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作 者:黄文笔 谢翠萍 陈家益 石艳 HUANG Wenbi;XIE Cuiping;CHEN Jiayi;SHI Yan(Center of Educational Technology and Information,Guangdong Medical University,Zhanjiang 524023,China;School of Biomedical Engineering,Guangdong Medical University,Zhanjiang 524023,China;School of Information Engineering,Lingnan Normal University,Zhanjiang 524048,China)
机构地区:[1]广东医科大学教育技术与信息中心,广东湛江524023 [2]广东医科大学生物医学工程学院,广东湛江524023 [3]岭南师范学院信息工程学院,广东湛江524048
出 处:《现代电子技术》2021年第21期25-29,共5页Modern Electronics Technique
基 金:国家自然科学基金(61705095);广东医科大学科研基金(GDMUM201827)。
摘 要:为了克服现有的滤波算法在去噪性能和计算复杂度上的瓶颈,为图像处理与分析提供高质量的图像,提出迭代的顺序加权中值图像滤波算法。算法根据噪声与信号像素分布的局部统计特征进行噪声检测,以迭代的方式调用加权中值滤波算法对噪声像素的灰度进行估测;加权算子的系数根据邻域像素与中心像素的空间距离,顺序地递减分布,以更加准确地体现邻域像素对中心像素的相关性与影响。从实验结果可知,相对于当前最新提出的算法,文中设计的算法具有优越的去噪性能和较好的细节保持能力,且其计算速度快于大部分的现有算法。An iterative sequentially-weighted median filtering algorithm is proposed to overcome the bottlenecks of the existing filtering algorithms in denoising effect and computational complexity,and provide high-quality images for image processing and analysis.In the proposed method,the noise is detected according to the local statistical features of distribution of noise and signal pixels,the gray level of the noisy pixel is estimated by calling weighted median filtering algorithm in an iterative way,and the coefficients of the weighted operator are distributed sequentially and decreasingly according to the special distances between the neighboring pixel and the central pixel,so as to precisely reflect the impact of the neighboring pixel on the central pixel and the correlations between the two pixels.It can be inferred from the experimental results that,in comparison with the newly proposed methods,the designed method possesses superior denoising performance and better capability of detail preservation,and its computational speed is faster than that of the most existing methods.
关 键 词:中值图像滤波 噪声检测 图像去噪 灰度估测 加权算子系数 加权中值去噪
分 类 号:TN911.73-34[电子电信—通信与信息系统] TP391[电子电信—信息与通信工程]
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