NAMF: A Non-local Adaptive Mean Filter for Salt-and-Pepper Noise Removal
This addresses image denoising for applications like photography or medical imaging, but it appears incremental as it builds on existing filter techniques.
The paper tackles salt-and-pepper noise removal in images by proposing NAMF, a non-local adaptive mean filter, which achieves better restoration quality across all noise levels compared to existing methods.
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.