一种基于模糊逻辑的图像自适应去噪算法

为克服单一使用中值滤波方法去除脉冲噪声会造成图像细节信息丢失,使图像变模糊的缺陷,提出一种新的基于模糊逻辑的图像自适应去噪算法.新算法通过分析像素不同方向邻域像素灰度值分布情况来检测脉冲噪声点,另外为更好地保持图像边缘等细节特征,使用改进MMEM(maximum-minimum exclusive median)算法对噪声像素点的灰度值进行估计.最后,新算法通过引入模糊逻辑规则,更加合理地进行噪声污染像素点的灰度值复原.仿真结果表明,与其他改进中值滤波算法相比新算法在去除脉冲噪声时能取得更好的效果.

An Adaptive Image De-noising Algorithm Based on Fuzzy Logic

A new adaptive image de-noising algorithm based on fuzzy logic is proposed by analyzing the deficiencies of median filter when it is used to eliminate impulsive noise. The new algorithm for detection of noise points is based on grayscale distribution of neighboring pixels in different directions, and it uses the improved algorithm of maximum-minimum exclusive median method to estimate the gray level of current noisy pixels. Introducing the fuzzy logic rules into the new algorithm, the gray level of noisy pixels will be restored more reasonably. Simulation results show that the new algorithm may bring about better effect in eliminating impulsive noise in comparison with the improved median filter methods.