| 基于小波变换的图像去噪优化算法 |
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| 引用本文： | 周文锐,狄红卫,任观就. 基于小波变换的图像去噪优化算法[J]. 计算机工程与设计, 2005, 26(12): 3244-3246 |
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| 作者姓名： | 周文锐 狄红卫 任观就 |
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| 作者单位： | 暨南大学,光电工程研究所,广东,广州,510632;广东省电信规划设计院,广东,广州,510630 |
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| 基金项目： | 广东省自然科学基金项目（04010465） |
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| 摘 要： | 提出了一种基于小波变换的图像去噪优化算法。先通过小波边缘检测法求出有噪图像的边缘图像；再利用广义交叉确认原理求出的阈值对原有噪图像进行小波去噪，得到平滑图像；最后，将边缘图像嵌入平滑图像中，得到去噪后的图像。该算法能在有效去噪的同时保留图像的细节信息，提高了信噪比。
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| 关 键 词： | 小波变换 边缘检测 阈值去噪 广义交叉确认 |
| 文章编号： | 1000-7024（2005）12-3244-03 |
| 收稿时间： | 2004-11-19 |
| 修稿时间： | 2004-11-19 |
Optimized image denoising algorithm based on wavelet transform |
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| ZHOU Wen-rui,DI Hong-wei,REN Guan-jiu. Optimized image denoising algorithm based on wavelet transform[J]. Computer Engineering and Design, 2005, 26(12): 3244-3246 |
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| Authors: | ZHOU Wen-rui DI Hong-wei REN Guan-jiu |
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| Affiliation: | 1. Institute of Photoelectricity Engineering, Jinan University, Guangzhou 510632, China; 2. Guangdong Planning and Designing Institute of Telecommunications, Guangzhou 510630, China |
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| Abstract: | An optimized image denoising algorithm based on wavelet transform is presented. At first, this method gets the edge image by the wavelet method of edge detection; Then, it gets the smoothing image of the input image using the wavelet threshold-denoising method whose threshold is obtained by the generalized cross validation theory; Finally, the edge image is embedded into the smoothing image, and the final denoising image is gained. The experiment results demonstrate that this algorithm can not only denoise effectively, but also keep the detail information. This method can improve the Signal-to-Noise Ratio. |
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| Keywords: | wavelet transform edge detection threshold denoising generalized cross validation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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