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In image processing and computer vision, anisotropic diffusion, also called Perona–Malik diffusion, is a technique aiming at reducing image noise without removing significant parts of the image content, typically edges, lines or other details that are important for the interpretation of the image. Anisotropic diffusion resembles the process that creates…
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diffusion image anisotropic images edges family filter perona malik resulting displaystyle coefficient function original noise equation smoothing also process isotropic
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Anisotropic diffusion | is a | generalization of this diffusion process | 0.90 | text |
| Anisotropic diffusion | is a | non-linear and space-variant transformation of the original image.In its original formulation | 0.90 | text |
| Anisotropic diffusion | is a | iterative process where a relatively simple set of computations is used to compute each successive image in the family and this process is continued until a sufficient degree of… | 0.90 | text |
| edges or lines | instance of | A more general formulation allows the locally adapted filter to be truly anisotropic close to linear structures | 0.80 | text |
| Anisotropic diffusion | has application | Anisotropic | 0.60 | section |
| Anisotropic diffusion | has application | With | 0.60 | section |
| Anisotropic diffusion | has application | Gaussian | 0.60 | section |
| Anisotropic diffusion | has application | This | 0.60 | section |
| Anisotropic diffusion | has application | When | 0.60 | section |
| Anisotropic diffusion | has application | Perona | 0.60 | section |
| Anisotropic diffusion | has application | Malik | 0.60 | section |
| Anisotropic diffusion | has application | Hence | 0.60 | section |
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