Unconditionally stable shock filters for image and geometry processing
2015
This work revisits the Shock Filters of Osher and Rudin [OR90] and shows how the proposed filtering process can be interpreted as the advection of image values along flow-lines. Using this interpretation, we obtain an efficient implementation that only requires tracing flow-lines and re-sampling the image. We show that the approach is stable, allowing the use of arbitrarily large time steps without requiring a linear solve. Furthermore, we demonstrate the robustness of the approach by extending it to the processing of signals on meshes in 3D.
Keywords:
- Computer vision
- Advection
- Arbitrarily large
- Theoretical computer science
- Filter (signal processing)
- Mathematical optimization
- Collaborative filtering
- Robustness (computer science)
- Artificial intelligence
- Geometry processing
- Image processing
- Computer science
- Polygon mesh
- Tracing
- Cognitive neuroscience of visual object recognition
- Correction
- Source
- Cite
- Save
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