Abstract
Exemplar-based texture synthesis is defined as the process of generating, from an input texture sample, new texture images that are perceptually equivalent to the input. In the present work, we model texture self-similarity with conditional Gaussian distributions in the patch space in order to extend the use of stitching techniques. Then, a multiscale texture synthesis algorithm is introduced, where texture patches are modeled at each scale as spatially variable Gaussian vectors in the patch space. The Gaussian distribution for each patch is inferred from the set of its nearest neighbors in the patch space obtained from the input sample. This approach is tested over several real and synthetic texture images, and its results show the effectiveness of the proposed technique for a wide range of textures. © 2016, Springer Science+Business Media New York.
| Original language | English |
|---|---|
| Pages (from-to) | 260-279 |
| Journal | Journal of Mathematical Imaging and Vision |
| Volume | 56 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Oct 2016 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Funding
Work partly founded by the European Research Council (advanced Grant Twelve Labors) and the Office of Naval research (ONR Grant N00014-14-1-0023).
Research Keywords
- Conditional locally Gaussian
- Multiscale
- Patch size
- Texture synthesis