利用线性预测去除图像椒盐噪声

针对去除灰度图像的椒盐噪声问题,提出一种利用线性预测去除椒盐噪声的算法。算法的优点是利用已知信息预测出未知信息。本文提出的算法根据椒盐噪声的特点,判断图像像素是信号像素还是可能的噪声像素,把图像信号像素作为已知信息,把噪声像素作为未知信息,采用三阶线性预测器,利用信号像素预测出噪声像素。该算法对于可能的噪声像素,采取预测算法进行预测,预测值作为噪声像素处理后的灰度值;而对于信号像素则不做任何处理,因而很好地保留了图像细节。实验结果表明,该算法的运算量小,去噪能力强,尤其在处理噪声高度污染图像时,去噪能力表现更为突出。

Removal of Salt-and-pepper Noises from Images by Linear Prediction

To remove salt-and-pepper noises from an image, an algorithm is proposed on the basis of linear pre- diction. Each pixel is estimated to be a signal pixel or possible noise pixel according to characteristics of the salt-and-pepper noise. Linear prediction is employed to the possible noise pixels, which are then replaced by the predicted values, while the signal pixels are kept untouched to preserve the detail of the image. Experimental results prove that the presented method has less calculation and shows strong denoising ability, especially for highly corrupted images.