DocumentCode
249441
Title
Locally Gaussian exemplar based texture synthesis
Author
Raad, Lara ; Desolneux, Agnes ; Morel, Jean-Michel
Author_Institution
CMLA, Ecole Normale Super. de Cachan, Cachan, France
fYear
2014
fDate
27-30 Oct. 2014
Firstpage
4667
Lastpage
4671
Abstract
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.
Keywords
image texture; statistical analysis; clever copy-paste procedure; locally Gaussian exemplar based texture synthesis; patch-based model; sampling algorithm; statistical psychophysically inspired model; Biological system modeling; Gaussian distribution; Image denoising; Image edge detection; Visualization; Gaussian Modeling; Image Patches; Texture Synthesis;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location
Paris
Type
conf
DOI
10.1109/ICIP.2014.7025946
Filename
7025946
Link To Document