An adaptive median filtering denoising algorithm for pepper and salt noised image
Fengqing Qin, Li Jiang, Liman Xie, Lilan Cao, Lihong Zhu, Chaorong Li, Yanhong Zhang, Xingdong Wen · Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021) · 2022
There are different degrees of “pepper γ salt” noise in most acquired images. To overcome the shortcomings of traditional median filtering algorithm, an adaptive median filtering algorithm is proposed. Firstly, the appropriate filter window size is automatically selected according to the intensity of noise in the image. Secondly, whether each pixel is a noise point is judged. The noise point outputs the median value and the non-noise point outputs the original value. Thirdly, the denoising effect of the two algorithms was compared by simulation experiments, and the influence of different “pepper & salt” noise density on denoising effect was tested. From the perspective of subjective visual effect and objective PSNR value, the denoising effect of adaptive median filtering is better than that of traditional median filtering.