一种新的脉冲噪声图像恢复方法

A New Impulse Noise Image Recovering Method

为消除图像中的脉冲噪声,提出一种窗口自适应开关中值滤波方法.利用BP神经网络将图像中的每个像素点分类为信号点或噪声点,再采用改进的中值滤波器对检测后的图像进行滤波处理.根据噪声检测结果,滤波器自适应调整窗口大小并选择性取样,逐点滤波消除图像中的噪声.该方法在抑制脉冲噪声、保护图像细节方面均优于以往基于中值滤波的方法,即使在图像遭受70%噪声污染的极端情况下,仍能得到很好恢复.

In order to denoise impulse noises in images, an adaptive window switching median filtering method is proposed in this paper. First, each pixel is classified as signal or noisy point by the BP-net. Next, the image is filtered by an improved median filter. According to the result of noise detection, the filter can adjust adaptively window＇s width and sample choicely, each noisy point in image is denoised by filtering. In terms of suppressing impulse noise and preserving image details, the proposed method is better than that, based on median filter. Even in the extreme case of 70% noise corruption, noisy images can be effectively recovered.