为了满足图象实时处理对算法速度和高斯噪声、脉冲噪声混合的噪声环境对算法鲁棒性的要求,以及适应能够同时抑制高斯噪声和脉冲噪声的需要,提出了一种可以有效滤除混合噪声(高斯噪声和正负脉冲噪声),而且可以快速实现的自适应滤波器——ABA滤波器.ABA滤波器应用了自适应的滤波结构,它将对脉冲噪声和高斯噪声、边缘区域和平坦区域分别进行处理;它的自适应判断和操作以均值操作为主,并将均值操作的结果充分利用在自适应处理中.实验仿真所得的数据显示,在脉冲噪声的密度小于10%的情况下,与其它一些滤波器相比,ABA滤波

This paper presents a new filter, called Averaging-Based Adaptive Filter (ABA Filter), whose objective is to overcome the deficiency of current filters that they can not simultaneously possess the merits of both efficiency and simplicity when dealing with mixed noise. Although adaptive filters are robust owing to their effectual structures, the complexity of these filters is generally too great to be realized in real time. However, for video applications, it is very important to design a fast filter. Compared with other adaptive filters, ABA filter uses averaging as its major operation and the averaging value is utilized repeatedly in its adaptive processing so that it needs much less processing time. The adaptive structure makes ABA filter able to adopt different algorithms according to different noise and different image areas. The experimental results show clearly that, when the density of impulse noise is lower than 10%, ABA filter is capable of eliminating the mixed Gaussian noise and impulse noise with much fewer operations.