Abstract | ||
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In this paper, we present a novel frames-based denoising algorithm. Using a general result on lifting frames, we construct a non-separable 3D frame capable of robust edge detection. This frame detects edge information by ensemble thresholding of the filtered data. The denoising uses a hyste resis thresholding step and an affine thresholding function, whic h are filter-adaptive and take full advantage of the threshold bou nds. The threshold bounds are statistically determined from the given data for each directional filter. We compare our denois ing method with other methods based on separable 3D wavelets and 3D median filtering, and report very encouraging results on applications to both synthetic and real confocal microscopy data. |
Year | DOI | Venue |
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2006 | 10.1109/ICASSP.2006.1660285 | Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference |
Keywords | Field | DocType |
edge detection,filtering theory,image denoising,image segmentation,microscopy,adaptive frames-based denoising,affine thresholding function,confocal microscopy data,directional filter,ensemble thresholding,hysteresis thresholding,robust edge detection | Affine transformation,Computer vision,Median filter,Pattern recognition,Computer science,Edge detection,Filter bank,Image segmentation,Artificial intelligence,Thresholding,Video denoising,Wavelet | Conference |
Volume | ISSN | ISBN |
2 | 1520-6149 | 1-4244-0469-X |
Citations | PageRank | References |
3 | 0.54 | 4 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Alberto Santamaría-Pang | 1 | 3 | 0.54 |
Teodor Stefan Bildea | 2 | 3 | 0.54 |
Ioannis Konstantinidis | 3 | 3 | 0.54 |
Ioannis A. Kakadiaris | 4 | 234 | 18.85 |