Locally Gaussian exemplar based texture synthesis
- Resource Type
- Conference
- Authors
- Raad, Lara; Desolneux, Agnes; Morel, Jean-Michel
- Source
- 2014 IEEE International Conference on Image Processing (ICIP) Image Processing (ICIP), 2014 IEEE International Conference on. :4667-4671 Oct, 2014
- Subject
- Components, Circuits, Devices and Systems
Biological system modeling
Image edge detection
Visualization
Gaussian distribution
Image denoising
Texture Synthesis
Gaussian Modeling
Image Patches
- Language
- ISSN
- 1522-4880
2381-8549
The main approaches to texture modeling are the statistical psychophysically inspired model and the patch-based model. In the first model the texture is characterized by a sophisticated statistical signature. The associated sampling algorithm estimates this signature from the example and produces a genuinely different texture. This texture nevertheless often loses accuracy. The second model boils down to a clever copy-paste procedure, which stitches verbatim copies of large regions of the example. We propose in this communication to involve a locally Gaussian texture model in the patch space. It permits to synthesize textures that are everywhere different from the original but with better quality than the purely statistical methods.