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Novel Spatially Adaptive Image Denoising Algorithm Based on Covariance Estimation in Wavelet Domain

Novel Spatially Adaptive Image Denoising Algorithm Based on Covariance Estimation in Wavelet Domain
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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. 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.
出处 《Journal of Beijing Institute of Technology》 EI CAS 2003年第4期390-394,共5页 北京理工大学学报(英文版)
基金 theMinisterialLevelAdvancedResearchFoundation( 2 0 0 2 0 960 0 0 1)
关键词 image processing DENOISING WAVELET covariance estimation image processing denoising wavelet covariance estimation
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参考文献10

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