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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Al-Ismaeil, K. Aouada, D. Ottersten, B. Mirbach, B. |
| Copyright Year | 2012 |
| Description | Author affiliation: Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Bruno Mirbach Advanced Engineering Department, IEE S.A. (Al-Ismaeil, K.; Aouada, D.; Ottersten, B.) |
| Abstract | The well-known bilateral filter is used to smooth noisy images while keeping their edges. This filter is commonly used with Gaussian kernel functions without real justification. The choice of the kernel functions has a major effect on the filter behavior. We propose to use exponential kernels with $L^{1}$ distances instead of Gaussian ones. We derive Stein's Unbiased Risk Estimate to find the optimal parameters of the new filter and compare its performance with the conventional one. We show that this new choice of the kernels has a comparable smoothing effect but with sharper edges due to the faster, smoothly decaying kernels. |
| Starting Page | 258 |
| Ending Page | 261 |
| File Size | 1524282 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467322164 |
| ISSN | 10514651 |
| e-ISBN | 9784990644109 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-11-11 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | ICPR Org Committee |
| Subject Keyword | Kernel Noise Image edge detection Noise measurement Noise reduction Radiometry Smoothing methods |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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