采用自适应四点窗中点滤波的高椒盐噪声滤除方法

摘要

In view of poor denoising performance and unideal speed of the current median filter,a fast and Adaptive Four-dot Midpoint Filter (AFMF) was proposed.Firstly,noise pixels and non-noise pixels of an image were identified using a simple extreme method to reduce the computational complexity.Then,the traditional full-point window was discarded,instead of median filtering,but on the basis of switch filtering and clipping filtering,a new nonlinear filtering method named midpoint filtering was adopted to simplify the algorithm flow,improve the calculation efficiency,improve the denoising effect.Finally,starting from a 3 × 3 window from inside to outside,the window was gradually enlarged to form adaptive filtering,until all the noise pixels were processed,the setting of window size parameters was avoided.The experimental results show that compared with AMF,SAMF,MDBUTMF and DBCWMF,AFMF not only has better denoising performance but also faster operation speed (about 0.18 s),but also does not need to set parameters,which is easy to operate and has strong practicability.%针对当前中值滤波器处理图像高椒盐噪声效果不佳和实时性不强等问题,提出了一种快速自适应四点窗中点滤波(AFMF)方法.首先,为了降低计算复杂度,使用简单的极值方法检测噪声点;然后,摒弃传统的全点窗口,不用中值滤波,而是在开关滤波和裁剪滤波的基础上,采用新型的非线性滤波方法:中点滤波,简化了算法的流程,提升了算法的计算效率,提高了去噪效果;最后,从3×3窗口开始到由里向外推进,逐渐增大窗口,形成自适应滤波,一直到噪声点处理完,如此避免了窗口大小参数的设置.实验结果表明,与AMF、SAMF、MDBUTMF以及DBCWMF相比,AFMF在处理高密度椒盐噪声上不仅有更好的去噪性能、更快的运行速度(约0.18s),且无需设置参数,可操作性强,具有较强的实用性.