基于边缘检测与双边滤波的彩色图像去噪  

Removing Noise of Color Images Based on Edge Detection and Bilateral Filter

作　　者：张闯[1] 迟健男[1] 张朝晖[1] 王志良[1] 

机构地区：[1]北京科技大学信息工程学院,北京100083

出　　处：《电子学报》2010年第8期1776-1783,共8页Acta Electronica Sinica

基　　金：国家自然科学基金资(No.60574090);国家863高技术研究发展计划(No.2007AA01Z160);博士后科学基金(No.200604000400)

摘　　要：针对彩色图像双边滤波去噪方法存在的不足,本文提出一种边缘检测与双边滤波相结合的彩色图像去噪方法.首先利用细胞神经网络(CNN)模型导出一种新的彩色图像分块自适应边缘检测算法,继承了CNN灰度边缘检测算法定位准确的优点,又弥补了CNN现有算法不能直接处理彩色图像的空白.接下来提出一种针对图像增强的边缘滤波算法,通过两级边缘检测满足去噪不同阶段对边缘检测的不同要求.在此基础上,用改进的双边滤波器对彩色图像进行去噪,通过非抗噪边缘图对噪声范围进行定位,以缩小双边滤波的范围,减少去噪过程带来的图像模糊,并且对双边滤波加权平均方式进行改进,减小噪声点本身的权重,降低高频噪声的影响.最后根据滤波后的去噪边缘图对彩色图像进行增强.实验结果表明,文中方法在有效去除噪声的同时保护和增强了图像中的边缘.For the disadvantages of color bilateral noise filtering,this paper presents an integrated approach to address these issues based on edge detection and bilateral filter.First,a new color edge detection algorithm of adaptive partition is derived from cellular neural network（CNN） model.This algorithm inherits the advantage of accurate positioning of CNN gray edge detection,and can deal directly with color images.Next,an edge filter is proposed for image enhancement,which satisfies different stages of denoising through two types of edge detection.On this basis,removing noise of color images uses of the improved bilateral filter.The scope of noise is localized by non-anti-noise edge map to reduce the denoising process and image blur.Average mode of bilateral filter is improved to reduce the weight of noise and the impact of high-frequency noise.Finally,color images are enhanced according to the edge map after filtering.The experimental results show that the proposed approach can effectively reduce the noise while preserving and enhancing edges.

关 键 词：边缘检测 双边滤波 彩色图像 边缘滤波 去噪 细胞神经网络(CNN) 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]