Reducing the Periodic Noise Effects in Digital Image by an Adaptive Median Filter in the Frequency Domain

Periodic noises are repetitive patterns on digital images and decreased the visual quality of images. The various methods for reducing the effects of the periodic noise in digital images are firstly investigated. Then an intelligent median filter in the frequency domain with an acceptable computational cost is proposed. In the proposed method, the regions of noise frequencies are determined by analyzing intelligently the spectral of noisy image. Then only for the destroyed frequencies by periodic noise, a median filter with proper size in the frequency domain is applied and the spectrum of the image with reduced periodic noise is computed. The compared methods including the proposed method, the mean and the median filtering techniques, all in frequency domain are implemented not only under MATLAB environment, but also by C programming under OpenCV library. The results in different conditions show that the proposed filter shows higher performances, visually and statistically, and also in needs very lower computational cost.