Modeling and analysis of a quantized median filtering method for digital image denoising
Abstract
This paper addresses the problem of digital image denoising using a median filtering method based on concepts inspired by quantum computing. In the proposed approach, pixel values are encoded in a manner analogous to quantum states, and their distribution is processed using the Quantum Fourier Transform. The median value estimation is performed based on a probabilistic distribution, which enables a direct comparison with the classical median filtering technique. Artificial noise is added to the images, and the quality of the images before and after filtering is evaluated using objective quality metrics. The experimental results demonstrate that the proposed quantum median filtering model provides a positive effect in restoring image quality and effectively reduces the impact of noise. This approach highlights the potential of applying quantum-inspired computational methods in the field of digital image processing.