PatchMatch
Princeton University · Adobe Systems (United States) · +1 more institution
Abstract
This paper presents interactive image editing tools using a new randomized algorithm for quickly finding approximate nearest-neighbor matches between image patches. Previous research in graphics and vision has leveraged such nearest-neighbor searches to provide a variety of high-level digital image editing tools. However, the cost of computing a field of such matches for an entire image has eluded previous efforts to provide interactive performance. Our algorithm offers substantial performance improvements over the previous state of the art (20-100x), enabling its use in interactive editing tools. The key insights driving the algorithm are that some good patch matches can be found via random sampling, and that…
Citation impact
- FWCI
- 59.42
- Percentile
- 100%
- References
- 44
Authors
4Topics & keywords
- Computer science
- Image editing
- Computer graphics
- Texture synthesis
- Key (lock)
- Context (archaeology)
- Image (mathematics)
- Artificial intelligence