arXiv:1910.07787
공식 코드 · Papers with Code
NAMF: A Non-local Adaptive Mean Filter for Salt-and-Pepper Noise Removal
원문 초록
In this paper, a novel algorithm called a non-local adaptive mean filter (NAMF) for removing salt-and-pepper (SAP) noise from corrupted images is presented. We employ an efficient window detector with adaptive size to detect the noise, the noisy pixel will be replaced by the combination of its neighboring pixels, and finally we use a SAP noise based non-local mean filter to reconstruct the intensity values of noisy pixels. Extensive experimental results demonstrate that NAMF can obtain better performance in terms of quality for restoring images at all levels of SAP noise.
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Adaptive Weight Modified Riesz Mean Filter For High-Density Salt and Pepper Noise Removal
A deep convolutional neural network for salt-and-pepper noise removal using selective convolutional blocks
Convolutional Neural Network with Median Layers for Denoising Salt-and-Pepper Contaminations
Noise2Noise: Learning Image Restoration without Clean Data
A Two-stage Method for Non-extreme Value Salt-and-Pepper Noise Removal
Salt and pepper noise removal method based on stationary Framelet transform with non-convex sparsity regularization
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