An Efficient Adaptive Weighted Switching Median Filter for Removing High Density Impulse Noise

Abstract

Restoration of images corrupted by impulse noise is a very active research area in image processing. In this paper, an Efficient Adaptive Weighted Switching Median filter for restoration of images that are corrupted by high density impulse noise is proposed. The filtering is performed as a two phase process-a detection phase followed by a filtering phase. In the proposed method, noise detection is done by HEIND algorithm proposed by Duan et al. The filtering algorithm is then applied to the pixels which are detected as noisy by the detection algorithm. All uncorrupted pixels in the image are left unchanged. The filtering window size is chosen adaptively depending on the local noise distribution around each corrupted pixels. Noisy pixels are replaced by a weighted median value of uncorrupted pixels in the filtering window. The weight value assigned to each uncorrupted pixels depends on its closeness to the central pixel.

Adaptive Sequentially Weighted Median Filter for Image Highly Corrupted by Impulse Noise

“…As improved versions of switching median or mean filter, weighted filters [19]- [24] remove impulse noise by taking the weighted median or mean of neighbor noise free pixels with a weighted operator, differentiating the contributions and impacts of neighbor pixels on the central pixel by weighted processing so as to achieve a better denoising result. The adaptive dynamically weighted median filter (ADWMF) [22] estimates the intensity of noisy pixel by employing the weighted median of a neighborhood of adaptive size; the weighted operator employed is derived from Gaussian surface.…”

Comparative analysis of Median filter family for Removing High-Density Noise in Magnetic Resonance Images

“…This filter has two stages; the first stage contains the detection of impulse noises using decision criteria while in the second stage the AMF is performed on the corrupted pixels without changing the good pixels. In the window of filter, noisy pixels are supplanted by the weighted median of clean pixels [7].…”