Soft morphological filter based on particle swarm algorithm
Dongquan Liu · Journal of Computer Applications · 2010
Typical median and mean filters have some drawbacks such as incomplete denoising and image blurring.Therefore,a new Improved Soft Morphological Filter (ISMF) was proposed to remove salt-and-pepper and Gaussian noise while preserving the details.In order to quantitatively analyze the parameters and nonlinear constraints in the filter,a modified simple Particle Swarm Optimization (msPSO) algorithm was given with high convergence speed and precision.The experimental results show that ISMF optimized by msPSO performs better on Peak Signal to Noise Ratio (PSNR) and shape error.