A New Class of Detail-Preserving Filters for Image Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Communications of the ACM
A New Scheme for Impulse Detection in Switching Median Filters for Image Filtering
ICCIMA '07 Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007) - Volume 03
Image restoration viawiener filtering in the frequency domain
WSEAS Transactions on Signal Processing
Tri-state median filter for image denoising
IEEE Transactions on Image Processing
Noise adaptive soft-switching median filter
IEEE Transactions on Image Processing
Selective removal of impulse noise based on homogeneity level information
IEEE Transactions on Image Processing
A fuzzy impulse noise detection and reduction method
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Fuzzy Two-Step Filter for Impulse Noise Reduction From Color Images
IEEE Transactions on Image Processing
WSEAS Transactions on Signal Processing
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In this paper, a restoration approach for noisy image is proposed where a boundary resetting boundary discriminative noise detection (BRBDND) and a median filtering with smallest window (MFSW) are applied. In the proposed image restoration approach, two stages are involved: noise detection and noise replacement. The BRBDND is used to detect noisy pixels in an image. If a pixel is uncorrupted, then keep it intact. Or replace it with an uncorrupted neighborhood pixel through the MFSW. Note that miss detection happens in the BDND presented in [17] when the noise density is high. The miss detection is even worse for cases with unbalanced noisy density where the portions for the salt noise and the pepper noise are different. A boundary resetting scheme is incorporated into the BDND. By this doing, the problem of miss detection described above can be prevented. Note that a larger window used in the median filtering leads to a stronger smoothing effect on the restored image. The reported median filtering approaches, like the modified noise adaptive soft-switching median filter (MNASM) in [17], uses larger windows generally. Thus, a median filtering with smallest window (MFSW) is proposed to improve the visual quality of restored image. Two examples are provided to justify the proposed image restoration approach BRBDND/MFSW where comparisons are made with the BDND/MNASM. The results indicate that the proposed BRBDND is able to deal with the miss detection problem in the BDND. It also shows that the proposed MFSW indeed improves the visual quality of restored image as expected. The simulation results suggest that the proposed restoration approach BRBDND/MFSW generally outperforms the BDND/MNASM both in the PSNR and the visual quality of restored image.