Restoration of highly salt-and-pepper-noise-corrupted images using novel adaptive trimmed median filter

The paper presents a novel adaptive trimmed median (ATM) filter to remove salt-and-pepper (SAP) noise of high noise density (ND). The proposed filter computes median of trimmed window of adaptive size containing noise-free pixels (NFP) for ND up medium range while performs new interpolation-based procedure at high ND. Further, for the rare scenarios especially at the boundary where denoising using interpolation is not good enough, the proposed filter denoises the candidate pixel with the help of nearest processed pixels. The proposed ATM filter effectively suppresses SAP noise because denoising mostly utilizes original non-noisy pixels. The proposed algorithm is evaluated for varying ND (10-90%) with different benchmark images (greyscale and coloured) over the existing approaches. The proposed ATM filter on an average provides 1.59 dB and 0.37 dB higher PSNR values on the greyscale and color images, respectively.