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The Improved BAMS Filter for Image Denoising  

Woo, Chang-Yong (경남대학교)
Park, Nam-Chun (경남대학교)
Publication Information
Journal of the Institute of Convergence Signal Processing / v.11, no.4, 2010 , pp. 270-277 More about this Journal
Abstract
The BAMS filter is a kind of wavelet shrinkage filter based on the Bayes estimators with no simulation, therefore it can be used for a real time filter. The denoising efficiency of BAMS filter is seriously affected by the estimated noise variance in each wavelet band. To remove noise in signals in existing BAMS filter, the noise variance is estimated by using the quartile of the finest level of details in the wavelet decomposition, and with this variance, the noise of the level is removed. In this paper, to remove the image noise includingodified quartile of the level of detail is proposed. And by these techniques, the image noises of mid and high frequency bands are removed, and the results showed that the increased PSNR of ab the midband noise, the noise variance estimation method using the monotonic transform and the mout 2[dB] and the effectiveness in denosing of low noise deviation images.
Keywords
Wavelet Transform; Bayes Estimator; Quartile; Monotonic transform; Minmax Estimation Risk; Threshold; Marginal Distribution; Prior Information;
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Times Cited By KSCI : 1  (Citation Analysis)
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