principles of low-pass, high-pass, and band-pass filters, including Gaussian and Butterworth filters, as well as their implementation using the Discrete Fourier Transform (DFT).
Through a series of experiments, I demonstrated how frequency filtering allows selective manipulation of spectral image components, thereby enhancing contrast and fine details. The obtained results indicate the high effectiveness of Fourier-based filtering methods in processing images affected by various types of noise and blurring, confirming their practical importance for medical imaging, satellite observation, and computer vision applications.
Keywords
Fourier transform, frequency filtering, noise reduction, image enhancement, Gaussian filter, Butterworth filter, frequency spectrum.
References
Gonzalez, R., & Woods, R. Digital Image Processing. Technosphere Publishing, 2018.
Brown, L. Advanced Filtering Techniques for Image Processing. Journal of Visual Computing, 2021.
Zhang, Y. Deep Learning Approaches for Image Enhancement. IEEE Transactions on Image Processing, 2022.
Smith, J. AI-Powered Image Filtering. Journal of Machine Learning, 2023.
Liu, M. Bilateral Filtering for Image Denoising. Springer, 2020.
Jain, A. K. Fundamentals of Digital Image Processing. Prentice Hall, 1989.
Oppenheim, A. V., & Schafer, R. W. Discrete-Time Signal Processing. Pearson, 2010.
Castleman, K. R. Digital Image Processing. Prentice Hall, 1996.
Gonzalez, R., & Woods, R. Fourier Transform and Frequency-Domain Filtering. In Digital Image Processing, 4th edition, 2018.
Pratt, W. K. Digital Image Processing: PIKS Scientific Inside. Wiley, 2007.
Article Statistics
Downloads
Copyright License

This work is licensed under a Creative Commons Attribution 4.0 International License.