Domain-independent severely noisy image segmentation via adaptive wavelet shrinkage using particle swarm optimization and fuzzy C-means

作者：

Highlights：

• Effective strategies for noisy image segmentation using adaptive wavelet shrinkage.

• Edge enhancement in wavelet domain improve the results.

• Significantly better performance than other methods on severely noisy images.

• No parameter-tuning required for different noise levels and types

• Very consistent results even when the noise level has a large variation.

摘要

•Effective strategies for noisy image segmentation using adaptive wavelet shrinkage.•Edge enhancement in wavelet domain improve the results.•Significantly better performance than other methods on severely noisy images.•No parameter-tuning required for different noise levels and types•Very consistent results even when the noise level has a large variation.

论文关键词：Noisy image segmentation,Fuzzy C-means,Particle swarm optimization,Wavelet thresholding,Severe noise,Edge enhancement

论文评审过程：Received 22 August 2018, Revised 26 March 2019, Accepted 19 April 2019, Available online 30 April 2019, Version of Record 20 May 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.04.050