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一种基于小波包分解的图像分类去噪方法

Classified Image Denoising Method Based on the Wavelet Package
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摘要 文章提出了一种基于小波包分解的图像分类去噪方法,即首先用高斯-拉普拉斯边缘检测方法检测出图像的边缘,得到边缘图像;然后利用小波包对图像平滑区域进行阀值去噪,同时对图像进行邻域平滑处理;最后将边缘图像嵌入平滑图像。此种方法不但可以保持图像的边缘信息,而且能够去除图像的噪声,提高了图像的去噪效果和清晰度。 In this paper,classified image denoising method based on the wavelet package is presented.At first,it detects the edge of image with Laplace of Gauss method of edge detection,and gets the edge image.Then it carries on thresh-old denoising on smoothing region with wavelet package,and carries on the level and smooth handle of neighborhood to the image at the same time ,finally,embed into the smoothing image with edge image.The method can not only keep the edge information of image,but also can denoise and improve the denoising effect and distinct of image.
作者 刁洪祥 蒋加伏 唐贤瑛
机构地区 长沙交通学院计算机工程系
出处 《计算机工程与应用》 CSCD 北大核心 2003年第20期74-76,共3页 Computer Engineering and Applications
基金 湖南省自然科学基金资助(编号:00JJY2059)
关键词 小波包分解 边缘检测 图像去噪 Decomposition of wavelet package,Edge detection,Image denoising
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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计算机工程与应用
2003年 第20期

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