Direction based adaptive weighted switching median filter for removing high density impulse noise

Restoration of images corrupted by impulse noises is a very common problem in the image processing. An efficient direction based adaptive weighted switching median filter for restoration of images corrupted by high density impulse noise is proposed in this paper. The filtering process consists of two phases – detection phase followed by a filtering phase. The detection phase in the proposed method uses HEIND algorithm put forward by Fei Duan et al. After detecting noisy pixel positions in the image, filtering algorithm is applied to those detected pixels. All uncorrupted pixels in the image are left unchanged by the filtering algorithm. The filtering algorithm uses uncorrupted pixels in the selected four directions for taking a decision on the filtering window size. Noisy pixels are replaced by a weighted median value of uncorrupted pixels in the filtering window or directional filtering window. The weight value assigned to each uncorrupted pixels depends on its closeness to the central corrupted pixel in the current filtering window.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► Direction based adaptive weighted switching median filter for image restoration is proposed. ► It is a switching median filter with two phases – detection phase and filtering phase. ► Detection phase uses HEIND algorithm proposed by Fei Duan et al. ► Filtering phase uses uncorrupted pixels in the selected four directions for deciding the filtering window size. ► Noisy pixels are replaced by a weighted median value of uncorrupted pixels in the filtering window.