| Novel Spatially Adaptive Image Denoising Algorithm Based on Covariance Estimation in Wavelet Domain |
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| 引用本文： | 谢志宏,沈庭芝,王海. Novel Spatially Adaptive Image Denoising Algorithm Based on Covariance Estimation in Wavelet Domain[J]. 北京理工大学学报(英文版), 2003, 12(4): 390-394 |
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| 作者姓名： | 谢志宏 沈庭芝 王海 |
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| 作者单位： | DepartmentofElectronicEngineering,SchoolofInformationScienceandTechnology,BeijingInstituteofTechnology,Beijing100081,China |
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| 基金项目： | theMinisterialLevelAdvancedResearchFoundation( 2 0 0 2 0 960 0 0 1) |
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| 摘 要： | A new method for image denoising is proposed. By analyzing image‘s statistical properties in wavelet domain, it is shown that the natural image has a strong and spatial variable covariance structure relationship in local space of sub-band. A non-direct estimation method is suggested to make an adaptive estimate of spatial variable covariance by estimating the correlation coefficient and variance of subband image separately. It can be used to estimate adaptive filtering of subband image. The experiment shows that this method can improve the image‘s SNR, and has strong ability to preserve edges.
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| 关 键 词： | 空间自适应算法 图象处理 协方差估计 小波去噪 通信 |
| 收稿时间： | 2003-06-17 |
Novel Spatially Adaptive Image Denoising Algorithm Based on Covariance Estimation in Wavelet Domain |
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| XIE Zhi-hong,SHEN Ting-zhi and WANG Hai. Novel Spatially Adaptive Image Denoising Algorithm Based on Covariance Estimation in Wavelet Domain[J]. Journal of Beijing Institute of Technology, 2003, 12(4): 390-394 |
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| Authors: | XIE Zhi-hong SHEN Ting-zhi WANG Hai |
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| Affiliation: | Department of Electronic Engineering, School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China;Department of Electronic Engineering, School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China;Department of Electronic Engineering, School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China |
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| Abstract: | A new method for image denoising is proposed. By analyzing image's statistical properties in wavelet domain, it is shown that the natural image has a strong and spatial variable covariance structure relationship in local space of sub-band. A non-direct estimation method is suggested to make an adaptive estimate of spatial variable covariance by estimating the correlation coefficient and variance of subband image separately. It can be used to estimate adaptive filtering of subband image. The experiment shows that this method can improve the image's SNR, and has strong ability to preserve edges. |
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| Keywords: | image processing denoising wavelet covariance estimation |
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