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An effective anisotropic diffusion (AD) mean filter variant is proposed for filtering of salt -and-pepper impulse noise. The implemented filter is robust to impulse noise ranging from low to high density levels. The algorithm involves a switching scheme in addition to utilizing the unsymmetric trimmed mean/median deviation to filter image noise while greatly preserving image edges, regardless of impulse noise density (ND). It operates with threshold parameters selected manually or adaptively estimated from the image statistics. It is further combined with the partial differential equations (PDE)-based AD for edge preservation at high NDs to enhance the properties of the trimmed mean filter. Based on experimental results, the proposed filter easily and consistently outperforms the median filter and its other variants ranging from simple to complex filter structures, especially the known PDE-based variants. In addition, the switching scheme and threshold calculation enables the filter to avoid smoothing an uncorrupted image, and filtering is activated only when impulse noise is present. Ultimately, the particular properties of the filter make its combination with the AD algorithm a unique and powerful edge-preservation smoothing filter at high-impulse NDs. © 2016 SPIE and IS&T [DOI: 10.1117/1.JEI.25.4.043001] [ABSTRACT FROM AUTHOR]

A new switching-based trimmed median filter to remove high-density salt-and-pepper noise in digital images is proposed. Initially, a 3 x 3 sliding window is applied on each pixel in the noisy image. The minimum-and maximum-intensity values are trimmed, and the noisy pixels are detected based on the predefined threshold value. In the filtering stage, the noisy pixels are replaced by median value of uncorrupted pixels in the trimmed array. At very high noise density, if all the pixels in the sliding window are corrupted, then the proposed algorithm replaces noisy pixels by the midpoint of recently processed pixels. The experimental results for various test images show that the performance of the proposed algorithm is superior to the existing algorithms, namely SMF, WMF, CWMF, AMF, DBA, and MDBUTMF in terms of visual quality and edge preservation, even at noise levels as high as 95%. [ABSTRACT FROM AUTHOR]