基于像素分类的像素值阈值噪声检测算法  

Pixel classification-based noise detector with pixel value threshold

作　　者：黄宴委[1] 祁冰露[1] 袁世强 

机构地区：[1]福州大学电气工程与自动化学院,福建福州350108 [2]上海华虹集成电路有限公司,上海201203

出　　处：《福州大学学报（自然科学版）》2012年第4期471-477,共7页Journal of Fuzhou University(Natural Science Edition)

基　　金：教育部博士点新教师基金资助项目(20113514120007);福建省自然科学基金资助项目(2010J05132);福建省教育厅科研资助项目(JA10034)

摘　　要：针对图像噪声常见的三种脉冲噪声模型,在像素差异均等性原则下,以窗口分块方式将图像像素分为噪声像素和非噪声像素子集,进而以噪声图像上下像素值阈值推导噪声类型判别式,得到一种非线性像素分类的图像噪声检测算法.以经典图像(Lena、Baboon)分别叠加上不同密度噪声进行噪声图像检测算法仿真测试,由检测精确性和正确性来评估所提出的检测算法的检测性能.仿真结果表明,该检测算法具有较好的检测效果,缺点是容易将部分非噪声像素识别为噪声像素.According to three kinds of impulse noises in image processing, a novel technique is presented to classify pixels by pixel difference uniformity with blocks into noise pixel sets and non -noise pixel sets. Moreover, a novel nonlinear noise detector is proposed to identify the noise types by a discfiminance with up - down pixel thresholds in noise image. The presented algorithm is tested by a classical image（Lena） and image（Baboon） with adding a different density noise. The simulation results are evaluated by two indexes, named detecting accuracy and detecting correctness. The results indicate that the proposed algorithm has a favorable detecting performance, but its shortage is easy to mistake a non -noise pixel for a noise pixel.

关 键 词：像素分类 像素阈值 噪声检测 脉冲噪声 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]