Name
Abstract | ||
|---|---|---|
In this paper we introduce a Bayesian best linear unbiased estimator (Bayesian BLUE) and apply it to generate optimal averaging filters. Linear filtering of signals is a basic operation frequently used in low level vision. In many applications, filter selection is ad hoc without proper theoretical justification. For example input signals are often convolved with Gaussian filter masks, i.e masks that are constructed from truncated and normalized Gaussian functions, in order to reduce the signal noise. In this contribution, statistical estimation theory is explored to derive statical optimal filter masks from first principles. Their shape and size are fully determined by the signal and noise characteristics. Adaption of the estimation theoretical point of view not only allows to learn optimal filter masks but also to estimate the variance of the estimate. The statistically learned filter masks are validated experimentally on image reconstruction and optical flow estimation. In these experiments our approach outperforms comparable approaches based on ad hoc assumptions on signal and noise or even do not relate their method at all to the signal at hand. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-69321-5_47 | DAGM-Symposium |
Keywords | Field | DocType |
statical optimal filter mask,statistically optimal averaging,signal noise,noise characteristic,optimal filter mask,example input signal,optical flow estimation,estimation theoretical point,filter mask,image restoration,optimal averaging filter,gaussian filter mask,image reconstruction,first principle,linear filtering | Iterative reconstruction,Gaussian filter,Pattern recognition,Linear filter,Minimum mean square error,Gaussian,Structure tensor,Artificial intelligence,Estimation theory,Image restoration,Mathematics | Conference |
Volume | ISSN | Citations |
5096 | 0302-9743 | 2 |
PageRank | References | Authors |
0.38 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kai Krajsek | 1 | 57 | 7.30 |
| Rudolf Mester | 2 | 534 | 64.48 |
| Hanno Scharr | 3 | 430 | 37.92 |