An efficient method to remove mixed Gaussian and random-valued impulse noise.
Ontology highlight
ABSTRACT: Mixed Gaussian and Random-valued impulse noise (RVIN) removal is still a big challenge in the field of image denoising. Existing denoising algorithms have defects in denoising performance and computational complexity. Based on the improved "detecting then filtering" strategy and the idea of inpainting, this paper proposes an efficient method to remove mixed Gaussian and RVIN. The proposed algorithm contains two phases: noise classification and noise removal. The noise classifier is based on Adaptive center-weighted median filter (ACWMF), three-sigma rule and extreme value processing. Different from the traditional "detecting then filtering" strategy, a preliminary RVIN removal step is added to the noise removal phase, which leads to three steps in this phase: preliminary RVIN removal, Gaus
SUBMITTER: Xing M
PROVIDER: S-EPMC8893653 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
ACCESS DATA