Name
Title | ||
|---|---|---|
An optimum shrinkage estimator based on minimum-probability-of-error criterion and application to signal denoising |
Abstract | ||
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We address the problem of designing an optimal pointwise shrinkage estimator in the transform domain, based on the minimum probability of error (MPE) criterion. We assume an additive model for the noise corrupting the clean signal. The proposed formulation is general in the sense that it can handle various noise distributions. We consider various noise distributions (Gaussian, Student's-t, and Laplacian) and compare the denoising performance of the estimator obtained with the mean-squared error (MSE)-based estimators. The MSE optimization is carried out using an unbiased estimator of the MSE, namely Stein's Unbiased Risk Estimate (SURE). Experimental results show that the MPE estimator outperforms the SURE estimator in terms of SNR of the denoised output, for low (0-10 dB) and medium values (10-20 dB) of the input SNR. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICASSP.2014.6854403 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
Gaussian noise,error statistics,mean square error methods,signal denoising,SURE,Stein unbiased risk estimate,additive model,mean squared error based estimators,minimum-probability-of-error criterion,noise distributions,optimal pointwise shrinkage estimator,signal denoising,Risk estimator,Stein's unbiased risk estimation,minimum probability of error,shrinkage function | Efficient estimator,Minimum-variance unbiased estimator,Mathematical optimization,Stein's unbiased risk estimate,Shrinkage estimator,Mean squared error,Bias of an estimator,Mathematics,Estimator,Consistent estimator | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jishnu Sadasivan | 1 | 0 | 1.01 |
| Subhadip Mukherjee | 2 | 36 | 7.57 |
| Chandra Sekhar Seelamantula | 3 | 142 | 37.43 |