| 基于小波变换的Wiener滤波算法去除苹果图像噪声 |
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| 引用本文： | 杨福增,张艳宁,王峥,杨青.基于小波变换的Wiener滤波算法去除苹果图像噪声[J].农业机械学报,2006,37(12):130-133,143. |
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| 作者姓名： | 杨福增 张艳宁 王峥 杨青 |
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| 作者单位： | 1. 西北农林科技大学机械与电子工程学院 712100 陕西省杨凌
2. 西北工业大学计算机科学与工程学院 710071 西安市 |
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| 基金项目： | 西北农林科技大学校科研和教改项目;西北农林科技大学校科研和教改项目;面向21世纪教育振兴行动计划(985计划);高等学校博士学科点专项科研项目 |
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| 摘 要： | 在小波变换的基础上，提出了一种基于小波变换的Wiener滤波去噪方法。采用该方法对苹果图像的加性噪声（高斯白噪声）去噪，结果PSNR为184．94，视觉效果清晰（而含噪声图像的PSNR为158．23，噪声太多不清晰）。好于邻域平均法（PSNR为174．15，视觉上含部分噪声）、中值滤波法（PSNR为182．4Z）、小波阔值去噪（PSNR为171．59，视觉上也含部分噪声）和Wiener滤波去噪法（PSNR为173．65）的去噪结果，更好于数学形态学的去噪结果（PSNR为150．46，视觉上含较多噪声）。试验结果表明，基于小波变换的Wiener滤波方法对苹果图像加性噪声的去噪效果具有信噪比高、视觉效果好等优点。
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| 关 键 词： | 苹果 小波变换 Wiener滤波 加性噪声 图像去噪 |
| 收稿时间： | 08 18 2006 12:00AM |
| 修稿时间： | 2006-08-18 |
Application of Wavelet Transform-based Wiener Filtering Method to Reduce Additive Noise in Apple Image |
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| Yang Fuzeng,Zhang Yanning,Wang Zheng,Yang Qing.Application of Wavelet Transform-based Wiener Filtering Method to Reduce Additive Noise in Apple Image[J].Transactions of the Chinese Society of Agricultural Machinery,2006,37(12):130-133,143. |
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| Authors: | Yang Fuzeng Zhang Yanning Wang Zheng Yang Qing |
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| Institution: | 1.Northwest A & F University 2.Northwestern Polytechnical University |
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| Abstract: | A wavelet transform-based Wiener filtering method was put forward. The method was applied in reducing additive noise in apple images, as a result, PSNR was 184.94(visual effect was clear), better than other methods such as neighborhood average (PSNR was 174.15), median filter (PSNR was 182.42), wavelet thresholding de-noise (PSNR was 171.59) and Wiener filter (PSNR was 173.65), and much better than mathematical morphology (PSNR was 150.46, with much noise in visual effect). The experimental results showed that wavelet transform-based Wiener filtering method applied in reducing additive noise in apple image has the advantages of high signal-to-noise, better visual effect than conventional de-noise methods, wavelet thresholding de-noise and Wiener filter de-noise. So wavelet transform-based Wiener filtering method applied to reduce additive noise in apple image is effective and practicable. |
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| Keywords: | Apple Wavelet transform Wiener filtering Additive noise Image denoising |
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