摘要
提出一种去除椒盐噪声的自适应云理论滤波算法,该算法采用云的极大判定法则将图像中的像素分类为噪声点和信息点。对检测出的噪声点,利用周围信息点通过自适应云推理进行去除,信息点保持其灰度值不变直接输出。实验结果表明,该算法能有效去除椒盐噪声,保护图像细节,尤其在高强度噪声下,优势突出,较传统中值滤波及其改进算法有更好的滤波性能。
An adaptive cloud theory filtering algorithm is proposed for salt and pepper noise removal, which divides the pixels of an image into signal part and noise part by means of the cloud maximum judgment criterion. The detected noise pixels are removed by using the adaptive cloud forecast, while the signal ones remain unchanged and are output directly. Experimental results indicate that ： 1 ） The proposed method can suppress salt and pepper noise and preserve image details effectively ;and 2） The filtering effect of our method outperforms that of the traditional and the improved median filtering, especially under the condition of high-intensity noise.
出处
《电光与控制》
北大核心
2016年第2期70-73,共4页
Electronics Optics & Control
关键词
图像处理
椒盐噪声
噪声检测
噪声去除
自适应
云理论
image processing
salt and pepper noise
noise detection
noise removal
adaptation
cloud theory
