LDNLM replaces the quadratic similarity and averaging steps of nonlocal means with deep convolutional feature extraction and linear attention operations to produce a linear-complexity denoiser for multiplicative noise that retains traditional NLM interpretability.
IEEE Transactions on Geoscience and Remote sensing 41(8), 1773–1784 (2003) 1
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Linear Attention Based Deep Nonlocal Means Filtering for Multiplicative Noise Removal
LDNLM replaces the quadratic similarity and averaging steps of nonlocal means with deep convolutional feature extraction and linear attention operations to produce a linear-complexity denoiser for multiplicative noise that retains traditional NLM interpretability.