Impulse noise removal by a global-local noise detector and adaptive median filter
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
Impulse noise removal utilizing second-order difference analysis
Signal Processing
Nonlocal means-based speckle filtering for ultrasound images
IEEE Transactions on Image Processing
Homogeneity similarity based image denoising
Pattern Recognition
Noise adaptive soft-switching median filter
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Efficient Nonlocal Means for Denoising of Textural Patterns
IEEE Transactions on Image Processing
Dictionary learning based impulse noise removal via L1-L1 minimization
Signal Processing
A switching weighted vector median filter based on edge detection
Signal Processing
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The decision-based non-local means filter is proposed to remove fixed-value impulse noise from the corrupted digital images. The proposed filter first identifies the corrupted pixels using the local statistics based noise detector and then removes the detected impulses using the reference image-based non-local means filter while keeping the uncorrupted pixels unaltered. Extensive simulations demonstrate that the proposed filter can remove impulse noise from the corrupted images effectively while preserving image details very well at the various noise ratios, which leads to its significantly better image restoration performance than numerous state-of-the-art switching-based filters.