关键词: 柔性形态滤波器, 粒子群优化, 约束优化, 椒盐噪声, 高斯噪声

Abstract: 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.

Key words: Soft Morphological Filter (SMF), Particle Swarm Optimization (PSO), Constrainted Optimization (CO), salt-and-pepper noise, Gaussian noise